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Review
. 2011 Jan;27(1):3-20.
doi: 10.1016/j.nut.2010.07.021. Epub 2010 Oct 29.

Brain fuel metabolism, aging, and Alzheimer's disease

Stephen Cunnane  1 , Scott Nugent  2 , Maggie Roy  2 , Alexandre Courchesne-Loyer  2 , Etienne Croteau  3 , Sébastien Tremblay  4 , Alex Castellano  5 , Fabien Pifferi  6 , Christian Bocti  7 , Nancy Paquet  3 , Hadi Begdouri  3 , M'hamed Bentourkia  3 , Eric Turcotte  3 , Michèle Allard  8 , Pascale Barberger-Gateau  9 , Tamas Fulop  7 , Stanley I Rapoport  10
Affiliations
Review

Brain fuel metabolism, aging, and Alzheimer's disease

Stephen Cunnane et al. Nutrition. 2011 Jan.

Abstract

Lower brain glucose metabolism is present before the onset of clinically measurable cognitive decline in two groups of people at risk of Alzheimer's disease--carriers of apolipoprotein E4, and in those with a maternal family history of AD. Supported by emerging evidence from in vitro and animal studies, these reports suggest that brain hypometabolism may precede and therefore contribute to the neuropathologic cascade leading to cognitive decline in AD. The reason brain hypometabolism develops is unclear but may include defects in brain glucose transport, disrupted glycolysis, and/or impaired mitochondrial function. Methodologic issues presently preclude knowing with certainty whether or not aging in the absence of cognitive impairment is necessarily associated with lower brain glucose metabolism VSports手机版. Nevertheless, aging appears to increase the risk of deteriorating systemic control of glucose utilization, which, in turn, may increase the risk of declining brain glucose uptake, at least in some brain regions. A contributing role of deteriorating glucose availability to or metabolism by the brain in AD does not exclude the opposite effect, i. e. , that neurodegenerative processes in AD further decrease brain glucose metabolism because of reduced synaptic functionality and hence reduced energy needs, thereby completing a vicious cycle. Strategies to reduce the risk of AD by breaking this cycle should aim to (1) improve insulin sensitivity by improving systemic glucose utilization, or (2) bypass deteriorating brain glucose metabolism using approaches that safely induce mild, sustainable ketonemia. .

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Conflict of interest statement

The authors declare no conflicts.

