METABOLIC ENERGY BALANCES IN KETOTIC
RAT BRAIN
by
YIFAN ZHANG
Submitted in partial fulfillment of the requirements
For the degree of Doctor of Philosophy
Dissertation Advisor: Joseph C LaManna, PhD
Department of Biomedical Engineering
CASE WESTERN RESERVE UNIVERSITY
August, 2013
CASE WESTERN RESERVE UNIVERSITY
SCHOOL OF GRADUATE STUDIES
We hereby approve the dissertation of
Yifan Zhang
candidate for the Doctor of Philosophy degree*.
Xin Yu , Sc. D
Joseph C. LaManna, Ph.D
Zhenghong Lee, Ph.D
Michelle. A. Puchowicz, Ph.D
Gerald . M. Saidel, Ph.D
Kingman. P. Strohl, M.D
(date) May 14th, 2013
* We also certify that written approval has been obtained for any proprietary material contained therein.
ii
Table of Contents
METABOLIC ENERGY BALANCES IN KETOTIC RAT BRAIN ...... I DEDICATION...... VII ACKNOWLEDGMENT ...... VIII ABSTRACT ...... IX LIST OF FIGURES ...... XI LIST OF TABLES ...... XIII ACRONYMS ...... XIV CHAPTER 1 OVERVIEW OF THE DISSERTATION ...... 1 CHAPTER 2 BACKGROUND ...... 5
2.1 BIOCHEMISTRY OF KETONE BODIES ...... 5
2.1.1 Ketone and ketone bodies ...... 5
2.1.2 Pathways and regulations of ketone bodies’ metabolism ...... 6
2.2 KETOSIS AND METHODS OF INDUCTION ...... 7
2.3 NEUROPROTECTION FROM KETOSIS ...... 9
2.3.1 Ketosis as a pre-conditioning for protection ...... 9
2.3.2 Ketosis as a therapy ...... 9
2.4 METABOLISM OF GLUCOSE AND KETONE BODIES...... 12
2.5 OVERVIEW OF METHODS TO ESTIMATE THE CMR ...... 14
2.5.1 KETY-SCHMIDT METHOD (MEASUREMENT OF UPTAKE) ...... 15
2.5.2 Compartmental Modeling method (Measurement of reaction) ...... 15
2.5.3 Inherent difficulties to determine the CMR ...... 17
2.6 UNPUBLISHED PILOT STUDIES ON CMRGLC AND OXIDATIVE METABOLISM ...... 19
2.6.1 Common mistakes and precautions in determining the CMRglc by FDG-PET ...... 19
2.6.2 Animal Anesthesia System Development ...... 20
iii
2.6.3 Unreported CMRglc data ...... 22
2.6.4 Unreported CMRglc meta-analysis data ...... 24
2.7 FIGURES AND TABLES ...... 25 CHAPTER 3 KETOSIS PROPORTIONATELY SPARES GLUCOSE UTILIZATION IN BRAIN ...... 33
3.1 ABSTRACT ...... 34
3.2 INTRODUCTION ...... 35
3.3 MATERIALS AND METHODS ...... 38
3.3.1 Animal Model and Diets ...... 38
3.3.2 Anesthesia and Surgery ...... 39
3.3.3 Physiological Parameters ...... 40
3.3.4 Image Acquisition and Blood Sampling ...... 40
3.3.5 Image Processing: Region and Volumes of Interest ...... 42
3.3.6 Parameter Estimation and Calculation of CMRglc ...... 43
3.4 RESULTS ...... 45
3.4.1 Physiological parameters ...... 45
3.4.2 Cerebral Glucose Metabolic Rates ...... 45
3.4.3 Meta-analysis of CMRglc in Ketotic Subjects ...... 46
3.5 DISCUSSION ...... 48
3.6 ACKNOWLEDGEMENTS ...... 52
3.7 FIGURES AND TABLES ...... 53 CHAPTER 4 CONTRIBUTIONS OF BRAIN GLUCOSE AND KETONE BODIES TO OXIDATIVE METABOLISM ...... 63
4.1 ABSTRACT ...... 64
4.2 INTRODUCTION ...... 65
iv
4.3 METHODS ...... 67
4.3.1 Animal Preparation and Diets ...... 67
4.3.2 Experimental Design, Tracer Preparation, and Infusions ...... 68
4.3.3 Estimation of the Contribution of Acetoacetate and Glucose to Oxidative Metabolism ...... 69
4.4 RESULTS AND DISCUSSIONS...... 70
4.5 Acknowledgments ...... 72
4.6 Figures and tables...... 73 CHAPTER 5 KETONE BODIES SPARES GLUCOSE OXIDATIVE METABOLISM IN DIET-INDUCED KETOSIS IN RAT BRAIN ...... 76
5.1 ABSTRACT ...... 76
5.2 INTRODUCTION ...... 78
5.3 METHODS ...... 82
5.3.1 Animal model and diets ...... 82
5.3.2 Tracer Infusion and tissue collection ...... 82
5.3.3 Analytical method and theory of flux analysis ...... 85
5.4 RESULTS ...... 87
5.4.1 Physiological parameters ...... 87
5.4.2 Plasma and BHB tracer enrichments ...... 88
5.4.3 First turn of CAC metabolites fluxes ...... 89
5.4.4 Pyruvate recycling and 2nd turns of CAC ...... 90
5.4.5 Metabolite concentrations ...... 92
5.5 DISCUSSION ...... 94
5.5.1 Changes of oxidative metabolism in ketosis ...... 94
v
5.5.2 Shunts to neurotransmitters ...... 96
5.5.3 Alterations of pyruvate recycling ...... 97
5.6 ACKNOWLEDGMENT ...... 101
5.7 FIGURES AND TABLES ...... 102 CHAPTER 6 CONCLUSIONS & FUTURE WORKS...... 114
6.1 INTRODUCTION ...... 114
6.2 ESTIMATION OF THE LUMPED CONSTANT IN KETOTIC RAT BRAINS ...... 120
6.2.1 Objective and specific aims ...... 120
6.2.3 Technical and scientific Challenges ...... 122
6.3 OPTIMIZING THE STABLE ISOTOPE STUDIES ON OXIDATIVE METABOLISM IN KETOSIS ...... 124
6.4 CONCLUSIONS ...... 126
6.5 FIGURES AND TABLES ...... 128 APPENDIX ...... 130
APPENDIX I SAMPLE FILES FOR PET PLASMA INPUT FUNCTIONS (.CRV) AND TIME ACTIVITY CURVES(.TAC) ...... 130
APPENDIX II MATLAB CODE FOR GJEDDE-PATLAK ANALYSIS ...... 133 APPENDIX III FDG-PET MODEL AND LC MEASUREMENT ...... 137
1. MODEL DEVELOPMENT ...... 137
18 2 DERIVATION OF THE COMPETITIVE REACTIONS OF GLUCOSE AND FDG ...... 139
18 3. FINDING THE PHOSPHORYLATION RATE OF GLUCOSE AND FDG ...... 141
18 4. LINKING THE PHOSPHORYLATION RATE OF GLUCOSE AND FDG ...... 144
5. ESTIMATION OF 18FDG KINETIC CONSTANTS ...... 145
6. ESTIMATION OF THE LUMPED CONSTANT (LC) ...... 146 BIBLIOGRAPHY ...... 149
vi
Dedication
This work is dedicated to my wife and parents.
vii
Acknowledgment
I would like to first thank my research advisor, Dr. Joseph LaManna, for his persistent professional education and support in my learning process. His deep insight in physiology is truly outstanding and of great value to my research. I would also like to thank Dr. Michelle Puchowicz and Dr. Zhenghong Lee, who had provided hand-to-hand guidance to my scientific investigation in analytical biochemistry, ketone body metabolism and radiology. Working with them was a great pleasure. I thank Dr. Xin Yu and Dr. Gerald Saidel, my academic advisor and committee member in Biomedical
Engineering, who had been vigorously setting high academic standards for my coursework education, teaching experiences and professional development. Their challenges made me today. Lastly, I thank Dr. Kingman Strohl for his insightful suggestions and criticisms to my work and presentations. These are certainly to benefit me greatly as a young researcher.
All my work is not possible without my colleagues and lab friends in the past five years.
I would also thank my colleagues, Youzhi Kuang, Dr. Kui Xu, Edwin Vazquez, Sharon
Zhang, and Lan Wang. Their technical supports are highly appreciated. I thank my lab student friends, Kevin Train, David Corn, and Donald Harris for working with me.
The research projects are supported by the National Institute of Health, R01 HL092933-
01, R21 NS062048-01 and Mouse Metabolic Phenotyping Center, MMPC U24 DK76169.
viii
Metabolic Energy Balances in Ketotic Rat Brain
Abstract
by
YIFAN ZHANG
The brain normally uses glucose as its primary fuel, but is able to use ketone bodies as
an alternative fuel during fasting, starvation, or feeding of high-fat, low-carb diets.
Ketosis, as a physiological state, has been shown to be neuroprotective since the 1920s.
The biochemical links between ketosis and neuroprotection has been of interest to
clinicians and scientists. To investigate the metabolic mechanism, we hypothesized that 1)
the total energy demand (glucose + ketone bodies) is constant during ketosis 2) in chronic
ketosis, ketone bodies spare glucose from oxidative metabolism and shunts towards
neurotransmitters. Using Positron Emission Tomography (PET) and 2-tissue
compartment modeling, we show that the cerebral metabolic rate of glucose (CMRglc) decreases linearly (9% per 1mM blood ketone body increase) in rats with diet-induced
ix
ketosis. In another study, using Liquid Chromatography and Gas-Chromatography Mass
Spectrometry (LC-MS, GC-MS), we applied carbon-13 (13C) isotopic flux analysis in
ketotic rat brains with either [U13C]-glucose or [U13C]-acetoacetate intravenous infusions.
The data show that ketosis reduced glucose carbon flux into the citric acid cycle and γ- aminobutyric acid (GABA), whereas ketone body carbon flux increased in these pathways. In conclusion, ketone bodies partition and spare glucose oxidative metabolism in ketotic rat brain. This may lead to further understanding to neuroprotection from changes of metabolic energy balances.
x
List of Figures
Figure 2.1 Illustration of BHB and AcAc inter-conversion and oxidation to acetyl-coA. 25
Figure 2.2 Ketone bodies utilization in the brain and synthesis in the liver...... 26
Figure 2.3 Schematics for 18FDG tracer study models ...... 27
Figure 2.4 Sample Rat PET images, as displayed in CARIMAS2 software...... 28
Figure 2.5 Experiment Set up for anesthesia system...... 29
Figure 3.1 Decreased cerebral metabolic rate for glucose (CMRglc) with increasing plasma ketone body concentrations in rats fed with ketogenic (KG) diet compared to standard diet (STD) ...... 53
Figure 3.2 . Meta-Analysis of CMRglc reduction in ketotic subjects (human or rats)...... 55
Figure 3.3 . Images of Volumes of the Interest (VOI)...... 57
Figure 4.1 Plasma molar enrichment (MPE %) at t = 50 min...... 73
Figure 4.2 Acetyl-CoA MPE in cortical brain...... 74
Figure 4.3 Contributions of glucose and AcAc to oxidative metabolism...... 75
Figure 5.1 Simplified schematics of metabolite labeling patterns with [U13C]-Glucose or [U13C]-Acetoacetate (AcAc) infusion...... 106
Figure 5.2 Brain metabolite M2 enrichment from [U13C]-glucose studies (Panel A) and [U13C]-Acetoacetate studies (Panel B)...... 108
Figure 5.3 Brain metabolite M1 enrichment from [U13C]-glucose studies (Panel A) and [U13C]-acetoacetate studies (Panel B)...... 110
Figure 5.4 Brain metabolite concentrations in rats infused with [U13C]-glucose (Panel A and B) or [U13C]- acetoacetate (Panel C and D)...... 111
Figure 5.5 Theoretical schemes for M+1 metabolites generation...... 112
xi
Figure 5.6 Chromatogram of the Citric Acid Cycle intermediates and neurotransmitters ...... 113
Figure 6.1 Proposed Neuron-Glial Compartmentation models for ketone metabolism studies. Figure reference from McKenna review 2007, JNR (112)...... 129
xii
List of Tables
Table 2.1 Unpublished data of meta-analysis of the studies on CMRglc during ketosis. 31
Table 2.2 Unpublished data on KG and STD rat CMRglc, with hyperoxia (100% O2 anesthesia) ...... 32
Table 3.1 Physiological Parameters ...... 58
Table 3.2 CMRglc in the volumes of interest (VOI) ...... 59
Table 3.3 Macronutrients of the standard (STD) diet and ketogenic (KG) diet ...... 60
Table 3.4 Micronutrients of the STD diet and KG diet ...... 62
Table 5.1 Physiological parameters of the rats...... 102
Table 5.2 Plasma and brain enrichments of glucose M+6 and ketone bodies M+4. .... 104
Table 6.1 Literature Lumped Constant (LC) numbers for 2-Deoxyglucose(DG) and 18FDG...... 128
xiii
Acronyms
α-KG α-Ketoglutarate, same as OHG, or oxoglutarate
AAT Aspartate Aminotransferase
AcAc Acetoacetate
ASP Aspartate
ATP Adenosine triphosphate
BAM Blood Acquisition Module
BHB β-Hydroxybutyrate
BBB Blood-Brain Barrier
13C Carbon-13
CAC Citric Acid Cycle (Same as TCA, or tricarboxyl acid cycle)
CBF Cerebral Blood Flow
CIT Citrate
CMR Cerebral Metabolic Rate
CMRglc Cerebral Metabolic Rate of Glucose
xiv
CMRket Cerebral Metabolic Rate of Ketone Bodies
CMRo2 Cerebral Metabolic Rate of Oxygen
CNS Central Nervous System
CPT Carnitine palmitoyltransferase
CT Computed Tomography
DG 2-14C-Deoxy-Glucose
EEG Electrocardiogram
ETC Electron Transport Chain
18F Fluorine-18
FDG 18[F]-2-Fluoro-Deoxy-Glucose
FDG-6-P 18[F]-2-Fluoro-Deoxy-Glucose-6-P
FUM Fumarate
FW Formula Weight (or molecular weight per mole)
G-6-P Glucose-6-phosphate
GABA γ-aminobutyric acid
xv
GAD Glutamate acid decarboxylase
GC-MS Gas Chromatography Mass Spectrometry
GLC Glucose
GLN Glutamine
GLU Glutamate
2H Deuterium
HPLC High-Performance Liquid Chromatography
HIF Hypoxia-Inducible Factors
HMG-CoA Hydroxymethylglutaryl-coA
IS Internal Standard
KB Ketone bodies
LAC Lactate
LC Lumped Constant
LC-MS Liquid Chromatography Mass Spectrometry
xvi
LDH Lactate dehydrogenase
MAL Malate
MCT Monocarboxylate Transporter
MPE Molar Percent Enrichment
MRI Magnetic Resonance Imaging
NAA 15N-Acetyl-Aspartate
NAD+ Nicotinamide adenine dinucleotide. (Reduced form: NADH)
NMR Nuclear Magnetic Resonance
OAA Oxaloacetate
PC Pyruvate carboxylase
PDH Pyruvate dehydrogenase
PET Positron Emission Tomography
PYR Pyruvate
ROI Region of Interest
ROS Reactive Oxygen Species
xvii
SD Standard Deviation
SEM Standard error of the mean
STD Standard diet
SUC Succinate
VOI Region of Interest
xviii
CHAPTER 1 OVERVIEW OF THE DISSERTATION
Ketone bodies (KB) are alternative energy fuel used in the brain during the state of ketosis (1) (2) (3) (4) (5). The state of ketosis is known to be neuro-protective against various pathological conditions in the brain, including cancer (6), Alzheimer’s diseases
(5, 7) , epilepsy (8-12), traumatic brain injury (13), and stroke (14). Hypothetical explanations to the mechanisms underlying the protections have been of great interest for scientists and clinicians. There are four major schools in current literature that explained the mechanisms. i) Ketone body utilization spares glucose utilization and oxidation (3,
15-17), which is believed to be vicious following neurological insults. ii) Ketosis changes the citric acid cycle (CAC) intermediates and neurotransmitters fluxes from KB and glucose, leading to a different state of neurotransmitter synthesis and utilization (18-20). iii) KB utilization changes the regulations of key molecular factors and proteins, allowing the brain to adapt to the neurological challenges (14, 21, 22). iv). KB utilization in the brain and in the mitochondria reduces the Reactive Oxygen Species (ROS) in the
Electron Transport Chain (ETC) (23, 24). This dissertation is summarizes my works on aspects (i) and (ii).
The basic scientific and engineering grounds were present in chapter 2. First, fundamentals of KB and glucose metabolism in the brain are illustrated. Secondly, the neuroprotection from ketone bodies, as are reported in literature, are discussed. Thirdly, the scientific and engineering methods to estimate glucose and KB metabolism are
1
reviewed. Lastly, my previously unpublished experimental setup for investigating the
glucose and ketone body metabolism are presented. Some of them are used in the
publications in the later chapters, but were not presented in the respective chapters.
In chapter 3, we present the work on ketosis’ effect to suppress the Cerebral Metabolic
Rate of glucose (CMRglc). We hypothesize that the total CMR of the brain from KB and
glucose is constant in diet-induced ketosis. As a result, we expected to see that the
CMRglc decrease during ketosis, in which KB utilization is known to increase (2, 4, 25).
We used Positron Emission Tomography (PET) and 2-Tissue Compartmental modeling
techniques (26, 27) , and tested this hypothesis on rats fed with 3-weeks of ketogenic
diet. This article has been submitted to the Journal of Cerebral Blood Flow and
Metabolism (JCBFM) and was accepted for publication on May 7th, 2013.
In chapter 4, we present the work on ketosis’ effect to switch the glucose oxidation to acetyl-CoA to KB. We hypothesized that the total glucose and ketone bodies’ fluxes towards the acetyl-coA is constant (downstream from CMRglc, where the first step of
glycolysis, phosphorylation, was studied and presented in chapter 3). We divided the
animal into 2 diet groups, standard (STD) and ketogenic (KG), and then further divided
into two infusion groups We infused either [U13C]glucose or [U13C]acetoacetate
intravenously to those rats(total 4 groups), and analyzed the plasma and brain
homogenate with Gas Chromatography Mass Spectrometry(GC-MS) and Liquid
Chromatography Mass Spectrometry(LC-MS), respectively. The results are1) from the
[U13C] glucose groups: isotopic flux from glucose tracer contributes less to the brain
2
acetyl coA generation during ketosis 2) from the [U13C]-acetoacetate groups: isotopic flux from KB tracer contributes more to the brain acetyl-coA generation during ketosis.
These data suggest that the oxidation of the fuels also switches downstream of glycolysis, in addition to glucose phosphorylation. This article has been published Oxygen Transport to Tissue 2013 (28).
In chapter 5, we present the investigation on how ketosis alters glucose and ketone balances in contributions to CAC intermediates and neurotransmitters (aspect ii of the hypothetical mechanism on neuroprotection). The experimental protocol is very similar with that presented in chapter 3, but with a different set of analytical methods. Only GC-
MS was performed. The data shows complex labeling patterns of the CAC intermediates, as well as neurotransmitters. We reported i) Brains CAC intermediates showed increased isotopic carbon fluxes from ketone bodies in ketosis, while carbon fluxes from glucose decreased in ketosis ii) GABA, is not normally synthesized from ketone bodies in normal conditions, shows significant flux from ketone bodies in ketosis. iii) Ketone bodies contributions to pyruvate recycling increased while glucose contributions to pyruvate recycling decreased in ketosis. A potential mechanism to explain the neuroprotection from ketosis’ contribution to “reservation” of carbon sources through the CAC (instead of being completely cleaved down to CO2) and neurotransmitter recycling is discussed.
This paper is to be submitted to the Journal of Neurochemistry, due by May 31st, 2013.
Finally, in the last chapter, chapter 6, a summary of the previous findings in chapter 3-
5 is presented. To the best of my knowledge, I presented two more additional projects for
3
future research. 1) Proposal to estimate the lumped constant (LC) in rats in ketosis. LC is
an important parameter used in FDG-PET experiments, to determine the CMRglc (26, 29).
Our paper in press (chapter 3) findings and conclusions are based on the assumption that
the LC was a constant in ketosis. The validation is a crucial point in future. 2).Proposal to
further investigate the brain ketone-glucose contributions to CAC intermediates and neurotransmitters in dynamic cerebral compartments. Our article to be submitted (chapter
5) presented the isotopic flux, in unit of percent enrichment (MPE) in the brain Zhang et al 2013 (28) during ketosis. However, this assumes steady state of isotopic balances in the brain, and does not reflect the dynamic substrate utilization rate (in μmol/100g/min tissue). More complex mathematical models, which takes into neuronal-glial interactions
(18, 30, 31) is proposed to address the problem.
4
Chapter 2 Background
2.1 Biochemistry of ketone bodies
2.1.1 Ketone and ketone bodies
Ketones are organic chemicals containing double carbon “C=” groups. Ketone bodies
(KB) are different from ketones. They are water-soluble molecules with ketones, generated as a by-product of β-oxidation of fatty acids. Physiological ketone bodies include acetoacetate (AcAc), β-hydroxybutyrate (BHB, also known as 3-BHB) and acetone. The first two ketone bodies are frequently by the body during the state known as ketosis, as this dissertation presents in detail. The chemical structures for the KB are shown in figure 2.1.
Both BHB (C4H8O3, FW=104) and AcAc (C4H6O3, FW=102) contain 4 backbone
carbons. AcAc is the oxidized form; BHB is the reduced form. They are inter-convertible
through BHB-dehydrogenase (E.C. 1.1.1.30). The ratios of BHB/AcAc are known as a
redox index (32, 33) in describing physiology.
+ + AcAc+ NADH+ H BHB+ NAD
↔
5
2.1.2 Pathways and regulations of ketone bodies’ metabolism
Ketone bodies (KB) are synthesized in the liver and transported to various tissues for
use (4, 34-37). First, long-chain fatty acid breaks down, transferring the acyl-coA to the
mitochondria through carnitine palmitoyl transferase (CPT). This step is positively
regulated by the CPT 1 and 2, and inhibited by malonyl-coA, the key enzyme for fatty
acid synthesis. Then, in the mitochondria, the acyl-coA is oxidized to acetyl-coA. The
key chemical involved is the hydroxymethylglutaryl-coA (HMG-CoA). Two of the
newly formed acetyl-coA then converts to one AcetoAcetate-coA (AcAc-coA) by AcAc-
coA thiolase. AcAc-coA can be used to generate HMG-CoA from HMG-coA synthase.
Finally, the breakdown of the HMG-CoA generates one AcAc plus a free acetyl-coA. In the BHB and AcAc synthesis, AcAc-coA synthesis is a necessary step.
Ketone bodies utilizations are also starting with AcAc-coA with AcAc-coA thiolase. It is noteworthy that usually the physiological redox in the blood is greater than 1 (i.e, BHB concentration is higher than that of AcAc) (33). The majority of the ketone bodies –BHB, cannot contribute to oxidative metabolism in the CAC and the generation of ATP without first been converted to AcAc and AcAc-coA. Ketone body utilization occurs in the brain and other tissues (32, 34)(Heart, kidney, muscles). Ketone bodies are present in very low concentrations (<0.1mM) in the human and rodent brain normally (3, 38, 39). Diffusion of ketone bodies through the blood brain barrier (BBB) is very low (40-42). The cerebral utilization of ketone bodies is through monocarboxyl transporters (MCT) (40) (41). The synthesis and utilization of ketone bodies are shown in figure 2.2.
