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.

  • Systematic Review
  • Published:

Differential expression of MicroRNAs in Alzheimer’s disease: a systematic review and meta-analysis

Molecular Psychiatry volume 27, pages 2405–2413 (2022)Cite this article

Subjects

A Correction to this article was published on 08 April 2022

This article has been updated

Abstract

Alzheimer’s disease (AD) results in progressive cognitive decline owing to the accumulation of amyloid plaques and hyperphosphorylated tau. MicroRNAs (miRNAs) have attracted attention as a putative diagnostic and therapeutic target for neurodegenerative diseases. However, existing meta-analyses on AD and its association with miRNAs have produced inconsistent results. The primary objective of this study is to evaluate the magnitude and consistency of differences in miRNA levels between AD patients, mild cognitive impairment (MCI) patients and healthy controls (HC). Articles investigating miRNA levels in blood, brain tissue, or cerebrospinal fluid (CSF) of AD and MCI patients versus HC were systematically searched in PubMed/Medline from inception to February 16th, 2021. Fixed- and random-effects meta-analyses were complemented with the I2 statistic to measure the heterogeneity, assessment of publication bias, sensitivity subgroup analyses (AD severity, brain region, post-mortem versus ante-mortem specimen for CSF and type of analysis used to quantify miRNA) and functional enrichment pathway analysis. Of the 1512 miRNAs included in 61 articles, 425 meta-analyses were performed on 334 miRNAs. Fifty-six miRNAs were significantly upregulated (n = 40) or downregulated (n = 16) in AD versus HC and all five miRNAs were significantly upregulated in MCI versus HC. Functional enrichment analysis confirmed that pathways related to apoptosis, immune response and inflammation were statistically enriched with upregulated pathways in participants with AD relative to HC. This study confirms that miRNAs’ expression is altered in AD and MCI compared to HC. These findings open new diagnostic and therapeutic perspectives for this disorder.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow chart.
Fig. 2: Forest plot for random-effects meta-analysis and important functions of miRNAs.
Fig. 3: Schematic diagram of miRNA and their pathogenesis in Alzheimer’s disease.
Fig. 4: Functional enrichment analysis results.

Similar content being viewed by others

Change history

References

  1. Prince M, Ali GC, Guerchet M, Prina AM, Albanese E, Wu YT. Recent global trends in the prevalence and incidence of dementia, and survival with dementia. Alzheimers Res Ther. 2016;8:23.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Checkoway H, Lundin JI, Kelada SN Neurodegenerative diseases. IARC Sci Publ. 2011:407-19.

  3. Alzheimer’s A. 2016 Alzheimer’s disease facts and figures. Alzheimers Dement. 2016;12:459–509.

    Article  Google Scholar 

  4. Kumar A, Nisha CM, Silakari C, Sharma I, Anusha K, Gupta N, et al. Current and novel therapeutic molecules and targets in Alzheimer’s disease. J Formos Med Assoc. 2016;115:3–10.

    Article  CAS  PubMed  Google Scholar 

  5. Salloway S, Sperling R, Fox NC, Blennow K, Klunk W, Raskind M, et al. Two phase 3 trials of bapineuzumab in mild-to-moderate Alzheimer’s disease. N Engl J Med. 2014;370:322–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Huang LK, Chao SP, Hu CJ. Clinical trials of new drugs for Alzheimer disease. J Biomed Sci. 2020;27:18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Brosius J. Waste not, want not-transcript excess in multicellular eukaryotes. Trends Genet. 2005;21:287–8.

    Article  CAS  PubMed  Google Scholar 

  8. Junn E, Mouradian MM. MicroRNAs in neurodegenerative diseases and their therapeutic potential. Pharm Ther. 2012;133:142–50.

    Article  CAS  Google Scholar 

  9. Qureshi IA, Mehler MF. Non-coding RNA networks underlying cognitive disorders across the lifespan. Trends Mol Med. 2011;17:337–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Ambros V, Bartel B, Bartel DP, Burge CB, Carrington JC, Chen X, et al. A uniform system for microRNA annotation. RNA. 2003;9:277–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Jiang W, Zhang Y, Meng F, Lian B, Chen X, Yu X, et al. Identification of active transcription factor and miRNA regulatory pathways in Alzheimer’s disease. Bioinformatics. 2013;29:2596–602.

