Convergence of Accelerated Brain Volume Decline in Normal Aging and Alzheimer's Disease Pathology

Overview

Journal J Alzheimers Dis

Publisher Sage Publications

Specialties Geriatrics
Neurology

Date 2024 Aug 23

PMID 39177595

Authors

Barbara Avelar-Pereira

Curran Michael Phillips

S M Hadi Hosseini

Affiliations

Soon will be listed here.

Abstract

Background: Age represents the largest risk factor for Alzheimer's disease (AD) but is typically treated as a covariate. Still, there are similarities between brain regions affected in AD and those showing accelerated decline in normal aging, suggesting that the distinction between the two might fall on a spectrum.

Objective: Our goal was to identify regions showing accelerated atrophy across the brain and investigate whether these overlapped with regions involved in AD or where related to amyloid.

Methods: We used a longitudinal sample of 137 healthy older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), who underwent magnetic resonance imaging (MRI). In addition, a total of 79 participants also had longitudinal positron emission tomography (PET) data. We computed linear-mixed effects models for brain regions declining faster than the average to investigate variability in the rate of change.

Results: 23 regions displayed a 0.5 standard deviation (SD) above average decline over 2 years. Of these, 52% overlapped with regions showing similar decline in a matched AD sample. Beyond this, the left precuneus, right superior frontal, transverse temporal, and superior temporal sulcus showed accelerated decline. Lastly, atrophy in the precuneus was associated with increased amyloid load.

Conclusions: Accelerated decline in normal aging might contribute to the detection of early signs of AD among healthy individuals.

References

Cho H, Choi J, Hwang M, Kim Y, Lee H, Lee H . In vivo cortical spreading pattern of tau and amyloid in the Alzheimer disease spectrum. Ann Neurol. 2016; 80(2):247-58. DOI: 10.1002/ana.24711. View

Veitch D, Weiner M, Aisen P, Beckett L, Cairns N, Green R . Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative. Alzheimers Dement. 2018; 15(1):106-152. DOI: 10.1016/j.jalz.2018.08.005. View

Stoub T, Bulgakova M, Leurgans S, Bennett D, Fleischman D, Turner D . MRI predictors of risk of incident Alzheimer disease: a longitudinal study. Neurology. 2005; 64(9):1520-4. DOI: 10.1212/01.WNL.0000160089.43264.1A. View

Petersen R, Aisen P, Beckett L, Donohue M, Gamst A, Harvey D . Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology. 2010; 74(3):201-9. PMC: 2809036. DOI: 10.1212/WNL.0b013e3181cb3e25. View

Herrup K . Reimagining Alzheimer's disease--an age-based hypothesis. J Neurosci. 2010; 30(50):16755-62. PMC: 3004746. DOI: 10.1523/JNEUROSCI.4521-10.2010. View

Fiest K, Jette N, Roberts J, Maxwell C, Smith E, Black S . The Prevalence and Incidence of Dementia: a Systematic Review and Meta-analysis. Can J Neurol Sci. 2016; 43 Suppl 1:S3-S50. DOI: 10.1017/cjn.2016.18. View

Fjell A, Walhovd K . Structural brain changes in aging: courses, causes and cognitive consequences. Rev Neurosci. 2010; 21(3):187-221. DOI: 10.1515/revneuro.2010.21.3.187. View

Nobis L, Manohar S, Smith S, Alfaro-Almagro F, Jenkinson M, Mackay C . Hippocampal volume across age: Nomograms derived from over 19,700 people in UK Biobank. Neuroimage Clin. 2019; 23:101904. PMC: 6603440. DOI: 10.1016/j.nicl.2019.101904. View

Mofrad S, Lundervold A, Lundervold A . A predictive framework based on brain volume trajectories enabling early detection of Alzheimer's disease. Comput Med Imaging Graph. 2021; 90:101910. DOI: 10.1016/j.compmedimag.2021.101910. View

10.

Flicker L . Modifiable lifestyle risk factors for Alzheimer's disease. J Alzheimers Dis. 2010; 20(3):803-11. DOI: 10.3233/JAD-2010-091624. View

11.

Hou Y, Dan X, Babbar M, Wei Y, Hasselbalch S, Croteau D . Ageing as a risk factor for neurodegenerative disease. Nat Rev Neurol. 2019; 15(10):565-581. DOI: 10.1038/s41582-019-0244-7. View

12.

Gordon B, Blazey T, Su Y, Hari-Raj A, Dincer A, Flores S . Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study. Lancet Neurol. 2018; 17(3):241-250. PMC: 5816717. DOI: 10.1016/S1474-4422(18)30028-0. View

13.

Cao K, Chen-Plotkin A, Plotkin J, Wang L . Age-correlated gene expression in normal and neurodegenerative human brain tissues. PLoS One. 2010; 5(9). PMC: 2947518. DOI: 10.1371/journal.pone.0013098. View

14.

Jagust W, Landau S, Koeppe R, Reiman E, Chen K, Mathis C . The Alzheimer's Disease Neuroimaging Initiative 2 PET Core: 2015. Alzheimers Dement. 2015; 11(7):757-71. PMC: 4510459. DOI: 10.1016/j.jalz.2015.05.001. View

15.

DeVivo R, Zajac L, Mian A, Cervantes-Arslanian A, Steinberg E, Alosco M . Differentiating Between Healthy Control Participants and Those with Mild Cognitive Impairment Using Volumetric MRI Data. J Int Neuropsychol Soc. 2019; 25(8):800-810. PMC: 6995275. DOI: 10.1017/S135561771900047X. View

16.

Hampel H, Burger K, Teipel S, Bokde A, Zetterberg H, Blennow K . Core candidate neurochemical and imaging biomarkers of Alzheimer's disease. Alzheimers Dement. 2008; 4(1):38-48. DOI: 10.1016/j.jalz.2007.08.006. View

17.

Akiyama H, Barger S, Barnum S, Bradt B, Bauer J, Cole G . Inflammation and Alzheimer's disease. Neurobiol Aging. 2000; 21(3):383-421. PMC: 3887148. DOI: 10.1016/s0197-4580(00)00124-x. View

18.

Gomez-Isla T, HOLLISTER R, West H, Mui S, Growdon J, Petersen R . Neuronal loss correlates with but exceeds neurofibrillary tangles in Alzheimer's disease. Ann Neurol. 1997; 41(1):17-24. DOI: 10.1002/ana.410410106. View

19.

Killiany R, Gomez-Isla T, Moss M, Kikinis R, Sandor T, Jolesz F . Use of structural magnetic resonance imaging to predict who will get Alzheimer's disease. Ann Neurol. 2000; 47(4):430-9. View

20.

Guo T, Korman D, Baker S, Landau S, Jagust W . Longitudinal Cognitive and Biomarker Measurements Support a Unidirectional Pathway in Alzheimer's Disease Pathophysiology. Biol Psychiatry. 2020; 89(8):786-794. PMC: 9682985. DOI: 10.1016/j.biopsych.2020.06.029. View