Evidence map›Paper›PMID 37182882›Full record

ArticleJournal of Alzheimer's disease : JAD2023

A Surface-Based Federated Chow Test Model for Integrating APOE Status, Tau Deposition Measure, and Hippocampal Surface Morphometry.

Jianfeng Wu, Yi Su, Yanxi Chen, Wenhui Zhu, Eric M Reiman, Richard J Caselli, Kewei Chen, Paul M Thompson, Junwen Wang, Yalin Wang and 1 more

Open access · greenAbstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 54% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Jianfeng WuSchool of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
Yi SuBanner Alzheimer's Institute, Phoenix, AZ, USA.
Yanxi ChenSchool of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
Wenhui ZhuSchool of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
Eric M ReimanBanner Alzheimer's Institute, Phoenix, AZ, USA.
Richard J CaselliDepartment of Neurology, Mayo Clinic Arizona, Scottsdale, AZ, USA.
Kewei ChenBanner Alzheimer's Institute, Phoenix, AZ, USA.
Paul M ThompsonImaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, USA.
Junwen WangDivision of Applied Oral Sciences & Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Yalin WangSchool of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
Alzheimer’s Disease Neuroimaging Initiative
Arizona State University · USBanner Alzheimer’s InstituteMayo Clinic in Arizona · USUniversity of Southern California · US

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD)U24AG021886 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI TATIANA M. FOROUD · 2002 to 2026
$119.8M
Research Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI REIMAN, ERIC MICHAEL · 2001 to 2020
$32.5M
APOE in the Predisposition to, Protection from and Prevention of Alzheimer's DiseaseR01AG069453 · NIA · BANNER HEALTH · PI ASHTON, NICHOLAS, LANGBAUM, JESSICA BROOKE · 2020 to 2025
$27.4M
Research Education ComponentP30AG072980 · NIA · BANNER HEALTH · PI Nicholas Ashton · 2021 to 2026
$24.9M
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease BiobanksU01AG068057 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Christos Davatzikos, Heng Huang · 2020 to 2026
$20.7M
Early joint cranial and brain development from fetal and pediatric imagingR01DE030286 · NIDCR · CHILDREN'S HOSPITAL OF LOS ANGELES · PI LEPORE, NATASHA, LINGURARU, MARIUS GEORGE · 2021 to 2025
$3.5M
Predicting the early childhood outcomes of preterm brain shape abnormalitiesR01EB025032 · NIBIB · CHILDREN'S HOSPITAL OF LOS ANGELES · PI LEPORE, NATASHA · 2017 to 2020
$2.6M
Tracer harmonization for amyloid and tau PET imaging using statistical and deep learning techniquesRF1AG073424 · NIA · BANNER HEALTH · PI SU, YI · 2022 to 2022
$2.3M
Hierarchical Bayesian Analysis of Retinotopic Maps of the Human Visual Cortex with Conformal GeometryR01EY032125 · NEI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI LU, ZHONG-LIN, WANG, YALIN · 2021 to 2024
$1.2M
Discover and Analyze Germline-Somatic Interactions in CancerR01LM013438 · NLM · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI LIU, LI, YANG, PING · 2021 to 2023
$1.0M
Developing a Univariate Neurodegeneration Imaging Biomarker with Optimal TransportationR21AG065942 · NIA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WANG, YALIN · 2020 to 2020
$445k
NEI NIH HHS R01 EY032125NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG072980NIA NIH HHS R01 AG069453NIA NIH HHS R21 AG065942NIA NIH HHS RF1 AG073424NIA NIH HHS U01 AG024904NIA NIH HHS U01 AG068057NIA NIH HHS U24 AG021886NIBIB NIH HHS R01 EB025032NIDCR NIH HHS R01 DE030286NLM NIH HHS R01 LM013438
6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is the most common type of age-related dementia, affecting 6.2 million people aged 65 or older according to CDC data. It is commonly agreed that discovering an effective AD diagnosis biomarker could have enormous public health benefits, potentially preventing or delaying up to 40% of dementia cases. Tau neurofibrillary tangles are the primary driver of downstream neurodegeneration and subsequent cognitive impairment in AD, resulting in structural deformations such as hippocampal atrophy that can be observed in magnetic resonance imaging (MRI) scans.

objectiveTo build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline.

methodsUsing data obtained from different institutions, we develop a surface-based federated Chow test model to study the synergistic effects of APOE, a previously reported significant risk factor of AD, and tau on hippocampal surface morphometry.

resultsWe illustrate that the APOE-specific morphometry features correlate with AD progression and better predict future AD conversion than other MRI biomarkers. For example, a strong association between atrophy and abnormal tau was identified in hippocampal subregion cornu ammonis 1 (CA1 subfield) and subiculum in e4 homozygote cohort.

conclusionOur model allows for identifying MRI biomarkers for AD and cognitive decline prediction and may uncover a corner of the neural mechanism of the influence of APOE and tau deposition on hippocampal morphology.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAmyloid beta-PeptidesApolipoproteins EAtrophyBiomarkersHippocampusHumansMagnetic Resonance Imagingtau ProteinsAmyloid beta-PeptidesApolipoproteins EBiomarkerstau ProteinsAlzheimer’s diseaseAPOEFederated Chow testhippocampal morphometrytau deposition

Identifiers

PMID37182882
PMCPMC10329869
OpenAlexW4376116016

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.