6
2.2 Ketosis and methods of induction
Ketosis is defined as a state in which the total blood ketone body (BHB+AcAc)
concentrations (alternatively, only BHB) exceed 0.5 mM (4, 25). There are three ways to
induce one subject (human or mammals) with ketosis: fasting (including starvation),
feeding of high-fat-low-carb diet, and acute infusion of ketone bodies (32, 43).
i) Fasting or starvation. In the history of scientific investigation on ketones, this model is
first tested. Long term (6-7 weeks) of fasting of obese patients were performed and
reported by Owen et al in 1960s. The authors demonstrated, via Kety-Schmidt method
(44) (discussed in section 2.4.1), that the cerebral arterial KB concentrations are
progressively elevated in chronic fasting. Fasting –generated ketosis is known to elevate
the blood KB concentrations while decrease blood glucose concentrations, causing a state
known as hypoglycemia (2, 15, 17, 45-47). It is apparent that during fasting, insulin level
in the blood will be low, and this hormone negatively regulates the lipolysis. Ketone
bodies are thus generated as a by-product of β-oxidation (33, 48, 49).
The cerebral blood flow (CBF) had been reported not to change in healthy volunteers undergoing prolonged fasting and high levels of ketosis. The pH in the blood decreased from 7.40 to 7.37 in 2-day fasted humans (15), a state of metabolic acidosis from hyperketonemia in the brain may or may not present (15, 39). ii) Diet-induced ketosis. Unlike fasting, where KB are generated from depletion of blood glucose (thus pulling the demand of fatty acid oxidation, (42)), this method works by
7
providing “excessive” fatty acid supply while drastically reduces glucose supply (also
indirectly pulling the demand for fatty acid oxidation). For humans, the ketogenic diets
(KG) typically contain 10% or less carbohydrate and more than 70% of fat (12, 48) For
experimental rodents, the KG diets contain less than 1% of carbohydrates and about 90%
of fat, due to less responsiveness (mechanism not clearly known; (16, 18, 50-53). Diet-
induced ketosis are not known to cause changes to blood glucose levels or causes adverse
effect to blood pH (16, 18, 51-53). However, the diet-induced ketosis is known to
increase the free fatty acid in the blood. Researchers are investigating into the improving
the diet compositions by altering the compositions (54).
iii) Ketosis from infusion of KB. This method is frequently used in NMR studies with
ketosis, where the measurement sensitivity of the tracer (discussed in section 2.4.3) is
low. Infusion of high load of exogenous ketones, typically more than 1mmol/kg/hr for 1-
3 hours (15, 55-58) can cause human hyperketonemia. It is also known that infusion of
KB can reset the coupling of CBF and CMRglc and CMRket, thus invalidate the
assumptions of uptake measurement (discussed in section 2.4.1) (56, 59).
8
2.3 Neuroprotection from ketosis
2.3.1 Ketosis as a pre-conditioning for protection
Ketone bodies as a pre-conditioning to protect against neuro-trauma had been reported mainly in basic science investigations (60). The reasons are that artificially induced neurological damages are easier to induce than finding subject with latency of neurological damages for treatment. Indeed, many rodent brain damage models, such as focal and global ischemia by arterial occlusion (61), served well in the investigative purposes. With these in vivo models, the neuroprotection by ketosis were commonly reported in rats: ketosis preconditioning were shown to reduce the infarct volumes (14)
(61), increase angiogenesis (62), increase the threshold for seizure occurrence (63)Bough
1999), decrease the edema and improve the ATP Suzuki (33), decrease the CO2 production from BHB (64), decrease of the contusion volumes (65), and alleviate glutamate cytotoxicities (24, 66).
2.3.2 Ketosis as a therapy
Ketosis as a therapy had been mainly tested in humans with epilepsy and less in other disease models. In human studies, the most relevant frequently used model of induction is through the ketogenic diet (9, 67, 68).
9
Before the 20th century, fast-induce ketosis had been reported to treat refractory
epilepsy. The diet-induced ketosis was first systematically proposed by Wilder et al in
1920th in Mayo Clinic (1). Large-scale human trials of ketogenic diet as a therapy for epilepsy (9) showed that at least 2/3 of the subjects with epilepsy had reduced occurrence of seizure activities. It has been suggested by Gilbert et al, that (68) as high as 4mM
blood ketone concentration was desired to reduce epilepsy. The mechanisms underlying
the anti-convulsant effects had been explored from different aspects, including decreased
neuronal excitability (69), increased ketone shunts to glutamate and GABA (19). More are discussed in chapter 5.2.
Diet-induced ketosis had also been reported to be neuroprotective against Alzheimer’s disease (70), traumatic brain injuries (64) , reversible focal ischemia (61), and glutamate
toxicity (24). For details, see review papers (5, 60).
It is important to note that the therapeutic effect of the ketosis has been shown to be age
– dependent. In developing rats, ketone bodies had more presence in the blood than in
adults (32, 41). The therapeutic effects of ketone bodies on refractory seizures had been
reported to be highly effective in children (71) .
Finally, the therapeutic effects from ketosis, in some cases, are reversible. Seizures can
be reported 1-2 weeks following the ketogenic diet (8) , but consumptions of
carbohydrates will immediately reverse the effect. This case may have been due to
switches (back and forth) of carbohydrates (primarily glucose) and ketone bodies as a
10
source of neurotransmitter generation, as discussed in chapter 5 ketogenic animals infused with [U13C]-glucose. In other studies, children with De Vivo’s disease who lacks
GLUT-1 transporters, can be treated with ketogenic diet, and no reversal of the effect be observed after 2-3 year (72). Future investigations into the reversibility of the therapeutic effects from ketosis are needed.
11
2.4 Metabolism of glucose and ketone bodies.
Glucose, a simple hexose, is widely thought to be the dominant energy substrate in the
brain in normal physiological conditions (4, 35) . To generate energy Adenosine
Triphosphate (ATP) in the brain, glucose first need to be mobilized in the plasma and the
liver, transported to the brain through the Blood Brain Barrier (BBB) by Glut-1
transporters (40, 41, 73).Then the glucose enters the cytosol to undergo the process of
glycolysis. The first step would be glucose becomes phosphorylated to glucose-6-
phosphate (G-6P), in the brain, mostly catalyzed by hexokinase 1 and 2 that follows
Michaelis-Menten kinetics (26, 74). Unlike what occurs in the liver, glucokinase is rarely
present to catalyze the glycolysis in the brain (49). Then the G-6P undergoes a series of
reactions and transformations to end up with two pyruvates, each with three carbons.
Pyruvate then lose one more carbon by the catalysis from pyruvate dehydrogenase and
enters the Citric Acid Cycle (CAC) as acetyl-coA (enters the mitochondria). ATP is then
generated from the citric acid cycle product, NADH (60).
Ketones bodies are produced as a by-product from fatty-acid oxidation via HMG-
CoA(60). During ketosis, the MCT transporters amount is elevated (40-42) . In the tissues, ketone bodies readily enter the mitochondria to merge into the CAC by converting to
AcAc, then AcAc-CoA, and then cleaving the four-carbon AcAc in the AcAc-CoA to two Acetyl groups and thus end up with two Acetyl-coA to enter the citric acid cycle.
ATP is then generated from the citric acid cycling similar with the fate of glycolysis.
12
Both glucose and ketone metabolic pathways merge at the CAC through the acetyl-coA, with each 1 mole of substrate contributing to 2 moles of acetyl-coA. On the ATP product side, complete glycolysis from 1 mole of glucose generates 34-36 moles ATP while each
1 mole of ketone oxidation generates 24-26 moles of ATP (2, 42). It is an interesting topic for physiologists how substrate carbon numbers or ATP demand-supply relationship drives the interactions between glucose and ketone metabolism.
In anesthetized rats, the global CMRglc is reported to be between 40-60 μmol/100g/min
(17, 26, 46, 47, 75, 76). On the other hand, the rate of ketone utilization in the brain,
CMRket, is defined as the rate of AcAc oxidation to AcAc-coA, in micromole per 100g wet tissue per minute (μmol/100g/min). For rats, CMRket is about 1-20 times less than
CMRglc (3, 15, 55, 57, 77, 78). The variations are probably from the methods of estimations. See section 2.5 and 2.6.
13
2.5 Overview of methods to estimate the CMR
The word “CMR” (cerebral metabolic rate) is a confusing term. In many cases, it can be represented by either “Uptake” or “Reaction” (or “Metabolism”). Metabolic substrates, such as glucose, ketones, oxygen, underwent three physical processes: diffusion (through concentration gradient), convection (through blood flow), and reactions (through chemical binding, such as hemoglobin for oxygen, Monocarboxylic transporters for ketones and lactate (72) GLUT-1 and GLUT-4 for glucose). Take glucose for example, in rat brain, the glucose concentration is about 5-10 times less than that of plasma and the diffusion process was inadequate to meet the demand of glucose. In this case, the dominant, salient features to measure would be either the convection – paraphrased as
“uptake”; or reaction – paraphrased as “metabolism” (the process of glucose phosphorylation to glucose-6-phosphate). To measure either case, one would need to impose a tracer or measure an endogenous tracer from the blood or plasma, which will undergo all three physical processes in the brain; when both the tracer and the tracee (in this case, glucose) reach steady state in the plasma or blood, assuming that diffusion was significantly lower than the “uptake” or “metabolism”, the convection rate would approximately equal to the reaction rate (Mathematically the two processes have opposite signs, if reaction causes the tracee to decrease (79)).
14
2.5.1 Kety-Schmidt Method (Measurement of uptake)
Kety and Schmidt pioneered in the clinical studies of CMRglc measurement methods by introducing convection-based measurement principles (44) . At steady state after an inert tracer infusion, the cerebral arterial and venous concentrations, as well as the total amount of tracer disappearance can be measured repeatedly until no A-V difference can be observed (See equation below; Vu is the total blood flow tracer taken by the brain from infusion to the end of study, S is the partition coefficient of blood flow tracer, CA and CV stand for cerebral glucose concentrations, respectively, u is the end time of the measurement). Assuming the tracer/tracee partition coefficient stays the same in the brain as ex vitro, the CBF can be estimated. Therefore the CMRglc= CBF× (CA-CV), divided by brain sample weight. This measurement scheme served as standard for years, and it worked for CMRglc, CMRket, and CMRo2. However, this method had obvious drawbacks: i) the brain arterial and venous sampling is highly invasive ii) measurement would be global CMRglc, does not allow regional CMRglc measurement.
2.5.2 Compartmental Modeling method (Measurement of reaction)
More than two decades later, Sokoloff et al published seminal works on estimating the
14 CMRglc by studying the phosphorylation rate, using a trapping tracer 2- [C]-
15
Deoxyglucose (DG) and autoradiography (26). The authors postulated transport and
phosphorylation rate constants (80), and assumed that the rate constants for DG and
glucose held fixed ratios. By further assuming Michaelis-Menten kinetic parameters Vm
and Km held constant ratios between the tracer (DG) and tracee (glucose), a lumped
constant (LC) was assumed. The CMRglc thus can be estimated if tissue and blood (or
plasma) activities are known during the study period. CMRglc would be inversely
proportional to LC if transport and phosphorylation rate constants are known. This
method was verified by in vivo human studies with FDG-PET published by Phelps et al
(27). The 2-DG and FDG-PET methods essentially measure the glucose phosphorylation rates. Given the high specific activities of the radio-tracers, very small of tracer volume was required, and no cerebral A-V samplings necessary. Furthermore, Gjedde and Patlak had respectively worked out graphic methods for DG and FDG compartmental models, making parameter estimations for FDG-PET more convenient (81-83). The advantage with PET versus 2-DG method comes with low remaining radioactivity after each study and readily 3-D tomographic assessment of glucose utilization without tissue collection.
The disadvantage is that sophisticated mathematical models would be needed, and the justifications of the assumptions are more demanding (84). These methods served as foundations for future generalized models with PET imaging. The details of the model development can be found at appendix iii. The model schematics are shown at figure 2-3.
16
2.5.3 Inherent difficulties to determine the CMR
Each cerebral metabolite has its own characteristics in terms of diffusion, reaction and
blood flow dependency. It is therefore very important to realize the respective
implications to technical (engineering) methods that need to be tailored in addressing
specific questions. Here, we specifically discuss CMRglc, CMRket and CMRo2
estimations.
CMRglc can be measured by either uptake or reaction method. Due to the availability of
trapping tracer, the reaction method by FDG-PET, or by 2-DG-autoradiography, are
much more convenient than the highly invasive Kety-Schmidt uptake method. However, there are two important drawbacks for the reaction methods. 1) The estimation from 2- tissue compartmental models usually underestimate the real metabolism, because the k5 terms, which specifies the loss of glucose-6-p downstreams through glycolysis, was assumed to be close to zero comparing with phosphorylation rate constant, “k3” (84) . 2)
The lumped constant (LC) is an experimental variable that may well change with physiological conditions (see section 2.5 and section 6.2). These directly impact the final calculation of CMRglc.
CMRket is more difficult to measure than CMRglc because of the lack of a trapping
tracer. Significant estimation error arises when the labeled tracer administered to the
subject loses in CO2 (as a result of oxidation) downstream. In this field, literature values
obtained by uptake method (3, 15, 55, 57) and reaction method (77, 78, 85) had great
17
discrepancies, ranging from 0.5μmol/100g/min to about 20μmol/100g/min in normal and
ketotic conditions. One alternative explanation would be that the measurement of blood
flow (CBF) from Kety-Schmidt method actually altered the baseline CBF, thus the
uncoupling artificially elevated the CMRket; on the other hand, it may have been the
tracer loss to CO2 from the non-trapping tracer measured by PET or other reaction-based
methods, such that severe underestimation made the apparent CMRket too low. In addition, the interconversions of the BHB and AcAc complicate the process of measurement of reactions, such that inhibition of the enzyme may be required for one to obtain a “true” reaction rate of ketone utilization (86). Finally, the process of pseudo-
ketogenesis, though not confirmed to present in the brain, had been shown to confound
the estimation of ketone utilization if uptake method was used (34) (87).
CMRo2 is a key index in studying the brain metabolism. Essentially, all oxidative fuel
metabolism study in the brain relies on the assumption about the CMRo2. Alternatively,
the CMRo2 can be measured by fMRI (BOLD) technique in combination with inversion
techniques to measure the CBF (88). Another reported method is to use 17O labeled
tracers. The uptake method of CMRo2 shares the same principles for CMRket and CMRglc
Aside from the determination of the CBF, the real challenge still lies on the determination
of cerebral venous concentration of the oxygen(89). For reaction-based methods, 15O
labeled H2O had been reported (90) . Due to the technical demands for a dedicated on-
site cyclotron and especially for the short half-life of 15O (only 122 seconds), this kind of
studies are not often performed (91) .
18
2.6 Unpublished Pilot Studies on CMRglc and oxidative metabolism
2.6.1 Common mistakes and precautions in determining the CMRglc by FDG-PET
The following summary pertains to the troubleshooting experiences on rat FDG-PET experiments on KG animals (see chapter 3).
1) Levels of ketosis. It is critical that the rats needed to be fasted overnight before the initiation of ketosis by KG diet.
2) Anesthesia. Only isoflurane was allowed during FDG-PET experiments.
3) Blood gas parameters. The blood gas parameters, especially the pH, are very sensitive measurement to respiratory and metabolic acidosis. Respiratory acidosis can be from hypo or hyper ventilations. Metabolic acidosis may be due to changes of glycolysis, especially pyruvate-lactate balances (92). The purpose of the setup is to avoid the overshadowing effects of the respiratory acidosis.
5) Injection of the tracers (FDG). Bubbles must be avoided while injecting the radioactive tracers.
19
6) Landmarks for image analysis, definitions of ROIs. The highest uptakes of the FDG
tracer are from the eyes (see figure 2.). It is easily confused with the frontal cortices. The
highest radioactivities occurred at the eye-cup.
7) Parameter estimations. First, we need to make careful choice of the Lumped
Constant (LC). The 2-DG and 18FDG has different LC values. The LC values in these
two conditions are reported to bear some linearity (93) in “normal conditions”, though the
mechanism is unclear. The LC is reported to change with age, insulin infusion, and may
well shift if the CBF is uncoupled with metabolism. The current best literature LC values
for rats are 0.71 (for Sprague-Dawley rats), which may probably work in wistar and
* * * fisher rats with the same age (3 months). Second, for the K1 , K2 , and K3 estimation:
Nonlinear fitting method requires good initial guess to obtain a good estimate. It is
* * * crucial that K1 , K2 be in the range of 0.1-1, while K3 should be one magnitude lower.
* * * Alternatively, graphic method to estimate the combination of K1 , K2 and K3 can be
used. In both cases, the steady state CMRglc should be evaluated 45 minutes post the
bolus injection of the tracer, if consistent estimation is needed (26).
2.6.2 Animal Anesthesia System Development
The experimental set-up for the estimations of the glucose and ketone metabolisms
would need to follow strict physiological criteria, such that respiratory acidosis,
hypoglycemia should be absent, as discussed in previous sections in chapter 2. In
20
addition, it is important that we manage the anesthesia level and stress levels of the animals that the anesthetized CMRglc data are consistent across different animals. Finally, the studies with the ketone and glucose metabolism needs careful amount of oxygen delivery, such that the rats receive physiological relevant amount of oxygen for brain glucose and ketone body utilizations.
Figure 2.5 illustrate the final working version of the anesthesia systems.
In figure 2.5, legend part b. The nose cone that interfaces the rat (a) has a bite bar (line perpendicular to the cone), that secures the front tooth; on top of that, two dotted vertical parallel lines indicates that the anesthesia line for isoflurane delivery. On the sides of the delivery tube, we drilled holes in it. When the rat exhales, those holes allows waste isoflurane and CO2 to escape (pointed to the right, as indicated by the arrow), to section d, which has a flask filled with water (~1-1.5L).
The solvency of CO2 to water is 1.45g/L solvency in water. Normal rats have
1.5ml/min/100g co2 production (94) . In a PET imaging experiment, which typically lasts about 80 minutes at the most, a rat that weight 300g produces approximately 0.36 liters of CO2. Assuming ideal non compressible gas for CO2 at room temperature, using
Avogadro's constant such that 1mol of CO2 would contain 22.4L, a water flask (1L, with water) would be able to contain ~ 0.7 liters. Therefore, 1L of water in that flask is sufficient for the animal to trap all of the CO2, even if the charcoal filter did not catch any, or if the animal did not breathe out any co2 from the mouth.
21
Next, consider the oxygen delivery. The atmosphere contains ~20% oxygen. When
awake, a rat breathes in ~20% to maintain its functions of the body and the brain.
However, during anesthesia, it is important to have more than 20% oxygen (95). For this
reason, we engineered the gas mixture of oxygen and room air, such that the mixture
contains 20%-100% oxygen, and is fully adjustable. Our unpublished data (section 2.6.3)
showed rats with unphysiological oxygen (hyperoxia) in the scan by improper delivery of
the oxygen (100%). Hypoxia and hyperoxia are known to alter the cerebral glucose and
ketone metabolism (48, 96).
We reports that the appropriate oxygen levels vary, but should be 20-30% during the
experiments. We also tested on several animals on the optimum maneuverable levels of
anesthesia, and concluded that 60-80 per minute respiration will not wake up the animal
during the 2 hour PET scan while maintaining reasonable blood gas parameters. Finally,
to minimize motion artifact from light anesthesia, a metal bite bar was inserted into the
nose cone.
2.6.3 Unreported CMRglc data
Before we published the papers (chapter 3-5), we had pilot studies on rats with ketosis
(KG) and with standard diet (STD). All CMRglc data published after 2012 were
22
performed using the revised animal anesthesia system, as described in figure 2.5. This
system was crucial in generating physiological normal parameters.
We had failed to generate these parameters in the pilot studies (data showing in table
2.2) for two reasons: i) Anesthesia levels. Several animals were sacrificed due to
improper handling of the anesthesia. High levels of isoflurane suppressed the respiration,
causing respiratory acidosis by hypoventilation (97). ii) Oxygen levels. The research
facility did not provide with nitrogen balance, and there the animals were anesthetized by
pure oxygen (100%), thus undergoing hyperoxia (See table 2.2). Such approaches fail to
provide reasonable normal physiology. In fact, two previous studies in literature, one
from our lab, suggest this to be the case (16, 78) . Comparing the data with hyperoxia will
need normalization, since the physiology changed. In addition, higher levels of anesthesia
(breathe rate ~30 in the pilot studies vs. Chapter 3 studies breathe rate ~60) by isoflurane
are known to artificially elevate the CMRglc compared with pentobarbital (98) . Finally,
the hyperoxia causes measurement of plasma glucose level by enzymatic method
(glucose oxidase, by YSI 2700, Yellow Spring , OH) to error prone (99) .
In sum, pilot studies of rats with hyperoxia anesthesia had respiratory acidosis, tripled
PaO2, low respiration rate. These data were not published, but served good references for study purposes.
23
2.6.4 Unreported CMRglc meta-analysis data
As is shown in table 2.2, we performed a CMRglc meta-analysis (unpublished) with literature values by either uptake method or reaction methods. This table differs from the published one in chapter 3 for two criteria: 1) Literature values without inclusion of the blood ketone levels were discarded for the published version 2) Literature values of the cerebral A-V differences with no report for CBF, or significant changes of CBF, were not used. We deem that the reasonable levels of the ketosis and the unchanged CBF are keys to maintaining stable ketosis.
24
2.7 Figures and tables
Figure 2.1 Illustration of BHB and AcAc inter-conversion and oxidation to acetyl-coA.
Pathway schematics from (60). AcAc thiolase is the key enzyme for ketone utilization.
25
Figure 2.2 Ketone bodies utilization in the brain and synthesis in the liver.
The transport of ketone bodies across the blood brain barrier (BBB) requires monocarboxylate transpoters (MCT). Pathways are shown in reference (18).
26
Figure 2.3 Schematics for 18FDG tracer study models .
27
Figure 2.4 Sample Rat PET images, as displayed in CARIMAS2 software.
The top left, bottom left, top right show the transversal, coronal and sagittal views of the rat brain. Bottom right image shows the 3-D view of the rat. The catheter that delivers
the 18FDG tracer had high residues and is highly visible. The highest uptake of 18FDG in the brain occurs at the eyes.
28
Figure 2.5 Experiment Set up for anesthesia system.
Rats are anesthetized by isoflurane and then passively breathing in the vaporized isoflurane in PET gantry. a) The rat b) customized nose cone. The dotted lines indicate tubes with holes to allow animals to exhale. c) Flask of water (used to add more vapor to vaporized isoflurane) d) Flask of water (used to absorb carbon dioxide) e) Isoflurane vaporizer f) 100% oxygen , delivered at 0.1-0.2 liters per minute g) Room air pump, delivered at 0.5-0.9 liters per minute h) Charcoal filter (traps waste gas).
