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Plasma Oligomer β-Amyloid and White Matter Microstructural Integrity in Cognitively Normal Older Adults According to Cerebral Amyloid Deposition

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The Journal of Prevention of Alzheimer's Disease Aims and scope Submit manuscript

Abstract

Background

Multimer detection system-oligomeric amyloid-β (MDS-OAβ) measure plasma OAβ level, which is associated with earlier Alzheimer’s disease (AD) pathology. However, no study has investigated MDS-OAβ differences in cognitive normal older adults (CN) with or without cerebral Aβ burden and its correlation with Aβ deposition and white matter (WM) integrity.

Objective

To investigate associations among cerebral Aβ burden, MDS-OAβ, and WM integrity in CN.

Design

This is a single center, cross-sectional study which used data from Catholic Aging Brain Imaging (CABI) database.

Setting

CABI database contains brain scans of patients who visited the outpatient clinic at Catholic Brain Health Center, Yeouido St. Mary’s Hospital, The Catholic University of Korea, between 2017 and 2022.

Participants

A total 34 amyloid-PET negative CN and 23 amyloid-PET positive CN were included.

Measurements

Plasma Aβ level using MDS-OAβ, cerebral Aβ deposition level using global standardized uptake value ratio (SUVR) values, WM integrity using fractional anisotropy (FA) and mean diffusivity (MD), and cortical thickness from structural MRI were utilized.

Restuls

The amyloid-PET positive group showed higher MDS-OAβ level than the amyloid-PET negative group (0.997 ± 0.19 vs. 0.79 ± 0.28, P <0.005), but they did not differ in WM integrity or cortical thickness. The MDS-OAβ positive group showed higher global cerebral Aβ deposition or mean global SUVR values (0.609 ± 0.135 vs. 0.533 ± 0.121 vs. P <0.05), lower regional FA of left forceps minor and the right superior longitudinal fasciculus (family-wise error rate, p <0.05), and lower cortical thickness of left fusiform (p <0.05, Monte Carlo simulation) than the MDS-OAβ negative group. MDS-OAβ was positively associated with global cerebral Aβ deposition (r=0.278, P <0.05) and negatively associated (r = − 0.324, P < 0.05) with regional WM integrity.

Conclusions

In this study, MDS-OAβ value demonstrated earlier and different AD pathology than cerebral Aβ retention according to amyloid-PET. Longitudinal studies are needed to elucidate the causal relationships of plasma OAβ and cerebral Aβ with WM integrity disturbance and cortical atrophy during the AD trajectory.

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References

  1. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of 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(3):280–92. doi:https://doi.org/10.1016/j.jalz.2011.03.003

    Article  PubMed  PubMed Central  Google Scholar 

  2. Erickson CM, Clark LR, Ketchum FB, Chin NA, Gleason CE, Largent EA. Implications of preclinical Alzheimer’s disease biomarker disclosure for US policy and society. Alzheimers Dement (Amst). 2022;14(1):e12339. doi:https://doi.org/10.1002/dad2.12339 doi: https://doi.org/10.1002/dad2.12339

    Article  PubMed  Google Scholar 

  3. Jack CR, Jr., Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535–62. doi:https://doi.org/10.1016/j.jalz.2018.02.018

    Article  PubMed  PubMed Central  Google Scholar 

  4. Janelidze S, Teunissen CE, Zetterberg H, Allue JA, Sarasa L, Eichenlaub U, et al. Head-to-Head Comparison of 8 Plasma Amyloid-beta 42/40 Assays in Alzheimer Disease. JAMA Neurol. 2021;78(11):1375–82. doi:https://doi.org/10.1001/jamaneurol.2021.3180

    Article  PubMed  Google Scholar 

  5. Chen GF, Xu TH, Yan Y, Zhou YR, Jiang Y, Melcher K, et al. Amyloid beta: structure, biology and structure-based therapeutic development. Acta Pharmacol Sin. 2017;38(9):1205–35. doi:https://doi.org/10.1038/aps.2017.28

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Cline EN, Bicca MA, Viola KL, Klein WL. The Amyloid-beta Oligomer Hypothesis: Beginning of the Third Decade. J Alzheimers Dis. 2018;64(s1):S567–S610. doi:https://doi.org/10.3233/JAD-179941

