Skip to main content

Advertisement

SpringerLink
Log in

Temporal trajectories of in vivo tau and amyloid-β accumulation in Alzheimer’s disease

  • Original Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

To investigate the temporal trajectories of tau and amyloid-β (Aβ) accumulation in Alzheimer’s disease (AD) by using the longitudinal positron emission tomography (PET) study.

Methods

A total of 132 participants, who were healthy volunteers or recruited in our memory disorder clinic, completed longitudinal 18F-flortaucipir and 18F-florbetaben PET studies with a mean follow-up time of 2 years. Referencing baseline data from 57 Aβ-negative cognitively unimpaired individuals, Z-scores and their annual changes were calculated with the global cortical or regional standardized uptake value ratios measured at baseline and follow-up after correcting for partial volume effect. The temporal trajectories of tau and Aβ burden as a function of time were obtained based on the spline models from the annual changes and baseline Z-score data.

Results

Tau burden first emerged in the Braak’s stage I–II regions, followed by stage III–IV regions, and finally in the stage V–VI regions. Time intervals between two time points at which Z-score curves rose above 2 were 17.3 years for the stages I–II and III–IV and 15.2 years for the stages III–IV and V–VI. Rise in the tau curve for stages I–II preceded that for global cortical Aβ, while the rise in global cortical Aβ curve preceded that for global cortical tau. Aβ accumulation rate was attenuated during the surge in tau burden in the global cortex and reached a plateau.

Conclusion

Sequential appearance of Aβ and tau accumulation supports a hypothetical dynamic biomarker model and Braak’s hierarchical tau spreading model in AD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Ingelsson M, Fukumoto H, Newell KL, Growdon JH, Hedley-Whyte ET, Frosch MP, et al. Early Abeta accumulation and progressive synaptic loss, gliosis, and tangle formation in AD brain. Neurology. 2004;62:925–31.

    Article  CAS  Google Scholar 

  2. Markesbery WR, Schmitt FA, Kryscio RJ, Davis DG, Smith CD, Wekstein DR. Neuropathologic substrate of mild cognitive impairment. Arch Neurol. 2006;63:38–46.

    Article  Google Scholar 

  3. Tapiola T, Alafuzoff I, Herukka SK, Parkkinen L, Hartikainen P, Soininen H, et al. Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol. 2009;66:382–9.

    Article  Google Scholar 

  4. Buchhave P, Minthon L, Zetterberg H, Wallin AK, Blennow K, Hansson O. Cerebrospinal fluid levels of beta-amyloid 1-42, but not of tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia. Arch Gen Psychiatry. 2012;69:98–106.

    Article  CAS  Google Scholar 

  5. Caroli A, Frisoni GB. Alzheimer's disease neuroimaging I. The dynamics of Alzheimer's disease biomarkers in the Alzheimer's disease neuroimaging initiative cohort. Neurobiol Aging. 2010;31:1263–74.

    Article  CAS  Google Scholar 

  6. Lo RY, Hubbard AE, Shaw LM, Trojanowski JQ, Petersen RC, Aisen PS, et al. Longitudinal change of biomarkers in cognitive decline. Arch Neurol. 2011;68:1257–66.

    Article  Google Scholar 

  7. Toledo JB, Xie SX, Trojanowski JQ, Shaw LM. Longitudinal change in CSF tau and Abeta biomarkers for up to 48 months in ADNI. Acta Neuropathol. 2013;126:659–70.

    Article  CAS  Google Scholar 

  8. Yang E, Farnum M, Lobanov V, Schultz T, Verbeeck R, Raghavan N, et al. Quantifying the pathophysiological timeline of Alzheimer's disease. J Alzheimers Dis. 2011;26:745–53.

    Article  Google Scholar 

  9. Jack CR Jr, Vemuri P, Wiste HJ, Weigand SD, Aisen PS, Trojanowski JQ, et al. Evidence for ordering of Alzheimer disease biomarkers. Arch Neurol. 2011;68:1526–35.

