Abstract
Purpose
The present multimodal neuroimaging study examined whether amyloid pathology and glucose metabolism are related to cortical volume loss over time in Alzheimer’s disease (AD) patients and healthy elderly controls.
Methods
Structural MRI scans of eleven AD patients and ten controls were available at baseline and follow-up (mean interval 2.5 years). Change in brain structure over time was defined as percent change of cortical volume within seven a-priori defined regions that typically show the strongest structural loss in AD. In addition, two PET scans were performed at baseline: [11C]PIB to assess amyloid-β plaque load and [18F]FDG to assess glucose metabolism. [11C]PIB binding and [18F]FDG uptake were measured in the precuneus, a region in which both amyloid deposition and glucose hypometabolism occur early in the course of AD.
Results
While amyloid-β plaque load at baseline was not related to cortical volume loss over time in either group, glucose metabolism within the group of AD patients was significantly related to volume loss over time (rho = 0.56, p < 0.05).
Conclusion
The present study shows that in a group of AD patients amyloid-β plaque load as measured by [11C]PIB behaves as a trait marker (i.e., all AD patients showed elevated levels of amyloid, not related to subsequent disease course), whilst hypometabolism as measured by [18F]FDG changed over time indicating that it could serve as a state marker that is predictive of neurodegeneration.
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References
Jack Jr CR. Alliance for aging research AD biomarkers work group: structural MRI. Neurobiol Aging. 2011;32 Suppl 1:S48–57.
Jack Jr CR, Knopman DS, Jagust WJ, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12:207–16.
Caroli A, Frisoni GB. The dynamics of Alzheimer’s disease biomarkers in the Alzheimer’s Disease Neuroimaging Initiative cohort. Neurobiol Aging. 2010;31:1263–74.
Frisoni GB, Fox NC, Jack Jr CR, Scheltens P, Thompson PM. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol. 2010;6:67–77.
Fjell AM, Walhovd KB. New tools for the study of Alzheimer’s disease: what are biomarkers and morphometric markers teaching us? Neuroscientist. 2011;17:592–605.
Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science. 2002;297:353–6.
Klunk WE, Engler H, Nordberg A, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol. 2004;55:306–19.
Rabinovici GD, Jagust WJ. Amyloid imaging in aging and dementia: testing the amyloid hypothesis in vivo. Behav Neurol. 2009;21:117–28.
Tolboom N, Yaqub M, van der Flier WM, et al. Detection of Alzheimer pathology in vivo using both 11C-PIB and 18F-FDDNP PET. J Nucl Med. 2009;50:191–7.
Jack Jr CR, Lowe VJ, Weigand SD, et al. Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer’s disease: implications for sequence of pathological events in Alzheimer’s disease. Brain. 2009;132:1355–65.
Ossenkoppele R, Tolboom N, Foster-Dinsley J, et al. Longitudinal imaging of Alzheimer pathology using [11C]PIB, [18F]FDDNP and [18F]FDG PET. Eur J Nucl Med Mol Imaging. 2012;39:990–1000.
Engler H, Forsberg A, Almkvist O, et al. Two-year follow-up of amyloid deposition in patients with Alzheimer’s disease. Brain. 2006;129:2856–66.
Villain N, Chetelat G, Grassiot B, et al. Regional dynamics of amyloid-beta deposition in healthy elderly, mild cognitive impairment and Alzheimer’s disease: a voxelwise PiB-PET longitudinal study. Brain. 2012;135:2126–39.
Villemagne VL, Pike KE, Chetelat G, et al. Longitudinal assessment of Abeta and cognition in aging and Alzheimer disease. Ann Neurol. 2011;69:181–92.
Rocher AB, Chapon F, Blaizot X, Baron JC, Chavoix C. Resting-state brain glucose utilization as measured by PET is directly related to regional synaptophysin levels: a study in baboons. Neuroimage. 2003;20:1894–8.
Schwartz WJ, Smith CB, Davidsen L, Savaki H, Sokoloff L, Mata M, et al. Metabolic mapping of functional activity in the hypothalamo-neurohypophysial system of the rat. Science. 1979;205:723–5.
Drzezga A, Becker JA, Van Dijk KR, et al. Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden. Brain. 2011;134:1635–46.
Li Y, Rinne JO, Mosconi L, et al. Regional analysis of FDG and PIB-PET images in normal aging, mild cognitive impairment, and Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2008;35:2169–81.
Mosconi L, Sorbi S, de Leon MJ, et al. Hypometabolism exceeds atrophy in presymptomatic early-onset familial Alzheimer’s disease. J Nucl Med. 2006;47:1778–86.
Drzezga A, Lautenschlager N, Siebner H, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study. Eur J Nucl Med Mol Imaging. 2003;30:1104–13.
