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Record W7117253439 · doi:10.1002/alz70856_098833

Sex‐specific patterns of a machine learning‐derived Alzheimer's brain atrophy imaging signature in participants without diagnosed cognitive impairment: A multi‐cohort study

2025· article· en· W7117253439 on OpenAlexaff
Filippos Anagnostakis, Mehrshad Saadatinia, Sarah Ko, Erdem Varol, Despina Kontos, Ajay Gupta, Adam Brickman, Li Shen, Guray Erus, Haochang Shou, Ye Tian, Andrew Zalesky, Christos Davatzikos, Susan M. Resnick, Junhao Wen

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsCognitionAtrophyNeuroimagingBrain agingCognitive declineCognitive impairmentPopulation

Abstract

fetched live from OpenAlex

Abstract Background We investigated sex differences in a machine learning‐derived imaging signature of AD brain atrophy (i.e., SPARE‐AD 5 ), in relation to age, genetic factors ( APOE ε4 allele), and multi‐organ biological age gap (BAG 2,3 ). Methods Data from the iSTAGING and MULTI consortia included 53,622 participants without diagnosed cognitive impairment (mean age: 61.8 ± 12.6 years; 54% women). The SPARE‐AD model uses a support vector machine with a linear kernel to distinguish between cognitively normal individuals and those with AD 5 . Generalized linear models assessed sex differences and nine BAG associations with SPARE‐AD, adjusting for age, sex, APOE ε4, and interactions, and analysis of covariance (ANCOVA) with Tukey's test to assess differences in SPARE‐AD scores between APOE ε4 allele carrier groups. Results Overall, SPARE‐AD increased with age (β = 0.018, p < 2e‐16). Women had higher SPARE‐AD scores than men (β = ‐0.393, p < 2e‐16). Women had higher SPARE‐AD scores at younger ages but lower values at older ages (β = 0.006, p < 2e‐16 for the age‐sex interaction term) when compared to males (Figure 1a). Furthermore, SPARE‐AD was positively associated with the number of APOE ε4 alleles (β = 0.018, p = 1.06e‐6). Non‐carriers and heterozygous carriers of the APOE ε4 allele exhibited lower SPARE‐AD scores compared to homozygous carriers in analyses of both combined sexes and in men alone; this pattern was not observed in women (Figure 1b‐d). Among the nine BAGs, the brain BAG was most strongly associated with SPARE‐AD in both sexes combined (β = 0.018, p = 1.09e‐302) (Figure 2a) and separately (women: β = 0.017, p = 5.08e‐128; men: β = 0.019, p = 4.24e‐175) (Figure 2b‐c). Other significant BAG associations were observed in men and not in women, including musculoskeletal (β = 0.004, p = 0.02), immune (β = 0.004, p = 0.02), and metabolic BAGs (β = 0.005, p = 0.02) (Figure 2b‐d). Conclusion SPARE‐AD scores increased with age and were higher in women at younger ages but lower than men at older ages, with a significant age*sex interaction, and were positively associated with the number of the APOE ε4 allele, particularly in men.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.332
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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