    Article  Google Scholar 

  10. 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;5:228–34.

    Article  CAS  Google Scholar 

  11. Mattsson N, Zetterberg H, Hansson O, Andreasen N, Parnetti L, Jonsson M, et al. CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA. 2009;302:385–93.

    Article  CAS  Google Scholar 

  12. Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, et al. Imaging brain amyloid in Alzheimer's disease with Pittsburgh compound-B. Ann Neurol. 2004;55:306–19.

    Article  CAS  Google Scholar 

  13. Villain N, Chetelat G, Grassiot B, Bourgeat P, Jones G, Ellis KA, et al. Regional dynamics of amyloid-beta deposition in healthy elderly, mild cognitive impairment and Alzheimer's disease: a voxelwise PiB-PET longitudinal study. Brain. 2012;135:2126–39.

    Article  Google Scholar 

  14. Cho H, Choi JY, Hwang MS, Kim YJ, Lee HM, Lee HS, et al. In vivo cortical spreading pattern of tau and amyloid in the Alzheimer disease spectrum. Ann Neurol. 2016;80:247–58.

    Article  CAS  Google Scholar 

  15. Cho H, Choi JY, Hwang MS, Lee JH, Kim YJ, Lee HM, et al. Tau PET in Alzheimer disease and mild cognitive impairment. Neurology. 2016;87:375–83.

    Article  CAS  Google Scholar 

  16. Jack CR Jr, Wiste HJ, Schwarz CG, Lowe VJ, Senjem ML, Vemuri P, et al. Longitudinal tau PET in ageing and Alzheimer's disease. Brain. 2018;141:1517–28.

    Article  Google Scholar 

  17. Southekal S, Devous MD Sr, Kennedy I, Navitsky M, Lu M, Joshi AD, et al. Flortaucipir F 18 quantitation using parametric estimation of reference signal intensity. J Nucl Med. 2018;59:944–51.

    Article  CAS  Google Scholar 

  18. Jack CR Jr, Wiste HJ, Lesnick TG, Weigand SD, Knopman DS, Vemuri P, et al. Brain beta-amyloid load approaches a plateau. Neurology. 2013;80:890–6.

    Article  CAS  Google Scholar 

  19. Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O, et al. Amyloid beta deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study. Lancet Neurol. 2013;12:357–67.

    Article  CAS  Google Scholar 

  20. Harrison TM, La Joie R, Maass A, Baker SL, Swinnerton K, Fenton L, et al. Longitudinal tau accumulation and atrophy in aging and alzheimer disease. Ann Neurol. 2019;85:229–40.

    Article  CAS  Google Scholar 

  21. Cho H, Choi JY, Lee HS, Lee JH, Ryu YH, Lee MS, et al. Progressive tau accumulation in Alzheimer disease: 2-year follow-up study. J Nucl Med. 2019;60:1611–21.

    Article  CAS  Google Scholar 

  22. Kang Y, Na DL. Seoul neuropsychological screening battery (SNSB). Incheon: Human Brain Research & Consulting Co.; 2003.

    Google Scholar 

  23. Sabri O, Sabbagh MN, Seibyl J, Barthel H, Akatsu H, Ouchi Y, et al. Florbetaben PET imaging to detect amyloid beta plaques in Alzheimer's disease: phase 3 study. Alzheimers Dement. 2015;11:964–74.

    Article  Google Scholar 

  24. Villemagne VL, Ong K, Mulligan RS, Holl G, Pejoska S, Jones G, et al. Amyloid imaging with (18)F-florbetaben in Alzheimer disease and other dementias. J Nucl Med. 2011;52:1210–7.

    Article  Google Scholar 

  25. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7:263–9.

    Article  Google Scholar 

  26. Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7:270–9.

    Article  Google Scholar 

  27. Thomas BA, Erlandsson K, Modat M, Thurfjell L, Vandenberghe R, Ourselin S, et al. The importance of appropriate partial volume correction for PET quantification in Alzheimer's disease. Eur J Nucl Med Mol Imaging. 2011;38:1104–19.