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Hanseeuw BJ, Betensky RA, Jacobs HIL, Schultz AP, Sepulcre J, Becker JA, et al. Association of Amyloid and Tau With Cognition in Preclinical Alzheimer Disease: A Longitudinal Study. JAMA Neurol. 2019;76(8):915–24. doi:https://doi.org/10.1001/jamaneurol.2019.1424

    Article  PubMed  PubMed Central  Google Scholar 

  8. An SSA, Lee BS, Yu JS, Lim K, Kim GJ, Lee R, et al. Dynamic changes of oligomeric amyloid beta levels in plasma induced by spiked synthetic Abeta42. Alzheimers Res Ther. 2017;9(1):86. doi:https://doi.org/10.1186/s13195-017-0310-6

    Article  PubMed  PubMed Central  Google Scholar 

  9. An SS, Lim KT, Oh HJ, Lee BS, Zukic E, Ju YR, et al. Differentiating blood samples from scrapie infected and non-infected hamsters by detecting disease-associated prion proteins using Multimer Detection System. Biochem Biophys Res Commun. 2010;392(4):505–9. doi:https://doi.org/10.1016/j.bbrc.2010.01.053

    Article  CAS  PubMed  Google Scholar 

  10. Lim K, Kim SY, Lee B, Segarra C, Kang S, Ju Y, et al. Magnetic microparticle-based multimer detection system for the detection of prion oligomers in sheep. Int J Nanomedicine. 2015;10(Spec Iss):241–50. doi:https://doi.org/10.2147/IJN.S88377

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Wang MJ, Yi S, Han JY, Park SY, Jang JW, Chun IK, et al. Oligomeric forms of amyloid-beta protein in plasma as a potential blood-based biomarker for Alzheimer’s disease. Alzheimers Res Ther. 2017;9(1):98. doi:https://doi.org/10.1186/s13195-017-0324-0

    Article  PubMed  PubMed Central  Google Scholar 

  12. Meng X, Li T, Wang X, Lv X, Sun Z, Zhang J, et al. Association between increased levels of amyloid-beta oligomers in plasma and episodic memory loss in Alzheimer’s disease. Alzheimers Res Ther. 2019;11(1):89. doi:https://doi.org/10.1186/s13195-019-0535-7

    Article  PubMed  PubMed Central  Google Scholar 

  13. Lee JJ, Choi Y, Chung S, Yoon DH, Choi SH, Kang SM, et al. Association of Plasma Oligomerized Beta Amyloid with Neurocognitive Battery Using Korean Version of Consortium to Establish a Registry for Alzheimer’s Disease in Health Screening Population. Diagnostics (Basel). 2020;10(4). doi:https://doi.org/10.3390/diagnostics10040237

  14. Youn YC, Kang S, Suh J, Park YH, Kang MJ, Pyun JM, et al. Blood amyloid-beta oligomerization associated with neurodegeneration of Alzheimer’s disease. Alzheimers Res Ther. 2019;11(1):40. doi:https://doi.org/10.1186/s13195-019-0499-7

    Article  PubMed  PubMed Central  Google Scholar 

  15. Nishioka C, Liang HF, Barsamian B, Sun SW. Amyloid-beta induced retrograde axonal degeneration in a mouse tauopathy model. Neuroimage. 2019;189:180–91. doi:https://doi.org/10.1016/j.neuroimage.2019.01.007

    Article  CAS  PubMed  Google Scholar 

  16. Salvadores N, Geronimo-Olvera C, Court FA. Axonal Degeneration in AD: The Contribution of Abeta and Tau. Front Aging Neurosci. 2020;12:581767. doi:https://doi.org/10.3389/fnagi.2020.581767

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Alobuia WM, Xia W, Vohra BP. Axon degeneration is key component of neuronal death in amyloid-beta toxicity. Neurochem Int. 2013;63(8):782–9. doi:https://doi.org/10.1016/j.neuint.2013.08.013

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Dean DC, 3rd, Hurley SA, Kecskemeti SR, O’Grady JP, Canda C, Davenport-Sis NJ, et al. Association of Amyloid Pathology With Myelin Alteration in Preclinical Alzheimer Disease. JAMA Neurol. 2017;74(1):41–9. doi:https://doi.org/10.1001/jamaneurol.2016.3232

    Article  PubMed  PubMed Central  Google Scholar 

  19. Collins-Praino LE, Francis YI, Griffith EY, Wiegman AF, Urbach J, Lawton A, et al. Soluble amyloid beta levels are elevated in the white matter of Alzheimer’s patients, independent of cortical plaque severity. Acta Neuropathol Commun. 2014;2:83. doi:https://doi.org/10.1186/s40478-014-0083-0