29
Author s (et al) An KG Year est Change Total Journa speci hes Tech ketosis CMRglc after the keton l es ia Method method changed? Change effect, % Ctrl e Comments Al Mudall al 1995 KG diet has calorie restriction; KG diet for Neurol Rats Y 2DG KG diet NS 87.30 0.11 0.66 three weeks but calory restriction. Chang 1993 Can J Hypoxia Vs. Normoxia study, did not Physio Kety BHB measure CMRglc. Only the extraction Phar Dogs Y Schmidt Infusion NA N/A 5 fraction measured. Corddr y 1982 J 3day fast Neuro or BHB Cerebellum; N.S decrease. Only look at chem Rats N 2DG Infusion N 83.91 0.48 2.34 frontal cortex Crane 1985 Not JCBF Y modified Rep Not reduction to 63% after 5 days in M(101 and uptake orte Repo pentobarbital anesthetized rats; ) Rats N method 2day fast NS NS 62.96 d rted Hemispheres same Not as Rep Not above orte Repo reduction to 78.5% in hemispheres and NS NS d rted frontal cortex Dalqui st 1976 Diffusion Pediat adult and Kety Not Not unit: umol/mg DNA /min; In adults. This r Res rat Y Schmidt 2day fast Reported reported 157.14 0.95 result is weird same as Diffusion above Infant and Kety Not Not unit: umol/mg DNA /min; In adults This is rat Y Schmidt 2day fast Reported reported 62.50 1.58 also sort of weird same Diffusion as adult and Kety 3 day Not Not above rat Y Schmidt fast Reported reported 80.95 2.44 unit: umol/mg DNA /min; In adults Same as above Diffusion Infant and Kety 3 day Not Not rat Y Schmidt fast Reported reported 75.00 2.00 unit: umol/mg DNA /min; In adults Hassel bach 1994 JCBF Hum FDG 3.5 day M an N PET Fast Yes No change 74.19 0.28 3.20 LC no change. Kety's method: -24% Hassel Yes for bach FDG global, but 1996 Hum PET + BHB N.S for AJP an N Kety infusion regional 39.22 67.98 0.30 2.40 BHB utilization up 5 folds also Hawki Starve 2 Not ns or 4 Rep 1986 modified days. No orte AJP Rats Y uptake ctrl NA NA d NA Only measured Cmrket contributes 3% Hawki ns 1971 Diffusion Bioche Adult and Kety Fast Did not measure CMRglc or CMRket. m J rats Y Schmidt 2day NA 0.23 2.81 Only a-v concentrations same fast 3 day 3.03 same fast 4 day 3.34 same Infuse acac 1.40 same suckli ng Infuse rats acac 2 7.28
30
Hassel bach 1995 Hum Kety 3.5 day s No change of Glucose influx AJP an N Schmidt fast NA No change NA 0.23 3.17 (unidirectional), did not measure CMRglc Owen Hum Not 1967 an 5-6 Rep J Clin (Obe Kety weeks orte Invest se) N Schmidt fast NA 29.00 d 7.83 Did not measure CMRglc or CMRket Pan 2002 Unk JCBF Hum 2 hr BHB now M an N NMR infusion NA n 2.25 Did not measure CMRglc Redie s FDG 1989 Hum PET + 20-24 AJP an N Kety Day fast Yes No change 55.17 0.05 4.27 LC decreased by 25% in ketosis Ruder man 1974 Only reports A-V diff; only significant for Bioche Kety 1-2 days 2days fast; Lactate down in fast rats. This is m J Rats Y Schmidt fast NA N/A ! 83.00 0.15 2.58 glucose oxidation, not uptake or utilization Linde Y 2005 and Kety Ketone Lactate Raised in the awake, but not JCBFM Rats N Schmidt Infusion 64.81 0.64 anesthetized. No CMRglc change Mans 1987 Metab olic Br modified Diseas Autoradio 2 days e Rats N graphy fast Yes 86 88.00 0.33 1.35 Lactate unchanged. Linde 1999 Acta Physiol Kety Did not induce ketosis. New CBF measure Scand Rats N Schmidt No NA method Prins 2009 J Neurot Autoradio KG diet, 7 KG diet as therapeutic (Not protective) rauma Rats Y graphy days NA Lactate up and recovered from the trauma Fast Jiang 1.5d , 2011 then inf JCBFM Rats Y NMR BHB NA 50.00 4.20 9.40 Lacks real control animal Bentou rkia KG diet 2009 and fast Unsu AJP Rats Y C11 PET 2day NA re Pure Oxygen Anesthesia; only has CMRket Issad whole body 1987 CMRglc Bioche Autoradio decreased m J Rats N graphy 2day fast NS 40% 94.23 0.33 1.95 Not significant different in the brain Cherel 1988 Metab Autoradio up to 3 Too small olism Rats Y graphy day fast NS to tell 1.30 glucose utilization index, not CMRglc same as above up to 8.5 NS 83.33 1.15 same as above up to 12 days fast NS 66.67 0.17 weird Gjedde 1975 Kety AJP Rats Y Schmidt 5 day fast 0.10 Only measured BUI
Table 2.1 Unpublished data of meta-analysis of the studies on CMRglc during ketosis.
NS: not significant. NA: not available.
31
Rat1 Rat2 Rat3 Rat4 Rat5 Rat6 Rat7 Age P56 P60 P61 P65 P75 P79 P62 Weight grams 229 267 270 292 294 276 325 Died 140min FDG Dose Injected uCi post-surgery 654 784 808 659 729 734 Dose per g uCi/g 2.45 2.90 2.77 2.24 2.64 2.26 Time btw fast & injct hrs 13.5 19 19 19 18 18.5 17.5 Pre-Img [BHB] mM 2.4 2.2 2.3 N/A 1.1 1.1 0.4 Pre-Img [Glc] in whole blood mM N/A N/A N/A N/A N/A 4.7 Pre-Img [Glc] in plasma (Cp) mM 6.6 5.78 N/A N/A N/A N/A Hematocrit (%) 42-44 41-43 43-45 45-48 43-45 45-47
Hematocrit stable Through H90min=3 H0mi H10= Imaging? Yes 9% Yes n=42 47 yes PET Very Delay 40sec, Heart Very Very Very Input function quality Heart Good Input Function good good good Wokeup Brain Image TAC quality @82min Breathe Rate at steady state b/min 51 32 41 35 42 37 Steady state sampling time min post injection 48 51,60 52 55 45 46 Plasma glucose At steady state mM 7.37 5.48 6.95 5.41 7.33 9.53 [BHB] At steady state mM 3.2 2.2 1.7 2.1 2.2 0.9 L-Lactate at steady state mM 1.55 1.05 1.15 1 0.99 0.85 Haemoglobin Oxygen Saturation 97%-18% at steady State % 99 98.9 99.05 97.95 97.6 99.09 7.18(Wr pH at steady state 7.31 7.35 7.3 N/A N/A ong?) has Pco2 at steady state mmHg 55 56 45 N/A N/A Error 333 Po2 at steady state mmHg 314(3 (wrong? 7C°) 152(25c°) 104(25C°) N/A N/A ) CMRglc,trapping,ODE method (K1-k3) umol/100g/min 75.8 61.09 42.43 81.89 CMRglc,nontrapping,ODE (K1- k4) umol/100g/min 94.8 60.96 64.94 96 CMRglc, trapping, Patlak (K1-k3) umol/100g/min 67.57 63.73 43.49 77.06 Table 2.2 Unpublished data on KG and STD rat CMRglc, with hyperoxia (100% O2 anesthesia) .
32
Chapter 3 Ketosis Proportionately Spares Glucose Utilization in Brain
(This chapter is a copy from article to be published by Journal of Cerebral Blood Flow and Metabolism, 2013.)
33
3.1 Abstract
The brain is dependent on glucose as a primary energy substrate, but is capable of
utilizing ketones such as β-hydroxybutyrate and acetoacetate, as occur with fasting,
starvation or chronic feeding of a ketogenic diet. The relationship between changes in
cerebral metabolic rates of glucose (CMRglc) and degree or duration of ketosis remains
18 uncertain. To investigate if CMRglc decreases with chronic ketosis, 2-[ F]fluoro-2- deoxy-D-glucose in combination with Positron Emission Tomography, was applied in anesthetized young adult rats fed three weeks of either standard or ketogenic diets.
CMRglc (µmol/min/100g) was determined in the cerebral cortex and cerebellum using
Gjedde-Patlak analysis. The average CMRglc significantly decreased in the cerebral
cortex (23.0 ± 4.9 vs. 32.9 ± 4.7) and cerebellum (29.3 ± 8.6 vs. 41.2 ± 6.4) with
increased plasma ketone bodies in the ketotic rats compared to standard diet group. The
reduction of CMRglc in both brain regions correlates linearly by ~9% for each 1mM
increase of total plasma ketone bodies (0.3 - 6.3 mM). Together with our meta-analysis,
these data revealed that the degree and duration of ketosis plays a major role in
determining the corresponding change in CMRglc with ketosis.
34
3.2 Introduction
Researchers and clinicians have been interested in brain metabolism during starvation,
fasting or acute ketosis for many decades. Under physiological blood glucose
concentrations the fractional contribution of ketone bodies to oxidative metabolism in
adult brain has remained uncertain. During prolonged starvation, brain energy
requirements have been traditionally accepted to be supplemented by ketone body
oxidation. (2, 17). The conviction was founded on the rationale that under glucose sparing conditions, a large portion of oxidative energy must be derived from ketone bodies and thus resulting in reduced glucose consumption. (2, 17, 102). Historically there has been
controversy amongst researchers whether there is a causal relationship between changes
in cerebral metabolic rates of glucose with degree and duration of ketosis. Inconsistencies
across studies were revealed when the effects of short-term fasting (or acute ketosis) on
changes in cerebral metabolic rates of glucose (CMRglc) were further explored (15, 35, 45,
76, 102)
We deem that ketones are effective against pathology associated with altered glucose metabolism and inadequate regulation of salvation pathways. We hypothesize that ketone bodies are neuroprotective through the restoration in energy balance via suppression of glucose oxidation and stabilization of ATP supply. Ketone bodies, such as β-
hydroxybutyrate (BHB) and acetoacetate (AcAc), are alternative energy substrates to
35
glucose especially important during development and glucose sparing conditions, such as
with fasting, starvation and diet-induced ketosis . (2, 18, 32, 33)The relationship between energy supply and demand and the partitioning of substrate utilization between glucose and ketones in brain continues to be explored. The ketogenic diet (high-fat, very low- carbohydrate) to induce chronic ketosis has been successfully used in the clinical setting as a therapy for intractable seizures for nearly a century . (9, 10, 12, 18 , 48)However, the
“mechanistic link” between the anticonvulsant effects and ketosis continues to be investigated and remains to be elucidated. (20) Ketone bodies as neuroprotective agents appear to related to the change in the regulation of the cell’s stress responses, (21) as well as changes in oxidative (glucose) metabolism(13, 14). Neuroprotection by ketosis is thought to be associated with improved mitochondrial function, decreased reactive oxygen species, apoptotic and inflammatory mediators, and increased protective pathways. (18, 60)
In the last few decades the 2-deoxy-D-glucose (2DG) or Positron Emission Tomography
(PET) approaches have been applied to ketotic studies, both animal, (13) (16, 47, 51)and
humans (15, 17, 56, 103). Reports of altered CMRglc as result of short-term fasting (15,
35, 45, 76, 102) or acute infusions of ketone bodies (56, 59)had generated discrepancies.
What remained to be clarified was (i) whether oxidation of ketone bodies can replace glucose proportionately during acute/mild ketosis under normglycemia and (ii) the percent of glucose sparing with degree of ketosis. Some studies reported generalized,
36
decreasing CMRglc with 3-5 days of fasting in humans(15, 17, 103)while in other studies
there were no significant changes in CMRglc(46, 51, 75, 102).
The goal of this study was to estimate CMRglc in chronic ketotic rats and to determine if ketosis induces a metabolic adaptation through changes in glucose phosphorylation rates.
The effects of ketosis on CMRglc in intact brain during stabilized blood glucose
conditions in diet-induced ketotic rats using positron emission tomography (PET) and 2-
[18F] fluoro-2-deoxy-D-glucose (18FDG) were determined. The rationale for using PET-
FDG was based on the principle that the phosphorylation rate of 18FDG (a trapping tracer)
can be used to estimate the phosphorylation rate of glucose. In support of our findings, a
retrospective analysis of historical data (meta-analysis) to resolve the inconsistencies
across studies was also performed(2, 15-17, 45-47, 51, 75, 76, 102, 103).
37
3.3 Materials and methods
3.3.1 Animal Model and Diets
Young adult male Wistar rats were purchased from Charles River (Wilmington, MA,
USA), 40 days old, and weighing ~150 grams. All procedures were performed in strict accordance with the National Institutes of Health Guide for Care and were approved by
Institutional Animal Care and Use Committee of Case Western Reserve University. Body weights were measured upon arrival and on the experimental day (Table 1). Littermates were housed 3 per cage in the Case Western Reserve University Animal Resource Center with 12h-12h light-dark cycle. All rats were allowed to acclimate for 1 week prior to initiating dietary protocols. Standard rodent diet (STD) was fed to all rats during the acclimation period (Labdiet Cincinnati, OH, USA, Prolab RMH3000 5ANE) ad libitum.
One week after their arrival, all rats were fasted overnight for 16 hours to deplete the liver glycogen stores and initiate ketosis. Rats were then randomly assigned to two diets,
STD or Ketogenic diet (ketogenic, KG; Research Diet, New Brunswick, NJ, USA,
D12369b) and fed for three weeks ad libitum until FDG-PET experiments. (62) The macro and micro-nutrient of the STD and KG diets is shown in Table 3. The original datasheets for the diets are included in supplementary Table 3 and 4.
38
3.3.2 Anesthesia and Surgery
On the experimental day (post three weeks of diets) rats were morning fasted for 6 hours prior to PET imaging. Rats were then anesthetized with vaporized 2.5% isoflurane balanced with pure oxygen delivered through a nose cone during the surgical placement of arterial and venous catheters: right jugular catheter (MRE, 0.035 mm ID and 0.084mm
OD, Braintree Scientific Inc, Braintree, MA, USA) was advanced towards the atrium for 18FDG injection and the tail artery (PE-50, 0.58mm I.D and 0.965mm O.D. Stoelting
Co. Wood Dale, IL, USA) was cannulated for blood sampling during the PET imaging period. (104) Rats were then transported to the Inveon PET (Siemens, Knoxville, TN,
USA) bed and maintained with a mixture of vaporized isoflurane, pure oxygen and room air. Anesthesia level (1-2%), oxygen flow rate (0.05-0.2 liters per minute) and air flow rate (0.5-0.6 liters per minute) were adjusted to achieve a consistent physiological status across animals. Absence of hind-leg pinch reflex was monitored throughout the PET scan to ensure depth of anesthesia. Heart rate, respiratory rate (breaths/min), plethysmography and oxygen saturation (%) were monitored (via hind leg senor) and recorded throughout the experiment using a pulse oximeter system (MouseOx, Starr life sciences, Oakmont,
PA, USA) (Table 1). To maintain breath rates (~70 per minute) and normal blood gases throughout the 1.5 h imaging process, isoflurane was adjusted, as well as the oxygen percentage and flow rates.
39
3.3.3 Physiological Parameters
Plasma glucose, lactate and total ketone bodies (BHB +AcAc) concentrations were
measured pre- and post-imaging (t=0, 60 min) from a blood sample collected (0.1 ml)
from the tail artery catheter. The whole blood samples were centrifuged and the plasma
separated and immediately frozen in dry ice; the end-of-imaging hematocrits were also
recorded. Plasma D-glucose and L-lactate were later measured by YSI 2700
Biochemistry Analyzer (YSI Inc., Yellow Springs, OH, USA) and the plasma total ketone
bodies were measured by gas chromatography mass spectrometry, as previously
31 described. Arterial blood gas parameters (pH, PaO2 and PaCO2) were measured at t=0, 45
min (ABL5 Radiometer, Copenhagen, Denmark); 45 minutes was considered the end
point where CMRglc reached steady state (81, 82). Arterial blood glucose was measured at t=15, 30, and 45 min to verify the steady state plasma glucose concentration during the experiment (Precision Xtra Meter, Abbott Diabetes Care, Inc, Alameda, CA, USA). The breath and heart rates were also recorded throughout the imaging process and were used as indicators for physiological status.
3.3.4 Image Acquisition and Blood Sampling
A dual-modal PET-CT device, Inveon (Siemens, Knoxville, TN), was used to image the 18FDG activities in the brain. The rat’s eyes were placed at the center of the field of
view for the best spatial resolution. First, a 10-minute transmission scan was performed
40
before the 18FDG tracer injection. The transmission scan generates tissue attenuation map
for attenuation correction in the PET images. Then 10 ± 2Mbq/100g of 18FDG was
injected through the jugular line at time zero. Simultaneously, a 60-minute list-mode PET
emission scan was started along with the automatic arterial sampling using a customized
Blood Acquisition Module (BAM). The BAM device acquires the whole blood radioactivity in the first 2.5 minutes post injection, at a rate of 0.2 ml/min, specified by a connected syringe pump (Harvard Pump 11 plus, Hollisten, MA, USA). The pump was stopped at 2.5 minutes post injection. Manual sampling for arterial blood activity was
performed at 3.5, 5, 7.5, 10, 15, 25, 40, 50, 60 minutes, using heparin-coated, micro-
capillary tubes (HT9H, Statspin, Westwood, MA, USA) with each tube’s volume no
more than 9µl. On the experimental day the total blood sample volumes were noted from
each rat which was less than 1.4ml.
After the PET emission scan, the manually sampled bloods were centrifuged (RH12,
Statspin, Westwood, MA, USA). The volume inside the micro-hematocrit tubes were pre-
measured as 8.3μl/37mm, therefore by measuring the length of the whole blood portion,
* whole blood activity per volume (Cwb ), was obtained by converting the counts from a
Gamma counter (LKB1282 Compugamma, LKB Instruments, Mt Waverley, Vic,
Australia) and time-correct to time zero . Hematocrit tubes were then broken and the
* plasma radioactivity (Cp ) was also counted and corrected for the decay. The hematocrits
at 3.5 (when manual sampling begins) and 60 minutes were recorded.
41
* * The first 2.5minutes of input function Cwb , was converted to Cp by a factor R. This follows
C* (t = 3.5) = p R * Cwb (t = 3.5)
The manually sampled plasma radioactivity data were time-corrected to the 18FDG injection time and the half-life (107 minutes). The BAM and manually sampled data were combined and saved in a text file for the Matlab (The MathWorks, Natick, MA, USA) program analysis. Factor R was not different between diet groups (1.7 ± 0.10 vs 1.6 ±
0.10; STD, KG, respectively).
3.3.5 Image Processing: Region and Volumes of Interest
The list mode emission data were binned to 34 frames: 6×10sec, 6×20sec, 4×30sec,
3×1min, 2×2min, 2×4min, and 5×8min. The reconstruction algorithm on the scanner was set to OSEM2D with a ramp filter supplied by the vendor of the scanner. The final images were saved as coronal, transversal and sagittal images with 128×128 pixels, and the resolution was 0.78 mm in the sagittal, transversal sections and 0.79 mm in the coronal section. The value of each voxel in the reconstructed PET image sets is converted to radioactivity per volume.
42
The processed PET radioactivity image data were analyzed using Carimas 2 (Turku PET centre,Turku, Finland), to generate the Region of Interest (ROI) and Volume of Interest
(VOI) data. Both the left and right eyes were identified as the landmarks. A rat brain atlas
(Paxinos and Watson, Academic Press) was used to guide the selection of the ROI and
VOI. Starting from the rear of the eyecup, with slice thickness 0.125 mm, the left and right entire cortical hemispheres were encircled and two separate VOI were generated.
Similarly, the whole volumetric cerebellum was selected as one VOI. A separate PET-CT image set for a rat of the same range (P60-P80) of age was overlaid to verify the cortical and cerebellar regions (see Figure3.4). The two hemispheres VOI and the cerebellum
VOI were saved to text files and made importable to the Matlab program as the Time
Activity Curve (TAC) format.
3.3.6 Parameter Estimation and Calculation of CMRglc
We developed a MatLab program to perform the parameter estimation and calculation of
CMRglc. The plasma input function was interpolated to render a time resolution of 0.1 second. Then the 34-frame TAC was matched with the input function for each of the time points. The Gjedde-Patlak plots were generated and only the last 6 matching points, namely the time after 25 minutes data were used to generate the parameter Ki, which follows:
43
* * * k1 k3 Ki = * * k2 + k3
* 18 * 18 While k1 is the FDG transport rate constant (/min) to the brain tissue, k2 is the FDG
* 18 reverse transport rate constant from tissue to the plasma (/min) and k3 is the FDG
phosphorylation rate constant (/min).
The lumped constant in both the KG and the STD diet rats were assumed to be 0.71
(105) . The 60-minute plasma glucose level, Cp, was used to generate the final CMRglc, which follows: (26, 27)
K *C CMRglc = i p LC
44
3.4 Results
3.4.1 Physiological parameters
There were no significant differences in body weights, blood gases, physiological
parameters, and plasma glucose concentrations between KG and STD diet groups
following 3-weeks of feeding the diets (Table 1). As expected, plasma ketone (BHB,
AcAc) concentrations were statistically higher and the plasma lactate concentrations were
lower in the KG rats compared to the STD group(62) . Ketosis ranged between 0.4- 6.2 mM as measured by total plasma ketone bodies (Figure 1); the STD group was mildly ketotic (0.3 -0.9 mM, plasma total ketone bodies) following a 6 hour fast prior to imaging.
Lactate concentrations in the plasma were significantly lower in the KG diet group (0.77
± 0.18 mM), Table 3.1.
3.4.2 Cerebral Glucose Metabolic Rates
The averages of the CMRglc (µmol/100g/ min) measured in both cerebral hemispheres
and cerebellums are shown in Table 2. There were no significant differences in CMRglc
between the left and right hemispheres The PET analysis revealed that diet induced
ketosis resulted in a significant decrease in the average CMRglc in both cerebral hemispheres and cerebellum compared to STD group. CMRglc was significantly lower in
the left and right cerebral hemispheres compared to the cerebellum, in both dietary
groups.
45
The CMRglc calculated with Gjedde-Patlak analysis was plotted as a function of the
measured total plasma ketone body concentrations (BHB + AcAc; mM) (Figure 1).
These data showed that cerebral (left and right hemispheres) and cerebellar CMRglc
decreased with increasing ketosis. The calculated CMRglc in each region was represented by a linear decrease with increasing total plasma ketone concentrations. There were no significant differences between left and right cerebral hemispheres, (CMRglcright = -2.9×
([BHB]+[AcAc]) + 34.9; R² = 0.59); whereas the cerebellar region was significantly
higher (CMRglc = -3.7× ([BHB]+[AcAc]) + 43.9; R² = 0.59) compared to Cerebral Cortex.
These data highlight the proportional change in CMRglc with increasing ketosis; thus for
every 1mM increase in total plasma ketone bodies CMRglc decreases by ~9%.
3.4.3 Meta-analysis of CMRglc in Ketotic Subjects
Meta-Analysis of CMRglc reduction in ketotic subjects (human or rats) was shown in
Figure 2. All data were collected from previously reported studies where CMRglc was
measured and level of ketosis was reported. CMRglc data from the ketotic subjects were normalized to the non-ketotic controls (%) and then graphed against the total blood ketone body concentrations (mM). The normalized glucose utilization rate decreased ~ 9% for each 1mM increase of the total blood ketone bodies. A summary of these data collected from the various studies measuring CMRglc and blood ketone concentrations
46
includes (see Figure 3.2 legend for details): PET-FDG studies conducted in fasted humans showing a 27% decrease in CMRglc following 3.5 days of fasting (45), in humans that were fasted for 3 weeks the authors reported a 46% decrease in CMRglc relative to the non-fasted baseline conditions (17). Other studies using different methodologies for assessing glucose utilization in ketotic rats showed similar decreases. In one study where
[6-14C] glucose and autoradiography was applied, glucose utilization decreased 12% in conscious 2-day fasted rats with mild ketosis(76).
47
3.5 Discussion
We report here, in diet-induced ketotic rats, decreases in CMRglc highly correlate with both the level and the duration of the ketosis. These data revealed that the degree and duration of ketosis play a major role in determining corresponding changes in CMRglc with ketosis. We also present a retrospective analysis of historical data (meta-analysis) that appears to reconcile the inconsistencies from previous studies which supports our conclusion.
The brain’s ability to switch from glucose oxidation towards ketone bodies requires a type of “cerebral metabolic adaptation”. This process is not well understood but is thought to be highly associated with the duration and level of ketosis(14, 32, 40,
41).Ketones are considered to supply up to 70% of the total energy demands once maximal metabolic adaptation occurs(2). Blood ketones become elevated during prolonged fasting or with a ketogenic diet reaching a state ketosis and glucose sparing.
During this process, monocaboxylic transporters (MCT) up-regulate at the blood brain barrier with increasing demand for ketone utilization by brain (40, 41). Recently, investigators have recognized additional therapeutic properties of ketosis, such as neuroprotection following stroke or injury(14, 60).What remains unclear is whether the neuroprotective or therapeutic properties of ketosis is as a result of changes in the regulation of metabolic signaling pathways. These would include those associated with
48
enzyme-catalyzed steps involved with glucose regulation (5) or glucose independent
pathways, such as the Nrf2 pathway (a "responder" to cellular stress) (21). In this study
we questioned whether cerebral metabolism of ketone bodies (CMRket) replaces CMRglc
following three weeks of diet-induced ketosis.