    Article  CAS  PubMed  Google Scholar 

  12. Wang J, Chen C, Zhang Y. An investigation of microRNA-103 and microRNA-107 as potential blood-based biomarkers for disease risk and progression of Alzheimer’s disease. J Clin Lab Anal. 2020;34:e23006.

    PubMed  Google Scholar 

  13. Hu YB, Li CB, Song N, Zou Y, Chen SD, Ren RJ, et al. Diagnostic value of microRNA for Alzheimer’s disease: a systematic review and meta-analysis. Front Aging Neurosci. 2016;8:13.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Boissonneault V, Plante I, Rivest S, Provost P. MicroRNA-298 and MicroRNA-328 regulate expression of mouse beta-amyloid precursor protein-converting enzyme 1. J Biol Chem. 2009;284:1971–81.

    Article  CAS  PubMed  Google Scholar 

  15. Wang X, Liu D, Huang H-Z, Wang Z-H, Hou T-Y, Yang X, et al. A novel MicroRNA-124/PTPN1 signal pathway mediates synaptic and memory deficits in Alzheimer’s disease. Biol Psychiatry. 2018;83:395–405.

    Article  CAS  PubMed  Google Scholar 

  16. McKeever PM, Schneider R, Taghdiri F, Weichert A, Multani N, Brown RA, et al. MicroRNA expression levels are altered in the cerebrospinal fluid of patients with young-onset Alzheimer’s disease. Mol Neurobiol. 2018;55:8826–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kiko T, Nakagawa K, Tsuduki T, Furukawa K, Arai H, Miyazawa T. MicroRNAs in plasma and cerebrospinal fluid as potential markers for Alzheimer’s disease. J Alzheimers Dis. 2014;39:253–9.

    Article  CAS  PubMed  Google Scholar 

  18. Takousis P, Sadlon A, Schulz J, Wohlers I, Dobricic V, Middleton L, et al. Differential expression of microRNAs in Alzheimer’s disease brain, blood, and cerebrospinal fluid. Alzheimers Dement. 2019;15:1468–77.

    Article  PubMed  Google Scholar 

  19. Brain, blood, and cerebrospinal fluid microRNAs and noncoding RNAs in Alzheimer’s disease: a systematic review and meta-analysis. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020150993, 2020, Accessed Date Accessed 2020 Accessed.

  20. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Cochrane Handbook for Systematic Reviews of Interventions version 6.0. http://www.training.cochrane.org/handbook, 2019, Accessed Date Accessed 2019 Accessed.

  22. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp, 2012, Accessed Date Accessed 2012 Accessed.

  23. Li J, Han X, Wan Y, Zhang S, Zhao Y, Fan R, et al. TAM 2.0: tool for MicroRNA set analysis. Nucleic Acids Res. 2018;46:W180–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Idda ML, Munk R, Abdelmohsen K, Gorospe M. Noncoding RNAs in Alzheimer’s disease. Wiley Interdiscip Rev RNA. 2018;9:e1463.

    Article  Google Scholar 

  25. Millan MJ. Linking deregulation of non-coding RNA to the core pathophysiology of Alzheimer’s disease: An integrative review. Prog Neurobiol. 2017;156:1–68.

    Article  CAS  PubMed  Google Scholar 

  26. Kim C, Kang D, Lee EK, Lee JS. Long noncoding RNAs and RNA-binding proteins in oxidative stress, cellular senescence, and age-related diseases. Oxid Med Cell Longev. 2017;2017:2062384.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zhu Y, Wang L, Yin Y, Yang E. Systematic analysis of gene expression patterns associated with postmortem interval in human tissues. Sci Rep. 2017;7:5435.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Vella LJ, Greenwood DL, Cappai R, Scheerlinck JP, Hill AF. Enrichment of prion protein in exosomes derived from ovine cerebral spinal fluid. Vet Immunol Immunopathol. 2008;124:385–93.

    Article  CAS  PubMed  Google Scholar 

  29. Cuk K, Zucknick M, Heil J, Madhavan D, Schott S, Turchinovich A, et al. Circulating microRNAs in plasma as early detection markers for breast cancer. Int J Cancer. 2013;132:1602–12.

