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Record W4399561968 · doi:10.1101/2024.06.10.598357

Sex, racial, and <i>APOE</i> -ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer’s disease

2024· preprint· en· W4399561968 on OpenAlexfundno aff
Amalia Peterson, Aditi Sathe, Dimitrios Zaras, Yisu Yang, Alaina Durant, Kacie Deters, Niranjana Shashikumar, Kimberly R. Pechman, Michael E. Kim, Chenyu Gao, Nazirah Mohd Khairi, Zhiyuan Li, Tianyuan Yao, Yuankai Huo, Logan Dumitrescu, Katherine A. Gifford, Jo Ellen Wilson, Francis E. Cambronero, Shannon L. Risacher, Lori L. Beason‐Held, Yang An, Konstantinos Arfanakis, Guray Erus, Christos Davatzikos, Duygu Tosun, Arthur W. Toga, Paul M. Thompson, Elizabeth C. Mormino, Panpan Zhang, Kurt G. Schilling, Marilyn Albert, Walter A. Kukull, Sarah Biber, Bennett A. Landman, Sterling C. Johnson, Julie A. Schneider, Lisa L. Barnes, David A. Bennett, Angela L. Jefferson, Susan M. Resnick, Andrew J. Saykin, Timothy J. Hohman, Derek B. Archer

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchAvid RadiopharmaceuticalsGenentechNational Institutes of HealthH. Lundbeck A/SEisaiSiemens Medical Solutions USAVanderbilt University Medical CenterNovo NordiskNorthern California Institute for Research and EducationBioClinicaU.S. Department of DefenseAlzheimer's Disease Neuroimaging InitiativeUniversity of PennsylvaniaVanderbilt UniversityUniversity of Southern CaliforniaBristol-Myers SquibbEli Lilly and CompanyVanderbilt Memory and Alzheimer's CenterBiogenNational Institute on AgingAlzheimer's Association
KeywordsAlleleApolipoprotein ELongitudinal studyDiseaseWhite (mutation)White matterGerontologyMedicineGeneticsBiologyInternal medicinePathologyGene

Abstract

fetched live from OpenAlex

Structured Abstract INTRODUCTION The effects of sex, race, and Apolipoprotein E ( APOE ) – Alzheimer’s disease (AD) risk factors – on white matter integrity are not well characterized. METHODS Diffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 ± 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FA FWcorr ) were used to assess differences in white matter microstructure by sex, race, and APOE- ε4 carrier status. RESULTS Sex differences in FA FWcorr in association and projection tracts, racial differences in FA FWcorr in projection tracts, and APOE- ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSION There are prominent differences in white matter microstructure by sex, race, and APOE- ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. Highlights Sex, race, and APOE- ε4 carrier status relate to white matter microstructural integrity Females generally have lower FA FWcorr compared to males Non-Hispanic Black adults generally have lower FA FWcorr than non-Hispanic White adults APOE- ε4 carriers tended to have higher FW than non-carriers Research in Context Systematic Review The authors used PubMed and Google Scholar to review literature that used conventional and free-water (FW)-corrected microstructural metrics to evaluate sex, race, and APOE- ε4 differences in white matter microstructure. While studies have previously explored differences by sex and APOE- ε4 status, less is known about racial differences and no large-scale FW-corrected analysis has been performed. Interpretation Sex and race were more associated with FA FWcorr while APOE- ε4 status was associated with FW metrics. Association, projection, limbic, and occipital transcallosal tracts showed the greatest differences. Future Direction Future studies to determine the biological and social pathways that lead to sex, racial, and APOE- ε4 differences are warranted. Consent Statement All participants provided informed consent in their respective cohort studies.

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)0.006
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.279
Teacher spread0.245 · 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
Published2024
Admission routes1
Has abstractyes

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