Previous studies measuring CMRglc in ketotic subjects report either changes in CMRglc
with ketosis or failure to detect significant changes(2, 15-17, 45-47, 51, 75, 76, 102,
103).Historically, it has been established that brain can utilize ketone bodies under ketotic
conditions(2) (5, 9, 10, 12, 20, 32, 35) . However, corresponding changes in CMRglc
during “metabolic adaptation” to ketosis has not been clearly described. Using PET-FDG
imaging, the focus of this study was to determine if CMRglc decreases with increasing
ketosis in adult anesthetized diet-induced ketotic rats. CMRglc in cerebral hemispheres
and cerebellum decreased with increasing ketosis (0.3-6.3 mM) in rats fed either STD or
KG diets for 3 weeks. These data are consistent with the conclusions described in the
classic human study by Owen et al (2). Their study was the first to highlight that the brain
can switch from glucose oxidation to ketone body oxidation with chronic ketosis. Most
revealing to us was a previous study using a similar rat model of diet-induced ketosis to measure changes CMRglc(51). The study failed to detect significant changes in CMRglc
even though the duration and method of induction of ketosis was similar. However, the
level of ketosis was 4-fold lower making it difficult to detect a corresponding change in
CMRglc with ketosis.
49
The most striking information obtained from our study was the correlative finding that
CMRglc decreased 9% with every 1% increase in total plasma ketones. Although not
previously reported as such, the results of this study are consistent with previous studies
measuring CMRglc in ketotic subjects, as our meta-analysis (Figure 3.2) also showed the
same linear association between level of ketosis and corresponding changes in CMRglc.
The meta-analysis supports our current findings and has brought new insight into
previous studies (as authors’ interpretations led to discrepancies or incomplete conclusions). One explanation for the discrepancies may be the difficulty to distinguish small changes in CMRglc with a small degree of ketosis. This was the case with our previous study in diet-induced ketotic rats where CMRglc was assessed using 2-DG(51).
The level of ketosis was less than 1mM, making it difficult to detect a less than 9%
decrease in glucose utilization using a non-imaging compartment modeling method.
Another consideration is the induction of ketosis through acute ketone body infusions.
The main difficulty to this approach is the lack of metabolic adaptation to ketosis (41,
62) . We have previously shown metabolic adaptation to ketosis is directly associated with duration of ketosis and level of ketosis (13, 62).Thus, in some studies using acute infusions of ketones to mimic ketotic conditions the outcome failed to show decreases (or consistency) in glucose utilization (56). An exception might be in studies where low
50
doses were given following short-term fasting, but the analytical approach often requires a higher degree of sensitivity for detecting small changes in CMRglc (57). Variabilities in experimental models such as, physiological status, level of ketosis via metabolic adaptation, and analytical approach play a key role in the measured outcome. The emphasis of our current study was to use PET imaging together with our diet-induced rat model of ketosis to measure detectable changes in CMRglc.
In summary, CMRglc decreased ~9% in both the cortex and the cerebellum for each 1mM increase in blood ketone bodies, which is consistent with diet-induced ketosis, as well as long and short term fasted ketosis. We attribute previous discrepancies to i) the failure to detect significant differences within and across studies, ii) in adequate metabolic adaptation to ketosis, and iii) difficulty in establishing and/or maintaining a higher degree of ketosis. Our work puts historical data into a current perspective by reconciling the inconsistencies from previous studies where little or no change in CMRglc with ketosis was reported. Nevertheless, the maximum percent ketone bodies that can replace glucose oxidation still need to be determined. A quantitative understanding of CMRglc and
CMRket under different durations and degrees of ketosis would elucidate the energy balance between glucose and ketone bodies.
51
3.6 Acknowledgements
We would thank the CASE Mouse Metabolic Phenotyping Center (MMPC; U24
DK76174) for assisting with GC-MS assays. This research has been supported by the
National Institutes of Health, R01 HL092933-01, R21 NS062048-01.
52
3.7 Figures and Tables
Figure 3.1 Decreased cerebral metabolic rate for glucose (CMRglc) with increasing
plasma ketone body concentrations in rats fed with ketogenic (KG) diet compared to
standard diet (STD) .
Volumes of the interest (VOI) were defined as the left and right hemispheres (panel A;
open circle, left and closed circle, right) and cerebellum (panel B). The CMRglc in each
region was calculated with Gjedde-Patlak analysis and plotted as a function of the
measured plasma total ketone body concentrations; the equation CMRglc = [slope ×
53
plasma total ketone concentrations + CMRglc at non-ketogenic state] corresponds to the linear correlation; “goodness of fit” was represented as the coefficient of determination,
R2, which reflected ~0.61 for each VOI. The STD diet group (n=9) total plasma ketone bodies were less than 0.87 mM and the KG diet group (n=10) was greater than 3.0 mM.
These results demonstrate that CMRglc decreased ~9% for each 1 mM increase in total plasma ketone body concentration in ketotic rats induced by 3 weeks of KG diet.
54
Figure 3.2 . Meta-Analysis of CMRglc reduction in ketotic subjects (human or rats).
All data were collected from previously reported studies where CMRglc was measured and level of ketosis was reported. Data were normalized (%) against control state (non- fasted, non-diabetic conditions) and graphed as a function of total blood ketone bodies level (mM). The study, method and reported outcome is noted for each point: (a) Data from Al-Mudallal et al, (51) ketosis by KG diet in rat, 2-DG method; no significant
cortical change in CMRglc, (b) Data from Corddry et al, (47) 3days fasted rats, 2-DG method; frontal cortical change, not significant, (c) &(d) Data from Dalquist et al, (46) 3
Days fasted rats, A-V uptake method; no significant change, (e) Data from Hasselbach et
al, (15) 3.5 days fasted humans, PET-FDG imaging; significant reduction, (f).Data from
55
Owen et al, (2) 5-6 weeks fasted obese human subjects, A-V uptake method, CMRglc, was
indirectly calculated by O2 consumption; significant change, (g) Data from Redies et al,
(17) 20-24 days fasted obese human subjects, PET-FDG and A-V uptake method;
significant CMRglc reduction, (h) Data from Ruderman et al, (45)1-2 days fasted rats, A-
V uptake method; trended significant, (i) Data from Mans et al, (76)2 days fasted rats,
compartmental modeling with non-trapping tracer (autoradiography); significant
reduction, (j) Data from Issad et al, (75) 2 days fasted rats, (autoradiography), no
significant change, (k) Data from Cherel et al, (102) 6 days fasted rats, modified 2DG
method, no significant change. The meta-analysis plot shows a linear relationship
between CMRglc and level of ketosis in human or rat subjects. For each 1mM of total blood ketone concentration increase there was approximately a 9 % decrease in CMRglc.
56
Figure 3.3 . Images of Volumes of the Interest (VOI).
VOI drawings were performed using CARIMAS2 software with the aid of a CT anatomical image set and a rat brain atlas. Top panels (yellow) indicate volume of left hemisphere in the transversal and sagittal planes. The bottom panels (pink) represent volume of cerebellum in the transversal and sagittal planes. VOI of right hemisphere are not shown. VOI drawings were performed using CARIMAS2 software.
57
Table 3.1 Physiological Parameters
Age (days) 72 ± 6 77 ± 7 Weight (g) 358 ± 33 360 ± 26 Blood Gas Parameters a pH 7.35 ± 0.04 7.32 ± 0.03
PaO2 (mm Hg) 112 ± 22 104 ± 20
PaCO2 (mm Hg) 53 ± 5 50 ± 5 Physiological Parameters b Breath Rate (Br/min) 63 ± 3 63 ± 5 Hematocrit (%) 48 ± 2 47 ± 2 Heart Rate (Beats/min) 378 ± 61 365 ± 37 Plasma Metabolic Parameters b BHB (mM) 0.36 ± 0.10 3.30 ± 0.85* AcAc (mM) 0.21 ± 0.11 0.61 ± 0.31* BHB+AcAc (mM) 0.51 ± 0.25 3.92 ± 1.04* BHB/AcAc ratio 1.74 ± 0.58 4.78 ± 1.19* L-Lactate (mM) 1.00 ± 0.10 0.77 ± 0.18* D-Glucose (mM) 11.51 ± 1.08 10.71 ± 1.87
* P<0.05 compared to STD diet group.
a Measured at 45 minutes post 18FDG injection
b Measured 60 minutes post 18FDG injection
Physiological parameters and concentrations of metabolites in plasma in rats fed standard
or ketogenic diets. Values are the means ± standard deviations. n, number of rats. Young
adult rats were fed either standard (STD) or ketogenic diet (KG) for three weeks prior to measurements of CMRglc.
58
Table 3.2 CMRglc in the volumes of interest (VOI)
VOI STD diet (n=9) KG diet (n=10) Left Hemisphere 33.5 ± 4.9 23.2 ± 4.8* Right Hemisphere 32.3 ± 4.7 22.8 ± 5.2* Hemispheres 32.9 ± 4.7 23.0 ± 4.9* Average Cerebellum 41.2 ± 6.4** 29.3 ± 8.6*, **
*P<0.05 compared to STD diet group, **P<0.05 compared to hemispheres
CMRglc (µmol/100g/min)
Cerebral metabolic rate for glucose (CMRglc) by positron emission tomography and 2-
18 [ F] fluoro-2-deoxy-D-glucose in rats fed standard or ketogenic diets. CMRglc (µmol/
100g/ min), at t=60 min post 18FDG injection. Values are the means± (SD); n, number of rats. *Significance p < 0.05 relative to STD. **Significance p < 0.05 relative to cortical hemisphere.
59
Table 3.3 Macronutrients of the standard (STD) diet and ketogenic (KG) diet
STD diet KG diet MacroNutrients (Labdiet 5ANE RMH3000) (Research Diets D12369B)
Starch % by weight 32.53 0.00 D glucose % by 0.12 0.00 weight Fructose % 0.16 0.00 by weight 0.97 <1% Sucrose % by 0.00 0.00 weight Lactose % Saturated % by weight 1.60 19.45 Monounsaturated % by 1.61 33.04 weight Polyunsaturated % 1.85 14.56 Pro tein % by weight 22.5 17.3 Fat % by weight 5.5 67.0 Carbohydrates % by 51.6 <1% weight 4.2 8.7 Protein % by energy 26.0 10.4 Fat % by energy 14.3 89.1 carbohydrates % by energy 59.7 0.5
60
STD diet KG diet
RMH3000) (Research Diets D12369B) Minerals Ca % 1.06 0.90 P % 0.76 0.69 Mg % 0.24 0.09 K % 0.93 0.62 S % 0.33 0.06 Na % 0.21 0.17 Cl % 0.37 0.28 Cr ppm (STD) or %(KG) * 0.91 0.00035 Cu ppm (STD) or %(KG) * 14 0.00104 I ppm (STD) or % (KG) * 0.98 0.00003 Fe ppm (STD) or % (KG) * 375 0.00779 Mn ppm (STD) or % (KG) * 99 0.01022 Se ppm (STD) or % (KG) * 0.38 0.00003 Zn ppm (STD) or % (KG) * 116 0.00502 F ppm 18.3 0 Co ppm 0.4 0 Vitamins Carotene ppm 1.2 0 Vitamin A IU/g 18 4000 ** Vitamin D3 IU/g 2.4 1000 ** Vitamin E IU/g 75 50 ** Vitamine K ppm 1.9 312.5 ** Thiamin Hydrochloride ppm 10 6000 ** Riboflavin ppm 14.3 6000 ** Niacin ppm 60 30000 ** Pantothenic Acid ppm 13 16000 (calcium salt) ** Folic acid ppm 1.2 2000 ** Pyridoxine ppm 8.17 7000 ** Biotin ppm 0.4 2.0 ** Vitamin B12 mcg/kg 77 10 ** Choline Chloride ppm 1999 0 Ascorbic Acid ppm 0 0
61
Table 3.4 Micronutrients of the STD diet and KG diet
*the STD diet nutrients are expressed in units of ppm, KG diet nutrients are expressed in % weight.
** The KG diet nutrients (Vitamins) are shown as their respective units in 1gram vitamin mix, which further mixes with the diet that contains 3917kcal. Refer to supplementary material 3, D12369B.
The STD diet datasheet was obtained from Cincinnati lab (cincinnatilab.com)
The KG diet datasheet was obtained from Research Diets (ResearchDiets.com)
62
Chapter 4 Contributions of Brain Glucose and Ketone Bodies to
Oxidative Metabolism
(This chapter has been published as an article :
Zhang, Y., Kuang, Y., LaManna, J. C., & Puchowicz, M. A. (2013). Contribution of
Brain Glucose and Ketone Bodies to Oxidative Metabolism. In Oxygen Transport to
Tissue XXXIV (pp. 365-370). Springer New York )
63
4.1 Abstract
Ketone bodies are an alternative energy substrate to glucose in brain. Under conditions of
oxidative stress, we hypothesize that ketosis stabilizes glucose metabolism by partitioning
glucose away from oxidative metabolism towards ketone body oxidation. In this study we
assessed oxidative metabolism in ketotic rat brain using stable isotope mass spectrometry
analysis. The contribution of glucose and ketone bodies to oxidative metabolism was
studied in cortical brain homogenates isolated from anesthetized ketotic rats. To induce
chronic ketosis, rats were fed either a ketogenic (high-fat, carbohydrate restricted) or
standard rodent chow for 3 weeks and then infused intravenously with tracers of [U-13C]
glucose or [U-13C] acetoacetate for 60 min. The measured percent contribution of
glucose or ketone bodies to oxidative metabolism was analyzed by measuring the 13C-
label incorpora- tion into acetyl-CoA. Using mass spectrometry (gas-chromatography;
GC-MS, and liquid-chromatography; LCMS) and isotopomer analysis, the fractional amount of substrate oxidation was measured as the M + 2 enrichment (%) of acetyl-CoA rela- tive to the achieved enrichment of the infused precursors, [U-13C] glucose or [U-13C]
acetoacetate. Results: the percent contribution of glucose oxidation in cortical brain in rats fed the ketogenic diet was 71.2 ± 16.8 (mean% ± SD) compared to the standard chow,
89.0 ± 14.6. Acetoacetate oxidation was significantly higher with ketosis compared to standard chow, 41.7 ± 9.4 vs. 21.9 ± 10.6. These data confer the high oxidative capacity
for glucose irrespective of ketotic or non-ketotic states. With ketosis induced by 3 weeks of diet, cortical brain utilizes twice as much acetoacetate compared to non-ketosis.
64
4.2 Introduction
This study was developed on the basis that ketones are effective against pathology associated with altered glucose metabolism, such as with ischemia reperfusion injury and seizure disorders. Ketosis can be induced by prolonged fasting or ketogenic (KG) diet. We had previously reported neuroprotection by ketosis following recovery from transient focal ischemia (14) . Using a rat model of ketosis, we hypothesized that the cerebral metabolic rate for glucose (CMRglc) decreases with increasing ketosis. Thus, a shift of oxidative metabolism away from glucose towards ketone bodies may result in neuroprotection, irrespective of the mechanistic link. It has been described in humans and rodents that CMRglc decreases with ketosis (16, 55) . To show the partitioning of glucose metabolism towards ketone oxidation, one would need to simultaneously measure CMRglc under ketotic and non-ketotic conditions. CMRglc can be readily measured by a metabolic trapping mechanism using 2-[18F]-Fluorodeoxyglucose
(18FDG) tracer and Positron Emission Tomography (PET) imaging system (16) .
However, the CMRket cannot be reliably measured due to various constraints. These include (i) costly use of PET imaging systems, (ii) lack of a trapping tracer for accurate measurements of ketone body utilization, (iii) short half- life of the currently available tracers, and (iv) relatively low sensitivity of nuclear magnetic resonance (NMR) (78,
106, 107).
To test in the cortical brain the partitioning of ketone utilization during ketosis, we designed a study using stable isotope tracers and mass spectrometry to estimate the
65
fractional contribution of glucose or ketone bodies (acetoacetate) to oxidative metabolism. This enabled the implementation of a relatively inexpensive method
(compared to PET), using an in vivo rat model of ketosis to study cortical brain glucose and ketone body metabolism. GC-MS and LC-MS systems are used for investigating intermediary metabolism, as they have high sensitivities to many analytes and metabolites. Compared to NMR methods, the use of small sample size therefore allows a smaller blood volume to sample. Stable isotopes of 13C-labeled tracers were infused into anesthetized rats and assayed by mass spectrometry. This approach assumes that the 13C-label incorporated acetyl-CoA is from the oxidation of the precursors, 13C- glucose or 13C-acetoacetate. Using isotopomer analysis, the M + 2 enrichment of acetyl-CoA was measured and the fractional percent contribution of substrates (glucose or ketone bodies) to oxidative metabolism was calculated as the mole percent enrichment (MPE) of acetyl-CoA (107, 108).
66
4.3 Methods
The experimental protocol employed in this study was approved by the Institutional
Animal Care and Use Committee (IACUC) at Case Western Reserve University.
4.3.1 Animal Preparation and Diets
Adult male Wistar rats (final weight: 310–440 g; n = 20) were purchased from
Charles River and were allowed to acclimatize in the CWRU Animal Resource
Center (ARC) for at least 1 week before feeding their respective diets. Rats were then
fed either the ketogenic (KG) or Standard (STD) diets for 3 weeks prior to the
experimental day (14, 16). The KG diet was purchased from Research Diet (New
Brunswick, NJ, USA) and the standard rodent chow (Teklad 8664) was provided by
CWRU ARC. All procedures were performed with approval from the Case Western
Reserve University IACUC. On the experimental day, both diet groups (KG and STD)
underwent the same surgical procedures for the placement of jugular and arte- rial
catheters and tracer infusions (16). Rats were morning fasted for 4 h prior to tracer
infusions prior to infusions. Anesthesia was induced with isoflurane balanced with a
mixture of N2/O2 and the rats were maintained under light anesthesia during the tracer
infusions. The flow rates of the gases were manually adjusted to maintain breath rates
(60–80 breath/min). Arterial blood gases were measured (ABL-5, Radiometer,
67
Copenhagen) to confirm stable arterial blood pH.
4.3.2 Experimental Design, Tracer Preparation, and Infusions
Four study groups were implemented: rats were infused with tracers of [U-13C]glu- cose
or [U-13C]AcAc and fed either standard (STD) or ketogenic (KG) diets. [U-13C] glucose
(99.8 %) was solved in 0.9 % NaCl solution to a final concentration of 38.7 mM. [U-
13C]AcAc was derived from [U-13C] ethyl-acetoacetate, as previously described (109)
and concentrated to 137 mM. All chemicals were purchased from Sigma-Aldrich.
Tracers were infused via the jugular vein catheter (0.50 or 1.0 mmol/ kg/h) (Harvard
Apparatus syringe pump-11 Plus) for 60 min. To verify steady-state conditions, blood
samples (100–200 mL) were taken from the tail artery at time point 0 (pre-infusion), and
at 15, 30, 40, 50, and 60 min (during infusion), immediately centrifuged and the plasma
frozen for GC-MS analysis of the [U-13C] precursor enrichments and concentrations of
glucose and acetoacetate. At the end of infusion, the rats were decapitated; the brains
were dissected immediately, frozen in liquid nitrogen, and stored at −80 °C. Cortical
sections (~200 mg tissue) were then dissected under frozen conditions and homogenized
using a specific organic solvent mixture designed for isolation of acyl-CoAs and related metabolites (107, 108).
68
4.3.3 Estimation of the Contribution of Acetoacetate and Glucose to Oxidative
Metabolism
Cortical brains were processed for 13C-acetyl-CoA (M + 2) enrichments (MPEs)
using LC-MS, a similar method as previously described (107, 108). The plasma MPE of
13C-glucose and 13C-AcAc was measured using GC-MS methods (107, 108). After back-
ground correction, the MPEs of the precursor 13C-substrates and the oxidative prod- uct
(acetyl-CoA), were calculated from the measured ion masses (M + 4, [U-13C] AcAc;
M + 6, [U-13C]glucose; M + 2, [U-13C]acetyl-CoA) to the unlabeled (MO,
endogenous intermediate); e.g., acetyl-CoA (M + 2) MPE = [M2/(M2 + M0) × 100]. The percent fractional contribution of glucose or AcAc to oxidative metabolism in cortical brain was estimated from the MPE of acetyl-CoA relative to the plasma MPE of the
13C-infused substrates and calculated: Substrate contribution to oxidative metabolism (%)
= [(brain acetylCoA MPE × 2)/(plasma glucose or AcAc MPE)] × 100. All data are expressed as mean ± SD. Statistical analyses were performed using a two sample t-test.
Significance was considered at the level of p < 0.05.
69
4.4 Results and Discussions
The fractional contribution of glucose or AcAc to cortical brain oxidative metabo- lism was estimated in anesthetized ketotic rats using stable isotope mass spectrom- etry analysis. The plasma MPE tracer dilution profiles of 13C-glucose and 13C-AcAc reached
steady-state conditions by 50 min (time course not shown). Ketosis induced by KG diet
did not significantly affect plasma 13C-glucose or 13C-AcAc MPE compared to STD
groups (9.8 ± 1.0 % vs. 9.2 ± 0.5 % and 20.9 ± 5.5 vs. 24.7 ± 3.3, respectively) (Fig. 4.1).
Cortical oxidative metabolism was significantly altered by ketosis (Figs. 4.2 and 4.3).
With glucose oxidation, a 30 % decrease in acetyl- CoA MPE was observed (Fig. 4.2,
see STD and KG groups given tracer infusions of [U-13C]glucose), whereas with AcAc
oxidation (see [U-13C]AcAc), acetyl-CoA MPE increased about 40 % with ketosis
(STD vs. KG groups). These data show a partitioning of brain glucose oxidation towards
ketone body oxidation with chronic ketosis. When estimating the percent contribution of
glucose to oxidative metabolism, ketosis (KG) resulted in a decrease in glucose
oxidation which was not significantly different from the STD diet group (Fig 4.3). Data
confirm the high oxidative capacity of glucose in cortical brain, irrespective of ketosis.
With respect to percent contribution of ketone body oxidation, ketosis resulted in an
increase in oxidative metabolism, as shown by the twofold increase in AcAc percent
contribution compared to STD diet (Fig. 4.3). Consistent with our hypothesis, ketosis
induced by diet plays a role in cortical brain utilization of AcAc. These findings
demonstrate the ability of brain to switch towards ketone body oxidation with ketosis
70
(Figs. 4.2 and 4.3) (78, 106). This model appears to overestimate oxidative metabolism by about 15 %. The sum of the percent contribution of glucose and AcAc to oxidative metabolism exceeds 100 % (Fig. 4.3). Indeed, in healthy non-ketotic mammals, glucose contribution to oxidative metabolism in brain is about 90 %. So we suspect that the fraction of ketone contribution to oxida- tion metabolism is overestimated by about
15 %. The reason for this overestimation remains to be determined. One explanation is the precursor pool of 13C-AcAc enrichment in brain tissue differs from plasma; an underestimation of the precursor MPE could account for this discrepancy.
71
4.5 Acknowledgments
The authors would like to thank the CASE MMPC, affiliated staff and faculty, for their technical assistance and helpful discussions on mass isotopomer analysis. This research was supported by the National Institutes of Health, R01 HL092933-01, R21
NS062048-01 and Mouse Metabolic Phenotyping Center, MMPC U24 DK76169.
72
4.6 Figures and tables
Figure 4.1 Plasma molar enrichment (MPE %) at t = 50 min.
