Evidence map›Paper›PMID 23932184›Full record

ReviewAlzheimer's & dementia : the journal of the Alzheimer's Association2013

The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception.

Michael W Weiner, Dallas P Veitch, Paul S Aisen, Laurel A Beckett, Nigel J Cairns, Robert C Green, Danielle Harvey, Clifford R Jack, William Jagust, Enchi Liu and 11 more

Open access · greenAbstract readReview
In one paragraph

Review in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 301 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
301citing papers in PubMed, 6 pooled it
76.0field-weighted citation impact, top 1% 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

301 citing papers in PubMed, 6 syntheses or guidelines pooled it, 993 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pediatric Brain Development in Down Syndrome: A Field in Its Infancy.Journal of the International Neuropsychological Society : JINS · 2018
    Pooled it
  5. Pooled it
  6. Pooled it
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Gene-Modulated Network Diffusion for Improved Modeling of Amyloid-bioRxiv : the preprint server for biology · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

241 more citing papers are in PubMed but not listed here.

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

21 authors at 15 institutions in 3 countries.

Michael W WeinerDepartment of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA. michael.weiner@ucsf.edu
Dallas P Veitch
Paul S Aisen
Laurel A Beckett
Nigel J Cairns
Robert C Green
Danielle Harvey
Clifford R Jack
William Jagust
Enchi Liu
John C Morris
Ronald C Petersen
Andrew J Saykin
Mark E Schmidt
Leslie Shaw
Li Shen
Judith A Siuciak
Holly Soares
Arthur W Toga
John Q Trojanowski
Alzheimer's Disease Neuroimaging Initiative
Mayo Clinic in Arizona · USSan Francisco VA Medical Center · USUniversity of California, Davis · USUniversity of California, San Diego · USUniversity of Pennsylvania · USBristol-Myers Squibb (United States) · USFoundation for the National Institutes of Health · USHarvard University · USIndiana University – Purdue University Indianapolis · USIndiana University School of MedicineJanssen (Belgium) · BEJanssen (United States) · USUniversity of California, Berkeley · USUniversity of California, Los Angeles · USWashington University in St. Louis · US

Funding

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 ComponentP30AG010133 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 1991 to 2020
$37.3M
Memory Circuitry in MCI and Early Alzheimer’s Disease Prodrome: Molecular DriversR01AG019771 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 2001 to 2021
$6.9M
NIA NIH HHS P30 AG010133NIA NIH HHS R01 AG019771NIA NIH HHS U24 AG021886
6 · The paper itself

Abstract

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

Indexed as

Early DiagnosisAlzheimer DiseaseHumansMulticenter Studies as TopicNeuroimagingUnited StatesAlzheimer's diseaseAmyloidBiomarkerMild cognitive impairmentTau

Identifiers

PMID23932184
PMCPMC4108198
OpenAlexW2007044705

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.