Folstein MF, Robins LN, Helzer JE. The mini-mental state examination. Arch Gen Psychiatry. 1983;40:812.
Albert MS, DeKosky ST, Dickson D, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:270–9.
McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:263–9.
Brix G, Zaers J, Adam LE, et al. Performance evaluation of a whole-body PET scanner using the NEMA protocol. National Electrical Manufacturers Association. J Nucl Med. 1997;38:1614–23.
Reuter M, Schmansky NJ, Rosas HD, Fischl B. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage. 2012;61:1402–18.
Sabuncu MR, Desikan RS, Sepulcre J, et al. The dynamics of cortical and hippocampal atrophy in Alzheimer disease. Arch Neurol. 2011;68:1040–8.
Fischl B, Sereno MI, Tootell RB, Dale AM. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp. 1999;8:272–84.
Whitwell JL, Jack Jr CR. Comparisons between Alzheimer disease, frontotemporal lobar degeneration, and normal aging with brain mapping. Top Magn Reson Imaging. 2005;16:409–25.
Svarer C, Madsen K, Hasselbalch SG, et al. MR-based automatic delineation of volumes of interest in human brain PET images using probability maps. Neuroimage. 2005;24:969–79.
Nissen IA, Boellaard R, Ossenkoppele R et al. Impact of partial volume corrections on quantitative brain PET studies [abstract]. SNM Conference 2012.
Teo BK, Seo Y, Bacharach SL, Carrasquillo JA, Libutti SK, Shukla H, et al. Partial-volume correction in PET: validation of an iterative postreconstruction method with phantom and patient data. J Nucl Med. 2007;48:802–10.
Wu Y, Carson RE. Noise reduction in the simplified reference tissue model for neuroreceptor functional imaging. J Cereb Blood Flow Metab. 2002;22:1440–52.
Yaqub M, Tolboom N, Boellaard R, van Berckel BN, van Tilburg EW, Luurtsema G, et al. Simplified parametric methods for [11C]PIB studies. Neuroimage. 2008;42:76–86.
Yamaguchi H, Hirai S, Morimatsu M, Shoji M, Nakazato Y. Diffuse type of senile plaques in the cerebellum of Alzheimer-type dementia demonstrated by beta protein immunostain. Acta Neuropathol. 1989;77:314–9.
Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging. 2001;20(1):45–57.
Chetelat G, Villemagne VL, Bourgeat P, et al. Relationship between atrophy and beta-amyloid deposition in Alzheimer disease. Ann Neurol. 2010;67(3):317–24.
Fagan AM, Head D, Shah AR, et al. Decreased cerebrospinal fluid Abeta[42] correlates with brain atrophy in cognitively normal elderly. Ann Neurol. 2009;65(2):176–83.
Villemagne VL, Burnham S, Bourgeat P, et al. Amyloid β deposition, neurodegeneration and cognitive decline in sporadic Alzheimer’s disease: a prospective cohort study. Lancet Neurol. 2013;12(4):357–67.
Tosun D, Schuff N, Mathis CA, Jagust W, Weiner MW. Spatial patterns of brain amyloid-beta burden and atrophy rate associations in mild cognitive impairment. Brain. 2011;134(Pt 4):1077–88.
Mormino EC, Kluth JT, Madison CM, et al. Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects. Brain. 2009;132(Pt 5):1310–23.
Andrews KA, Modat M, Macdonald KE, et al. Atrophy rates in asymptomatic amyloidosis: implications for Alzheimer prevention trials. PLoS One. 2013;8(3):e58816.
Driscoll I, Zhou Y, An Y, et al. Lack of association between 11C-PiB and longitudinal brain atrophy in non-demented older individuals. Neurobiol Aging. 2011;32(12):2123–30.
Josephs KA, Whitwell JL, Ahmed Z, et al. Beta-amyloid burden is not associated with rates of brain atrophy. Ann Neurol. 2008;63(2):204–12.
Chetelat G, Villemagne VL, Villain N, et al. Accelerated cortical atrophy in cognitively normal elderly with high beta-amyloid deposition. Neurology. 2012;78(7):477–84.
Doré V, Villemange VL, Bourgeat P, et al. Cross-sectional and longitudinal analysis of the relationship between Aβ deposition, cortical thickness, and memory in cognitively unimpaired individuals and in Alzheimer disease. JAMA Neurol. 2013;70(7):903–11.
DeSanti S, de Leon MJ, Rusinek H, et al. Hippocampal formation glucose metabolism and volume losses in MCI and AD. Neurobiol Aging. 2001;22(4):529–39.
