Spatial correlation between brain aerobic glycolysis and amyloid-β (Aβ) deposition

Vlassenko, Andrei G.; Vaishnavi, S. Neil; Couture, Lars; Sacco, Dana; Shannon, Benjamin J.; Mach, Robert H.; Morris, John C.; Raichle, Marcus E.; Mintun, Mark A.

doi:10.1073/pnas.1010461107

Cited by 405Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsMedical Imaging Techniques and Applications

Spatial correlation between brain aerobic glycolysis and amyloid-β (Aβ) deposition

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Vlassenko, Andrei G., Vaishnavi, S. Neil, Couture, Lars, Sacco, Dana, Shannon, Benjamin J., Mach, Robert H., Morris, John C., Raichle, Marcus E. +1 more·2010·Proceedings of the National Academy of Sciences

DOI 10.1073/pnas.1010461107PMC PMC2955133

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Abstract

Amyloid-β (Aβ) plaque deposition can precede the clinical manifestations of dementia of the Alzheimer type (DAT) by many years and can be associated with changes in brain metabolism. Both the Aβ plaque deposition and the changes in metabolism appear to be concentrated in the brain's default-mode network. In contrast to prior studies of brain metabolism which viewed brain metabolism from a unitary perspective that equated glucose utilization with oxygen consumption, we here report on regional glucose use apart from that entering oxidative phosphorylation (so-called "aerobic glycolysis"). Using PET, we found that the spatial distribution of aerobic glycolysis in normal young adults correlates spatially with Aβ deposition in individuals with DAT and cognitively normal participants with elevated Aβ, suggesting a possible link between regional aerobic glycolysis in young adulthood and later development of Alzheimer pathology.

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Brain aerobic glycolysis was previously found to be highest in regions most vulnerable to amyloid deposition.
“Similarly, brain AG was previously found to be highest in regions most vulnerable to amyloid deposition”
From Aerobic glycolysis in the human brain is associated with development and neotenous gene expression (2014) · cites this paper as Vlassenko et al., 2010
Aerobic glycolysis identifies regions most vulnerable to amyloid-beta deposition in Alzheimer's disease.
“Further, AG identifies regions most vulnerable to amyloid-beta deposition in Alzheimer’s disease”
From Aerobic glycolysis in the human brain is associated with development and neotenous gene expression (2014) · cites this paper as Vlassenko et al., 2010
Young ApoE4 carriers showed increased brain activity in default network regions, as well as in the hippocampus and the temporal lobe, possibly due to increased aerobic glycolysis.
“Young ApoE4 carriers showed increased brain activity in default network regions, as well as in the hippocampus and the temporal lobe, possibly due to increased aerobic glycolysis.34”
From ApoE4-dependent lysosomal cholesterol accumulation impairs mitochondrial homeostasis and oxidative phosphorylation in human astrocytes (2023) · cites this paper as [34]
Abundant data from human and cell-based studies either suggest or demonstrate bioenergetic factors regulate both APP processing and Aβ production.
“Whether Aβ changes precede either age-related or AD-related brain bioenergetic changes is less clear-cut, especially since abundant data from human and cell-based studies either suggest or demonstrate bioenergetic factors regulate both APP processing and Aβ production [95–100].”
From Brain aging, Alzheimer's disease, and mitochondria (2011) · cites this paper as [99]
Whether Aβ changes precede either age-related or AD-related brain bioenergetic changes is less clear-cut.
“Whether Aβ changes precede either age-related or AD-related brain bioenergetic changes is less clear-cut, especially since abundant data from human and cell-based studies either suggest or demonstrate bioenergetic factors regulate both APP processing and Aβ production [95–100].”
From Brain aging, Alzheimer's disease, and mitochondria (2011) · cites this paper as [99]