"V体育ios版" Figures

Figure 1
Figure 1
Lower overall brain volume with age modified from [206]. Based on these data, between about 30 y old (white bars) and 70 y old (black bars), the overall rate of decrease is about 1.6%/decade, or 6–7%, with no difference between men and women.
Figure 2
Figure 2
The pathway of ketone synthesis. When acetyl CoA production from β-oxidized fatty acids exceeds the capacity of the tricarboxylic acid cycle, the excess acetyl CoA can condense into ketones, a process that happens predominantly but not exclusively in the liver.
Figure 3
Figure 3
The relationship between plasma ketones (shown here only as β-hydroxybutyrate; β-HB) and cerebral metabolic rate of ketones (CMRβ-HB; left hand y-axis) over a physiological range of plasma β-HB. In the original studies, two different methods were used to calculate CMRβ-HB: (i) PET (n=5 points collected close together in the bottom left of the graph between β-HB values of 0.0–0.2 mM; ○) [207], and (ii) arterio-venous difference taking into account cerebral blood flow – (n=26; ◇ [19]), and (n=10 controls □, and n=12 presumed Alzheimer’s disease ▲) [21]. Arterio-venous difference in brain β-HB uptake was reportedly the same in Alzheimer’s disease as in the controls [21]. Combined together, the 53 data points from these three studies provide the following equation of the line for CMRβ-HB over a plasma β-HB concentration range from 0.0–1.5 mM: y = 1.677x + 0.0454 (r = 0.638; p < 0.0001). The right hand y axis shows the percentage contribution of ketones to the energy requirements of the whole human brain over a physiological range of plasma β-HB. The intercept of ~18% of brain energy requirements being met by β-HB at a plasma β-HB concentration of 1.5 mM is corroborated by two additional papers that reported arterio-venous differences across the brain to derive CMRβ-HB for higher plasma β-HB values averaging 2 and 7 mM, achieved during β-HB infusion [20] and experimental starvation [22], respectively.
Figure 4
Figure 4
11C-Acetoacetate uptake into the brain of rats on a control diet (normal), ketogenic diet, or fasted 48 h (means ± SD; n = 4/group), expressed as metabolic rate for acetoacetate. The uptake was measured by PET imaging and shows that brain uptake of ketones is stimulated to an approximately equivalent extent by 48 h fasting or 10 d on a very high fat ketogenic diet [154].
Figure 5
Figure 5
Brain PET images showing 11C-acetoacetate (11C-AcAc; left) and 18F-fluorodeoxyglucose (18F-FDG; right) uptake by the human brain. Note that the color scales are not the same. As shown in the experimental protocol below the images, the tracers are injected sequentially with computed tomography scans before each injection. By sequentially injecting the tracers during one experiment, this approach minimizes intra-individual variability and provides a direct comparison between the brain uptake of the two tracers. Expressed as the relative term - standardized uptake values - our preliminary, unpublished data show that the brain uptake of 11C-AcAc is somewhat lower in the healthy elderly (mean - 74 y old; n=5) than in healthy young adults (mean – 26 y old; n=5). In this study, all subjects were screened to eliminate those with cognitive deficit and symptomatic disease, and were on no medications. When summed across 18 brain regions, the aging-related difference in brain 11C-AcAc uptake was about 50% less than for 18F-FDG. These measurements have not yet been corrected for any possible effect of aging-related brain atrophy, nor have they been expressed as metabolic rates. The aim of reporting these preliminary data here is to demonstrate the feasibility of these dual tracer PET measurements and not to make a claim at this time as to differences between the two age groups.
Figure 6
Figure 6
Schematic overview of the concept that brain hypometabolism (Phase 1) contributes to the neuropathology underlying Alzheimer’s disease (AD; Phase 2), leading to the clinical symptoms of AD (Phase 3). The neuropathology and declining functionality of the brain can further contribute to brain hypometabolism, thereby completing a vicious cycle. In Phase 1, the hypometabolism is reportedly associated with various components of glucose utilization including one or a combination of impaired glucose transport (GLUT), impaired pyruvate dehydrogenase complex (PDHC) activity, and/or impaired α-ketoglutarate dehydrogenase complex activity (KDHC). Although the focus is on hypometabolism of glucose, it is not yet clear whether brain hypometabolism in AD affects glucose specifically or whether metabolism of other brain fuels such as ketones is also impaired. Brain hypometabolism is represented here as the first phase in the etiology of AD because it is the earliest known change in the brain associated with a risk factor predisposing to AD (presence of an apo E4 allele). In Phase 2, the microvascular changes involve altered blood-brain barrier function. In the normal brain, tau hyperphosphorylation can be stimulated by acute low glucose availability (see Section 4.1), so we propose that it is a consequence of brain hypometabolism. We propose that some brain areas are more susceptible to chronic brain hypometabolism, which can lead to regionalized brain starvation in areas that cannot adequately compensate by endogeneous gluconeogenesis. Hence, regionalized starvation and gluconeogenesis are shown here as consequences of brain hypometabolism. The cause brain hypometabolism is not yet known so it is possible that components of Phase 2 (particularly microvasculature changes and/or tau hyperphosphorylation can contribute to Phase 1, thereby further increasing the chances of developing Phase 3). Phase 3 represents the clinically observable phase which starts when the brain can no longer cope with the combination of chronic hypometabolism and neuropathological changes (Phases 1 and 2). Two related strategies are predicted to be potentially able to break the cycle (or delay it) and both involve a sustained improvement in brain fuel supply (dotted circle): (i) sustained improvement in brain glucose metabolism, which is probably dependent on sustained improvement in systemic glucose metabolism, and/or (ii) glucose replacement by ketones which are the brain’s preferred alternative physiological fuel to glucose. Such strategies are only likely to be effective if they can prevent Phase 1 becoming Phase 2, i.e. interrupting the deleterious impact of brain hypometabolism on the development of neuropathology, thereby preventing clinical symptoms of AD.
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