Plasma biomarkers of Alzheimer’s disease improve prediction of cognitive decline in cognitively unimpaired elderly populations

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Abstract

Plasma biomarkers of amyloid, tau, and neurodegeneration (ATN) need to be characterized in cognitively unimpaired (CU) elderly individuals. We therefore tested if plasma measurements of amyloid-β (Aβ)42/40, phospho-tau217 (P-tau217), and neurofilament light (NfL) together predict clinical deterioration in 435 CU individuals followed for an average of 4.8 ± 1.7 years in the BioFINDER study. A combination of all three plasma biomarkers and basic demographics best predicted change in cognition (Pre-Alzheimer’s Clinical Composite; R ² = 0.14, 95% CI [0.12–0.17]; P < 0.0001) and subsequent AD dementia (AUC = 0.82, 95% CI [0.77–0.91], P < 0.0001). In a simulated clinical trial, a screening algorithm combining all three plasma biomarkers would reduce the required sample size by 70% (95% CI [54–81]; P < 0.001) with cognition as trial endpoint, and by 63% (95% CI [53–70], P < 0.001) with subsequent AD dementia as trial endpoint. Plasma ATN biomarkers show usefulness in cognitively unimpaired populations and could make large clinical trials more feasible and cost-effective.

Abstract

Plasma biomarkers of amyloid, tau and neurodegeneration (ATN) need to be characterized in cognitively unimpaired (CU) elderly individuals. Here, the authors show plasma ATN biomarkers predict clinical deterioration and cognitive decline and show in a simulated clinical trial combining all three biomarkers reduced the required sample size.

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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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Multimodel Inference: Understanding AIC and BIC in Model Selection

K. Burnham (2004)

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Alzheimer's disease.

Kaj Blennow, Mony J. de Leon, Henrik Zetterberg (2006)

Alzheimer's disease is the most common cause of dementia. Research advances have enabled detailed understanding of the molecular pathogenesis of the hallmarks of the disease--ie, plaques, composed of amyloid beta (Abeta), and tangles, composed of hyperphosphorylated tau. However, as our knowledge increases so does our appreciation for the pathogenic complexity of the disorder. Familial Alzheimer's disease is a very rare autosomal dominant disease with early onset, caused by mutations in the amyloid precursor protein and presenilin genes, both linked to Abeta metabolism. By contrast with familial disease, sporadic Alzheimer's disease is very common with more than 15 million people affected worldwide. The cause of the sporadic form of the disease is unknown, probably because the disease is heterogeneous, caused by ageing in concert with a complex interaction of both genetic and environmental risk factors. This seminar reviews the key aspects of the disease, including epidemiology, genetics, pathogenesis, diagnosis, and treatment, as well as recent developments and controversies.

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Author and article information

Contributors

Niklas Mattsson-Carlgren: Niklas.Mattsson-Carlgren@med.lu.se

Oskar Hansson:

ORCID: http://orcid.org/0000-0001-8467-7286

Oskar.Hansson@med.lu.se

Journal

Journal ID (nlm-ta): Nat Commun

Journal ID (iso-abbrev): Nat Commun

Title: Nature Communications

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2041-1723

Publication date (Electronic): 11 June 2021

Publication date PMC-release: 11 June 2021

Publication date Collection: 2021

Volume: 12

Electronic Location Identifier: 3555

Affiliations

[1 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Clinical Memory Research Unit, , Lund University, ; Lund, Sweden

[2 ]GRID grid.411843.b, ISNI 0000 0004 0623 9987, Memory Clinic, , Skåne University Hospital, ; Lund, Sweden

[3 ]GRID grid.417540.3, ISNI 0000 0000 2220 2544, Eli Lilly and Company, ; Indianapolis, IN USA

[4 ]GRID grid.411843.b, ISNI 0000 0004 0623 9987, Department of Neurology, , Skåne University Hospital, ; Lund, Sweden

[5 ]GRID grid.4514.4, ISNI 0000 0001 0930 2361, Wallenberg Centre for Molecular Medicine, , Lund University, ; Lund, Sweden

Author information

Sebastian Palmqvist http://orcid.org/0000-0002-9267-1930

Jeffrey L. Dage http://orcid.org/0000-0002-2192-1699

Oskar Hansson http://orcid.org/0000-0001-8467-7286

Article

Publisher ID: 23746

DOI: 10.1038/s41467-021-23746-0

PMC ID: 8196018

PubMed ID: 34117234

SO-VID: 3c3b96e7-fcf0-45c8-b0f0-0a17c6b3f5be

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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 : 14 January 2021

Date accepted : 10 May 2021

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Keywords: alzheimer's disease,neurodegeneration,predictive markers

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ScienceOpen disciplines: Uncategorized

Keywords: alzheimer's disease, neurodegeneration, predictive markers

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Plasma biomarkers of Alzheimer’s disease improve prediction of cognitive decline in cognitively unimpaired elderly populations

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Alternative approaches to Alzheimer's Disease

Most cited references 39

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

Multimodel Inference: Understanding AIC and BIC in Model Selection

Alzheimer's disease.

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