    PubMed  PubMed Central  Google Scholar 

  20. Quintela-Lopez T, Ortiz-Sanz C, Serrano-Regal MP, Gaminde-Blasco A, Valero J, Baleriola J, et al. Abeta oligomers promote oligodendrocyte differentiation and maturation via integrin beta1 and Fyn kinase signaling. Cell Death Dis. 2019;10(6):445. doi:https://doi.org/10.1038/s41419-019-1636-8

    Article  PubMed  PubMed Central  Google Scholar 

  21. Hutton C, Draganski B, Ashburner J, Weiskopf N. A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging. Neuroimage. 2009;48(2):371–80. doi:https://doi.org/10.1016/j.neuroimage.2009.06.043

    Article  PubMed  Google Scholar 

  22. Lee JH, Lee KU, Lee DY, Kim KW, Jhoo JH, Kim JH, et al. Development of the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease Assessment Packet (CERAD-K): clinical and neuropsychological assessment batteries. J Gerontol B Psychol Sci Soc Sci. 2002;57(1):P47–53. doi:https://doi.org/10.1093/geronb/57.1.p47

    Article  PubMed  Google Scholar 

  23. Babapour Mofrad R, Scheltens P, Kim S, Kang S, Youn YC, An SSA, et al. Plasma amyloid-beta oligomerization assay as a pre-screening test for amyloid status. Alzheimers Res Ther. 2021;13(1):133. doi:https://doi.org/10.1186/s13195-021-00873-w

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Thurfjell L, Lilja J, Lundqvist R, Buckley C, Smith A, Vandenberghe R, et al. Automated quantification of 18F-flutemetamol PET activity for categorizing scans as negative or positive for brain amyloid: concordance with visual image reads. J Nucl Med. 2014;55(10):1623–8. doi:https://doi.org/10.2967/jnumed.114.142109

    Article  CAS  PubMed  Google Scholar 

  25. Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. 2006;31(4):1487–505. doi:https://doi.org/10.1016/j.neuroimage.2006.02.024

    Article  PubMed  Google Scholar 

  26. Liu Y, Spulber G, Lehtimaki KK, Kononen M, Hallikainen I, Grohn H, et al. Diffusion tensor imaging and tract-based spatial statistics in Alzheimer’s disease and mild cognitive impairment. Neurobiol Aging. 2011;32(9):1558–71. doi:https://doi.org/10.1016/j.neurobiolaging.2009.10.006

    Article  PubMed  Google Scholar 

  27. Zhan L, Leow AD, Zhu S, Baryshev M, Toga AW, McMahon KL, et al. A novel measure of fractional anisotropy based on the tensor distribution function. Med Image Comput Comput Assist Interv. 2009;12(Pt 1):845–52. doi:https://doi.org/10.1007/978-3-642-04268-3_104

    PubMed  Google Scholar 

  28. Yang FPG, Bal SS, Lee JF, Chen CC. White Matter Differences in Networks in Elders with Mild Cognitive Impairment and Alzheimer’s Disease. Brain Connect. 2021;11(3):180–8. doi:https://doi.org/10.1089/brain.2020.0767

    Article  PubMed  Google Scholar 

  29. Lim HK, Jung WS, Ahn KJ, Won WY, Hahn C, Lee SY, et al. Regional cortical thickness and subcortical volume changes are associated with cognitive impairments in the drug-naive patients with late-onset depression. Neuropsychopharmacology. 2012;37(3):838–49. doi:https://doi.org/10.1038/npp.2011.264

    Article  PubMed  Google Scholar 

  30. Fischl B, Dale AM. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A. 2000;97(20):11050–5. doi:https://doi.org/10.1073/pnas.200033797

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. The jamovi project (2023). jamovi (Version 2.3.210) [Computer Software]. Retrieved from https://www.jamovi.org

  32. Krause-Sorio B, Siddarth P, Kilpatrick L, Milillo MM, Aguilar-Faustino Y, Ercoli L, et al. Yoga Prevents Gray Matter Atrophy in Women at Risk for Alzheimer’s Disease: A Randomized Controlled Trial. J Alzheimers Dis. 2022;87(2):569–81. doi:https://doi.org/10.3233/JAD-215563