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Mejı́as, R., Villadiego, J., Pintado, C. O., Vime, P. J., Gao, L., Toledo‐Aral, J. J., Echevarrı́a, M., & López‐Barneo, J. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.0122-06.2006 · Cited by 74 · see citing works
Cerebral Glucose Transport and Metabolism in Preterm Human Infants
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Excitotoxicity, apoptosis and neuropsychiatric disorders
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Excitotoxic neurodegeneration in Alzheimer disease
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Isolation of glyceraldehyde 3-phosphate dehydrogenase (Gapdh) cDNA from the distal half of mouse chromosome 16: further indication of a link between Alzheimer's disease and glycolysis
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The brain's default mode network
Raichle, M. E. (2015) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071013-014030 · Cited by 3,904 · see citing works
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Alzheimer’s Disease: The Challenge of the Second Century
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Neuronal activity regulates the regional vulnerability to amyloid-β deposition
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Brain Glucose Metabolism: Integration of Energetics with Function.
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Mitochondria and Mitochondrial Cascades in Alzheimer’s disease
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What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus
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The Alzheimer’s disease mitochondrial cascade hypothesis: progress and perspectives
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Regional aerobic glycolysis in the human brain
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Memory loss in Alzheimer's disease
Jahn, H. (2013) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2013.15.4/hjahn · Cited by 653 · see citing works
Astrocyte-neuron metabolic cooperation shapes brain activity
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Imaging the evolution and pathophysiology of Alzheimer disease
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Resting-state functional connectivity in normal brain aging
Ferreira, L. K., & Busatto, G. F. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.01.017 · Cited by 586 · see citing works
The Regulation and Function of Lactate Dehydrogenase A: Therapeutic Potential in Brain Tumor
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Brain imaging and fluid biomarker analysis in young adults at genetic risk for autosomal dominant Alzheimer's disease in the presenilin 1 E280A kindred: a case-control study
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Estrogen: A master regulator of bioenergetic systems in the brain and body
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Circadian clock proteins regulate neuronal redox homeostasis and neurodegeneration
Musiek, E. S., Lim, M. M., Yang, G., Bauer, A. Q., Qi, L., Lee, Y., Roh, J. H., Ortiz-Gonzalez, X., Dearborn, J. T., Culver, J. P., et al. (2013) · Journal of Clinical Investigation · doi:10.1172/jci70317 · Cited by 524 · see citing works
Resting state functional connectivity in preclinical Alzheimer’s disease
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Aerobic glycolysis in the human brain is associated with development and neotenous gene expression
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“Furthermore, AG identifies regions most vulnerable to amyloid-beta deposition in Alzheimer’s disease (Vlassenko et al., 2010).”
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Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden
Drzezga, A. E., Becker, J. A., Dijk, K. R. A. V., Sreenivasan, A., Talukdar, T., Sullivan, C., Schultz, A. P., Sepulcre, J., Putcha, D., Greve, D. N., et al. (2011) · Brain · doi:10.1093/brain/awr066 · Cited by 377 · see citing works
Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity
