Evidence map›Paper›PMID 34924383›Full record

ArticleJournal of Alzheimer's disease : JAD2022

Studying APOE ɛ4 Allele Dose Effects with a Univariate Morphometry Biomarker.

Gang Wang, Wenju Zhou, Deping Kong, Zongshuai Qu, Maowen Ba, Jinguang Hao, Tao Yao, Qunxi Dong, Yi Su, Eric M Reiman and 4 more

Open access · greenAbstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

14 authors at 6 institutions in 2 countries.

Gang WangSchool of Ulsan Ship and Ocean College, Ludong University, Yantai, China.
Wenju ZhouSchool of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China.
Deping KongSchool of Information and Electrical Engineering, Ludong University, Yantai, China.
Zongshuai QuSchool of Information and Electrical Engineering, Ludong University, Yantai, China.
Maowen BaDepartment of Neurology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China.
Jinguang HaoSchool of Information and Electrical Engineering, Ludong University, Yantai, China.
Tao YaoSchool of Information and Electrical Engineering, Ludong University, Yantai, China.
Qunxi DongInstitute of Engineering Medicine, Beijing Institute of Technology, Beijing, China.
Yi SuBanner Alzheimer's Institute, Phoenix, 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.
Yalin WangDepartment of Neurology, Mayo Clinic Arizona, Scottsdale, AZ, USA.
Alzheimer’s Disease Neuroimaging Initiative
Ludong University · CNBanner Alzheimer’s InstituteMayo Clinic in Arizona · USArizona State University · USQingdao University · CNShanghai University · CN

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Research Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI GONZALEZ HERNANDEZ, GRACIELA · 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 HEATHER Allyson BIMONTE-NELSON · 2021 to 2026
$24.9M
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
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 AG024904NIBIB NIH HHS R01 EB025032NIDCR NIH HHS R01 DE030286
6 · The paper itself

Abstract

backgroundA univariate neurodegeneration biomarker (UNB) based on MRI with strong statistical discrimination power would be highly desirable for studying hippocampal surface morphological changes associated with APOE ɛ4 genetic risk for AD in the cognitively unimpaired (CU) population. However, existing UNB work either fails to model large group variances or does not capture AD induced changes.

objectiveWe proposed a subspace decomposition method capable of exploiting a UNB to represent the hippocampal morphological changes related to the APOE ɛ4 dose effects among the longitudinal APOE ɛ4 homozygotes (HM, N = 30), heterozygotes (HT, N = 49) and non-carriers (NC, N = 61).

methodsRank minimization mechanism combined with sparse constraint considering the local continuity of the hippocampal atrophy regions is used to extract group common structures. Based on the group common structures of amyloid-β (Aβ) positive AD patients and Aβ negative CU subjects, we identified the regions-of-interest (ROI), which reflect significant morphometry changes caused by the AD development. Then univariate morphometry index (UMI) is constructed from these ROIs.

resultsThe proposed UMI demonstrates a more substantial statistical discrimination power to distinguish the longitudinal groups with different APOE ɛ4 genotypes than the hippocampal volume measurements. And different APOE ɛ4 allele load affects the shrinkage rate of the hippocampus, i.e., HM genotype will cause the largest atrophy rate, followed by HT, and the smallest is NC.

conclusionThe UMIs may capture the APOE ɛ4 risk allele-induced brain morphometry abnormalities and reveal the dose effects of APOE ɛ4 on the hippocampal morphology in cognitively normal individuals.

Indexed as

AllelesBiomarkersAgedAlzheimer DiseaseAmyloid beta-PeptidesApolipoprotein E4AtrophyFemaleHippocampusHumansLongitudinal StudiesMagnetic Resonance ImagingMaleAmyloid beta-PeptidesApolipoprotein E4BiomarkersEffect sizemagnetic resonance imagingpermutation t-testradial distanceregions-of-interestsubspace decomposition

Identifiers

PMID34924383
PMCPMC10498787
OpenAlexW4200174461

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.