    Article  PubMed  PubMed Central  Google Scholar 

  33. Kim KY, Park J, Jeong YH, Kim HJ, Lee E, Park JY, et al. Plasma amyloid-beta oligomer is related to subjective cognitive decline and brain amyloid status. Alzheimers Res Ther. 2022;14(1):162. doi:https://doi.org/10.1186/s13195-022-01104-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Zott B, Simon MM, Hong W, Unger F, Chen-Engerer HJ, Frosch MP, et al. A vicious cycle of beta amyloid-dependent neuronal hyperactivation. Science. 2019;365(6453):559–65. doi:https://doi.org/10.1126/science.aay0198

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Li S, Jin M, Koeglsperger T, Shepardson NE, Shankar GM, Selkoe DJ. Soluble Abeta oligomers inhibit long-term potentiation through a mechanism involving excessive activation of extrasynaptic NR2B-containing NMDA receptors. J Neurosci. 2011;31(18):6627–38. doi:https://doi.org/10.1523/JNEUROSCI.0203-11.2011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wang PN, Chou KH, Chang NJ, Lin KN, Chen WT, Lan GY, et al. Callosal degeneration topographically correlated with cognitive function in amnestic mild cognitive impairment and Alzheimer’s disease dementia. Hum Brain Mapp. 2014;35(4):1529–43. doi:https://doi.org/10.1002/hbm.22271

    Article  CAS  PubMed  Google Scholar 

  37. Racine AM, Adluru N, Alexander AL, Christian BT, Okonkwo OC, Oh J, et al. Associations between white matter microstructure and amyloid burden in preclinical Alzheimer’s disease: A multimodal imaging investigation. Neuroimage Clin. 2014;4:604–14. doi:https://doi.org/10.1016/j.nicl.2014.02.001

    Article  PubMed  PubMed Central  Google Scholar 

  38. Chao LL, Decarli C, Kriger S, Truran D, Zhang Y, Laxamana J, et al. Associations between white matter hyperintensities and beta amyloid on integrity of projection, association, and limbic fiber tracts measured with diffusion tensor MRI. PLoS One. 2013;8(6):e65175. doi:https://doi.org/10.1371/journal.pone.0065175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Wolf D, Fischer FU, Scheurich A, Fellgiebel A, Alzheimer’s Disease Neuroimaging I. Non-Linear Association between Cerebral Amyloid Deposition and White Matter Microstructure in Cognitively Healthy Older Adults. J Alzheimers Dis. 2015;47(1):117–27. doi:https://doi.org/10.3233/JAD-150049

    Article  CAS  PubMed  Google Scholar 

  40. Gold BT, Zhu Z, Brown CA, Andersen AH, LaDu MJ, Tai L, et al. White matter integrity is associated with cerebrospinal fluid markers of Alzheimer’s disease in normal adults. Neurobiol Aging. 2014;35(10):2263–71. doi:https://doi.org/10.1016/j.neurobiolaging.2014.04.030

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Madhavan A, Schwarz CG, Duffy JR, Strand EA, Machulda MM, Drubach DA, et al. Characterizing White Matter Tract Degeneration in Syndromic Variants of Alzheimer’s Disease: A Diffusion Tensor Imaging Study. J Alzheimers Dis. 2016;49(3):633–43. doi:https://doi.org/10.3233/JAD-150502

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Mayo CD, Mazerolle EL, Ritchie L, Fisk JD, Gawryluk JR, Alzheimer’s Disease Neuroimaging I. Longitudinal changes in microstructural white matter metrics in Alzheimer’s disease. Neuroimage Clin. 2017;13:330–8. doi:https://doi.org/10.1016/j.nicl.2016.12.012

    Article  PubMed  Google Scholar 

  43. Alexander AL, Hurley SA, Samsonov AA, Adluru N, Hosseinbor AP, Mossahebi P, et al. Characterization of cerebral white matter properties using quantitative magnetic resonance imaging stains. Brain Connect. 2011;1(6):423–46. doi:https://doi.org/10.1089/brain.2011.0071

    Article  PubMed  PubMed Central  Google Scholar 

  44. Desai MK, Sudol KL, Janelsins MC, Mastrangelo MA, Frazer ME, Bowers WJ. Triple-transgenic Alzheimer’s disease mice exhibit region-specific abnormalities in brain myelination patterns prior to appearance of amyloid and tau pathology. Glia. 2009;57(1):54–65. doi:https://doi.org/10.1002/glia.20734