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Intracerebroventricular Streptozotocin Injections as a Model of Alzheimer’s Disease: in Search of a Relevant Mechanism
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Loss of Brain Aerobic Glycolysis in Normal Human Aging
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Brain aging, Alzheimer's disease, and mitochondria
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The serendipitous discovery of the brain's default network
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Insulin Resistance and Alzheimer’s Disease: Bioenergetic Linkages
Neth, B. J., & Craft, S. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00345 · Cited by 275 · see citing works
The human connectome in Alzheimer disease — relationship to biomarkers and genetics
Yu, M., Sporns, O., & Saykin, A. J. (2021) · Nature Reviews Neurology · doi:10.1038/s41582-021-00529-1 · Cited by 265 · see citing works
Oxidative Stress and Beta Amyloid in Alzheimer’s Disease. Which Comes First: The Chicken or the Egg?
Tamagno, E., Guglielmotto, M., Vasciaveo, V., & Tabaton, M. (2021) · Antioxidants · doi:10.3390/antiox10091479 · Cited by 272 · see citing works
Hyperconnectivity is a fundamental response to neurological disruption.
Hillary, F. G., Román, C. A. F., Venkatesan, U. M., Rajtmajer, S. M., Bajo, R., & Castellanos, N. P. (2014) · Neuropsychology · doi:10.1037/neu0000110 · Cited by 248 · see citing works
Resting-State Brain Functional Connectivity Is Altered in Type 2 Diabetes
Musen, G., Jacobson, A. M., Bolo, N. R., Simonson, D. C., Shenton, M. E., McCartney, R. L., Flores, V. L., & Hoogenboom, W. S. (2012) · Diabetes · doi:10.2337/db11-1669 · Cited by 242 · see citing works
A brief history of the resting state: The Washington University perspective
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Altered glucose metabolism in Alzheimer's disease: Role of mitochondrial dysfunction and oxidative stress
Dewanjee, S., Chakraborty, P., Bhattacharya, H., Chacko, L., Singh, B., Chaudhary, A., Javvaji, K., Pradhan, S. R., Vallamkondu, J., Dey, A., et al. (2022) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2022.09.032 · Cited by 235 · see citing works
Potential role of orexin and sleep modulation in the pathogenesis of Alzheimer’s disease
Roh, J. H., Jiang, H., Finn, M. B., Stewart, F. R., Mahan, T. E., Cirrito, J. R., Heda, A., Snider, B. J., Li, M., Yanagisawa, M., et al. (2014) · The Journal of Experimental Medicine · doi:10.1084/jem.20141788 · Cited by 230 · see citing works
A transcriptional signature of hub connectivity in the mouse connectome
Fulcher, B., & Fornito, A. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1513302113 · Cited by 227 · see citing works
Mechanisms of Mitochondrial Dysfunction in Alzheimer’s Disease
Cadonic, C., Sabbir, M. G., & Albensi, B. C. (2016) · Molecular Neurobiology · doi:10.1007/s12035-015-9515-5 · Cited by 226 · see citing works
The sirtuin pathway in ageing and Alzheimer disease: mechanistic and therapeutic considerations
Bonda, D., Lee, H., Camins, A., Pallàs, M., Casadesús, G., Smith, M. A., & Zhu, X. (2011) · The Lancet Neurology · doi:10.1016/s1474-4422(11)70013-8 · Cited by 221 · see citing works
Lifespan brain activity, β-amyloid, and Alzheimer's disease
Jagust, W. J., & Mormino, E. C. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.09.004 · Cited by 221 · see citing works
Inflammatory microglia are glycolytic and iron retentive and typify the microglia in APP/PS1 mice
Holland, R., McIntosh, A. L., Finucane, O. M., Mela, V., Rubio‐Araiz, A., Timmons, G. A., McCarthy, S. A., Gun’ko, Y. K., & Lynch, M. A. (2017) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2017.10.017 · Cited by 217 · see citing works
Insulin Resistance as a Link between Amyloid-Beta and Tau Pathologies in Alzheimer’s Disease
Mullins, R. J., Diehl, T. C., Chia, C. W., & Kapogiannis, D. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00118 · Cited by 213 · see citing works
Mitochondrial dysfunction in microglia: a novel perspective for pathogenesis of Alzheimer’s disease
Li, Y., Xia, X., Wang, Y., & Zheng, J. (2022) · Journal of Neuroinflammation · doi:10.1186/s12974-022-02613-9 · Cited by 219 · see citing works
