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

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 40...

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Published inAlzheimer's & dementia Vol. 11; no. 6; pp. e1 - e120
Main Authors Weiner, Michael W, Veitch, Dallas P, Aisen, Paul S, Beckett, Laurel A, Cairns, Nigel J, Cedarbaum, Jesse, Green, Robert C, Harvey, Danielle, Jack, Clifford R, Jagust, William, Luthman, Johan, Morris, John C, Petersen, Ronald C, Saykin, Andrew J, Shaw, Leslie, Shen, Li, Schwarz, Adam, Toga, Arthur W, Trojanowski, John Q
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.06.2015
Subjects
Online AccessGet full text
ISSN1552-5260
1552-5279
1552-5279
DOI10.1016/j.jalz.2014.11.001

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Abstract 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.
AbstractList 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.
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.
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.
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.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.
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, [18F]‐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.
Author Green, Robert C.
Trojanowski, John Q.
Jack, Clifford R.
Shen, Li
Aisen, Paul S.
Toga, Arthur W.
Schwarz, Adam
Saykin, Andrew J.
Petersen, Ronald C.
Jagust, William
Cedarbaum, Jesse
Morris, John C.
Luthman, Johan
Shaw, Leslie
Beckett, Laurel A.
Veitch, Dallas P.
Harvey, Danielle
Weiner, Michael W.
Cairns, Nigel J.
AuthorAffiliation x Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
b Department of Radiology, University of California, San Francisco, CA, USA
e Department of Neurology, University of California, San Francisco, CA, USA
l Department of Radiology, Mayo Clinic, Rochester, MN, USA
w Udall Parkinson’s Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
m Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
n Neuroscience Clinical Development, Neuroscience & General Medicine Product Creation Unit, Eisai Inc., Philadelphia, PA, USA
i Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
u Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
h Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, Saint Louis, MO,
AuthorAffiliation_xml – name: w Udall Parkinson’s Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
– name: t Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
– name: f Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
– name: h Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
– name: q Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
– name: r Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
– name: m Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
– name: i Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
– name: p Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
– name: x Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
– name: c Department of Medicine, University of California, San Francisco, CA, USA
– name: v Alzheimer’s Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
– name: g Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
– name: l Department of Radiology, Mayo Clinic, Rochester, MN, USA
– name: j Neurology Early Clinical Development, Biogen Idec, Cambridge, MA, USA
– name: o Department of Neurology, Mayo Clinic, Rochester, MN, USA
– name: u Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
– name: d Department of Psychiatry, University of California, San Francisco, CA, USA
– name: e Department of Neurology, University of California, San Francisco, CA, USA
– name: s Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN, USA
– name: n Neuroscience Clinical Development, Neuroscience & General Medicine Product Creation Unit, Eisai Inc., Philadelphia, PA, USA
– name: a Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
– name: k Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
– name: b Department of Radiology, University of California, San Francisco, CA, USA
Author_xml – sequence: 1
  fullname: Weiner, Michael W
– sequence: 2
  fullname: Veitch, Dallas P
– sequence: 3
  fullname: Aisen, Paul S
– sequence: 4
  fullname: Beckett, Laurel A
– sequence: 5
  fullname: Cairns, Nigel J
– sequence: 6