    Article  PubMed  PubMed Central  Google Scholar 

  45. Mormino EC, Kluth JT, Madison CM, Rabinovici GD, Baker SL, Miller BL, et al. Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects. Brain. 2009;132(Pt 5):1310–23. doi:https://doi.org/10.1093/brain/awn320

    Article  CAS  PubMed  Google Scholar 

  46. Chetelat G, Villemagne VL, Pike KE, Baron JC, Bourgeat P, Jones G, et al. Larger temporal volume in elderly with high versus low beta-amyloid deposition. Brain. 2010;133(11):3349–58. doi:https://doi.org/10.1093/brain/awq187

    Article  PubMed  Google Scholar 

  47. Shankar GM, Li S, Mehta TH, Garcia-Munoz A, Shepardson NE, Smith I, et al. Amyloid-beta protein dimers isolated directly from Alzheimer’s brains impair synaptic plasticity and memory. Nat Med. 2008;14(8):837–42. doi:https://doi.org/10.1038/nm1782

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Soderberg L, Johannesson M, Nygren P, Laudon H, Eriksson F, Osswald G, et al. Lecanemab, Aducanumab, and Gantenerumab - Binding Profiles to Different Forms of Amyloid-Beta Might Explain Efficacy and Side Effects in Clinical Trials for Alzheimer’s Disease. Neurotherapeutics. 2022. doi:https://doi.org/10.1007/s13311-022-01308-6

  49. Swanson CJ, Zhang Y, Dhadda S, Wang J, Kaplow J, Lai RYK, et al. A randomized, double-blind, phase 2b proof-of-concept clinical trial in early Alzheimer’s disease with lecanemab, an anti-Abeta protofibril antibody. Alzheimers Res Ther. 2021;13(1):80. doi:https://doi.org/10.1186/s13195-021-00813-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Ma D, Fetahu IS, Wang M, Fang R, Li J, Liu H, et al. The fusiform gyrus exhibits an epigenetic signature for Alzheimer’s disease. Clin Epigenetics. 2020;12(1):129. doi:https://doi.org/10.1186/s13148-020-00916-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Koychev I, Hofer M, Friedman N. Correlation of Alzheimer Disease Neuropathologic Staging with Amyloid and Tau Scintigraphic Imaging Biomarkers. J Nucl Med. 2020;61(10):1413–8. doi:https://doi.org/10.2967/jnumed.119.230458

    Article  CAS  PubMed  Google Scholar 

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Acknowledgement

We thank So Jung Kim, a researcher of the Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea, for her help in acquisition of blood samples.

Funding

Funding: This research was funded by Peoplebio inc. This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MIST) (No. 2022R1A2C109321512) and by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) and Korea Dementia Research Center (KDRC), funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (grant number: HU22C0011). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

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Authors and Affiliations

Authors

Contributions

Authors’ contributions: Author Hyun Kook Lim had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Sheng-Min Wang and Hyun Kook Lim drafted the manuscript and contributed to project design, data collection, management, analysis, and interpretation. Yoo Hyun Um and Dong Woo Kang contributed to project design, data collection, and management. Chang Uk Lee and Philip Scheltens contributed to data management and revision of the manuscript.

Corresponding author

Correspondence to Hyun Kook Lim.

Ethics declarations

Conflict of interest disclosure: Dr Scheltens is a full-time employee of EQT Life Sciences (formerly LSP) and Professor Emeritus at Amsterdam University Medical Centers. He has received consultancy fees (paid to the university) from Alzheon, Brainstorm Cell and Green Valley. Within his university affiliation he is global PI of the phase 1b study of AC Immune, Phase 2b study with FUJI-film/Toyama, phase 2 study of UCB and co-chair of the phase 3 study with NOVO-Nordisk. Until November 2022 he acted as chair of the EU steering committee of the phase 2b program of Vivoryon and the phase 2b study of Novartis Cardiology.

Ethical standards: The study was conducted in accordance with ethical and safety guidelines set forth by the Institutional Review Board of Yeouido St. Mary’s Hospital, The Catholic University of Korea (IRB number: SC18TNSI0063). All subjects provided written informed consent.

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Wang, SM., Kang, D.W., Um, Y.H. et al. Plasma Oligomer β-Amyloid and White Matter Microstructural Integrity in Cognitively Normal Older Adults According to Cerebral Amyloid Deposition. J Prev Alzheimers Dis 10, 837–846 (2023). https://doi.org/10.14283/jpad.2023.87

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