    Article  CAS  PubMed  Google Scholar 

  30. Mizuno H, Nakamura A, Aoki Y, Ito N, Kishi S, Yamamoto K, et al. Identification of muscle-specific microRNAs in serum of muscular dystrophy animal models: promising novel blood-based markers for muscular dystrophy. PLoS One. 2011;6:e18388.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Pigati L, Yaddanapudi SC, Iyengar R, Kim DJ, Hearn SA, Danforth D, et al. Selective release of microRNA species from normal and malignant mammary epithelial cells. PLoS One. 2010;5:e13515.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Jiang MC, Ni JJ, Cui WY, Wang BY, Zhuo W. Emerging roles of lncRNA in cancer and therapeutic opportunities. Am J Cancer Res. 2019;9:1354–66.

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Knebl J, DeFazio P, Clearfield MB, Little L, McConathy WJ, McPherson R, et al. Plasma lipids and cholesterol esterification in Alzheimer’s disease. Mech Ageing Dev. 1994;73:69–77.

    Article  CAS  PubMed  Google Scholar 

  34. Ginsberg L, Atack JR, Rapoport SI, Gershfeld NL. Regional specificity of membrane instability in Alzheimer’s disease brain. Brain Res. 1993;615:355–7.

    Article  CAS  PubMed  Google Scholar 

  35. Chang TY, Chang C. ApoE and lipid homeostasis in Alzheimer’s disease: introduction to the thematic review series. J Lipid Res. 2017;58:823.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Kitagishi Y, Nakanishi A, Ogura Y, Matsuda S. Dietary regulation of PI3K/AKT/GSK-3beta pathway in Alzheimer’s disease. Alzheimers Res Ther. 2014;6:35.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Roth KA. Caspases, apoptosis, and Alzheimer disease: causation, correlation, and confusion. J Neuropathol Exp Neurol. 2001;60:829–38.

    Article  CAS  PubMed  Google Scholar 

  38. Kumar A, Singh A. Ekavali. A review on Alzheimer’s disease pathophysiology and its management: an update. Pharmacol Rep. 2015;67:195–203.

    Article  CAS  PubMed  Google Scholar 

  39. Hardy J. The amyloid hypothesis for Alzheimer’s disease: a critical reappraisal. J Neurochem. 2009;110:1129–34.

    Article  CAS  PubMed  Google Scholar 

  40. Rosenmann H. Immunotherapy for targeting tau pathology in Alzheimer’s disease and tauopathies. Curr Alzheimer Res. 2013;10:217–28.

    Article  CAS  PubMed  Google Scholar 

  41. dos Santos P, Leide C, Ozela PF, de Fatima de Brito Brito M, Pinheiro AA, Padilha EC, et al. Alzheimer’s disease: a review from the pathophysiology to diagnosis, new perspectives for pharmacological treatment. Curr medicinal Chem. 2018;25:3141–59.

    Article  Google Scholar 

  42. Choi S-H, Aid S, Caracciolo L, Minami SS, Niikura T, Matsuoka Y, et al. Cyclooxygenase-1 inhibition reduces amyloid pathology and improves memory deficits in a mouse model of Alzheimer’s disease. J neurochemistry. 2013;124:59–68.

    Article  CAS  Google Scholar 

  43. Rice DB, Kloda LA, Levis B, Qi B, Kingsland E, Thombs BD. Are MEDLINE searches sufficient for systematic reviews and meta-analyses of the diagnostic accuracy of depression screening tools? A review of meta-analyses. J Psychosom Res. 2016;87:7–13.

    Article  PubMed  Google Scholar 

  44. Marshall IJ, Marshall R, Wallace BC, Brassey J, Thomas J. Rapid reviews may produce different results to systematic reviews: a meta-epidemiological study. J Clin Epidemiol. 2019;109:30–41.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This paper demonstrates independent research and all authors are acknowledged for their contributions to this study.