Tracers of [U-13C]glucose and [U-13C] AcAc (acetoacetate) were infused in two diet groups, standard (STD) and ketogenic (KG). Steady- state MPE was achieved by t = 50 min (time course not shown). 13C-glucose infusions resulted in a 10 % plasma MPE in both diet groups. As a result of an increase in infusion rate of [U-13C]AcAc in the KG diet group compared to STD diet, a two fold increase in the 13C-AcAc plasma MPE was observed (mean ± SD; *p < 0.05)
73
Figure 4.2 Acetyl-CoA MPE in cortical brain.
Rats fed STD or KG diets were infused with either [U-13C]glucose or [U-13C]AcAc tracers. Ketosis resulted in decreased glucose MPE with a parallel increase in AcAc MPE
74
Figure 4.3 Contributions of glucose and AcAc to oxidative metabolism.
Percent contribution of glucose oxidation in cortical brain decreased with ketosis. A significant increase in percent contri- bution to AcAc oxidation with ketosis was also observed
75
Chapter 5 Ketone bodies spares glucose oxidative metabolism in diet-
induced ketosis in rat brain
(This chapter is to be submitted to the Journal of Neurochemistry as a manuscript in June,
2013)
5.1 Abstract
It is known that ketosis is neuroprotective to the brain. The mechanistic links from
ketone bodies and glucose oxidations in the citric acid cycle (CAC) to neuroprotection
remains to be explored. We hypothesized that ketone bodies serves the neuroprotective
roles through sparing of the glucose carbon shunting to CAC intermediates and
neurotransmitters. Rats were fed with either standard (STD) or ketogenic (KG) for 3-4
weeks and then infused with either [U13C]-glucose or [U13C]-acetoacetate to study glucose and ketone bodies’ fluxes toward oxidative metabolism. The plasma and brain homogenates were analyzed by gas-chromatography and mass spectrometry (GC-MS) for the isotopic fluxes. Results: 1) Brain [U13C]-glucose fluxes to CAC intermediates and neurotransmitters are reduced in ketosis; brain [U13C]-acetoacetate fluxes to CAC intermediates and neurotransmitters are increased in ketosis. 2) KG rat brains have significantly increased [U13C]-acetoacetate fluxes to GABA comparing with those in
STD brains. 3) During ketosis, [U13C]-glucose infusion increases brain glutamine and
76
glutamate concentrations, while the uptake of [U13C]-acetoacetate decreased brain glutamate and glutamine concentrations. It can be concluded that diet-induced ketosis spares brain glucose oxidations with ketone bodies. Ketosis may protect the brain through reduction of the glutamate and glutamine and increasing GABA concentrations.
77
5.2 Introduction
Chronic feeding of ketogenic diet had long been demonstrated to be neuroprotective. In
humans, ketogenic diet pre-conditioning is known to reduce epilepsy occurrence (1, 8,
10) . In animal studies, ketogenic diet is shown to be both protective in many injury
models, including epilepsy, ischemia, traumatic brain injuries and hypoxia (13, 14, 63,
110). The hypothetical interpretations of the mechanism to neuroprotection from ketone
bodies come from i) Ketosis increases consumptions of ketone bodies and decreases
consumptions of glucose in the brain (3, 13, 15-17). ii) Ketosis alters availabilities of
brain neurotransmitters, such as glutamate, and GABA, either in neurons or astrocytes.
(18, 53, 111) iii) Adaptation to ketosis shifts important molecular regulator proteins and
transporters (14, 21, 40, 41, 65) in the brain. iv) Ketosis reduces Reactive Oxygen
Species (ROS) productions (21-23) and glutamate toxicity (24) to the brain.
Our lab approached this mechanistic problem through the first two ideas. We deem that the biochemical pathways of the glucose and ketones are responsible for changes of the molecular regulators and the intracellular chemical milieu. First, changes of glucose and ketone bodies fates in utilization and oxidations directly leads to changes of downstream metabolites concentration and fluxes, therefore triggers altered enzymatic equilibriums.
Chronic adaptation to the altered biochemical equilibriums leads to changes of protein expressions (32, 33, 41). Thus the third idea for explanation of neuroprotection is dependent on the first two ideas. Secondly, the utilization and oxidation of the ketone bodies and glucose are related to ATP generations through the electron transport chain in
78
the mitochondria (22, 66, 112). To this sense, the fourth idea can also be partly attributed
to the changes in the utilization and oxidations of glucose and ketone bodies. Lastly, the
citric acid cycling activities is linked together with the glutamate-glutamine cycling
activities, which is responsible for generation of the glutamate and GABA. Ketosis was
believed to increase ketone bodie’s shunts to glutamine (19), similar with acetate in the
astrocytes (113) during traumatic injury, that can generate specific pool of glutamate that ultimately turns to GABA. Conversion of glutamate to glutamine also reduces cytotoxicity (24). GABA, as the major inhibitory neurotransmitter, is also believed to be associated with anti-epileptic effect (66, 114), as well as significant contributions to the
glutamate-glutamine recycling (115). Therefore, it is important to trace the ketone and
glucose utilization and oxidations, as well as their contributions to neurotransmitters.
We had recently shown that diet-induced ketosis suppresses the cerebral metabolic rate
of glucose (CMRglc) in adult rats (16) . Assuming the cerebral oxygen metabolic rate
(CMRo2) stays relatively constant in ketosis, the reported reduction of CMRglc
(essentially the steady state phosphorylation rate of glucose) seemed directly translates to
ketone bodies’ sparing of glucose oxidative metabolism. However, the phosphorylation
accounts only for the first step of glycolysis. The pathways of complete oxidation of
glucose and ketone bodies converge at the entrance of citric acid cycle (CAC), where
acetyl-coA was used to generate citrate. Furthermore, as the turning of the CAC
proceeds, carbons from glucose or ketone bodies continue to be shunted towards
glutamate through α-ketoglutarate- glutamate transferase, and further complicated cycling
79
between neuron and astroglial cells in the brain are reported (116, 117). To clarify
whether ketone bodies spares the glucose oxidative metabolism, it is imperative to
investigate the CAC intermediates and neurotransmitters fluxes and concentrations in the
working brain.
Previous works on the brain ketone body metabolic rates in humans and rats had
generated very different results (2, 3, 55-57, 77, 78, 106). The CMRket reported in ketosis
had varied between 2-8μmol/100g/min (55, 56, 78) to about 20μmol/100g/min (2, 15, 57)
humans during different models of ketosis. No evidence can be shown that the
differences are solely due to species differences. We speculate two possible reasons.
First, unlike glucose metabolism studies (13, 15-17) , the investigation of ketone bodies lacks a trapping radiotracer (77, 78, 106) . Usually, stable isotopes, with much less sensitivity, are applied to the subject or animals at orders of magnitude higher (28).
However, the brain presents very low concentration of ketone bodies, even during ketosis
(3, 38) . The infusion or injection of exogenous ketone bodies are reported to increase the cerebral blood flow (CBF), which directly causes uncoupling of the metabolism and shifts the baseline level of metabolism in ketosis (56) . This idea can also be supported by
the observation that the studies with radiotracers with low amount of infusion (77, 78,
106) often yield lower ketone utilization or oxidations rate than when high amount
infusion of tracers were applied (57). Secondly, the adaptation and stabilization of
ketosis, as a necessary step for neuroprotection, requires increased regulation of
molecular mechanisms is age dependent (33, 41) and ketotic-duration-dependent (13, 21,
80
40) , which may not present with some acute high-infusion studies. The presence or
absence of the adaptation phenomena in the studies may lead to the variations of the
results. For these two reasons, one must carefully design the ketosis induction method to
study the biochemistry underlying neuroprotection from ketosis.
To address the ketone bodies’ neuroprotection in terms of oxidative metabolism and fluxes to neurotransmitters, we infused [U13C]-glucose and [U-13C]-acetoacetate (AcAc)
in chronically diet-induced ketotic rats. We intentionally infused significantly lesser
amount than what had been reported in literature (18, 53, 55-57, 106). Highly sensitive
Mass –Spectrometry was used to analyze the labeled metabolites in the brain as well as
the plasma.
81
5.3 Methods
5.3.1 Animal model and diets
Young adult male Wistar rats were purchased from Charles River (Wilmington, MA,
USA), 40 days old and weighing ~150 grams. All procedures were performed in strict
accordance with the National Institutes of Health Guide for Care and were approved by
Institutional Animal Care and Use Committee of Case Western Reserve University. Body weights were measured upon arrival and on the experimental day (Table 1). Littermates were housed in the Case Western Reserve University Animal Resource Center with 12h-
12h light-dark cycle. All rats were allowed to acclimate for 1 week prior to initiating
dietary protocols. Standard rodent diet (STD) was fed to all rats during the acclimation
period (Labdiet Cincinnati, OH, USA, Prolab RMH3000 5ANE) ad libitum. One week
after their arrival, all rats were fasted overnight for 16 hours to deplete the liver glycogen
stores and initiate ketosis. Rats were then randomly assigned to two diets, STD or
Ketogenic diet (ketogenic, KG; Research Diet, New Brunswick, NJ, USA, D12369b) and
fed for three weeks ad libitum until experiment day.
5.3.2 Tracer Infusion and tissue collection
[U- 13C] glucose (99.8 %) was purchased from Sigma-Isotec (St. Louis, MO, USA,
Cat#389374) and solved in 0.9 % NaCl solution, with a concentration of 38.7 mM.
[U13C]-AcAc was derived from [U13C] ethyl-acetoacetate, also purchased from Sigma-
82
Aldrich. (St. Louis, MO, USA, Cat# CX1474), as previously described (118) and
concentrated to 137 mM (107). All other reagent chemicals were purchased from Sigma-
Aldrich. The animals were divided into four groups:
1) Standard Chow (STD) diet, infused with [U13-C] glucose at 0.5mmol/kg/hr 2) STD
diet, infused with [U13C]-acetoacetate at 0.5mmol/kg/hr 3) KG diet, infused with [U13-C]
glucose at 0.5mmol/kg/hr 4) KG diet, infused with [U-13C]-acetoacetate at 1mmol/kg/hr.
We had previously reported that the two groups with [U-13C]-Glucose infusion for 50
minutes both achieved ~10% plasma glucose M+6 enrichment, while the other two
groups with [U-13C] acetoacetate infusion for 50 minutes both achieved ~ 20% plasma
AcAc M+4 enrichment (28).
On the experimental day (3-4 weeks of diets) rats were morning fasted for 6 hours
prior to infusion of the stable isotopes. Rats were then anesthetized with vaporized 1.5% isoflurane balanced with pure oxygen delivered through a nose cone during the surgical
placement of arterial and venous catheters: right jugular catheter (MRE, 0.035 mm ID
and 0.084mm OD, Braintree Scientific Inc, Braintree, MA, USA) was advanced towards
the atrium for isotope infusion and the tail artery was cannulated with the same type of
catheter for blood sampling during the experiment period. [U13C]-tracers were constantly
infused via the jugular vein catheter (Harvard Apparatus syringe pump-11 Plus) for 50
min. Anesthesia level (1-2%), oxygen flow rate (0.05-0.2 liters per minute) and air flow
rate (0.5-0.6 liters per minute) were adjusted to achieve a consistent physiological status
across animals. Absence of hind-leg pinch reflex was monitored throughout the
83
experiment to ensure depth of anesthesia. Heart rate, respiratory rate (breaths/min),
plethysmography and arterial oxygen saturation (%) were monitored (via hind leg sensor) and recorded throughout the experiment using a pulse oximeter system (MouseOx, Starr life sciences, Oakmont, PA, USA) (Table 1). To maintain breath rates (~70 per minute) and normal blood gases throughout the 50 minutes infusion process, isoflurane was adjusted, as well as the oxygen percentage and flow rates. The breath and heart rates were also recorded throughout the experimental process and were used as indicators for physiological status. Arterial blood pH were measured at t=0, 45 min (ABL5 Radiometer,
Copenhagen, Denmark to ensure the absence of respiratory acidosis.
To verify that glucose or ketone bodies are at steady-state conditions, blood samples
(100–200 m L) were taken from the tail artery at time point 0 (pre-infusion), and at 15, 30,
40, 50 minutes, immediately centrifuged and the plasma frozen for GC-MS analysis of the [U- 13C] tracer enrichments and concentrations of glucose and AcAc . In addition to
the verification of the tracer enrichment steady state, plasma D-glucose and L-lactate
were also measured by YSI 2700 Biochemistry Analyzer (YSI Inc., Yellow Springs, OH,
USA) at 45 minutes post infusion. The total amount of blood drawn from each animal
during the infusion is less than 1.5ml.
At the end of infusion, the rats were decapitated; the brains were dissected immediately, frozen in liquid nitrogen, and stored at −80 °C. Cortical sections (~200 mg tissue) were then dissected under frozen conditions and homogenized using a specific organic solvent mixture designed for isolation of acyl-CoAs. Briefly, the homogenates were mixed with
84
CAC internal standards, homogenized with 3 ml of methanol and 3ml of methanol/water
1:1 containing 5% acetic acid using a polytron homogenizer, then centrifuged for 30
minutes at 3400 rpm.
5.3.3 Analytical method and theory of flux analysis
The brain sample pellets were extracted by a mixture of Acetonitrile and 2-Propanol
(3:1) and then centrifuged. Then the extracts were dried by nitrogen for 1-2 hours. The extracted pellets were derivatized by reagent TBDMCS (Regis Technologies, Inc. Morton
Grove, IL, USA) by incubating at 70 °C for 30 minutes, similar with previously
described (Kombu et al) . The derivatized products were measured under Gas-
Chromatography Mass Spectrometry (GC-MS). The maximum oven temperature was set
to 320 °C, the pressure was 14.82 psi, and the flow velocity was 45cm/sec. CAC
intermediates, including citrate (m/z 459), succinate (m/z 289), fumarate (m/z 287), and
malate (m/z 419) were ran under scan mode. Other intermediates and neurotransmitter,
including aspartate (m/z 418), glutamate (m/z 432), glutamine (m/z 431) and GABA (m/z
274) were also measured. Internal standards of BHB D6, 2-oxohydroxyglutarate (2-OHG,
m/z 433) D4, Succinate D4 and glutamate D4 were added to help determine the
concentrations. GABA and fumarate concentrations were cross-corrected by succinate D4
internal standards; malate and citrate concentrations were cross-corrected by 3-OHG D4
internal standards.
85
To determine the isotopic fluxes of the intermediates, Molar Percent Enrichment (MPE)
was determined by taking the ratio of isotopic abundance/sum of all isotopic abundances.
The MPEs for all measured metabolites were further corrected for natural abundance and
background by applying matrix method, as previously described (119) . Briefly, each
metabolite M0 were ran in a separate GC-MS experiment, and the fractions of the M+1 through the M+N (N being the highest detectable labeled m/z shift from M0) were recorded as a correction matrix. The raw data are then organized in a diagonal matrix is then multiplied by the inverse of the correction matrix to subtract the background MPE.
Because both the [U13C]-glucose and [U13C-AcAc] enters the CAC as two acetyl-coA,
we interpret the dominant of the labeling pattern of the intermediates to be from pyruvate
dehydrogenase (PDH) activities, as shown in M+2 (%). Malate M+3 (%) would be
directly from pyruvate carboxylase (PC) activities, derived from [U13C]-glucose infusion groups only. Other labeling patterns that come from pyruvate recycling are interpreted as non-dominant pathways and considered minor contributions to oxidative metabolism
(See Figure 2).
86
5.4 Results
5.4.1 Physiological parameters
The rats in all four study groups had very similar weight, age, as well as the anesthesia
levels during the study. The KG animals infused with [U13C]-AcAc were approximately
1 week older than the rest groups. The ketogenic rats infused with [U13C]-AcAc had showed an increased hematocrit from the other groups, but are still in a physiological range. All four groups of rats had the similar plasma glucose levels, and showed no signs of hypoglycemia or hyperglycemia during anesthesia and tracer infusion. Anesthesia level of 60-70 breaths per minutes (awake rats have > 100 breaths per minute) by isoflurane indicates low suppression of brain metabolism.
The STD diet animal groups had less than 0.75mM of total ketone body (BHB+AcAc) concentrations. The KG diet animal groups had 1.7-3.9mM of total ketone body concentrations. The plasma lactate levels were always higher in the STD diet groups comparing with the KG groups. In all 4 groups, the lactate levels were below 2mM, which indicates dominant aerobic respiration.
Animal groups with the same diet conditions but different infusion ([U13C]-glucose or
[U13C]-AcAc) did not show difference in physiological parameters except BHB/AcAc
redox ratios, which are all different in the four study groups. The group with STD diet
and [U13C]-AcAc infusion had the lowest BHB/AcAc redox, while the KG diet group
with [U13C]-glucose infusion had the highest BHB/AcAc redox. The [U13C]-glucose
87
tracer infusion resulted in higher BHB/AcAc in redoxes in both diet groups. Arguably, the redox state is the most sensitive physiological parameters, and this indicates the amount of the different tracers indeed had some impact, though not high, to the energy balance states.
5.4.2 Plasma and BHB tracer enrichments
As are presented in table 2, infusion of [U13C]-glucose tracers resulted in ~10% enrichment of brain glucose M+6 in both diet groups. In the plasma, the enrichment of glucose M+6 was also ~10% in both diet groups. This establishes the same glucose tracer pool availability to both STD and KG animals. Infusion of [U13C]-AcAc tracer resulted in
~95% of enrichment of brain AcAc M+4 in both dietary groups. In the plasma, the enrichment of AcAc M+4 was ~25% in both diet groups. Unlike glucose tracer, the brain in both diet groups showed higher tracer appearance than in the blood pool.
The major ketone body, BHB, showed different labeling patterns in the brain and in the plasma. In the plasma, BHB M+4 enrichment in the STD and KG infused with [U13C]- glucose were both below 4% and showed no difference. However, when [U13C]-AcAc is given to both groups and that yields similar AcAc M+4 percent of enrichment, the KG group showed higher BHB M+4 enrichment. In the cortical brain tissue, the lowest BHB
M+4 enrichment was observed in the KG rats infused with the [U13C]- glucose. The highest BHB M+4 enrichment was observed in the STD rats infused with [U13C]-AcAc.
88
It is important to note that the current GC-MS method does not allow separation of
M+1, M+2 and M+3 signals from AcAc and BHB labels. This is because the TBDMCS method cleaves the four carbons chains to two double-carbon chains. As a result, we simplified the interpretations of the actual M+2 of the derivatized ketone bodies to M+4, as the dominant labeled ketone bodies.
5.4.3 First turn of CAC metabolites fluxes
In this case, we only consider the first turn of CAC metabolites and neurotransmitter
M+2 fluxes only, without the complex label exchanges from pyruvate recycling and the second turn of CAC. M+2 was used as the primary indicator of oxidative metabolism in the CAC, because both the U13C-glucose and U13C-AcAc can only label two of the acetyl-coA carbons in the first turn.
When U13C-glucose was infused, we detected that 1) Acetyl coA M+2 had decreased by
~50%. 2) M+2 fluxes from succinate had decreased by 45%. Fumarate, citrate and malate are unchanged. 3) Neurotransmitter and glutamine. Aspartate, glutamate, glutamine and
GABA all decreased ~35%. No change of citrate flux had been observed. We had also detected malate M+3 in the U13C-glucose infused brains, values are 0.75±0.23% for STD and 0.51±0.12%, with no statistical significance of difference (P=0.08, data not shown in
89
figures). Finally, 2-oxoglutarate, a convertible form of α-ketoglutarate, produced undetectable amount of M+2. (Figure 3A)
When [U13C]-AcAc was infused, we detected that 1) Acetyl coA M+2 had increased to
~260%. 2) M+2 fluxes from citrate, succinate, malate, all had increased; the increment
were approximately 11, 2, 9 folds. 3) Neurotransmitters, aspartate, glutamate M+2 fluxes
had increased by approximately 7 and 10 folds. 4) M+2 fluxes towards fumarate and
GABA, which showed undetectable amount in STD rat brain, showed observable and
significant amount in KG rats. In short, the KG rat showed high increase of contribution
of ketone body carbons towards all measured CAC intermediates, as well as
neurotransmitters.
5.4.4 Pyruvate recycling and 2nd turns of CAC
In this case, we only consider the metabolites M+1. M+1 labeling patterns come from
either the second turn of CAC (see figure 1D) or the activities of pyruvate recycling from
malate (figure 5A and 5B). For GABA and succinate, the M+1 account for all pyruvate
recycling activities from malate plus all the second turn of CAC. For citrate, the M+1
only comes from pyruvate recycling, not the second turn of CAC (Figure 5). For other
measured metabolites, the pyruvate recycling from malate and second turn of CAC
together contribute to the majority of M+1, but some small portion of their M+2 may also
be from the pyruvate recycling from malate and the second turn of CAC. Interestingly,
90
except for U13C-glucose infusion groups, where we detected malate M+3 as mentioned, no M+3, M+4 or M+5 were observed in any metabolites in any study groups. This essentially rules out the labeled oxaloacetate combining with labeled acetyl coA scenario since no citrate M+3 could be detected.
For [U13C]- glucose infused rats, KG group showed significantly reduced M+ 1 flux for
citrate (~50%) as well as malate (~30%). M+ 1 flux from other CAC intermediates did
not show significant differences. In addition, glutamine M+1 decreased ~50%. When
citrate M+1 (Figure 3) were used to compare with their respective M+2 (figure 2), which
reflect the pyruvate recycling versus combined PC and PDH activities, the M+1/M+2
ratios are 43% for STD rat and 21% for KG brains. In addition, glutamate M+1/M+2
ratios dropped from 54% for the STD rat to 41% in KG rats, indicating recycling of
glucose that generates glutamate had decreased. For all other metabolites, the M+1/M+2
ratio were not significant different between STD and KG animals. No aspartate M+1 had
been detected. 2-Oxoglutarate M+1 remained unchanged in both diet conditions.
For [U13C]-AcAc infused rats, KG group showed increased M+1 fluxes for citrate (~2
folds), succinate (~2.5 folds), fumarate (~3 folds), malate(~2.5 folds), glutamate(~2
folds), glutamine(2 folds), and GABA(~7 folds). For citrate, the M+1 were lower than
M+2 in STD rat brains, indicating that the exogenous ketone bodies are highly recycled.
The M+1/M+2 ratios for citrate decreased from 3.9 for STD rats to 0.7 for KG rats,
suggesting that ketone bodies are significantly used in oxidative metabolism rather than
being recycled. Similar observations were found in fumarate M+1/M+2 ratios
91
(M+1=0.8%, M+2 not detected in STD, M+1/M+2= 1.6 for KG) , malate M+1/M+2 ratios (M+1/M+2= 4.8 for STD and 1.4 for KG), glutamate M+1/M+2 ratios
(M+1/M+2=4.7 for STD, 0.9 for KG), glutamine M+1/M+2 ratios (M+1/M+2=1.74 for
STD, 0.6 for KG), GABA M+1/M+2 ratios (M+1=0.3% for STD, M+2 no detected in
STD. M+1/M+2=0.8 for KG). The data suggest that ketosis actively shunts carbons from ketone bodies to all neurotransmitters and significantly decreased the amount of recycling.
Succinate did not show any significant change of M+1/M+2 ratios. Similar with [U13C]- glucose infusion studies, no aspartate M+1 had been detected. 2-Oxohydroxyglutarate
M+1 remained unchanged in both diet conditions.
5.4.5 Metabolite concentrations
The [U13C]-glucose infusion studies showed that the animals had increased glutamate
(6.6μmol/g in STD, 10.7μmol/g in KG), glutamine (4.5μmol/g in STD, 6.6μmol/g in KG), malate(0.25μmol/g in STD, 0.35μmol/g in KG), citrate(0.17μmol/g in STD, 0.28μmol/g in KG), as well as the expected BHB (0.02μmol/g in STD, 0.19μmol/g in KG) and AcAc
(5nmol/g in STD, 28nmol/g in KG) in the cortical brains in ketosis. The data suggest that glucose augment glutamate synthesis during ketosis, and increases glucose oxidative metabolism. Interestingly, succinate, the key intermediate for oxidation and electron transport chain, did not show significant change of concentrations. GABA, aspartate, fumarate concentrations did not change, either (Figure 4A, 4B).
