The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Altered Brain Mitochondrial Metabolism in Healthy Aging as Assessed by in vivo Magnetic Resonance Spectroscopy
Open accessAbstract
A decline in brain function is a characteristic feature of healthy aging; however, little is known about the biologic basis of this phenomenon. To determine whether there are alterations in brain mitochondrial metabolism associated with healthy aging, we combined 13 C/ 1 H magnetic resonance spectroscopy with infusions of [1- 13 C]glucose and [2- 13 C]acetate to quantitatively characterize rates of neuronal and astroglial tricarboxylic acid cycles, as well as neuroglial glutamate–glutamine cycling, in healthy elderly and young volunteers. Compared with young subjects, neuronal mitochondrial metabolism and glutamate–glutamine cycle flux was ∼30% lower in elderly subjects. The reduction in individual subjects correlated strongly with reductions in N-acetylaspartate and glutamate concentrations consistent with chronic reductions in brain mitochondrial function. In elderly subjects infused with [2- 13 C]acetate labeling of glutamine, C4 and C3 differed from that of the young subjects, indicating age-related changes in glial mitochondrial metabolism. Taken together, these studies show that healthy aging is associated with reduced neuronal mitochondrial metabolism and altered glial mitochondrial metabolism, which may in part be responsible for declines in brain function.
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Cites
An Energy Budget for Signaling in the Grey Matter of the Brain
Attwell, D., & Laughlin, S. B. (2001) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-200110000-00001 · Cited by 3,543
Insights into the ageing mind: a view from cognitive neuroscience
Hedden, T., & Gabrieli, J. D. E. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1323 · Cited by 2,223
Mitochondrial DNA mutations, oxidative stress, and apoptosis in mammalian aging
Kujoth, G. C., Hiona, A., Pugh, T. D., Someya, S., Panzer, K., Wohlgemuth, S. E., Hofer, T., Seo, A. Y., Sullivan, R., Jobling, W. A., et al. (2005) · Science · doi:10.1126/science.1112125 · Cited by 2,165
Thinning of the Cerebral Cortex in Aging
Salat, D. H. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh032 · Cited by 1,851
Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain
Resnick, S. M., Pham, D. L., Kraut, M. A., Zonderman, A. B., & Davatzikos, C. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-08-03295.2003 · Cited by 1,425
Determination of the rate of the glutamate/glutamine cycle in the human brain by in vivo 13 C NMR
Shen, J., Petersen, K. F., Behar, K. L., Brown, P., Nixon, T. W., Mason, G. F., Petroff, O. A. C., Shulman, G. I., Shulman, R. G., & Rothman, D. L. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.14.8235 · Cited by 462
Self-citationNeuronal-glial glucose oxidation and glutamatergic-GABAergic function.
Hyder, F., Patel, A. B., Gjedde, A., Rothman, D. L., Behar, K. L., & Shulman, R. G. (2006) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/sj.jcbfm.9600263 · Cited by 408
Self-citationDecreases in regional cerebral blood flow with normal aging
Martin, A. J., Friston, K. J., Colebatch, J. G., & Frackowiak, R. S. J. (1991) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.1991.121 · Cited by 393
Voxel-based mapping of brain gray matter volume and glucose metabolism profiles in normal aging
Kalpouzos, G., Chételat, G., Baron, J.-C., Landeau, B., Mevel, K., Godeau, C., Barré, L., Constans, J.-M., Viader, F., Eustache, F., et al. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2007.05.019 · Cited by 392 · cited 2×
“Studies using positron emission tomography (PET) have shown decreases in brain glucose metabolism associated with aging (Salat et al, 2004; Kalpouzos et al, 2009), but these may not be related to mitochondrial changes.”
BackgroundResultLebon, V., Petersen, K. F., Cline, G. W., Shen, J., Mason, G. F., Dufour, S., Behar, K. L., Shulman, G. I., & Rothman, D. L. (2002) · The Journal of Neuroscience · doi:10.1523/jneurosci.22-05-01523.2002 · Cited by 371
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The Role of Oxidative Stress in Parkinson's Disease
Dias, V., Junn, E., & Mouradian, M. M. (2013) · Journal of Parkinson’s Disease · doi:10.3233/jpd-130230 · Cited by 1,845
Verkhratsky, A., & Nedergaard, M. (2018) · Physiological Reviews · doi:10.1152/physrev.00042.2016 · Cited by 1,678
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Samuel, V. T., Petersen, K. F., & Shulman, G. I. (2010) · The Lancet · doi:10.1016/s0140-6736(10)60408-4 · Cited by 1,189
Self-citationEctopic Fat in Insulin Resistance, Dyslipidemia, and Cardiometabolic Disease
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Metadata
- Authors
- Boumezbeur, F., Mason, G. F., de Graaf, R. A., Behar, K. L., Cline, G. W., Shulman, G. I., Rothman, D. L., & Petersen, K. F.
- Venue
- Journal of Cerebral Blood Flow & Metabolism
- Publisher
- SAGE Publications
- Published
- 2009-09-30
- Volume
- 30
- Issue
- 1
- Pages
- 211-221
- ISSN
- 0271-678X (ISSN-L)
- 1559-7016
- OpenAlex
- W2000867410
- Cited by
- 238
- References
- 12
- FWCI
- 10.80
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Boumezbeur, F., Mason, G. F., de Graaf, R. A., Behar, K. L., Cline, G. W., Shulman, G. I., Rothman, D. L., & Petersen, K. F. (2010). Altered Brain Mitochondrial Metabolism in Healthy Aging as Assessed by in vivo Magnetic Resonance Spectroscopy. Journal of Cerebral Blood Flow & Metabolism. https://doi.org/10.1038/jcbfm.2009.197
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