Association of Excessive Daytime Sleepiness With Longitudinal β-Amyloid Accumulation in Elderly Persons Without Dementia
Carvalho, D. Z., Louis, E. K. S., Knopman, D. S., Boeve, B. F., Lowe, V. J., Roberts, R. O., Mielke, M. M., Przybelski, S. A., Machulda, M. M., Petersen, R. C., et al. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2018.0049 · Cited by 207 · see citing works
Selective loss of cortical endothelial tight junction proteins during Alzheimer’s disease progression
Yamazaki, Y., Shinohara, M., Shinohara, M., Yamazaki, A., Murray, M. E., Liesinger, A. M., Heckman, M. G., Lesser, E. R., Parisi, J. E., Petersen, R. C., et al. (2019) · Brain · doi:10.1093/brain/awz011 · Cited by 202 · see citing works
Bidirectional Relationship between Functional Connectivity and Amyloid-β Deposition in Mouse Brain
Bero, A. W., Bauer, A. Q., Stewart, F. R., White, B. R., Cirrito, J. R., Raichle, M. E., Culver, J. P., & Holtzman, D. M. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.5845-11.2012 · Cited by 181 · see citing works
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Impaired default network functional connectivity in autosomal dominant Alzheimer disease
Chhatwal, J. P., Schultz, A. P., Johnson, K., Benzinger, T. L. S., Jack, C., Ances, B. M., Sullivan, C. A., Salloway, S. P., Ringman, J. M., Koeppe, R. A., et al. (2013) · Neurology · doi:10.1212/wnl.0b013e3182a1aafe · Cited by 179 · see citing works
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Direct comparison of fluorodeoxyglucose positron emission tomography and arterial spin labeling magnetic resonance imaging in Alzheimer's disease
Musiek, E. S., Chen, Y., Korczykowski, M., Saboury, B., Martinez, P. M., Reddin, J. S., Alavi, A. A., Kimberg, D. Y., Wolk, D. A., Julin, P., et al. (2011) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2011.06.003 · Cited by 180 · see citing works
Reactive astrocytes: The nexus of pathological and clinical hallmarks of Alzheimer’s disease
Price, B. R., Johnson, L. A., & Norris, C. M. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101335 · Cited by 174 · see citing works
PET amyloid-beta imaging in preclinical Alzheimer's disease
Vlassenko, A. G., Benzinger, T. L. S., & Morris, J. C. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2011.11.005 · Cited by 173 · see citing works
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2-Deoxy-D-Glucose Treatment Induces Ketogenesis, Sustains Mitochondrial Function, and Reduces Pathology in Female Mouse Model of Alzheimer's Disease
Yao, J., Chen, S., Mao, Z., Cadenas, E., & Brinton, R. D. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021788 · Cited by 169 · see citing works
Local and distant relationships between amyloid, tau and neurodegeneration in Alzheimer's Disease
Iaccarino, L., Tammewar, G., Ayakta, N., Baker, S. L., Bejanin, A., Boxer, A. L., Gorno-Tempini, M. L., Janabi, M., Kramer, J. H., Lazaris, A., et al. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.09.016 · Cited by 165 · see citing works
White Matter Lipids as a Ketogenic Fuel Supply in Aging Female Brain: Implications for Alzheimer's Disease
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Sirtuin1: A Promising Serum Protein Marker for Early Detection of Alzheimer’s Disease
Kumar, R. K., Chaterjee, P., Sharma, P. K., Singh, A. K., Gupta, A., Gill, K., Tripathi, M., Dey, A. B., & Dey, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061560 · Cited by 163 · see citing works
Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight
Vogel, J. W., Corriveau‐Lecavalier, N., Franzmeier, N., Pereira, J. B., Brown, J. A., Maaß, A., Botha, H., Seeley, W. W., Bassett, D. S., Jones, D. T., et al. (2023) · Nature reviews. Neuroscience · doi:10.1038/s41583-023-00731-8 · Cited by 160 · see citing works
From inflamm-aging to immune-paralysis: a slippery slope during aging for immune-adaptation
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The Extrinsic and Intrinsic Functional Architectures of the Human Brain Are Not Equivalent
