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Record W4416841651 · doi:10.1007/s40263-025-01251-y

Hippocampal Atrophy on Magnetic Resonance Imaging as a Surrogate Marker for Clinical Benefit and Neurodegeneration in Early Symptomatic Alzheimer’s Disease: Synthesis of Evidence from Observational and Interventional Trials

2025· article· en· W4416841651 on OpenAlexaff
Susan Abushakra, P. Murali Doraiswamy, John A. Hey, Duygu Tosun, Frederik Barkhof, Jerome Barakos, Jeffrey R. Petrella, J. Patrick Kesslak, Aidan Power, Marwan N. Sabbagh, Anton P. Porsteinsson, Sharon Cohen, Serge Gauthier, David Watson, Emer McSweeney, Merçé Boada, Earvin Liang, Luc Bracoud, Rosalind McLaine, Susan Flint, Jean F. Schaefer, Yongxin Yu, Margaret Bray, Suzanne Hendrix, Sam Dickson, Adem Albayrak, Martin Tolar

Bibliographic record

VenueCNS Drugs · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsAtrophySurrogate endpointMagnetic resonance imagingObservational studyCognitive declineNeurologyNeurodegenerationClinical trialDementia

Abstract

fetched live from OpenAlex

Amyloid-plaque reduction is currently the only recognized surrogate outcome for Alzheimer’s disease (AD) trials, allowing accelerated approval of plaque-clearing amyloid antibodies. However, plaque reduction does not facilitate the development of new non-plaque-clearing treatments. The hippocampus is among the first brain regions affected by AD pathology, exhibiting synaptic dysfunction and neurodegeneration that manifests as hippocampal atrophy and memory decline. We evaluated hippocampal volume (HV) as a potential surrogate outcome that can predict clinical benefit in disease-modification trials. Using published data from observational and interventional studies that examined both cognition and HV on volumetric magnetic resonance imaging (vMRI), we evaluated the cross-sectional correlations of HV to cognitive performance, the longitudinal correlations of HV atrophy to cognitive decline, HV sensitivity to drug effects, and the correlations between drug effects on HV atrophy and cognitive decline. We also examined the magnitude of HV protection that corresponds to meaningful clinical benefit. Analyses from 30 observational studies encompassing 13,187 individuals (2633 cognitively normal; 10,554 early AD) showed significant cross-sectional correlations between baseline HV and cognition, and longitudinal correlations between HV atrophy and cognitive decline over ≥ 1 year. The relationship of HV–cognitive drug effects was examined at the group level in nine placebo-controlled trials of five antiamyloid agents that evaluated HV in early AD trials of at least 18 months’ duration. These trials included four amyloid antibodies (aducanumab, lecanemab, donanemab, and gantenerumab) and one oral anti-oligomer agent (valiltramiprosate). Individual-level HV–cognition relationships were examined in two valiltramiprosate studies, one of which included diffusion tensor imaging (DTI) providing microstructural correlates of HV drug effects and helping distinguish neuroprotection from brain edema. Across these anti-amyloid drug trials (total N ~10,000), there was a linear relationship between drug effects on slowing of cognitive decline and slowing of HV atrophy. Two anti-oligomer trials (valiltramiprosate) reported significant subject-level correlations between drug effects on HV and cognition over 18–24 months ( r = −0.40 to −0.44, p < 0.005, N = 50/69), with significant correlations of drug effects on brain microstructure (decreased mean diffusivity) with both HV and cognitive benefits, supporting reduced neurodegeneration. The minimal HV preservation at the mild cognitive impairment (MCI) stage that is associated with clinical benefit is estimated to be ≥ 40 mm 3 or ≥ 10% of atrophy in the placebo arm over 18 months. Our findings demonstrate that hippocampal atrophy is an early indicator of cognitive decline in AD, linked to amyloid and tau-related neurodegeneration. HV on standardized vMRI is sensitive to anti-amyloid treatments, demonstrating strong correlations between slowed hippocampal atrophy and slowed cognitive decline. Data from over 23,000 subjects over three decades support HV as a surrogate marker for predicting clinical benefit in early symptomatic AD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.148
GPT teacher head0.426
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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