Biomarker modeling of Alzheimer’s disease using PET-based Braak staging

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Abstract

Gold-standard diagnosis of Alzheimer’s disease (AD) relies on histopathological staging systems. Using the topographical information from [ ¹⁸F]MK6240 tau positron-emission tomography (PET), we applied the Braak tau staging system to 324 living individuals. We used PET-based Braak stage to model the trajectories of amyloid-β, phosphorylated tau (pTau) in cerebrospinal fluid (pTau ₁₈₁, pTau ₂₁₇, pTau ₂₃₁ and pTau ₂₃₅) and plasma (pTau ₁₈₁ and pTau ₂₃₁), neurodegeneration and cognitive symptoms. We identified nonlinear AD biomarker trajectories corresponding to the spatial extent of tau-PET, with modest biomarker changes detectable by Braak stage II and significant changes occurring at stages III–IV, followed by plateaus. Early Braak stages were associated with isolated memory impairment, whereas Braak stages V–VI were incompatible with normal cognition. In 159 individuals with follow-up tau-PET, progression beyond stage III took place uniquely in the presence of amyloid-β positivity. Our findings support PET-based Braak staging as a framework to model the natural history of AD and monitor AD severity in living humans.

Abstract

The authors used PET imaging to stage individuals according to the Braak neuropathological system for Alzheimer’s disease. PET stage was associated with biomarker and cognitive changes, highlighting the potential to stage Alzheimer’s disease in living people.

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NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

Clifford R. Jack, David Bennett, Kaj Blennow … (2018)

In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

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An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Rahul Desikan, Florent Ségonne, Bruce Fischl … (2006)

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

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Neuropathological stageing of Alzheimer-related changes

H Braak, E Braak (1991)

Eighty-three brains obtained at autopsy from nondemented and demented individuals were examined for extracellular amyloid deposits and intraneuronal neurofibrillary changes. The distribution pattern and packing density of amyloid deposits turned out to be of limited significance for differentiation of neuropathological stages. Neurofibrillary changes occurred in the form of neuritic plaques, neurofibrillary tangles and neuropil threads. The distribution of neuritic plaques varied widely not only within architectonic units but also from one individual to another. Neurofibrillary tangles and neuropil threads, in contrast, exhibited a characteristic distribution pattern permitting the differentiation of six stages. The first two stages were characterized by an either mild or severe alteration of the transentorhinal layer Pre-alpha (transentorhinal stages I-II). The two forms of limbic stages (stages III-IV) were marked by a conspicuous affection of layer Pre-alpha in both transentorhinal region and proper entorhinal cortex. In addition, there was mild involvement of the first Ammon's horn sector. The hallmark of the two isocortical stages (stages V-VI) was the destruction of virtually all isocortical association areas. The investigation showed that recognition of the six stages required qualitative evaluation of only a few key preparations.

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Author and article information

Contributors

Joseph Therriault:

ORCID: http://orcid.org/0000-0002-7826-4781

joseph.therriault@mail.mcgill.ca

Pedro Rosa-Neto:

ORCID: http://orcid.org/0000-0001-9116-1376

pedro.rosa@mcgill.ca

Journal

Journal ID (nlm-ta): Nat Aging

Journal ID (iso-abbrev): Nat Aging

Title: Nature Aging

Publisher: Nature Publishing Group US (New York )

ISSN (Electronic): 2662-8465

Publication date (Electronic): 25 April 2022

Publication date PMC-release: 25 April 2022

Publication date (Print): 2022

Volume: 2

Issue: 6

Pages: 526-535

Affiliations

[1 ]GRID grid.459278.5, ISNI 0000 0004 4910 4652, Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, , Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest de l’Île de Montréal, ; Montreal, Quebec Canada

[2 ]GRID grid.14709.3b, ISNI 0000 0004 1936 8649, Department of Neurology and Neurosurgery, , Faculty of Medicine, McGill University, ; Montreal, Quebec Canada

[3 ]GRID grid.21925.3d, ISNI 0000 0004 1936 9000, Department of Psychiatry, , University of Pittsburgh School of Medicine, ; Pittsburgh, PA USA

[4 ]GRID grid.1649.a, ISNI 000000009445082X, Clinical Neurochemistry Laboratory, , Sahlgrenska University Hospital, ; Mölndal, Sweden

[5 ]GRID grid.8761.8, ISNI 0000 0000 9919 9582, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, , University of Gothenburg, ; Gothenburg, Sweden

[6 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, ; London, UK

[7 ]GRID grid.454378.9, Biomedical Research Unit for Dementia at South London, , NIHR Biomedical Research Centre for Mental Health and Maudsley NHS Foundation, ; London, UK

[8 ]GRID grid.59062.38, ISNI 0000 0004 1936 7689, Department of Math & Statistics, , University of Vermont, ; Burlington, VT USA

[9 ]GRID grid.83440.3b, ISNI 0000000121901201, Department of Neurodegenerative Disease, , UCL Institute of Neurology, Queen Square, ; London, UK

[10 ]GRID grid.83440.3b, ISNI 0000000121901201, UK Dementia Research Institute at UCL, ; London, UK

Author information

Joseph Therriault http://orcid.org/0000-0002-7826-4781

Tharick A. Pascoal http://orcid.org/0000-0001-9057-8014

Firoza Z. Lussier http://orcid.org/0000-0002-6877-4825

Cécile Tissot http://orcid.org/0000-0003-2711-3833

Nicholas J. Ashton http://orcid.org/0000-0002-3579-8804

Thomas K. Karikari http://orcid.org/0000-0003-1422-4358

Juan Lantero-Rodriguez http://orcid.org/0000-0002-7426-678X

Paramita Saha-Chaudhuri http://orcid.org/0000-0003-1987-320X

Kaj Blennow http://orcid.org/0000-0002-1890-4193

Henrik Zetterberg http://orcid.org/0000-0003-3930-4354

Pedro Rosa-Neto http://orcid.org/0000-0001-9116-1376

Article

Publisher ID: 204

DOI: 10.1038/s43587-022-00204-0

PMC ID: 10154209

PubMed ID: 37118445

SO-VID: 888bae90-4c99-4f9b-bff7-de9f3ae47288

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 23 September 2021

Date accepted : 8 March 2022

Funding

Funded by: FundRef https://doi.org/10.13039/501100000024, Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada);

Award ID: #170846

Award Recipient : Joseph Therriault

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Keywords: alzheimer's disease,diagnostic markers,ageing

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Keywords: alzheimer's disease, diagnostic markers, ageing

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Biomarker modeling of Alzheimer’s disease using PET-based Braak staging

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Alternative approaches to Alzheimer's Disease

Most cited references 71

NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Neuropathological stageing of Alzheimer-related changes

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Cited by 60

Most referenced authors 1,880