Mennes, M., Kelly, C. A. M., Colcombe, S. J., Castellanos, F. X., & Milham, M. P. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs010 · Cited by 160 · see citing works
Energy Failure
Pathak, D., Berthet, A., & Nakamura, K. (2013) · Annals of Neurology · doi:10.1002/ana.24014 · Cited by 157 · see citing works
Apolipoprotein E, not fibrillar β-amyloid, reduces cerebral glucose metabolism in normal aging
Jagust, W. J., Landau, S. M., & Initiative, F. T. A. D. N. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.3266-12.2012 · Cited by 162 · see citing works
A Deposition in Aging Is Associated with Increases in Brain Activation during Successful Memory Encoding
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Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease
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Blood oxygenation level‐dependent (BOLD)‐based techniques for the quantification of brain hemodynamic and metabolic properties – theoretical models and experimental approaches
Yablonskiy, D. A., Sukstanskii, A. L., & He, X. (2012) · NMR in Biomedicine · doi:10.1002/nbm.2839 · Cited by 148 · see citing works
Ushering in the study and treatment of preclinical Alzheimer disease
Langbaum, J. B. S., Fleisher, A., Chen, K., Ayutyanont, N., Lopera, F. J., Quiroz, Y. T., Caselli, R. J., Tariot, P. N., & Reiman, E. M. (2013) · Nature Reviews Neurology · doi:10.1038/nrneurol.2013.107 · Cited by 145 · see citing works
Amyloid-β diurnal pattern: possible role of sleep in Alzheimer's disease pathogenesis
Lucey, B. P., & Bateman, R. J. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.03.035 · Cited by 144 · see citing works
Functional network integrity presages cognitive decline in preclinical Alzheimer disease
Buckley, R. F., Schultz, A. P., Hedden, T., Papp, K. V., Hanseeuw, B. J., Marshall, G. A., Sepulcre, J., Smith, E. E., Rentz, D. M., Johnson, K. A., et al. (2017) · Neurology · doi:10.1212/wnl.0000000000004059 · Cited by 143 · see citing works
Neuroketotherapeutics: A modern review of a century-old therapy
Koppel, S. J., & Swerdlow, R. H. (2017) · Neurochemistry International · doi:10.1016/j.neuint.2017.05.019 · Cited by 140 · see citing works
Molecular properties underlying regional vulnerability to Alzheimer’s disease pathology
Grothe, M. J., Sepulcre, J., Gonzalez-Escamilla, G., Jelistratova, I., Schöll, M., Hansson, O., Teipel, S. J., & Initiative, A. D. N. (2018) · Brain · doi:10.1093/brain/awy189 · Cited by 142 · see citing works
Local molecular and global connectomic contributions to cross-disorder cortical abnormalities
Hansen, J. Y., Shafiei, G., Vogel, J. W., Smart, K. A., Bearden, C. E., Hoogman, M., Franke, B., van Rooij, D., Buitelaar, J. K., McDonald, C. R., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32420-y · Cited by 125 · see citing works
Within-patient correspondence of amyloid-β and intrinsic network connectivity in Alzheimer’s disease
Myers, N., Pasquini, L., Göttler, J., Grimmer, T., Koch, K., Ortner, M., Neitzel, J., Mühlau, M., Förster, S., Kurz, A., et al. (2014) · Brain · doi:10.1093/brain/awu103 · Cited by 132 · see citing works
Brain imaging in the study of Alzheimer's disease
Reiman, E. M., & Jagust, W. J. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.075 · Cited by 134 · see citing works
Human neoteny revisited: The case of synaptic plasticity
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Mitochondrial control of microglial phagocytosis by the translocator protein and hexokinase 2 in Alzheimer’s disease
Fairley, L. H., Lai, K. O., Wong, J. H., Chong, W. J., Vincent, A. S., D’Agostino, G. A., Wu, X., Naik, R. R., Jayaraman, A., Langley, S. R., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2209177120 · Cited by 127 · see citing works
Brain cells derived from Alzheimer’s disease patients have multiple specific innate abnormalities in energy metabolism
Ryu, W., Bormann, M. K., Shen, M., Kim, D., Forester, B. P., Park, Y., So, J., Seo, H., Sonntag, K., & Cohen, B. M. (2021) · Molecular Psychiatry · doi:10.1038/s41380-021-01068-3 · Cited by 125 · see citing works
Lactate deficit in an Alzheimer disease mouse model: the relationship with neuronal damage
