Evidence map›Paper›PMID 27567874›Full record

ArticleJournal of Alzheimer's disease : JAD2016

Staging Alzheimer's Disease Risk by Sequencing Brain Function and Structure, Cerebrospinal Fluid, and Cognition Biomarkers.

Guangyu Chen, Hao Shu, Gang Chen, B Douglas Ward, Piero G Antuono, Zhijun Zhang, Shi-Jiang Li, Alzheimer’s Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

  1. Stage-Aware Event-Based Modeling (SA-EBM) for Disease Progression.Proceedings of machine learning research · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Mitochondria and Mitochondrial Cascades in Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2018
    Review
  20. Review
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

8 authors.

Guangyu ChenDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.
Hao ShuDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.
Gang ChenDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.
B Douglas WardDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.
Piero G AntuonoDepartment of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
Zhijun ZhangDepartment of Neurology, Affiliated ZhongDa Hospital, Neuropsychiatric Institute and Medical School of Southeast University, Nanjing, Jiangsu, China.
Shi-Jiang LiDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.
Alzheimer’s Disease Neuroimaging Initiative

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Alzheimer's Disease Connectome ProjectUF1AG051216 · NIA · MEDICAL COLLEGE OF WISCONSIN · PI BENDLIN, BARBARA BRIGITTA, LI, SHI-JIANG · 2016 to 2019
$5.8M
An FMRI Index as a Risk Marker for Alzheimer's DiseaseR01AG020279 · NIA · MEDICAL COLLEGE OF WISCONSIN · PI LI, SHI-JIANG · 2002 to 2013
$3.3M
Imaging Software of Functional Connectivity MRI for Alzheimer's DiseaseR44AG035405 · NIA · BRAINSYMPHONICS, LLC · PI HU, HUI · 2013 to 2015
$1.8M
NIA NIH HHS R01 AG020279NIA NIH HHS R44 AG035405NIA NIH HHS U01 AG024904NIA NIH HHS UF1 AG051216
6 · The paper itself

Abstract

This study aims to develop a composite biomarker that can accurately measure the sequential biological stages of Alzheimer's disease (AD) on an individual level. We selected 144 subjects from the Alzheimer's Disease Neuroimaging Initiative 2 datasets. Ten biomarkers, from brain function and structure, cerebrospinal fluid, and cognitive performance, were integrated using the event-based probabilistic model to estimate their optimal temporal sequence (Soptimal). We identified the numerical order of the Soptimal as the characterizing Alzheimer's disease risk events (CARE) index to measure disease stage. The results show that, in the Soptimal, hippocampal and posterior cingulate cortex network biomarkers occur first, followed by aberrant cerebrospinal fluid amyloid-β and p-tau levels, then cognitive deficit, and finally regional gray matter loss and fusiform network abnormality. The CARE index significantly correlates with disease severity and exhibits high reliability. Our findings demonstrate that use of the CARE index would advance AD stage measurement across the whole AD continuum and facilitate personalized treatment of AD.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseBiomarkersBrainCognitionCognitive DysfunctionDatabases, FactualFemaleHumansMaleMiddle AgedRisk FactorsBiomarkersAlzheimer’s diseasebiomarkers sequenceCARE indexfunctional connectivitystage

Identifiers

PMID27567874
PMCPMC5055443

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.