92
The [U13C]-AcAc infusion studies showed that the animals had decreased glutamate
(6.9μmol/g in STD, 3.79μmol/g in KG) and glutamine (4.7μmol/g in STD, 2.7μmol/g in
KG) in the cortical brains in ketosis. All measured CAC intermediates, as well as GABA
and aspartate, did not show changes in concentrations. The BHB (0.02μmol/g in STD,
0.18μmol/g in KG) and AcAc (7nmol/g in STD, 28nmol/g in KG) concentration in each
diet group was similar with the respective groups in [U13C]-glucose infusion studies.
Those data confer that ketone bodies are able to reduce the glutamate and glutamine pool in ketosis, while maintaining the pools in the CAC intermediates (Figure 5.4C,5.4D).
93
5.5 Discussion
5.5.1 Changes of oxidative metabolism in ketosis
In this study, we have first demonstrated that in the rats with chronic diet-induced ketosis, glucose contributions to cortical citric acid cycle flux were spared by the ketone bodies, in consistent with our previous report with ketone bodies’ sparing effect on glucose phosphorylation rates (16). Unlike the glucose phosphorylation, the oxidative metabolism involves further downstream biochemistry (as the carbon contributions to acetyl coA generation) at the entrance of CAC, as well as the turning of CAC and generation of neurotransmitters, which may or may not theoretically generate consistent results. Our study had proved that the ketone bodies’ ability to suppress glucose metabolism is not limited at the first step of phosphorylation.
Secondly, the carbon shunting switch from glucose to ketone bodies towards succinate may suggest more succinate participation in the respiration and electron transport chain
(14) . We had previously shown that rats infused with BHB had increased succinate content in the brain, and it appeared that the succinate concentration increase may be accountable for stabilizing HIF, which may explain the neuroprotection of ketosis from angiogenesis. Our new data suggests that the ketosis does not increase the unlabeled succinate content, but rather worked to increase the flux from ketone bodies to generate succinate while reducing the glucose contribution to succinate. To this sense, ketotic subjects would have increased brain succinate if either extra glucose or ketone bodies are
94
given; however, ketone bodies are more effective in generating succinate in this state
(Figure 4).
Furthermore, although no statistical significance was found in fumarate and malate in
the brains infused with [U13C]-glucose, the data trends to suggest that the glucose fluxes in these two intermediates also decrease in ketosis. Citrate flux, which serves as converging point neurotransmitters (glutamate, aspartate, GABA) as well as CAC self-
turning, appeared to be unchanged for sources from glucose fuels, but significantly
increased for ketone body fuels. In diet-induced ketotic rat brains where no tracer is given,
we can thus expect a net increase of citrate appearance comparing with the normal
unketotic conditions. Meanwhile, the total carbon supply to the CAC intermediates
(except for malate) may be maintained in ketosis, as are shown in figure 4.
The sparing of glucose oxidation from ketosis in the CAC intermediates is an
important step for verification of our hypothesis that total energy demand (glucose +
ketone bodies) stays constant during diet-induced ketosis. The generation of ATP is fundamentally dependent on the functionalities of the electron transport chain activities, as well as the citric acid cycle intermediate balances. Although it is not certain whether brain energy balance is fundamentally a carbon molar balance from the total energy supply, our data suggests that cerebral metabolic rate (CMR) total may remain relatively constant, if the carbon loss in respiration and pyruvate-lactate interconventions are relatively small.
95
5.5.2 Shunts to neurotransmitters
A metabolic fuel “switch” towards neurotransmitters is also observed in ketosis. The
drastic reduction of glucose contributions to neurotransmitters and glutamine M+2 was in
consistent with our previous report of CMRglc reduction (phosphorylation rate) in diet-
induced ketotic rats, where we showed approximately 9% decrease of CMRglc for each
1mM of total ketone body increaseand a maximum of ~35% of CMRglc was reported in
rats with plasma total ketone bodies ~4mM (16),. In this study, the glutamate, glutamine
and GABA from glucose tracer are both reduced by ~35% in rats with ketosis, although
the total plasma ketone bodies were only 2.5mM in ketosis, which corresponds to ~25%
decrease in phosphorylation rate. The artifact from changes and uncoupling of
metabolism from blood flow is not very likely, because the infusion amount set in this
study is ~1/30 of that used by Hasselbach et al 1996 (56), where 25% increase of CBF
was reported. Such difference in reductions from phosphorylation (prediction, -25%) and neurotransmitter (measured, -35%) generations may be from less reduction of carbons shuntings of glucose source in the CAC, where citrate was unchanged. A likable explanation would be a less responsive decrease of recycling from glucose in the neurons
(120) .
Our studies showed that ketone bodies, which the brain normally rarely uses to generate GABA, can n be utilized to generate GABA in ketosis (Fig 3). As previously
96
shown in cultured neurons (58) , ketone bodies are effectively shunted towards GABA.
The current study suggests that the ketone bodies are very potent precursors for GABA
synthesis when pyruvate recycling partitioning part is fulfilled (see next section). Similar
phenomenon (absence in STD diet but presence in KG) was found in fumarate M+2,
which reflect backfluxed malate M+2 (see next section). We speculate that the backflux
from malate to fumarate increases in ketosis. Future work would be needed (121) .
Finally, it appears that the neurotransmitter concentrations in the brains are all highly responsive to the tracer infusion, as observed by the clear glutamate and glutamine concentration changes in all study groups (Fig 4). However, GABA and aspartate are less responsive to infusion. It could well be a sensitivity issue. Indeed, many literatures on compartmentation in the neuron-astroglial interactions in normal and ketotic brains had focused on the GLU-GLN cycling and deeming its key contribution to oxidative metabolism (55, 57, 116, 122). While recognizing the important roles of the cycling from
GLU-GLN, we deem that GABA and aspartate, especially GABA, deserves more
scrutiny in explaining the biochemical mechanisms underlying neuroprotection from
ketosis (58, 115) . Whether the GABA pool changes in ketotic rat brain in vivo in tracer
conditions deserves more investigation.
5.5.3 Alterations of pyruvate recycling
Pyruvate recycling phenomena are present in the brain, in which the carbons from
malate are taken back to pyruvate and re-enters the CAC from PC or PDH. This
97
seemingly futile cycle is important for complete oxidation of carbon-fuels. Pyruvate
recycling is an alternative explanation that accounts for the substrate partitioning, in addition to the neuronal-glial cyclings of glu-gln. NMR techniques that can effectively detect different labeling patterns of C-4 Glutamate and glutamine (117, 123) , suggesting
that a different partition, or pathways, of the fuels in oxidative metabolism. Ketones
bodies are shown to be recycled in the brain (18, 58, 117), particularly in astrocytes (18,
112, 124, 125) , when studied by a convenient acetate tracers. Whether the recycling occurs in neurons in vivo is under investigation (58, 120, 126, 127) . On the other hand, one can also assess the PC/PDH contribution ratios to glutamate, glutamine and other detectable amino acids by NMR (18, 117, 128). However, our study tool, the GC-MS
cannot allow positional tracing, thus cannot distinguish signals from the different
positioning of M+1 or M+2 s from PC and PDH. Considering these two aspects, a better
interpretation of the labeled metabolites would be to directly distinguish the M+2 and
M+1. M+2 were naturally the dominant labeling pattern from [U13C]-tracers, while M+1 can only occur after the first turn of CAC, which includes pyruvate recycling.
Most of our measured metabolites M+1 are theoretically from either pyruvate recycling or the second turn of the CAC (fig 5). Because citrate M+3 was never observed in any study groups, it is reasonable to assume that the recombination of labeled oxaloacetate and labeled acetyl-coA was negligible. It is therefore reasonable to assume that pyruvate recycling would be able to explain the majority labeling patterns of M+1 we observed.
98
First, in brains of rats infused with [U13C]-glucose, we showed that M+1 was no more than that of M+2 in all measured CAC intermediates; in brains of rats infused with U13C-
AcAc, we showed that M+1 was no less than that of M+2 in all measured CAC
intermediates. We interpret this by assuming two partitioning pathways for ketone and
glucose to enter the CAC and neurotransmitters. If pyruvate recycling step is always
preferred and prioritizes in the brain when exogenous ketones were present, the distinct
labeling patterns of GABA and fumarate can clearly be explained. On the other hand, for
exogenous glucose, the brain prioritizes it to oxidation instead of recycling in ketosis.
This idea shares the same principles with the non-stoichimtric partitioning of glutamate-
glutamine (112) and the literature data where ketosis was reported to increase the
pyruvate recycling (Melo et al, Ostad et al) , although no clear distinctions from the
carbon source for recycling was made. Our data suggest that ketosis decreases the
carbons from pyruvate-recycled glucose to the neurotransmitters, while promotes more
ketone carbons to be recycled, generate glutamate, glutamine and GABA. Our
interpretation can also explain Yudkoff’s theory (19), where ketosis reserves a pool of
carbons at glutamine and releases upon energy needs. Pyruvate recycling may serve as a
potential important reservoir during ketosis.
Secondly, the aspartate M+1 was never observed in our study, indicating that pyruvate
recycling does not come with a commensurate, though futile cycle of pyruvate
carboxylation. This is further verified by the absence of citrate M+3.
99
Finally, 2-Oxohydroxyglutarate (OHG) M+1 was present in all groups; though no
statistical significance was seem in any group-group comparison. The α-ketogluorate
M+1 thus will probably present, although we cannot detect it by current GC-MS derivatization method. If it were present, then it should serve the source for glutamate and glutamine, as well as GABA (fig 5). Considering the neuronal-glial compartmentation of neuron-glial cells (116, 117, 122, 123, 128) , if M+1 of GABA is solely synthesized in neurons, our data confers that the reserved carbons to synthesize the inhibitory neurotransmitters are present for ketone bodies anytime in ketosis. Unfortunately, we did not acquire multi-time point data for the 2-OHG and GABA M+1, so that some compartmental model could be developed to estimate the flux from α-keotglutarate to the
GABA synthesis. Future work on this would shield light to the carbon reserves impact towards neuroprotection.
100
5.6 Acknowledgment
We would like to thank Donald Harris for assisting with some tissue processing work.
101
5.7 Figures and tables
Table 5.1 Physiological parameters of the rats.
STD/U13C- KG/U13C- STD/U13C- KG/U13C- Glucose(n=4) Glucose(n=6) AcAc(n=7) AcAc(n=3)
Age 81 ± 12 69 ± 7 68 ± 6 79 ± 1 ǂ
Weight (g) 363 ± 52 340 ± 32 340 ± 27 385 ± 17ǂ
pH 7.35 ± 0.02 7.33 ± 0.04 7.38 ± 0.07 7.39 ± 0.02
Physiological Parameters
Breath Rate (/min) 62 ± 3 67 ± 5 68 ± 4 70 ± 1
Hematocrit (%) 45 ± 1 44 ± 2 42 ± 2 48 ± 2ǂ
Plasma Parameters
BHB (mM) 0.29 ± 0.17 2.28 ± 0.54* 0.25 ± 0.10 2.24 ± 0.81 ǂ
AcAc (mM) 0.17 ± 0.06 0.43 ± 0.07* 0.26 ± 0.12 0.67 ± 0.29ǂ
BHB+AcAc (mM) 0.45 ± 0.23 2.53 ± 0.35* 0.51 ± 0.22 2.91 ± 1.10ǂ
BHB/AcAc ratio 1.64 ± 0.34 4.97 ± 0.74* 1.03 ± 0.19 3.46 ± 0.32ǂ
L-Lactate (mM) 1.15 ± 0.31 0.68 ± 0.12* 1.22 ± 0.22 0.77 ± 0.20ǂ
D-Glucose (mM) 10.1 ± 0.8 10.8 ± 1.3 9.3 ± 1.3 10.4 ± 0.9
102
Rats were divided into four study groups. STD: standard chow diet. KG: ketogenic diet.
Rats were constantly infused with either [U13C]-glucose or [U13C] - acetoacetate (AcAc) for 50 minutes. All data presented are Mean ± SD. * P<0.05 in student 2-t test, when
comparing the KG rats with STD rats (both infused with [U13C]-glucose). ǂ: P<0.05 in
student 2-t test, when comparing the KG rats with STD rats (both infused with [U13C]-
AcAc). †: P<0.05 in student 2-t test, when comparing the KG rat with the STD rat (both
infused with the same [U13C] tracer).
103
Table 5.2 Plasma and brain enrichments of glucose M+6 and ketone bodies M+4.
STD/U13C- KG/U13C- STD/U13C- KG/U13C-
Glucose(n=4) Glucose(n=6) AcAc(n=7) AcAc(n=3)
Brain Glucose M6 % 10.6 ± 1.1 10.8 ± 1.2 - -
Brain AcAc M4 % 97.7 ± 0.9 96.7 ± 2.4 93.9 ± 2.9 95.3 ± 0.4
Brain BHB M4 % 19.8 ± 2.9 0.5 ± 0.3* 50.7 ± 3.6 15.1 ± 3.2ǂ
Plasma Glucose M6 % 9.1 ± 0.6 10.1 ± 1.3 - -
Plasma AcAc M4% 5.2 ± 1.5 3.4 ± 0.7* 26.3 ± 4.2 22.3 ± 3.7
plasma BHB M4 % 3.9 ± 1.0 3.6 ± 0.2 11.5 ± 1.4 13.9 ± 1.1ǂ
Tracer Infusion Rate 0.5 0.5 0.5 1 (mmol/kg/hr)
*: P<0.05 in student 2-t test, when comparing the ketogenic (KG) rats with standard diet
(STD) (both infused with [U13C]-glucose). All data presented are Mean ± SD. ǂ: P<0.05 in student 2-t test, when comparing the KG rats with STD rats (both infused with [U13C]-
Acetoacetate). “-”: measurement was not performed. AcAc: acetoacetate. BHB: β- hydroxybutyrate.
104
105
Figure 5.1 Simplified schematics of metabolite labeling patterns with [U13C]-Glucose or [U13C]-Acetoacetate (AcAc) infusion.
All schematics do not account for pyruvate recycling and glutamine-glutamate cycling between astroglial cells and neurons. Backfluxes are indicated by by-directional half arrows. All positional carbons are noted from left to right (C1-C5). Labeled C13 are presented by filled circles. Panel A: Brain metabolites labeling pattern from [U13C]- glucose , only considering pyruvate dehydrogenase (PDH) activities and the first turn of
Citric Acid Cycle (CAC) from citrate to oxaloacetate. Panel B: [U13C]-glucose tracer or
[U13C]-AcAc infusion, only considering PDH activities and the second turn of CAC.
Panel C: [U13C]-glucose tracer, only considering pyruvate carboxylase (PC) activities and the second turn of CAC, from oxaloacetate to malate. Panel D: [U13C]-AcAc tracer, considering both PDH and PC activities and the first turn of the citric acid cycle. The second turn of CAC will be the same as shown in panel C. ASP: aspartate; AAT, aspartate aminotransferase; Alpha-KG: α-ketoglutarate; BHB, β-hydroxybutyrate; GAD:
Glutamate acid decarboxylase; GLU: glutamate; GLN: glutamine.
106
107
Figure 5.2 Brain metabolite M2 enrichment from [U13C]-glucose studies (Panel A) and
[U13C]-Acetoacetate studies (Panel B).
All data are presented as Mean ± SD. *: P<0.05 in student 2-t test, when comparing metabolites M2 enrichment from rats fed with ketogenic (KG) vs. standard (STD) diets.
2OHG: 2-oxoglutarate. ASP: aspartate.
108
109
Figure 5.3 Brain metabolite M1 enrichment from [U13C]-glucose studies (Panel A) and
[U13C]-acetoacetate studies (Panel B).
All data are presented as Mean ± SD. *: P<0.05 in student 2-t test, when comparing metabolites M1 enrichment from rats fed with ketogenic (KG) vs. standard (STD) diets.
2OHG: 2-oxohydroxyglutarate. ASP: aspartate.
110
Figure 5.4 Brain metabolite concentrations in rats infused with [U13C]-glucose (Panel A
and B) or [U13C]- acetoacetate (Panel C and D).
Data bar graphs are presented as mean ± SD. *P<0.05 in student 2-t test, when comparing metabolites concentrations between standard diet (STD) vs. ketogenic diet
(KG) rat brains. AcAc: Acetoacetate. ASP: aspartate. BHB: β-hydroxybutyrate.
111
Figure 5.5 Theoretical schemes for M+1 metabolites generation.
Filled circles indicate 13C labeling. M+1 metabolites that come from malate M+2 after
the first turn of citric acid cycle (CAC) are indicated in square circles. Panel A shows the
M+1 metabolites from the combination of unlabeled oxaloacetate and acetyl-coA M+1.
Panel B shows the M+1 metabolites from the combination of labeled oxaloacetate and unlabeled acetyl-coA. Pyruvate recycling was considered, but not distinguished between neurons and astroglial compartments. Backfluxes are indicated by by-directional arrows.
Malate M+3 from [U13C]-glucose infusion scenario are ignored due to its low enrichment
(<10%) relative to M+2. All carbon positions are noted from left to right (C1-C5). ASP:
aspartate; AAT, aspartate aminotransferase; Alpha-KG: α-ketoglutarate; BHB, β- hydroxybutyrate; Fum: fumarate; GAD: Glutamate acid decarboxylase; GLU: glutamate;
GLN: glutamine; PC: pyruvate carboxylase; PDH: pyruvate dehydrogenase.
112
Figure 5.6 Chromatogram of the Citric Acid Cycle intermediates and neurotransmitters
113
Chapter 6 Conclusions & Future works
6.1 Introduction
In the previous chapters, we had presented that diet-induced ketosis can i) spare glucose
phosphorylation in the brain (chapter 3) ii) decreases the acetyl-coA synthesis from
glucose while increases acetyl-coA synthesis from ketone bodies (chapter 4) iii) switch the fuel source for oxidative metabolism and neurotransmitters from glucose to ketone bodies (chapter 5). All the evidence seemed to imply that brain energy balances are essentially the fuel demand balance: the total energy demand of glucose and ketone bodies (CMRo2 that come from both CMRglc and CMRket), stays constant. Our future
goal, investigation of ketone bodies’ neuroprotective mechanism, lies on validation of
this hypothesis.
Future works should be done with these guidelines:
On energy metabolism:
1) Studies of the energy fuel utilization and oxidations in humans and animals vary
with experimental conditions. It is important to perform meta-analysis of the data (see
figure 3.2), apply appropriate normalization to eliminate inconsistencies of the absolute
values due to anesthesia, physiological state and species differences. It is also known that
the brain energy metabolism has ~20% of it as house-keeping portion during isoelectric
state (98) , estimated when overdose pentobarbital was applied to animals (no EEG
114
signal were detected). Our data can only be compared with the non-isoelectric or awake subjects’ data.
2) Different methods of ketosis induction play key roles in the stability and effect of ketosis (See section 2.4 and 5.1).
The focus of this dissertation is on the explanations of the diet-induced ketosis, with known stable up-regulation of MCT transporters (40) , and assumed no change of CBF.
The level of the ketosis we observed was comparatively higher than many literature values, as reported by ketosis induced by fasting or 2-3 days feeding of ketogenic diet
(see chapter 3 table and figures). It is also higher comparing with previously reported diet-induced ketosis for 3-4 weeks but with calorie restrictions (51, 52), as well as shorter-term diet-induced ketosis in mice (18, 53). The only studies that yield higher mean level of blood ketones were reported are either from infusion of ketones + starvation for 1.5 days (57) and chronic fasting (2) cases. It is important to understand that levels of ketosis, as indicated by both the redox of the BHB/AcAc and total ketone body concentrations, are keys to compare the studies by categories.
3) Age differences and the implications to metabolic energy balances. The current studies of the rats under ketosis were 3 months old adults. Considering the fact the experimental rat life span (2-2.5 years), the animals we used are healthy young adults. In the aged rats, the ketone and glucose metabolism were significantly different. Hence, the translation of our studies to older rats or human subjects requires caution.
115
Ketone bodies were to more extent used in developing rat and human brains (32, 43).
This had been supported by several experimental reports. In humans, the ketogenic diet, as a regiment to contain epilepsy occurrences, was more efficient when applied to children than adults (129); in suckling rats, the brain A-V differences of the ketone bodies were 3-4 times greater than young adults, suggesting higher ketone body uptake.
Furthermore, in animals with brain injuries (contusion) and ketogenic diet applied as a treatment, young rats with ~1 month old exhibited more reduction of contusion volumes compared with ~2.5-months old adults (13). All these evidence implies that the ketone bodies utilization rates and neuroprotective roles were weakened as subject ages.
Lastly, the (85) the aging brain volume (Cerebral Blood Volume) has been reported to decrease. There are controversies as to whether the CMRglc decreases in aged human and animals (100, 130), with more recent publications in 2012 (85) pointing out that the global glucose utilization may decrease (CMRglc multiplied by volume). The lesson from the controversies of the energy balances with aging is that the CMR estimations are very dependent on the volume and flow of the system. Age-related alterations of the shift of energy demand (development, or revolution related) (32, 60), as well as the alterations of vasculature volumes cannot be ignored.
4) Clarifications of neuronal and glial metabolism from ketone bodies.
Our studies on the oxidative metabolism from ketone and glucose tracers were performed by GC-MS method. Comparing with the NMR method, GC-MS had
116
advantages on 1) higher sensitivity, able to measure brain metabolites with 10-100nmol/g
tissue, whereas NMR method usually can only detect μmol/g concentrations of
metabolites in brain. 2) Metabolites with similar structures but different molecular weight
can be readily separated, even in if the concentrations are low. For example, glutamate
(GLU) and glutamine (GLN) signals are clearly separated in GC-MS chromatogram by
the TBDMCS derivatization method (118, 131) , whereas NMR method can only
distinguish the GLU and GLN peak with C-4 with high sensitivity. Other positional GLU and GLN signals were often overlapped. Separations of the signals were done offline with additional assumptions (116, 132). NMR method, had the advantages on 1)
Positional labeling identification. For example, [U-13C]-glucose infusion can generate
13 13 [1,2- C2]GABA from PDH activities and [3,4- C2]GABA from PC activities (133). In
the GC-MS chromatogram, both signals would be GABA M+2 and not identifiable. The
NMR spectrum can separate those positional carbon labeling patterns. 2) The acquisition
of the signals can be done in vivo instead of ex vivo. Dedicated NMR machine with
dedicated animal or human coil can be used to obtain metabolite time activity curve,
which can be used to generate ordinary differential equations from isotopic mass balances
(116).
Considering the trade-offs of using NMR and mass spectrometry, we now propose
working in the future with NMR to study the neuronal-glial interactions in ketosis. This will be presented in section 6.3.
On the measurement and estimation techniques,
117
1) Validations of constant CBF or changed CBF values across study groups.
Tracer infusion may or may not perturb the brain physiology, in a dose dependent
manner; it is also depending on the baseline state of the investigation. (Implications of
infusions that may perturb the systems were discussed in section 2.4.1, 2.4.3 and 5.2). As
were discussed, the CMR of any metabolite that mainly gets utilize through blood flow
(CBF) and reactions can be either measured by Kety-Schmidt method, or compartmental
modeling and tracer infusion. The universal assumptions were that diffusions were
negligible, and hence either the uptake or reaction rate would be representative of
metabolic rate. However, careful examination of the 2-Tissue compartmental model and
other multiple tissue compartmental models (84) implies that the assumptions for reaction
rates were always dependent on known CBF that is not different than when determined in
a separate experiment in literature. High exogenous stable tracers may shift the CBF, and
lead to suspicious conclusions. For example, many NMR rat studies on the glutamate- glutamine cycling were based on more than 3mmol/kg/hr infusion of the ketone or glucose tracers (18, 39, 53, 56, 103, 117, 123, 134) . Assuming a 300g rat has ~7% of the body weight as blood with normglycemia (glucose) at 10mM and mild ketosis at 2mM, it would only have ~0.2mmol of glucose and 0.04mmol of ketone bodies in its body. The loading of the exogenous glutamate was interpreted (30, 112) as “exogenous glutamate regulates endogenous metabolism”. While reasonable, the changes of the physiological system may well undermine the conclusions.