Zhang, M., Cheng, X., Dang, R., Zhang, W., Zhang, J., & Yao, Z. (2018) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nly102 · Cited by 130 · see citing works
Shift in brain metabolism in late onset Alzheimer’s disease: Implications for biomarkers and therapeutic interventions
Yao, J., Rettberg, J. R., Klosinski, L. P., Cadenas, E., & Brinton, R. D. (2011) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2011.10.005 · Cited by 124 · see citing works
Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease
Lehmann, M., Madison, C. M., Ghosh, P. M., Seeley, W. W., Mormino, E., Greicius, M. D., Gorno-Tempini, M. L., Kramer, J. H., Miller, B. L., Jagust, W. J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1221536110 · Cited by 122 · see citing works
Socially responsive effects of brain oxidative metabolism on aggression
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Cerebrospinal fluid lactate levels and brain [18F]FDG PET hypometabolism within the default mode network in Alzheimer’s disease
Liguori, C., Chiaravalloti, A., Sancesario, G., Stefani, A., Sancesario, G. M., Mercuri, N. B., Schillaci, O., & Pierantozzi, M. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3417-2 · Cited by 117 · see citing works
Mitochondrial hyperpolarization in iPSC-derived neurons from patients of FTDP-17 with 10+16 MAPT mutation leads to oxidative stress and neurodegeneration
Esteras, N., Rohrer, J. D., Hardy, J., Wray, S., & Abramov, A. Y. (2017) · Redox Biology · doi:10.1016/j.redox.2017.03.008 · Cited by 117 · see citing works
Amyloid Beta Resistance in Nerve Cell Lines Is Mediated by the Warburg Effect
Newington, J. T., Pitts, A., Chien, A., Arseneault, R., Schubert, D. A., & Cumming, R. C. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019191 · Cited by 121 · see citing works
Mitochondrial Regulation of Microglial Immunometabolism in Alzheimer’s Disease
Fairley, L. H., Wong, J. H., & Barron, A. M. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.624538 · Cited by 120 · see citing works
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IC‐P‐195: Region‐specific associations of brain glucose metabolism with age and beta‐amyloid in normal aging
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Authors: Vlassenko, A. G., Vaishnavi, S. N., Couture, L., Sacco, D., Shannon, B. J., Mach, R. H., Morris, J. C., Raichle, M. E., & Mintun, M. A.
Affiliations: Washington University in St. Louis (US)
Departments of aRadiology,
Neurology,
Corresponding author: Mintun, Mark A.
ORCID: Vlassenko, Andrei G.
Vaishnavi, S. Neil
Sacco, Dana
Mach, Robert H.
Morris, John C.
Raichle, Marcus E.
Venue: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences
Published: 2010-09-13
Volume: 107
Issue: 41
Pages: 17763-17767
ISSN: 0027-8424 (ISSN-L)
1091-6490
DOI: 10.1073/pnas.1010461107
PMC: PMC2955133
OpenAlex: W2137243283
Cited by: 404
References: 84
Citations by year: 2026: 20 · 2025: 21 · 2024: 15 · 2023: 21 · 2022: 26 · 2021: 22 · 2020: 24 · 2019: 20 · 2018: 28 · 2017: 41 · 2016: 20 · 2015: 23 · 2014: 28 · 2013: 33 · 2012: 28
FWCI: 20.41
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Proceedings of the National Academy of Sciences (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: National Institutes of Health (5p20mh077967-04, AG05681, AG003991)
National Institute on Aging (P50AG005681, P01AG003991)
National Institute of Mental Health (P20MH-077967)
National Institute of Neurological Disorders and Stroke (F30NS057901, P30NS048056, P50NS006833)
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 › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
Keywords: aerobic glycolysis, amyloid-beta deposition, Alzheimer's disease, default mode network, brain glucose metabolism, oxidative phosphorylation, spatial correlation, young adults, positron emission tomography
MeSH terms: Adult, Alzheimer Disease, Amyloid, Brain, Female, Glucose, Glycolysis, Humans, Male, Oxygen, Positron-Emission Tomography

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Spatial correlation between brain aerobic glycolysis and amyloid-β (Aβ) deposition

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