Jagust W, Gitcho A, Sun F, Kuczynski B, Mungas D, Haan M. Brain imaging evidence of preclinical Alzheimer’s disease in normal aging. Ann Neurol. 2006;59(4):673–81.
Meguro K, LeMestric C, Landeau B, Eustache F, Baron J-C. Relations between hypometabolism in the posterior association neocortex and hippocampal atrophy in alzheimer’s disease: a PET/MRI correlative study. J Neurol Neurosurg Psychiatry. 2001;71:315–21.
Yamaguchi S, Meguro K, Itoh M, et al. Decreased cortical glucose metabolism correlates with hippocampal atrophy in Alzheimer’s disease as shown by MRI and PET. J Neurol Neurosurg Psychiatry. 1997;62:596–600.
Chetelat G, Desgranges B, Landeau B, Mezenge F, Poline JB, de la Sayette V, et al. Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer’s disease. Brain. 2008;131:60–71.
Förster S, Grimmer T, Miederer I, et al. Regional expansion of hypometabolism in Alzheimer’s disease follows amyloid deposition with temporal delay. Biol Psychiatry. 2012;71:792–7.
Knopman DS, Jack Jr CR, Wiste HJ, et al. Selective worsening of brain injury biomarker abnormalities in cognitively normal elderly persons with β-amyloidosis. JAMA Neurol. 2013;70(8):1030–8.
Cohen AD, Price JC, Weissfeld LA, et al. Basal cerebral metabolism may modulate the cognitive effects of aβ in mild cognitive impairment: an example of brain reserve. J Neurosci. 2009;29(47):14770–8.
Förster S, Yousefi BH, Wester HJ, et al. Quantitative longitudinal interrelationships between brain metabolism and amyloid deposition during a 2-year follow-up in patients with early Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2012;39(12):1927–37.
Cirrito JR, Kang JE, Lee J, et al. Endocytosis is required for synaptic activity-dependent release of amyloid-beta in vivo. Neuron. 2008;58:42–51.
Briellmann RS, Syngeniotis A, Jackson GD. Comparison of hippocampal volumetry at 1.5 Tesla and at 3 Tesla. Epilepsia. 2001;42(8):1021–4.
Scorzin JE, Kaaden S, Quesada CM, Müller CA, Fimmers R, Urbach H, et al. Volume determination of amygdale and hippocampus at 1.5 and 3.0 T MRI in temporal lobe epilepsy. Epilepsy Res. 2008;82(1):29–37.
Acknowledgments
This study was sponsored by Internationale Stichting Alzheimer Onderzoek (ISAO; project number #11539) and Hersenstichting Nederland (KS2011(1)-24).
We thank the support of the Athinoula A. Martinos Center for Biomedical Imaging at MGH including analysis methods developed by NIH grant P41RR14075.
Disclosure statement
Dr. Van Berckel receives research support from the American Health Assistance Foundation, Alzheimer Association, Internationale Stichting Alzheimer Onderzoek, the Center of Translational Molecular Medicine and the Dutch Organisation for Scientific Research.
Dr. Barkhof serves on the editorial boards of Brain, European Radiology, the Journal of Neurology, Neurosurgery & Psychiatry, the Journal of Neurology, Multiple Sclerosis and Neuroradiology and serves as a consultant for Bayer-Schering Pharma, Sanofi-Aventis, Biogen-Idec, UCB, Merck-Serono, Jansen Alzheimer Immunotherapy, Baxter, Novartis and Roche.
Dr. Scheltens serves/has served on the advisory boards of: Genentech, Novartis, Roche, Danone, Nutricia, Baxter and Lundbeck. He has been a speaker at symposia organised by Lundbeck, Merz, Danone, Novartis, Roche and Genentech. For all his activities he receives no personal compensation. He serves on the editorial board of Alzheimer’s Research & Therapy and Alzheimer Disease and Associated Disorders, is a member of the scientific advisory board of the EU Joint Programming Initiative and the French National Plan Alzheimer.
Dr. Reuter receives funding from several grants: NINDS 5R01NS052585-05, NIBIB 5R01EB006758-04, NINDS 2-R01-NS042861-06A1, NINDS 5-P01-NS058793-03, and NICHD R01-HD071664.
There are no other actual or potential conflicts of interest to disclose. All authors have read and agreed with the contents of the manuscript. The results of the study have not been published before and they are not under consideration to be published by another journal.
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Adriaanse, S.M., van Dijk, K.R.A., Ossenkoppele, R. et al. The effect of amyloid pathology and glucose metabolism on cortical volume loss over time in Alzheimer’s disease. Eur J Nucl Med Mol Imaging 41, 1190–1198 (2014). https://doi.org/10.1007/s00259-014-2704-z
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DOI: https://doi.org/10.1007/s00259-014-2704-z