118
2) Validations of the lumped constant (LC) in the FDG-PET experiments. This topic is discussed in section 6.2. Briefly, the FDG-PET and 2-DG methods both require compartmental modeling. The lumped constant is a practical conversion factor that relates tracer (FDG or DG) phosphorylation rate to that of real glucose phosphorylation rate. This number has been reported to shift significantly with age (100) , insulin infusion
(135), and slightly with hyperglycemia (29, 136). One must carefully examine the LC to validate that what we used in chapter 3.2 , LC=0.71, is held true (105) in ketosis.
119
6.2 Estimation of the Lumped Constant in ketotic rat brains
6.2.1 Objective and specific aims
To investigate the Lumped Constant (LC) values of 2-[18]Fluoro-2-Deoxy-Glucose (FDG) in the young adult wistar rat brain, during fast-induced and diet-induced ketosis, using 1) estimation of brain glucose phosphorylation rate studies by FDG-PET 2) estimation of brain glucose uptake rate with 133Xenon Infusion and measurement of the cerebral blood
flow (CBF). The values of LC obtained at different states of ketosis and different
methods will offer us the validation of the Cerebral Metabolic Rate of Glucose (CMRglc)
at steady state measurement by FDG-PET method.
We have recently reported that the diet-induced ketosis reduces the CMRglc in a rat
model, using 2-[18] Fluoro-2-Deoxy-Glucose (FDG) and Positron Emission Tomography
(PET) technique (chapter 3). The FDG-PET method requires using a correction factor,
the Lumped Constant (LC), to estimate the CMRglc. In that study, we assumed a constant
LC in the plasma BHB + AcAc levels 0-6mM in the diet-induced ketotic rats. However,
insofar we do not have the proof that the LC is real constant across this range and in other
ketosis models. Any variations of the LC may change the CMRglc estimation significantly and undermine our interpretations. As of 2013, the LC had never been reported in diet- induced ketotic rats. To validate our previous CMRglc estimation in diet-induced ketotic
rats, we propose to investigate the LC in the diet-induced ketosis. We also propose to
compare LC values in different models of ketosis. The results of the LC values obtained
120
will allow future researchers to study the CMRglc in rats with FDG-PET technique, with better and more confident understanding of the ketotic process and energy balance of glucose and ketones in ketosis.
6.2.2 .Background of the lumped constants
To obtain CMRglc by FDG-PET, one would need to assume an appropriate value of
CMRFDG to CMRglc ratio, which requires a Lumped Constant (LC; CMRglc=CMRFDG/LC.
See appendix I for derivations) that involves FDG and glucose Michaelis-Menten
constants (26, 27). The LC value plays vital role in estimating the CMRglc and any
change would undermine the data interpretation. We currently assumed LC to be constant
in rats with plasma total ketone bodies ranging 0-6mM (Chapter 3 article), and from that
we reported the CMRglc decreases during diet-induced ketosis. However, due to the lack
of literature data on LC in diet-induced ketotic rats, we will need to obtain the data by
ourselves. If we find that LC in ketogenic diet group really did not change compare with
the LC in rats fed with standard diet (STD), then our conclusion would be that CMRglc
indeed decreases during diet-induced ketosis; if LC increases, then our previous CMRglc
data would be an overestimation, i.e, diet-induced ketosis reduce the CMRglc more; lastly,
if LC decreases, then our previous CMRglc overestimates, and thus our thought that
CMRglc decreases in diet-induced ketosis may not be valid.
121
Due to the different physiological and pathological conditions, as well as the method to
estimate the LC, and the species, the LC values reported in literature have been very
different. Some reported increase of LC by fasting, insulin infusion or ketone infusions
while others reported decrease of LC in fasting (15, 17, 56, 103, 135, 136).
It is worthwhile to note three important phenomena in investigating the LC in ketosis,
with FDG-PET or DG-Autoradiography methods. (i) Both the DG and FDG trap in the
brain, due to the 2- position deoxy group on the carbon chains. However, the LC values are different since DG and FDG have different pharmacokinetics (135, 137). It had been
shown that the LC for DG and FDG are held a proportionality relationship, so
investigating one may lead to understanding of another (93). (ii) Fasting or starvation
induced ketosis usually accompanies hypoglycemia (low blood glucose levels than
normal), while diet-induced ketosis does not induce hypoglycemia (high blood glucose
levels than normal) (16, 51). Ketosis induced by infusion may not cause hypoglycemia
(56, 59). In addition, it is unknown whether a classic study of LC(93) had overlooked
possible complications from hypoglycemia by infusion insulin(138). (iii) Fasting and
diet-induced ketosis do not change the CBF(15, 17, 62), however infusion may increase
the CBF(56, 59).
6.2.3 Technical and scientific Challenges The possible challenges of the studies are 1)
Maintaining the steady physiological states for the animals. The study lasts more than
105 minutes, in which the rat is anesthetized and several injections made. 2) Brain
122
surgery for the venous blood (confluence sinus) may be challenging. 3) Parameter estimations of the rate constants may or may not be identifiable for all studies. Different methods of estimation may be needed (29, 81-84).
123
6.3 Optimizing the stable isotope studies on oxidative metabolism in
ketosis
Our previous work (chapter 5) on the oxidative metabolism was performed using stable
isotopes and Mass Spectrometry. As discussed, the disadvantages of the GC-MS and LC-
MS comparing with NMR methods are 1) lack of distinction for positional carbon labeling patterns 2) cannot measure in vivo brain metabolites. Due to these limitations, we were unable to address two important issues underlying oxidative metabolism in brain during ketosis.
The expanded compartmental model would be similar with what had presented by
McKenna’s review (Figure 6.2). This scheme is favored due to three reasons. First, scheme includes the key glutamate-glutamine cycling pattern from neuron and astrocytes.
Often, studies with C1 or C6 labeled glucose tracer, or C2 or C4 labeled ketone tracers were used and glutamate C-4 signals (directly from 1st turn of CAC) were compared with
C3 (from CAC exchange and second turns) signals (31, 116, 122, 132) .
Second, this scheme includes important pyruvate recycling from both the astrocytes and
neurons. We deem that astrocytes may present a large pool of glutamine reserve(19, 58),
and astrocytes were shown to present with significant pyruvate recycling activities (18,
117, 120), which matches with what we reported in chapter 5 . Although it is not clear whether the neurons have the recycling in vivo (58, 120, 126), it is worthwhile to assume
that it did exist in neurons.
124
Finally, the GABA synthesis from glutamate is largely neuronal. The astrocytes provide
extra reserves of the carbons from glutamine (124) . This is important because our
reported findings (chapter 5.4) regarding the absence of GABA M+2 from ketone bodies would need this re-examination. Whether one can really distinguish GABAergic versus
glutamatergic labeling patterns will need more solid verifications (115).
125
6.4 Conclusions
In this dissertation, we have examined the effects that diet-induced ketosis i) suppresses the glucose phosphorylation, ii) switches the acetyl-coA synthesis from glucose to ketone bodies, iii) spares glucose shunts to citric acid cycle intermediates, and iv) spares glucose shunts to glutamate and GABA generations. All those evidences imply that diet-induced ketosis readily changes the energy balance of the fuels in rat brain.
The findings are crucial in understanding the neuroprotection from ketosis for several reasons. First, the diet-induced ketosis we investigated is the most prevalent therapeutic scheme used in treatment of human epilepsy, which affects more than 1% of the whole population (9). Secondly, the animal model we had used and reported had the similar levels of ketosis comparing with real human studies (8). We also took careful effort to ensure that the physiological parameters matches closely to those reported in normal humans. Thirdly, the findings on the biochemical and metabolic pathways of ketone bodies and glucose are directly linked with the mitochondria respiration and ATP synthesis, as succinate, a key citric acid cycle intermediate, participates readily with the electron transport chain. In addition, the acetyl-coA, which we measured in ketosis, directly reflects the converging point of ketone and glucose metabolism, which is not often reported elsewhere. Lastly, our data directly support the hypothesis that ketone bodies spares glucose shunts to glutamate and GABA, which are key neurotransmitters responsible for neuronal transduction, glutamate toxicity and ictal event in seizures. Our data not only offers reasonable explanations to the neuroprotection from ketosis, but also
126
explains the reversibilities of neuroprotection when glucose is re-consumed after ketosis is established (69).
Future work on the metabolic explanations of neuroprotections from ketosis would require more validation. It is important to verify that the methodologies used in examining the cerebral metabolism are valid, and the key assumptions are held true when ketosis is introduced (for example, the lumped constant, and the cerebral blood flow).
In-depth examinations of neuronal and astroglial partitioning effect of ketosis are also required. Particularly, recent advances in astrocytes researches suggest that the supporting cells are crucial in the maintenance of organisms (139). Our current work attributes the ketone bodies’ sparing effects to pyruvate recycling. More complex labeling patterns may be elucidated when one can combine the GC-MS analytical expertise with the NMR analysis for the dynamic fuel utilization rates.
127
6.5 Figures and tables
Table 6.1 Literature Lumped Constant (LC) numbers for 2-Deoxyglucose(DG) and 18FDG.
Blood studied Referenc Phy/Path Induction Trace Ketone Baselin LC e No. Year Subject models Method r range e LC Values
(26) 1977 Rat Normal N/A DG Unknown 0.48 N/A
(27) 1979 Human Normal N/A FDG Unknown 0.42 N/A
12-24 month decreased (100) 1983 Rat old N/A DG Unknown 0.50 to 0.42
(137) 1988 Rat Glioma N/A DG Unknown 0.52 1.17
3 week Up to Decrease (17) 1989 Human Ketosis fast FDG 4.3mM 0.57 d to 0.43
Insulin Increased (135) 1990 Rat Hypoglycemia infusion DG Unknown 0.48 to 1.20
Hyperglycemi Glucose decreased (136) 1990 Rat a infusion DG Unknown 0.48 to 0.36
Fasted Total up No (15) 1994 Human Ketosis 3.5 days FDG to 3.2mM 0.70 change
Ketone Total up (56) 1996 Human Ketosis infusion FDG to 2.4mM N/A N/A
Malignant increased (140) 1998 Human tumor N/A FDG Unknown 0.86 to 1.40
(105) 2006 Rat Normal N/A FDG Unknown 0.71 N/A
128
Figure 6.1 Proposed Neuron-Glial Compartmentation models for ketone metabolism studies. Figure reference from McKenna review 2007, JNR (112).
129
Appendix
Appendix I Sample Files for PET plasma input functions (.crv) and time
activity curves(.tac)
Sample.crv file sample-time[seconds] plasma[nCi/cc]
0 547.3515883
0.1 547.3515883
0.2 691.3914799
0.3 777.8154149
0.4 633.7755232
0.5 576.1595666
0.6 316.8877616
0.7 604.9675449
…
120.3 15152.9966
120.4 13885.44555
120.5 14807.30086
120.6 16478.1636
120.7 15152.9966
120.8 13885.44555
…
130
490 9923.677264
899 7123.665015
1500 6019.007608
2438 3997.548287
3009 3764.115389
3543 2967.918152
Sample_cerebellum.tac file start[seconds] end[nCi/cc] value[nCi/cc]
0 10 2829.106689
10 20 4613.858887
20 30 4754.794922
30 40 5594.768066
40 50 5126.583984
50 60 6224.883301
60 80 6251.560059
80 100 7075.844727
100 120 6940.621094
120 140 7094.312012
140 160 7483.741699
131
160 180 7189.648438
180 210 6995.331543
210 240 7180.974121
240 270 7296.687988
270 300 7154.744141
300 360 7468.562012
360 420 7459.20459
420 480 7350.770996
480 600 7556.668457
600 720 7706.485352
720 960 7935.446289
960 1200 8245.056641
1200 1680 8536.75293
1680 2160 8764.333984
2160 2640 8973.729492
2640 3120 9024.181641
3120 3600 9044.180664
132
Appendix II Matlab code for Gjedde-Patlak analysis
% suppose you have three vectors
%
% vector 1 is the time t
% vector 2 is the plasma activity nCi/cc data_input
% vector 3 is the ROI activity nCi/cc ROI_output
% You want to plot the gjedde-patlak graph and find slope K
%% Getting input function fname=uigetfile('*.crv'); % input function has suffix crv inputfun=dlmread(fname,'\t',1, 0); t_input=inputfun(:,1); data_input=inputfun(:,2); clear ans fname
% Getting ROI fname=uigetfile('*.tac'); % output function; i.e time activity curve outputfun=dlmread(fname,'\t',1, 0); t_output= (outputfun(:,1)+outputfun(:,2))./2 ;
data_output=outputfun(:,3); clear ans fname
%% Now integrate the plasma input function with time
133
% first interpolate and make input function smooth
t_fine=150:0.1:max(t_input);
figure (1)
plot (t_input, data_input)
% Use spline or interp1 data_fine=interp1(t_input(1499:end), data_input(1499:end), t_fine);
figure (2)
plot (t_fine, data_fine);
data_fine=data_fine';
t_fine=t_fine';
figure (3)
t_input1=[t_input(1:1500);t_fine];
data_input1=[data_input(1:1500);data_fine];
plot (t_input1,data_input1, '.-'); % input1 are the fine input function time and curve
% Then find the indices of the t_input1 that matches t_output
ind=zeros(1, length(t_output));
for i=1:(length(t_output))
temp=abs( t_input1-t_output(i) );
%NOTE : must satisfy max(t_input)> max ( t_output) to have this code work
ind(i)=min ( find(temp<0.11) ); % find all matching indices,
134
% pick the closest index from t, so we can find the output function
% time point that matches the input function time point end
% Then integrate the input function with repect to time
%
% Gjedde Patlak Theory states that the slope is LHS / RHS
% left hand side is TAC(t) / PlasmaInputFunction(t)
% right hand side is
% TimeIntegratedPlasmaInputFunction(t)/PlasmaInputFunction(t)
for i=1:(length(t_output))
LHS(i)=data_output(i)/data_input1(ind(i));
RHS(i)= ( trapz(t_input1(1:ind(i)),data_input1(1:ind(i))) )/ data_input1(ind(i)) ; end
%% add your manual code over here stem (RHS (end-15:end), LHS(end-15:end),'o');grid on
% this plots the patlak graph . we need to find the slope for this one.
%% Now finding out the slope p=polyfit ( RHS(end-6:end), LHS(end-6:end),1); % only fit the last time points
p(1)*60/10*1000
135
plasmaglc=6.5*1.2; % steady state plasma glucose level. It is measured. Needs to manually change with different studies.
LC=0.71 % Lumped constant is assumed 0.71. See J Nucl Med January 2007 vol. 48 no. 1 94-99
%%
CMRglc= plasmaglc/LC * p(1) *60/10*1000 % x60 to convert sec^1 to min^1
% /10 to convert water 1L to 100g water tissue gram
% x1000 to convert mmole to microMole
% final unit for CMRglc uMole/100g/min
136
Appendix III FDG-PET model and LC measurement
1. Model development
Glucose and its radiolabeled derivative 18FDG which enter the plasma can be transported
into interstitial fluid and then into tissue cells. Within the cells, these substrates are
phosphorylated to form glucose-6-P and 18FDG-6-P. Whereas the cellular glucose-6-P
can be dephosphorylated, the 18FDG-6-P cannot be dephosphorylated. (26, 27) Also, both glucose-6-P and 18FDG-6-P remain within the cells. See figure 2.3.
After the phosphorylation process, glucose-6-P undergoes further glycolytic steps in the
18 brain and eventually lost to CO2. FDG-6-P does not undergo further glycolytic steps.
Therefore, at steady state, plasma glucose and 18FDG-6-P concentrations are not changed;
in the brain, glucose, 18FDG, and 18FDG-6-P concentrations are also staying constant.
However, the glucose-6-P concentration does not reach steady state when other aforementioned metabolites are constant. The rate of glucose-6-P concentration change in the brain is defined as Cerebral Metabolic Rate of Glucose (CMRglc).
State Variables
C ,C : Plasma and intracellular glucose concentrations (mM) p e
C : Glucose-6-P concentration (mM) m
137
C* ,C* : Plasma and intracellular labeled FDG concentrations (nCi/ml) p e
C* : FDG-6-P concentration (nCi/ml) m
Transport and metabolic processes
Dynamic molar balances of intracellular endogenous glucose and glucose-6-P lead to
dC (1.1) e =−−kC kCR(, C C* ) + kC dt 1 p 24e ee m
dCm * (1.2) = R(,CCee )−− k45C mk C m dt
Where R(C ,C* ) characterizes the forward competitive reaction rate to form glucose-6-P. e e
The ‘k’s are first-order rate constants for chemical reaction and transport. From dynamic balances of the 18FDG tracer, the concentrations change according to
* dCe * * * * * * (1.3) = k1 Cp − k2Ce − R (Ce ,Ce ) dt
* dCm * * (1.4) = R (Ce ,Ce ) dt
138
Where R*(C ,C* ) characterizes the forward competitive reaction rate to form 18FDG-6-P: e e
The ‘k’s are first-order rate constants for chemical reaction and transport of 18FDG and 18FDG-6-P. The tissue radioactivities correspond to the measureable output:
(1.5)
2 Derivation of the competitive reactions of glucose and 18FDG
In this case, both glucose and 18FDG can be phosphorylated by the same enzyme (E), hexokinase. The phosphorylation of 18FDG is inhibitive to the phosphorylation of glucose
and vice versa. Here, we define glucose as “substrate (S)” and 18FDG as “Inhibitor(I)”.
The chemical reaction processes are (For equation 2.1-2.6, see reference link
below: http://ocw.mit.edu/courses/chemical-engineering/10-492-2-integrated-chemical-
engineering-topics-i-introduction-to-biocatalysis-fall-2004/lecture-notes/lecture4.pdf)
k1 (2.1) [S]+[E]←→[SE] k→[E]+[P ] k 2 S
k3 (2.2) [I]+[E]←→[P ] k 4 I
Note that we assume that only the forward phosphorylation reaction processes are
competitive. The de-phosphorylation process is not thought to be competitive in the
discussion. Therefore equation (2.1) has unidirectional reaction to form Ps.
The reaction rate equations are
139
dS[] =−+k[ S ][ E ] k [ SE ]; dt 12
dP[] (2.3) S == k[] SE dt
dI[] dP[] =−+=−kIE[ ][ ] kP [ ]I dt 34I dt
For the substrate and the inhibitor at equilibrium, we set the derivatives equal to zero and obtain the equilibrium constants:
[ES ][ ] k [ES ][ ] (2.4) K ==⇒=2 []SE m []SE k K 1 m
[IE ][ ] k4 [EI ][ ] (2.5) KPiI= =⇒=[] []PkIi3 K
Therefore the total concentration of compounds that contains enzyme would be
[]SI [] (2.6) [E0 ]=+ [][ E SE ][ += PI ] [](1 E ++ ) KKmi from (2.4) and (2.6) we find the intermediate concentration :
[]S []E (2.7) []SE = 0 Km(1++ [ SK ]/ mi [ IK ]/ )
From (2.7) and (1.3) we arrive the product (Ps) production rate
dP[] []S []E kE[][] S (2.8) s =k[] SE = k 00= dt Km(1++ [ SK ]/ m [ IK ]/ i ) K mm + KIK [ ]/ i + [ S ]
140
The maximum reaction rate occurs when gets very large:
dP[] s ≈≡ kE[]0 Vm dt max
so that
dP[ ] V [] S (2.9) sm= dtKKIKSmm++[ ]/ i [ ]
3. Finding the phosphorylation rate of glucose and 18FDG
From equation (2.8), we can write the brain glucose (substrate) phosphorylation rate R
and brain 18FDG (inhibitor) phosphorylation rate R* as follows:
C V (3.1) R(C ,C* ) = e m e e K + C*K / K * + C m e m m e
C*V * (3.2) R*(C ,C* ) = e m e e K * + C K * / K + C* m e m m e
* 18 Here Km and Km are half-maximum rate concentrations for glucose and FDG,
* respectively. The Vm and Vm are the maximum phosphorylation rates for glucose
and 18FDG, respectively.
141
For glucose, if K >> C*K / K * + C (meaning the enzyme affinity is very low) , then m e m m e
the reaction is approximated as first order:
(3.1a)
Here we have defined a first order rate constant k3 to relate the glucose concentration to
the phosphorylation rate. Similarly, for 18FDG when K * >> C K * / K + C* , m e m m e
C**V RV***(,)CC **≈em ⇒=* e e ≈ m (3.2a) R (,)CCee * k3 ** Km CKem
* 18 We here define k3 to relate the FDG phosphorylation rate to a first order constant.
Consequently, the model equations for endogenous glucose (1.1) (1.2) simplify as:
dCe (3.3) = k1Cp − k2Ce − k3Ce + k4Cm dt
(3.4)
Similarly, (1.3) and (1.4) leads to
* dCe * * * * * * (3.5) = k1 Cp − k2Ce − k3Ce dt
and the approximation for the cerebral metabolic rate of FDG:
142
* dCm * * (3.6) CMRFDG ; = k3Ce dt
If the FDG is constantly infused for a sufficient long period of time, then becomes
constant:
dC* p =⇒∞0 C* ( ) dt p
The Laplace transform C*(s) = L C*(t) applied to the variables of Eq.(3.5) yields { }
(3.7) sC*(s) = k *C* (s) − (k * + k * )C*(s) e 1 p 2 3 e
Omit the following equation, which is not needed:
sC* (s) = k *C*(s) m 3 e
From equation (3.7), when s ==> 0 corresponding to t ↑ ∞ , we find
** ** ** 0=−+kC1 p ()s ( kC2 ee () ss kC3 ()) so that
k * k * (3.8) lim sC*(s) = 1 sC* (s) ⇒ C*(∞) = 1 C* (∞) s→0 e k * + k * p e k * + k * p 2 3 2 3
143
4. Linking the phosphorylation rate of glucose and 18FDG
If the dephosphorylation rate is much smaller than phosphorylation rate
, then we can relate the cerebral metabolic rate of glucose to brain glucose concentration:
dCm (4.1) CMRglc= ≈ Cem k343− C k= C ek φ dt
where φ = 1− C k C k . If the rate of loss of the phosphorylated glucose is sufficiently m 4 e 3
small, then φ ≈1 or approximately a constant close to one.
For the endogenous glucose at steady state (equation 3.3 equal to zero)
k C − k C = k C − k C = C k φ 1 p 2 e 3 e 4 m e 3
At steady state (ss), we can relate brain glucose concentration to plasma concentration as:
(4.3) CkCkep()ss= 1 () ss /( 23+φk )
From (4.2) & (4.3) ,
k k φ (4.4) CMRglc = 1 3 C (ss) k +φk p 2 3
Because the glucose rate constants are hard to estimate, we relate glucose rate
constants to 18FDG kinetic constants, which can be estimated because the radioactivities
144
can be measured in the brain non-invasively. The ratio of the FDG phosphorylation
kinetic constant from Eq. (3.2a) and the glucose rate constant and (3.1a) is
(4.5)
If we define a ratio λ of FDG kinetic coefficients to glucose rate coefficients as:
k * k φ (4.6) λ ≡ 1 / 1 k * + k * k +φk 2 3 2 3
then substitution of Eqs. (4.5) and (4.6) into 4.4) yields
k φ k* kk** φC ()ss kk** = 1 3 = 13 p = 13 (4.7) CMRglcCpp(ss) ** ** C()ss k2+φλ kf 3 kk23 ++ f( k23kL) C
where (LC) is assumed to be a constant:
λ f (4.8) LC ≡ φ
and is called a “Lumped Constant”. Equation (4.7) is used as an operational equation for the estimation of CMRglc.
