Cited by 348Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsCancer-related cognitive impairment studies

2014 Update of the Alzheimer’s Disease Neuroimaging Initiative: A review of papers published since its inception

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Weiner, Michael W., Veitch, Dallas P., Aisen, Paul S., Beckett, Laurel A., Cairns, Nigel J., Cedarbaum, Jesse, Green, Robert C., Harvey, Danielle +12 more·2015·Alzheimer's & Dementia

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 initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. 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 largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's 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 select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) 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; (6) 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. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data 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 (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

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Crossref · 10.1016/j.jalz.2014.11.001

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  • SNPs in and around APOE, BIN1, SORL1, and CR1 have been associated with traits including medial temporal lobe atrophy and cortical thickness.

    “SNPs in and around candidate genes including APOE, BIN1, SORL1, and CR1 have been associated with traits including medial temporal lobe atrophy and cortical thickness [225–228]”

    From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [225]

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Research works printed but not linked: 18

  1. [38]Mueller SG Weiner MW Thal LJ Petersen RC Jack CR Jagust W Ways toward an early diagnosis in Alzheimer’s disease: the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Alzheimers Dement 2005 1 55 66 17476317 PMC1864941
  2. [225]Li Y Wang Y Wu G Shi F Zhou L Lin W Discriminant analysis of longitudinal cortical thickness changes in Alzheimer’s disease using dynamic and network features Neurobiol Aging (in press) PMC3086988 21272960
  3. [350]Weiner MW Veitch DP Aisen PS Beckett LA Cairns NJ Green RC The Alzheimer’s Disease Neuroimaging Initiative: a review of papers published since its inception Alzheimers Dement 2012 8 1 Suppl S1 S68 22047634 PMC3329969
  4. [363]Rasmussen JM Lakatos A van Erp TG Kruggel F Keator DB Fallon JT Alzheimer’s Disease Neuroimaging. Empirical derivation of the reference region for computing diagnostic sensitive (1)(8)fluorodeoxyglucose ratios in Alzheimer’s disease based on the ADNI sample Biochim Biophys Acta 2012 1822 457 466 21958592 PMC5849233
  5. [402]Hinrichs C Singh V Mukherjee L Xu G Chung MK Johnson SC Spatially augmented LP boosting for AD classification with evaluations on the ADNI dataset Neuroimage 2009 48 138 149 19481161 PMC2773131
  6. [427]Kohannim O Hibar DP Stein JL Jahanshad N Hua X Rajagopalan P Discovery and replication of gene influences on brain structure using LASSO regression Front Neurosci 2012 6 115 22888310 PMC3412288
  7. [469]Mukherjee S Kim S Gibbons LE Nho K Risacher SL Glymour MM Alzheimer’s Disease Neuroimaging. Genetic architecture of resilience of executive functioning Brain Imaging Behav 2012 6 621 633 22711244 PMC3607298
  8. [471]Ramanan VK Kim S Holohan K Shen L Nho K Risacher SL Genome-wide pathway analysis of memory impairment in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks Brain Imaging Behav 2012 6 634 648 22865056 PMC3713637
  9. [488]Thambisetty M An Y Nalls M Sojkova J Swaminathan S Zhou Y Effect of complement CR1 on brain amyloid burden during aging and its modification by APOE genotype Biol Psychiatry 2013 73 422 428 23022416 PMC3535537
  10. [513]Hibar DP Kohannim O Stein JL Chiang MC Thompson PM Multi-locus genetic analysis of brain images Front Genet 2011 2 73 22303368 PMC3268626
  11. [527]Hibar DP Stein JL Kohannim O Jahanshad N Saykin AJ Shen L Voxelwise gene-wide association study (vGeneWAS): multivariate gene-based association testing in 731 elderly subjects Neuroimage 2011 56 1875 1891 21497199 PMC3366726
  12. [539]Swaminathan S Shen L Kim S Inlow M West JD Faber KM Alzheimer’s Disease Neuroimaging, and N.-L.N.F.S. Group Analysis of copy number variation in Alzheimer’s disease: the NIALOAD/NCRAD Family Study Curr Alzheimer Res 2012 9 801 814 22486522 PMC3500615
  13. [541]Hibar DP Stein JL Ryles AB Kohannim O Jahanshad N Medland SE Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects Brain Imaging Behav 2013 7 102 115 22903471 PMC3779070
  14. Acosta O Bourgeat P Fripp J Zuluaga MA Fripp J Salvado O Ourselin S Automated voxel-based 3D cortical thickness measurement in a combined Lagrangian-Eulerian PDE approach using partial volume maps Med Image Anal 2009 13 730 743 19648050 PMC3068613
  15. Bourgeat P Chételat G Villemagne VL Fripp J Raniga P Pike K β-amyloid burden in the temporal neocortex is related to hippocampal atrophy in elderly subjects without dementia Neurology 2010 74 121 127 20065247
  16. Ellis KA Rowe CC Villemagne VL Martins RN Masters CL Salvado O Szoeke C Ames D the AIBL Research Group Addressing population aging and Alzheimer’s disease through the Australian imaging biomarkers and lifestyle study: collaboration with the Alzheimer’s Disease Neuroimaging Initiative Alzheimers Dement 2010 6 291 296 20451879
  17. Rowe CC Ellis KA Rimajova M Bourgeat P Pike KE Jones G Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging Neurobiol Aging 2010 31 1275 1283 20472326
  18. Bahar-Fuchs A Moss S Pike KE Villemagne VL Masters CL Rowe C Savage G Olfactory deficits and Aβ burden in AD, MCI and healthy ageing: a PiB PET Study J Alzheimers Dis 2010 22 1081 1087 20930316

