publication . Article . 2012

Dissociation between brain amyloid deposition and metabolism in early mild cognitive impairment.

Liyong Wu; Jared Rowley; Sara Mohades; Antoine Leuzy; Marina Tedeschi Dauar; Monica Shin; Vladimir Fonov; Jianping Jia; Serge Gauthier; Pedro Rosa-Neto; ...
Open Access English
  • Published: 01 Oct 2012 Journal: PLoS ONE (issn: 1932-6203, Copyright policy)
  • Publisher: Public Library of Science (PLoS)
Abstract
Background The hypothetical model of dynamic biomarkers for Alzheimer’s disease (AD) describes high amyloid deposition and hypometabolism at the mild cognitive impairment (MCI) stage. However, it remains unknown whether brain amyloidosis and hypometabolism follow the same trajectories in MCI individuals. We used the concept of early MCI (EMCI) and late MCI (LMCI) as defined by the Alzheimer’s disease Neuroimaging Initiative (ADNI)-Go in order to compare the biomarker profile between EMCI and LMCI. Objectives To examine the global and voxel-based neocortical amyloid burden and metabolism among individuals who are cognitively normal (CN), as well as those with EMC...
Subjects
Medical Subject Headings: mental disorders
free text keywords: Medicine, R, Science, Q, Research Article, Biology, Neuroscience, Neuroimaging, Pet, Molecular Neuroscience, Mental Health, Psychiatry, Dementia, Neurology, Alzheimer Disease, Neurodegenerative Diseases, Radiology, Nuclear medicine, PET imaging
Funded by
CIHR
Project
  • Funder: Canadian Institutes of Health Research (CIHR)
,
NIH| CORE-- CLINICAL
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 3P30AG010129-11S1
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| "MR Morphometrics and Cognitive Decline Rate in Large-Scale Aging Studies"
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5K01AG030514-02
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| Alzheimers Disease Neuroimaging Initiative
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U01AG024904-01
  • Funding stream: NATIONAL INSTITUTE ON AGING
Communities
Neuroinformatics
43 references, page 1 of 3

1 Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, et al (2011) Alzheimer’s disease. Lancet 377: 1019–1031.21371747 [PubMed]

2 Jack CR Jr, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, et al (2010) Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol 9: 119–128.20083042 [OpenAIRE] [PubMed]

3 Wu L, Rosa-Neto P, Gauthier S (2011) Use of biomarkers in clinical trials of Alzheimer disease: from concept to application. Mol Diagn Ther 15: 313–325.22188635 [PubMed]

4 Hardy JA, Higgins GA (1992) Alzheimer’s disease: the amyloid cascade hypothesis. Science 256: 184–185.1566067 [PubMed]

5 Aisen PS, Petersen RC, Donohue MC, Gamst A, Raman R, et al (2010) Clinical Core of the Alzheimer’s Disease Neuroimaging Initiative: progress and plans. Alzheimers Dement 6: 239–246.20451872 [OpenAIRE] [PubMed]

6 Weiner MW, Aisen PS, Jack CR Jr, Jagust WJ, Trojanowski JQ, et al. (2010) The Alzheimer’s disease neuroi maging initiative: progress report and future plans. Alzheimers Dement 6: 202–211 e207.

7 Chetelat G, Villemagne VL, Bourgeat P, Pike KE, Jones G, et al (2010) Relationship between atrophy and beta-amyloid deposition in Alzheimer disease. Ann Neurol 67: 317–324.20373343 [PubMed]

8 Okello A, Koivunen J, Edison P, Archer HA, Turkheimer FE, et al (2009) Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 73: 754–760.19587325 [OpenAIRE] [PubMed]

9 Koivunen J, Scheinin N, Virta JR, Aalto S, Vahlberg T, et al (2011) Amyloid PET imaging in patients with mild cognitive impairment: a 2-year follow-up study. Neurology 76: 1085–1090.21325653 [OpenAIRE] [PubMed]

10 Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, et al (2010) Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging 32: 1207–1218.

11 Mosconi L, Berti V, Glodzik L, Pupi A, De Santi S, et al (2010) Pre-clinical detection of Alzheimer’s disease using FDG-PET, with or without amyloid imaging. J Alzheimers Dis 20: 843–854.20182025 [OpenAIRE] [PubMed]

12 Langbaum JB, Chen K, Lee W, Reschke C, Bandy D, et al (2009) Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neuroimage 45: 1107–1116.19349228 [OpenAIRE] [PubMed]

13 Mosconi L, Tsui WH, De Santi S, Li J, Rusinek H, et al (2005) Reduced hippocampal metabolism in MCI and AD: automated FDG-PET image analysis. Neurology 64: 1860–1867.15955934 [OpenAIRE] [PubMed]

14 Chen K, Langbaum JB, Fleisher AS, Ayutyanont N, Reschke C, et al (2010) Twelve-month metabolic declines in probable Alzheimer’s disease and amnestic mild cognitive impairment assessed using an empirically pre-defined statistical region-of-interest: findings from the Alzheimer’s Disease Neuroimaging Initiative. Neuroimage 51: 654–664.20202480 [OpenAIRE] [PubMed]

