The A4 study: <i>β</i>‐amyloid and cognition in 4432 cognitively unimpaired adults

Insel, Philip S.; Donohue, Michael C.; Sperling, Reisa A.; Hansson, Oskar; Mattsson‐Carlgren, Niklas

doi:10.1002/acn3.51048

Cited by 52 publications

(59 citation statements)

References 29 publications

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“…Similarly, individual measures within the PACC do not change uniformly [33]. Consistent with our findings in FAD, sensitive memory tests detect early decline in preclinical LOAD, potentially even before the threshold of amyloid positivity is reached, while measures of global cognition begin to change closer to symptom onset [33,34].…”

Section: Discussionsupporting

confidence: 83%

Quantitative detection and staging of presymptomatic cognitive decline in familial Alzheimer’s disease: a retrospective cohort analysis

et al. 2020

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Background Understanding the earliest manifestations of Alzheimer’s disease (AD) is key to realising disease-modifying treatments. Advances in neuroimaging and fluid biomarkers have improved our ability to identify AD pathology in vivo. The critical next step is improved detection and staging of early cognitive change. We studied an asymptomatic familial Alzheimer’s disease (FAD) cohort to characterise preclinical cognitive change. Methods Data included 35 asymptomatic participants at 50% risk of carrying a pathogenic FAD mutation. Participants completed a multi-domain neuropsychology battery. After accounting for sex, age and education, we used event-based modelling to estimate the sequence of cognitive decline in presymptomatic FAD, and uncertainty in the sequence. We assigned individuals to their most likely model stage of cumulative cognitive decline, given their data. Linear regression of estimated years to symptom onset against model stage was used to estimate the timing of preclinical cognitive decline. Results Cognitive change in mutation carriers was first detected in measures of accelerated long-term forgetting, up to 10 years before estimated symptom onset. Measures of subjective cognitive decline also revealed early abnormalities. Our data-driven model demonstrated subtle cognitive impairment across multiple cognitive domains in clinically normal individuals on the AD continuum. Conclusions Data-driven modelling of neuropsychological test scores has potential to differentiate cognitive decline from cognitive stability and to estimate a fine-grained sequence of decline across cognitive domains and functions, in the preclinical phase of Alzheimer’s disease. This can improve the design of future presymptomatic trials by informing enrichment strategies and guiding the selection of outcome measures.

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Section: Discussionsupporting

confidence: 83%

Quantitative detection and staging of presymptomatic cognitive decline in familial Alzheimer’s disease: a retrospective cohort analysis

et al. 2020

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“…Though the PACC and similar measures are in use in observational studies and ongoing prevention trials, it is important to note that the PACC is weighted toward memory measures and may not fully capture early disruptions in other cognitive domains 25 , 26 , 42 , 43 . Given the potential for clinically variable symptomatic presentations of AD pathology (including language and visuospatial predominant forms), further work using additional, diverse cognitive tests is needed to determine the extent to which plasma NT1 may predict changes in executive, language, and visuospatial function on the path to Alzheimer’s disease.…”

Section: Discussionmentioning

confidence: 99%

Plasma N-terminal tau fragment levels predict future cognitive decline and neurodegeneration in healthy elderly individuals

et al. 2020

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The availability of blood-based assays detecting Alzheimer’s disease (AD) pathology should greatly accelerate AD therapeutic development and improve clinical care. This is especially true for markers that capture the risk of decline in pre-symptomatic stages of AD, as this would allow one to focus interventions on participants maximally at risk and at a stage prior to widespread synapse loss and neurodegeneration. Here we quantify plasma concentrations of an N-terminal fragment of tau (NT1) in a large, well-characterized cohort of clinically normal elderly who were followed longitudinally. Plasma NT1 levels at study entry (when all participants were unimpaired) were highly predictive of future cognitive decline, pathological tau accumulation, neurodegeneration, and transition to a diagnosis of MCI/AD. These predictive effects were particularly strong in participants with even modestly elevated brain β-amyloid burden at study entry, suggesting plasma NT1 levels capture very early cognitive, pathologic and neurodegenerative changes along the AD trajectory.

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“…This maximizes the chance of a therapeutic benefit and avoids needless risk of exposure to the compound by participants who cannot derive any benefit from it. Moreover, amyloid PET has become an enabling technology for studies in earlier phases of the pathological cascade, before the onset of clinical symptoms [12,13].…”

Section: Confirmation Of Disease Biologymentioning

confidence: 99%

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Schwarz

2021

Neurotherapeutics

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Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect—especially with a clear relationship to dose—can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to “de-risk” the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer’s disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

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The A4 study: β‐amyloid and cognition in 4432 cognitively unimpaired adults

Cited by 52 publications

References 29 publications

Quantitative detection and staging of presymptomatic cognitive decline in familial Alzheimer’s disease: a retrospective cohort analysis

Quantitative detection and staging of presymptomatic cognitive decline in familial Alzheimer’s disease: a retrospective cohort analysis

Plasma N-terminal tau fragment levels predict future cognitive decline and neurodegeneration in healthy elderly individuals

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

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