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Authors
Weiner, M. W., Veitch, D. P., Aisen, P. S., Beckett, L. A., Cairns, N. J., Cedarbaum, J., Green, R. C., Harvey, D., Jack, C. R., Jagust, W., Luthman, J., Morris, J. C., Petersen, R. C., Saykin, A. J., Shaw, L., Shen, L., Schwarz, A., Toga, A. W., Trojanowski, J. Q., & Initiative, A. D. N.
Affiliations
  • San Francisco VA Medical Center (US)
  • University of California San Diego (US)
  • University of California, Davis (US)
  • Washington University in St. Louis (US)
  • Biogen (United States) (US)
  • Brigham and Women's Hospital (US)
  • Mayo Clinic (US)
  • University of California, Berkeley (US)
  • Eisai (United States) (US)
  • Indiana University Indianapolis (US)
  • University of Pennsylvania (US)
  • Eli Lilly (United States) (US)
  • University of Southern California (US)
Corresponding author
Weiner, Michael W.
Venue
Alzheimer's & Dementia
Publisher
Wiley
Published
2015-06
Volume
11
Issue
6
Pages
e1-120
ISSN
  • 1552-5260 (ISSN-L)
  • 1552-5279
OpenAlex
W1797408175
Cited by
348
References
565
Citations by year
2026: 27 · 2025: 22 · 2024: 28 · 2023: 18 · 2022: 18 · 2021: 43 · 2020: 28 · 2019: 38 · 2018: 36 · 2017: 45 · 2016: 33 · 2015: 11
FWCI
5.74
Type
journal article
Language
en
Open access
Locations
  • Alzheimer s & Dementia (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion, other-oa)
  • IUScholarWorks (Indiana University) (submittedVersion)
Funders
  • Eli Lilly and Company
  • Pfizer
  • Biogen
  • Synarc
  • TauRx Pharmaceuticals
  • Bayer HealthCare
  • Servier
  • Ipsen
  • National Institutes of Health (5u01ag024904-10)
  • National Institute on Aging (U01-AG-024904, P30AG010129, P30AG010133, R01AG012975, R01AG030048, P30AG036468, P30AG010124, P01AG009215, P01AG017586, U01AG010483, U01AG029213, P50AG005681, R01AG016381, P01AG003991, R01AG019771, RC2AG036535, P01AG019724)
  • National Cancer Institute (P30CA093373)
  • National Institute of General Medical Sciences (R01GM088336)
  • National Institute of Neurological Disorders and Stroke (P50NS053488)
  • National Center for Research Resources (UL1RR024146, R25RR026008)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
Keywords
Alzheimer's disease, Alzheimer's Disease Neuroimaging Initiative
MeSH terms
Alzheimer Disease, Brain, Humans, Radionuclide Imaging, Multicenter Studies as Topic, Biomarkers, Nootropic Agents, Early Diagnosis

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