15 Landau SM, Harvey D, Madison CM, Reiman EM, Foster NL, et al (2010) Comparing predictors of conversion and decline in mild cognitive impairment. Neurology 75: 230–238.20592257 [OpenAIRE] [PubMed]

43 references, page 1 of 3
Abstract
Background The hypothetical model of dynamic biomarkers for Alzheimer’s disease (AD) describes high amyloid deposition and hypometabolism at the mild cognitive impairment (MCI) stage. However, it remains unknown whether brain amyloidosis and hypometabolism follow the same trajectories in MCI individuals. We used the concept of early MCI (EMCI) and late MCI (LMCI) as defined by the Alzheimer’s disease Neuroimaging Initiative (ADNI)-Go in order to compare the biomarker profile between EMCI and LMCI. Objectives To examine the global and voxel-based neocortical amyloid burden and metabolism among individuals who are cognitively normal (CN), as well as those with EMC...
Subjects
Medical Subject Headings: mental disorders
free text keywords: Medicine, R, Science, Q, Research Article, Biology, Neuroscience, Neuroimaging, Pet, Molecular Neuroscience, Mental Health, Psychiatry, Dementia, Neurology, Alzheimer Disease, Neurodegenerative Diseases, Radiology, Nuclear medicine, PET imaging
Funded by
CIHR
Project
  • Funder: Canadian Institutes of Health Research (CIHR)
,
NIH| CORE-- CLINICAL
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 3P30AG010129-11S1
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| "MR Morphometrics and Cognitive Decline Rate in Large-Scale Aging Studies"
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5K01AG030514-02
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| Alzheimers Disease Neuroimaging Initiative
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U01AG024904-01
  • Funding stream: NATIONAL INSTITUTE ON AGING
Communities
Neuroinformatics
43 references, page 1 of 3

1 Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, et al (2011) Alzheimer’s disease. Lancet 377: 1019–1031.21371747 [PubMed]

2 Jack CR Jr, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, et al (2010) Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol 9: 119–128.20083042 [OpenAIRE] [PubMed]

3 Wu L, Rosa-Neto P, Gauthier S (2011) Use of biomarkers in clinical trials of Alzheimer disease: from concept to application. Mol Diagn Ther 15: 313–325.22188635 [PubMed]

4 Hardy JA, Higgins GA (1992) Alzheimer’s disease: the amyloid cascade hypothesis. Science 256: 184–185.1566067 [PubMed]

5 Aisen PS, Petersen RC, Donohue MC, Gamst A, Raman R, et al (2010) Clinical Core of the Alzheimer’s Disease Neuroimaging Initiative: progress and plans. Alzheimers Dement 6: 239–246.20451872 [OpenAIRE] [PubMed]

6 Weiner MW, Aisen PS, Jack CR Jr, Jagust WJ, Trojanowski JQ, et al. (2010) The Alzheimer’s disease neuroi maging initiative: progress report and future plans. Alzheimers Dement 6: 202–211 e207.

7 Chetelat G, Villemagne VL, Bourgeat P, Pike KE, Jones G, et al (2010) Relationship between atrophy and beta-amyloid deposition in Alzheimer disease. Ann Neurol 67: 317–324.20373343 [PubMed]

8 Okello A, Koivunen J, Edison P, Archer HA, Turkheimer FE, et al (2009) Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 73: 754–760.19587325 [OpenAIRE] [PubMed]

9 Koivunen J, Scheinin N, Virta JR, Aalto S, Vahlberg T, et al (2011) Amyloid PET imaging in patients with mild cognitive impairment: a 2-year follow-up study. Neurology 76: 1085–1090.21325653 [OpenAIRE] [PubMed]

10 Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, et al (2010) Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging 32: 1207–1218.

11 Mosconi L, Berti V, Glodzik L, Pupi A, De Santi S, et al (2010) Pre-clinical detection of Alzheimer’s disease using FDG-PET, with or without amyloid imaging. J Alzheimers Dis 20: 843–854.20182025 [OpenAIRE] [PubMed]

12 Langbaum JB, Chen K, Lee W, Reschke C, Bandy D, et al (2009) Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neuroimage 45: 1107–1116.19349228 [OpenAIRE] [PubMed]

13 Mosconi L, Tsui WH, De Santi S, Li J, Rusinek H, et al (2005) Reduced hippocampal metabolism in MCI and AD: automated FDG-PET image analysis. Neurology 64: 1860–1867.15955934 [OpenAIRE] [PubMed]

14 Chen K, Langbaum JB, Fleisher AS, Ayutyanont N, Reschke C, et al (2010) Twelve-month metabolic declines in probable Alzheimer’s disease and amnestic mild cognitive impairment assessed using an empirically pre-defined statistical region-of-interest: findings from the Alzheimer’s Disease Neuroimaging Initiative. Neuroimage 51: 654–664.20202480 [OpenAIRE] [PubMed]

15 Landau SM, Harvey D, Madison CM, Reiman EM, Foster NL, et al (2010) Comparing predictors of conversion and decline in mild cognitive impairment. Neurology 75: 230–238.20592257 [OpenAIRE] [PubMed]

43 references, page 1 of 3
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