    Article  Google Scholar 

  28. Donohue MC, Jacqmin-Gadda H, Le Goff M, Thomas RG, Raman R, Gamst AC, et al. Estimating long-term multivariate progression from short-term data. Alzheimers Dement. 2014;10:S400–10.

    PubMed  PubMed Central  Google Scholar 

  29. Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82:239–59.

    Article  CAS  Google Scholar 

  30. La Joie R, Bejanin A, Fagan AM, Ayakta N, Baker SL, Bourakova V, et al. Associations between [(18)F]AV1451 tau PET and CSF measures of tau pathology in a clinical sample. Neurology. 2018;90:e282–e90.

    Article  Google Scholar 

  31. Cho H, Lee HS, Choi JY, Lee JH, Ryu YH, Lee MS, et al. Predicted sequence of cortical tau and amyloid-beta deposition in Alzheimer disease spectrum. Neurobiol Aging. 2018;68:76–84.

    Article  CAS  Google Scholar 

  32. Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12:207–16.

    Article  CAS  Google Scholar 

  33. Crary JF, Trojanowski JQ, Schneider JA, Abisambra JF, Abner EL, Alafuzoff I, et al. Primary age-related tauopathy (PART): a common pathology associated with human aging. Acta Neuropathol. 2014;128:755–66.

    Article  CAS  Google Scholar 

  34. Duyckaerts C, Braak H, Brion JP, Buee L, Del Tredici K, Goedert M, et al. PART is part of Alzheimer disease. Acta Neuropathol. 2015;129:749–56.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We express our special appreciation to Tae Ho Song and Won Taek Lee (PET technologists) who managed all PET scans with enthusiasm.

Funding

This research was supported by a grant from Korean Neurological Association (KNA-19-MI-12), faculty research grant of Yonsei University College of Medicine for (6-2018-0068), Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2017R1A2B2006694) and the Ministry of Education (NRF-2018R1D1A1B07049386), and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI18C1159).

Author information

Author notes

  1. Min Seok Baek and Hanna Cho contributed equally to this work.

Authors and Affiliations

  1. Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea

    Min Seok Baek, Hanna Cho, Myung Sik Lee & Chul Hyoung Lyoo

  2. Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea

    Hye Sun Lee

  3. Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea

    Jae Yong Choi, Jae Hoon Lee & Young Hoon Ryu

  4. Division of RI-Convergence Research, Korea Institute Radiological and Medical Sciences, Seoul, South Korea

    Jae Yong Choi

Authors
  1. Min Seok Baek
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hanna Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hye Sun Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jae Yong Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jae Hoon Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Young Hoon Ryu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Myung Sik Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Chul Hyoung Lyoo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Y. H. Ryu Conception and design, Administrative support, Collection and assembly of data, Data analysis and interpretation, Supervision, Final approval of manuscript

C. H. Lyoo Conception and design, Administrative support, Collection and assembly of data, Data analysis and interpretation, Manuscript writing, Final approval of manuscript

Corresponding authors

Correspondence to Young Hoon Ryu or Chul Hyoung Lyoo.

Ethics declarations

Competing interests

The authors declare that they have no competing interests.

Ethics approval and consent to participate

This study was approved by the institutional review board of Gangnam Severance Hospital and written informed consent was obtained from all participants.

Additional information

Publisher’s note

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

This article is part of the Topical Collection on Neurology

Electronic supplementary material

ESM 1

(DOC 648 kb)

ESM 2

(DOC 427 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baek, M., Cho, H., Lee, H. et al. Temporal trajectories of in vivo tau and amyloid-β accumulation in Alzheimer’s disease. Eur J Nucl Med Mol Imaging 47, 2879–2886 (2020). https://doi.org/10.1007/s00259-020-04773-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-020-04773-3

Keywords

Search

Navigation