Author information

Author notes

  1. These authors contributed equally: Sojung Yoon, Sung Eun Kim.

Authors and Affiliations

  1. Yonsei University College of Medicine, Seoul, Republic of Korea

    Sojung Yoon, Sung Eun Kim & Sung Hwi Hong

  2. Division of Biomedical Engineering, Hankuk University of Foreign Studies, Kyoungki-do, Republic of Korea

    Younhee Ko

  3. College of Medicine, Gyeongsang National University, Jinju, Republic of Korea

    Gwang Hun Jeong

  4. Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea

    Keum Hwa Lee & Jae Il Shin

  5. Department of Psychiatry, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea

    Jinhee Lee

  6. Department of Psychiatry, University of Ottawa, Ontario, ON, Canada

    Marco Solmi

  7. Department of Mental Health, The Ottawa Hospital, Ontario, ON, Canada

    Marco Solmi

  8. Clinical Epidemiology Program, Ottawa Hospital Research Institute (OHRI), Ottawa, ON, Canada

    Marco Solmi

  9. School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada

    Marco Solmi

  10. Faculty of Medicine, University of Versailles Saint-Quentin-en-Yvelines, Montigny-le-Bretonneux, France

    Louis Jacob

  11. Parc Sanitari Sant Joan de Déu/CIBERSAM, Universitat de Barcelona, Fundació Sant Joan de Déu, Sant Boi de Llobregat, Barcelona, Spain

    Louis Jacob & Ai Koyanagi

  12. Centre for Health, Performance, and Wellbeing, Anglia Ruskin University, Cambridge, UK

    Lee Smith

  13. Department of Preventive Intervention for Psychiatric Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan

    Andrew Stickley

  14. Stockholm Center for Health and Social Change (SCOHOST), Södertörn University, Huddinge, Sweden

    Andrew Stickley

  15. Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada

    Andre F. Carvalho

  16. Department of Psychiatry, University of Toronto, Toronto, ON, Canada

    Andre F. Carvalho

  17. Pain and Rehabilitation Centre and Department of Health, Medicine and Caring Sciences, Linkoping University, Linkoping, Sweden

    Elena Dragioti

  18. Department of Medicine, University of Cambridge, Cambridge, UK

    Andreas Kronbichler

  19. ICREA, Pg. Lluis Companys 23, Barcelona, Spain

    Ai Koyanagi

  20. Centre of Chronic Illness and Ageing, University of Greenwich, London, UK

    Trevor Thompson

  21. Suzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA, 90015, USA

    Hans Oh

  22. Early Psychosis: Interventions and Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    Gonzalo Salazar de Pablo, Joaquim Radua & Paolo Fusar-Poli

  23. Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    Gonzalo Salazar de Pablo

  24. Institute of Psychiatry and Mental Health. Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), CIBERSAM, Madrid, Spain

    Gonzalo Salazar de Pablo

  25. Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain

    Joaquim Radua

  26. Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden

    Joaquim Radua

  27. Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy

    Paolo Fusar-Poli

  28. OASIS service, South London and Maudsley NHS Foundation Trust, London, UK

    Paolo Fusar-Poli

  29. National Institute of Health Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK

    Paolo Fusar-Poli

Authors
  1. Sojung Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sung Eun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Younhee Ko
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gwang Hun Jeong
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Keum Hwa Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jinhee Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Marco Solmi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Louis Jacob
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Lee Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Andrew Stickley
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Andre F. Carvalho
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Elena Dragioti
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Andreas Kronbichler
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Ai Koyanagi
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Sung Hwi Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Trevor Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Hans Oh
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Gonzalo Salazar de Pablo
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Joaquim Radua
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Jae Il Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Paolo Fusar-Poli
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SY and JIS designed the study. SY, SUK and JIS searched the literature, and extracted data. Any discrepancies were resolved via discussion between SY, SUK and JIS. SY, SUK, YK, GHJ, KHL and JIS undertook the statistical analyses and interpreted the data. SY and SUK made the figures and tables. All authors drafted and critically revised the manuscript. All authors approved the final version of the manuscript for publication.

Corresponding author

Correspondence to Jae Il Shin.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised: In this article the affiliation details for Author JAE IL SHIN were incorrectly given as ‘Department of Psychiatry, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea’ but should have been ‘Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea’.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yoon, S., Kim, S.E., Ko, Y. et al. Differential expression of MicroRNAs in Alzheimer’s disease: a systematic review and meta-analysis. Mol Psychiatry 27, 2405–2413 (2022). https://doi.org/10.1038/s41380-022-01476-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-022-01476-z

This article is cited by

Search

Advanced search

Quick links