  fullname: Cedarbaum, Jesse
– sequence: 7
  fullname: Green, Robert C
– sequence: 8
  fullname: Harvey, Danielle
– sequence: 9
  fullname: Jack, Clifford R
– sequence: 10
  fullname: Jagust, William
– sequence: 11
  fullname: Luthman, Johan
– sequence: 12
  fullname: Morris, John C
– sequence: 13
  fullname: Petersen, Ronald C
– sequence: 14
  fullname: Saykin, Andrew J
– sequence: 15
  fullname: Shaw, Leslie
– sequence: 16
  fullname: Shen, Li
– sequence: 17
  fullname: Schwarz, Adam
– sequence: 18
  fullname: Toga, Arthur W
– sequence: 19
  fullname: Trojanowski, John Q
BackLink https://www.ncbi.nlm.nih.gov/pubmed/26073027$$D View this record in MEDLINE/PubMed
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2013; 66
2013; 65
2013; 68
2013; 126
2013; 64
2008; 39
2004; 3
2013; 70
2012; 18
2012; 17
2008; 30
2012; 15
2004; 1025
2012; 12
2012; 11
2012; 10
2011; 487
2013; 59
2013; 54
2008; 27
2013; 111
2013; 60
2008; 21
2012; 29
2012; 28
2010; 192
2012; 27
2012; 26
2010; 2
2012; 22
2012; 21
2010; 6
2011; 122
2012; 20
2010; 9
2011; 121
2011; 259
2009; 66
2011; 258
2009; 62
2009; 65
2010; 2010
2011; 2
2011; 1
2013; 84
2013; 102
2012; 39
2012; 36
2011; 3
2011; 6
2012; 34
2011; 5
2012; 33
2011; 134
2012; 32
2011; 7
2012; 31
2012; 30
2014; 311
2004; 55
2009; 73
2013; 76
2013; 78
2013; 73
2013; 75
2013; 74
2013; 80
2013; 81
2013; 212
2005; 1
2008; 43
2008; 41
2012; 44
2012; 513
2010; 56
2010; 53
2013; 26
2010; 58
2013; 28
2013; 27
2013; 22
2013; 21
2013; 24
2013; 23
2008; 7
2008; 4
2010; 67
2013; 18
2013; 17
2010; 68
2013; 11
2013; 10
2013; 550
2014; 8
2010; 74
2010; 75
2013; 66C
2012
2011
2013; 43
2010
2013; 40
2009
2008
2012; 66C
2014; 84
2013; 36
2013; 32
2013; 35
2013; 34
2010; 256
2010; 133
2009; 6
2009; 5
2014
2009; 4
2013
2009; 3
2009; 302
2007; 47
2010; 10
2013; 3
2006; 31
2013; 4
2010; 14
2013; 1
2010; 13
2013; 2
2010; 107
2010; 19
2010; 223
2010; 221
2011; 52
2011; 55
2011; 54
2011; 57
2011; 56
2011; 59
2011; 58
2013; 7
1995; 373
2013; 8
2014; 133
2011; 194
2013; 5
2011; 193
2014; 22
2013; 9
2010; 21
2013; 87C
2014; 127
2009; 13
2010; 20
2010; 27
2010; 25
2010; 24
2010; 479
2011; 72
2007; 6
2011; 68
2014; 19
2014; 18
2009; 19
2010; 6334
2010; 30
2014; 12
2014; 10
2010; 31
2010; 37
2010; 6330
2011; 82
2013; 500
2011; 77
2011; 76
2002; 4
2014; 102P1
2014; 41
2012; 109
2010; 49
2010; 48
2006; 46
2003; 24
2014; 35
2005; 15
2010; 52
2010; 51
2012; 119
2014; 33
2010; 50
2009; 106
2009; 45
2012; 61
2009; 44
2012; 60
2009; 47
2009; 46
2009; 41
2012; 2012
2010; 153B
2013; 9(5 Suppl)
2011; 15
2012; 59
2011; 14
2011; 16
2012; 56
2011; 19
2009; 48
2012; 53
2012; 52
2013; 83C
2012; 72
2012; 71
2012; 295
2011; 168
2006; 63
2011; 22
2013; 273
2011; 26
2011; 25
2012; 69
2011; 27
2012; 68
2012; 63
2012; 62
2009; 23
2012; 83
2012; 263
2009; 21
2002; 297
2012; 1822
2006; 9
2008; 16
2009; 132
2011; 31
2013; 266
2011; 30
2006; 5
2011; 32
2009; 251
2012; 79
2012; 78
2009; 29
2009; 28
2012; 73
2009; 36
2009; 30
2012; 2
2011; 43
2012; 6
2012; 7
2012; 8
2012; 9
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Snippet Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic,...
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and...
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and...
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proquest
pubmed
crossref
wiley
elsevier
SourceType Open Access Repository
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StartPage e1
SubjectTerms Alzheimer Disease - cerebrospinal fluid
Alzheimer Disease - diagnosis
Alzheimer Disease - genetics
Alzheimer Disease - pathology
Alzheimer's disease
Amyloid
Biomarker
Biomarkers - cerebrospinal fluid
Brain - diagnostic imaging
Brain - pathology
Early Diagnosis
Humans
Mild cognitive impairment
Multicenter Studies as Topic
Neurology
Nootropic Agents - therapeutic use
Radionuclide Imaging
Tau
Title 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception
URI https://www.clinicalkey.es/playcontent/1-s2.0-S1552526014028659
https://dx.doi.org/10.1016/j.jalz.2014.11.001
https://onlinelibrary.wiley.com/doi/abs/10.1016%2Fj.jalz.2014.11.001
https://www.ncbi.nlm.nih.gov/pubmed/26073027
https://www.proquest.com/docview/1689310518
https://pubmed.ncbi.nlm.nih.gov/PMC5469297
Volume 11
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