5. Estimation of 18FDG kinetic constants
To evaluate according to Eq. 4.7, the kinetic parameters of the tagged
FDG reactions must be estimated. The optimal parameter estimates are those for which
145
the model output matches the data from dyn3amic PET scans following
tracer injection of tagged 18FDG. The output is evaluated using the following kinetic model:
* dCe * * * * * * (3.5) = k1 Cp − k2Ce − k3Ce 3 dt
* dCm * * (3.6) = k3Ce dt
* * With the initial conditions Cm (0) =Ce (0) =0 . This is achieved numerically by solving
the initial-value problem and applying optimal least-squares estimation (e.g., using
MATLAB codes “ode15s” and “lsqcurvefit”). The 18FDG kinetic constants can be
determined. Alternatively, fitting of the data can be achieved either with graphic
methods(81-83), or multi-exponential (Analytical solutions to the ODEs).
6. Estimation of the Lumped Constant (LC)
LC is a combination of equilibrium constants, kinetic coefficients, and reaction
rates for FDG and glucose(26, 27, 29). There is no mechanistic proof that LC is constant under different physiological conditions. It is assumed, however, that LC has only small variations, which can be determined experimentally(29, 105, 135, 136). At steady state, the metabolic reaction and uptake rates of glucose (net phosphorylation) are equal:
dC (6.1) m = CMRglc(ss) = CBF(C − C ) dt A V ss ss
146
The uptake rate be obtained from experimental measurement of the cerebral blood flow
CBF and the arterial and cerebral venous concentrations of glucose CA and CV .
Similarly, at the steady-state, the FDG metabolic reaction and uptake rates are equal:
dC* (6.2) m = CMR (ss) = CBF(C* − C* ) dt FDG A V ss ss
The ratio of these steady-state rates eliminates CBF:
dC* / dt CMR (ss) (C* − C* ) (6.3) m = FDG = A V ss dC / dt CMRglc(ss) (C − C ) m ss A V ss
From Eqs. (3.6) and (4.1) for cerebral metabolic rates and (4.5), we obtain
(C* − C* ) dC* / dt C*k * fC* A V ss = m = e 3 = e (C − C ) dC / dt φC k φC A V ss m ss e 3 ss e ss
At steady state, C* = C*(∞) and C = C (ss) so that substituting Eqs. (3.8) and (4.3) e e e e
yields
k* fC1 * ()∞ (C*−+ C *) fC *()∞ k ** k p fC**()∞ 1 C ()∞ (6.4) AVss = e = 23 =pp = () (CA − CCV )ssφ e ()ss k1 φλCp ()ss LC Cp ()ss φ Cp ()ss k23+φk
We can use Eq. (6.4) to estimate the LC from experimental measurements with constant
infusion of 18FDG, cerebral arterial and venous blood collections, and a standard 18FDG -
18 PET procedure. Then, using Eq. (4.7), we can estimate CMRglc(ss) by injecting FDG
147
tracer and then use PET to measure dynamic responses of radioactivity in the brain and plasma glucose concentration. With these data, the model equations provide the basis for estimating the 18FDG kinetic constants and LC.
148
Bibliography
1. Wilder RM. The effect of ketonemia on the course of epilepsy. Mayo Clinic
Bulletin. 1921;2:307.
2. Owen OE, Morgan AP, Kemp HG, Sullivan JM, Herrera MG, Cahill GF, Jr. Brain
metabolism during fasting. The Journal of clinical investigation. 1967 Oct;46(10):1589-
95. PubMed PMID: 6061736. Pubmed Central PMCID: 292907.
3. Hawkins RA, Williamson DH, Krebs HA. Ketone-body utilization by adult and suckling rat brain in vivo. The Biochemical journal. 1971 Mar;122(1):13-8. PubMed
PMID: 5124783. Pubmed Central PMCID: 1176682.
4. Sokoloff L. Metabolism of ketone bodies by the brain. Annual review of medicine.
1973;24:271-80. PubMed PMID: 4575857.
5. Cunnane S, Nugent S, Roy M, Courchesne-Loyer A, Croteau E, Tremblay S, et al.
Brain fuel metabolism, aging, and Alzheimer's disease. Nutrition. 2011 Jan;27(1):3-20.
PubMed PMID: 21035308. Pubmed Central PMCID: 3478067.
6. Seyfried TN, Mukherjee P. Targeting energy metabolism in brain cancer: review and hypothesis. Nutrition & metabolism. 2005 Oct 21;2:30. PubMed PMID: 16242042.
Pubmed Central PMCID: 1276814.
7. Kashiwaya Y, Takeshima T, Mori N, Nakashima K, Clarke K, Veech RL. D-beta- hydroxybutyrate protects neurons in models of Alzheimer's and Parkinson's disease.
149
Proceedings of the National Academy of Sciences of the United States of America. 2000
May 9;97(10):5440-4. PubMed PMID: 10805800. Pubmed Central PMCID: 25847.
8. Freeman JM, Vining EP, Pillas DJ, Pyzik PL, Casey JC, Kelly LM. The efficacy of the ketogenic diet-1998: a prospective evaluation of intervention in 150 children.
Pediatrics. 1998 Dec;102(6):1358-63. PubMed PMID: 9832569.
9. Kinsman SL, Vining EP, Quaskey SA, Mellits D, Freeman JM. Efficacy of the ketogenic diet for intractable seizure disorders: review of 58 cases. Epilepsia. 1992 Nov-
Dec;33(6):1132-6. PubMed PMID: 1464275.
10. LENNOX WG. Ketogenic diet in the treatment of epilepsy. New England Journal of Medicine. 1928;199(2):74-5.
11. Schwartzkroin PA. Mechanisms underlying the anti-epileptic efficacy of the ketogenic diet. Epilepsy research. 1999 Dec;37(3):171-80. PubMed PMID: 10584967.
12. Swink TD, Vining EP, Freeman JM. The ketogenic diet: 1997. Advances in pediatrics. 1997;44:297-329. PubMed PMID: 9265974.
13. Prins ML, Hovda DA. The effects of age and ketogenic diet on local cerebral metabolic rates of glucose after controlled cortical impact injury in rats. Journal of neurotrauma. 2009 Jul;26(7):1083-93. PubMed PMID: 19226210. Pubmed Central
PMCID: 2843133.
150
14. Puchowicz MA, Zechel JL, Valerio J, Emancipator DS, Xu K, Pundik S, et al.
Neuroprotection in diet-induced ketotic rat brain after focal ischemia. Journal of cerebral
blood flow and metabolism : official journal of the International Society of Cerebral
Blood Flow and Metabolism. 2008 Dec;28(12):1907-16. PubMed PMID: 18648382.
Pubmed Central PMCID: 3621146.
15. Hasselbalch SG, Knudsen GM, Jakobsen J, Hageman LP, Holm S, Paulson OB.
Brain metabolism during short-term starvation in humans. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and
Metabolism. 1994 Jan;14(1):125-31. PubMed PMID: 8263048.
16. LaManna JC, Salem N, Puchowicz M, Erokwu B, Koppaka S, Flask C, et al.
Ketones suppress brain glucose consumption. Advances in experimental medicine and
biology. 2009;645:301-6. PubMed PMID: 19227486. Pubmed Central PMCID: 2874681.
17. Redies C, Hoffer LJ, Beil C, Marliss EB, Evans AC, Lariviere F, et al.
Generalized decrease in brain glucose metabolism during fasting in humans studied by
PET. The American journal of physiology. 1989 Jun;256(6 Pt 1):E805-10. PubMed
PMID: 2786677.
18. Melo TM, Nehlig A, Sonnewald U. Neuronal-glial interactions in rats fed a
ketogenic diet. Neurochemistry international. 2006 May-Jun;48(6-7):498-507. PubMed
PMID: 16542760.
151
19. Yudkoff M, Daikhin Y, Horyn O, Nissim I, Nissim I. Ketosis and brain handling of glutamate, glutamine, and GABA. Epilepsia. 2008 Nov;49 Suppl 8:73-5. PubMed
PMID: 19049594. Pubmed Central PMCID: 2722878.
20. Yudkoff M, Daikhin Y, Melo TM, Nissim I, Sonnewald U, Nissim I. The ketogenic diet and brain metabolism of amino acids: relationship to the anticonvulsant effect. Annual review of nutrition. 2007;27:415-30. PubMed PMID: 17444813.
21. Milder JB, Liang LP, Patel M. Acute oxidative stress and systemic Nrf2 activation by the ketogenic diet. Neurobiology of disease. 2010 Oct;40(1):238-44.
PubMed PMID: 20594978. Pubmed Central PMCID: 3102314.
22. Sullivan PG, Rippy NA, Dorenbos K, Concepcion RC, Agarwal AK, Rho JM.
The ketogenic diet increases mitochondrial uncoupling protein levels and activity. Annals of neurology. 2004 Apr;55(4):576-80. PubMed PMID: 15048898.
23. Maalouf M, Sullivan PG, Davis L, Kim DY, Rho JM. Ketones inhibit mitochondrial production of reactive oxygen species production following glutamate excitotoxicity by increasing NADH oxidation. Neuroscience. 2007 Mar 2;145(1):256-64.
PubMed PMID: 17240074. Pubmed Central PMCID: 1865572.
24. Noh HS, Hah YS, Nilufar R, Han J, Bong JH, Kang SS, et al. Acetoacetate protects neuronal cells from oxidative glutamate toxicity. Journal of neuroscience research. 2006 Mar;83(4):702-9. PubMed PMID: 16435389.
152
25. Daniel PM, Love ER, Moorehouse SR, Pratt OE, Wilson P. Factors influencing utilisation of ketone-bodies by brain in normal rats and rats with ketoacidosis. Lancet.
1971 Sep 18;2(7725):637-8. PubMed PMID: 4105949.
26. Sokoloff L, Reivich M, Kennedy C, Des Rosiers MH, Patlak CS, Pettigrew KD, et al. The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. Journal of neurochemistry. 1977 May;28(5):897-916. PubMed PMID: 864466.
27. Phelps ME, Huang SC, Hoffman EJ, Selin C, Sokoloff L, Kuhl DE. Tomographic measurement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2- deoxy-D-glucose: validation of method. Annals of neurology. 1979 Nov;6(5):371-88.
PubMed PMID: 117743.
28. Zhang Y, Kuang Y, LaManna JC, Puchowicz MA. Contribution of brain glucose and ketone bodies to oxidative metabolism. Advances in experimental medicine and biology. 2013;765:365-70. PubMed PMID: 22879057.
29. Holden JE, Mori K, Dienel GA, Cruz NF, Nelson T, Sokoloff L. Modeling the dependence of hexose distribution volumes in brain on plasma glucose concentration: implications for estimation of the local 2-deoxyglucose lumped constant. Journal of cerebral blood flow and metabolism : official journal of the International Society of
Cerebral Blood Flow and Metabolism. 1991 Mar;11(2):171-82. PubMed PMID: 1997495.
153
30. McKenna MC, Sonnewald U, Huang X, Stevenson J, Zielke HR. Exogenous glutamate concentration regulates the metabolic fate of glutamate in astrocytes. Journal of neurochemistry. 1996 Jan;66(1):386-93. PubMed PMID: 8522979.
31. Jeffrey FM, Marin-Valencia I, Good LB, Shestov AA, Henry PG, Pascual JM, et al. Modeling of brain metabolism and pyruvate compartmentation using C NMR in vivo: caution required. Journal of cerebral blood flow and metabolism : official journal of the
International Society of Cerebral Blood Flow and Metabolism. 2013 May 8. PubMed
PMID: 23652627.
32. Nehlig A. Brain uptake and metabolism of ketone bodies in animal models.
Prostaglandins, leukotrienes, and essential fatty acids. 2004 Mar;70(3):265-75. PubMed
PMID: 14769485.
33. Veech RL. The therapeutic implications of ketone bodies: the effects of ketone bodies in pathological conditions: ketosis, ketogenic diet, redox states, insulin resistance, and mitochondrial metabolism. Prostaglandins, leukotrienes, and essential fatty acids.
2004 Mar;70(3):309-19. PubMed PMID: 14769489.
34. Fink G, Desrochers S, Des Rosiers C, Garneau M, David F, Daloze T, et al.
Pseudoketogenesis in the perfused rat heart. The Journal of biological chemistry. 1988
Dec 5;263(34):18036-42. PubMed PMID: 3056937.
154
35. Gjedde A, Crone C. Induction processes in blood-brain transfer of ketone bodies during starvation. The American journal of physiology. 1975 Nov;229(5):1165-9.
PubMed PMID: 1200135.
36. Morris AA. Cerebral ketone body metabolism. Journal of inherited metabolic disease. 2005;28(2):109-21. PubMed PMID: 15877199.
37. Prins ML. Cerebral ketone metabolism during development and injury. Epilepsy research. 2012 Jul;100(3):218-23. PubMed PMID: 22104087. Pubmed Central PMCID:
3306503.
38. van den Berg CJ, Garfinkel D. A stimulation study of brain compartments.
Metabolism of glutamate and related substances in mouse brain. The Biochemical journal.
1971 Jun;123(2):211-8. PubMed PMID: 5164952. Pubmed Central PMCID: 1176925.
39. Pan JW, Rothman TL, Behar KL, Stein DT, Hetherington HP. Human brain beta-
hydroxybutyrate and lactate increase in fasting-induced ketosis. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood
Flow and Metabolism. 2000 Oct;20(10):1502-7. PubMed PMID: 11043913.
40. Leino RL, Gerhart DZ, Duelli R, Enerson BE, Drewes LR. Diet-induced ketosis increases monocarboxylate transporter (MCT1) levels in rat brain. Neurochemistry international. 2001 May;38(6):519-27. PubMed PMID: 11248400.
155
41. Vannucci SJ, Simpson IA. Developmental switch in brain nutrient transporter
expression in the rat. American journal of physiology Endocrinology and metabolism.
2003 Nov;285(5):E1127-34. PubMed PMID: 14534079.
42. Simpson IA, Carruthers A, Vannucci SJ. Supply and demand in cerebral energy
metabolism: the role of nutrient transporters. Journal of cerebral blood flow and
metabolism : official journal of the International Society of Cerebral Blood Flow and
Metabolism. 2007 Nov;27(11):1766-91. PubMed PMID: 17579656. Pubmed Central
PMCID: 2094104.
43. Nehlig A, Pereira de Vasconcelos A. Glucose and ketone body utilization by the brain of neonatal rats. Progress in neurobiology. 1993 Feb;40(2):163-221. PubMed PMID:
8430212.
44. Kety SS, Schmidt CF. The Nitrous Oxide Method for the Quantitative
Determination of Cerebral Blood Flow in Man: Theory, Procedure and Normal Values.
The Journal of clinical investigation. 1948 Jul;27(4):476-83. PubMed PMID: 16695568.
Pubmed Central PMCID: 439518.
45. Ruderman NB, Ross PS, Berger M, Goodman MN. Regulation of glucose and ketone-body metabolism in brain of anaesthetized rats. The Biochemical journal. 1974
Jan;138(1):1-10. PubMed PMID: 4275704. Pubmed Central PMCID: 1166169.
156
46. Dahlquist G, Persson B. The rate of cerebral utilization of glucose, ketone bodies,
and oxygen: a comparative in vivo study of infant and adult rats. Pediatric research. 1976
Nov;10(11):910-7. PubMed PMID: 980550.
47. Corddry DH, Rapoport SI, London ED. No effect of hyperketonemia on local
cerebral glucose utilization in conscious rats. Journal of neurochemistry. 1982
Jun;38(6):1637-41. PubMed PMID: 7077332.
48. DeVivo DC, Pagliara AS, Prensky AL. Ketotic hypoglycemia and the ketogenic
diet. Neurology. 1973 Jun;23(6):640-9. PubMed PMID: 4736310.
49. Salas J, Salas M, Vinuela E, Sols A. Glucokinase of Rabbit Liver. The Journal of biological chemistry. 1965 Mar;240:1014-8. PubMed PMID: 14284695.
50. Hartman AL, Vining EP. Clinical aspects of the ketogenic diet. Epilepsia. 2007
Jan;48(1):31-42. PubMed PMID: 17241206.
51. al-Mudallal AS, Levin BE, Lust WD, Harik SI. Effects of unbalanced diets on
cerebral glucose metabolism in the adult rat. Neurology. 1995 Dec;45(12):2261-5.
PubMed PMID: 8848204.
52. Al-Mudallal AS, LaManna JC, Lust WD, Harik SI. Diet-induced ketosis does not cause cerebral acidosis. Epilepsia. 1996 Mar;37(3):258-61. PubMed PMID: 8598184.
157
53. Yudkoff M, Daikhin Y, Nissim I, Lazarow A, Nissim I. Brain amino acid
metabolism and ketosis. Journal of neuroscience research. 2001 Oct 15;66(2):272-81.
PubMed PMID: 11592124.
54. Kashiwaya Y, Pawlosky R, Markis W, King MT, Bergman C, Srivastava S, et al.
A ketone ester diet increases brain malonyl-CoA and Uncoupling proteins 4 and 5 while decreasing food intake in the normal Wistar Rat. The Journal of biological chemistry.
2010 Aug 20;285(34):25950-6. PubMed PMID: 20529850. Pubmed Central PMCID:
2923987.
55. Pan JW, de Graaf RA, Petersen KF, Shulman GI, Hetherington HP, Rothman DL.
[2,4-13 C2 ]-beta-Hydroxybutyrate metabolism in human brain. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood
Flow and Metabolism. 2002 Jul;22(7):890-8. PubMed PMID: 12142574. Pubmed Central
PMCID: 2995543.
56. Hasselbalch SG, Madsen PL, Hageman LP, Olsen KS, Justesen N, Holm S, et al.
Changes in cerebral blood flow and carbohydrate metabolism during acute hyperketonemia. The American journal of physiology. 1996 May;270(5 Pt 1):E746-51.
PubMed PMID: 8967461.
57. Jiang L, Mason GF, Rothman DL, de Graaf RA, Behar KL. Cortical substrate oxidation during hyperketonemia in the fasted anesthetized rat in vivo. Journal of cerebral blood flow and metabolism : official journal of the International Society of
158
Cerebral Blood Flow and Metabolism. 2011 Dec;31(12):2313-23. PubMed PMID:
21731032. Pubmed Central PMCID: 3323194.
58. Lund TM, Obel LF, Risa O, Sonnewald U. beta-Hydroxybutyrate is the preferred substrate for GABA and glutamate synthesis while glucose is indispensable during depolarization in cultured GABAergic neurons. Neurochemistry international. 2011
Aug;59(2):309-18. PubMed PMID: 21684314.
59. Linde R, Hasselbalch SG, Topp S, Paulson OB, Madsen PL. Global cerebral blood flow and metabolism during acute hyperketonemia in the awake and anesthetized rat. Journal of cerebral blood flow and metabolism : official journal of the International
Society of Cerebral Blood Flow and Metabolism. 2006 Feb;26(2):170-80. PubMed PMID:
16001018.
60. Prins ML. Cerebral metabolic adaptation and ketone metabolism after brain injury.
Journal of cerebral blood flow and metabolism : official journal of the International
Society of Cerebral Blood Flow and Metabolism. 2008 Jan;28(1):1-16. PubMed PMID:
17684514. Pubmed Central PMCID: 2857668.
61. Suzuki M, Suzuki M, Kitamura Y, Mori S, Sato K, Dohi S, et al. Beta-
hydroxybutyrate, a cerebral function improving agent, protects rat brain against ischemic
damage caused by permanent and transient focal cerebral ischemia. Japanese journal of
pharmacology. 2002 May;89(1):36-43. PubMed PMID: 12083741.
159
62. Puchowicz MA, Xu K, Sun X, Ivy A, Emancipator D, LaManna JC. Diet-induced
ketosis increases capillary density without altered blood flow in rat brain. American
journal of physiology Endocrinology and metabolism. 2007 Jun;292(6):E1607-15.
PubMed PMID: 17284577.
63. Bough KJ, Eagles DA. A ketogenic diet increases the resistance to
pentylenetetrazole-induced seizures in the rat. Epilepsia. 1999 Feb;40(2):138-43.
PubMed PMID: 9952258.
64. Prins ML, Lee SM, Fujima LS, Hovda DA. Increased cerebral uptake and
oxidation of exogenous betaHB improves ATP following traumatic brain injury in adult
rats. Journal of neurochemistry. 2004 Aug;90(3):666-72. PubMed PMID: 15255945.
65. Prins ML, Giza CC. Induction of monocarboxylate transporter 2 expression and
ketone transport following traumatic brain injury in juvenile and adult rats.
Developmental neuroscience. 2006;28(4-5):447-56. PubMed PMID: 16943667.
66. Maalouf M, Rho JM, Mattson MP. The neuroprotective properties of calorie restriction, the ketogenic diet, and ketone bodies. Brain research reviews. 2009
Mar;59(2):293-315. PubMed PMID: 18845187. Pubmed Central PMCID: 2649682.
67. DeVivo DC, Leckie MP, Ferrendelli JS, McDougal DB, Jr. Chronic ketosis and cerebral metabolism. Annals of neurology. 1978 Apr;3(4):331-37. PubMed PMID:
666275.
160
68. Gilbert DL, Pyzik PL, Freeman JM. The ketogenic diet: seizure control correlates
better with serum beta-hydroxybutyrate than with urine ketones. Journal of child
neurology. 2000 Dec;15(12):787-90. PubMed PMID: 11198492.
69. Bough KJ, Schwartzkroin PA, Rho JM. Calorie restriction and ketogenic diet
diminish neuronal excitability in rat dentate gyrus in vivo. Epilepsia. 2003 Jun;44(6):752-
60. PubMed PMID: 12790887.
70. Henderson ST. Ketone bodies as a therapeutic for Alzheimer's disease.
Neurotherapeutics : the journal of the American Society for Experimental
NeuroTherapeutics. 2008 Jul;5(3):470-80. PubMed PMID: 18625458.
71. Lefevre F, Aronson N. Ketogenic diet for the treatment of refractory epilepsy in
children: A systematic review of efficacy. Pediatrics. 2000 Apr;105(4):E46. PubMed
PMID: 10742367.
72. De Vivo DC, Trifiletti RR, Jacobson RI, Ronen GM, Behmand RA, Harik SI.
Defective glucose transport across the blood-brain barrier as a cause of persistent hypoglycorrhachia, seizures, and developmental delay. The New England journal of medicine. 1991 Sep 5;325(10):703-9. PubMed PMID: 1714544.
73. Pardridge WM, Boado RJ, Farrell CR. Brain-type glucose transporter (GLUT-1)
is selectively localized to the blood-brain barrier. Studies with quantitative western
blotting and in situ hybridization. The Journal of biological chemistry. 1990 Oct
15;265(29):18035-40. PubMed PMID: 2211679.
161
74. Lowry OH, Passonneau JV. The Relationships between Substrates and Enzymes of Glycolysis in Brain. The Journal of biological chemistry. 1964 Jan;239:31-42. PubMed
PMID: 14114860.
75. Issad T, Penicaud L, Ferre P, Kande J, Baudon MA, Girard J. Effects of fasting on tissue glucose utilization in conscious resting rats. Major glucose-sparing effect in working muscles. The Biochemical journal. 1987 Aug 15;246(1):241-4. PubMed PMID:
3675558. Pubmed Central PMCID: 1148265.
76. Mans AM, Davis DW, Hawkins RA. Regional brain glucose use in unstressed rats after two days of starvation. Metabolic brain disease. 1987 Dec;2(4):213-21. PubMed
PMID: 3505339.
77. Hawkins RA, Mans AM, Davis DW. Regional ketone body utilization by rat brain in starvation and diabetes. The American journal of physiology. 1986 Feb;250(2 Pt
1):E169-78. PubMed PMID: 2937307.
78. Bentourkia M, Tremblay S, Pifferi F, Rousseau J, Lecomte R, Cunnane S. PET study of 11C-acetoacetate kinetics in rat brain during dietary treatments affecting ketosis.
American journal of physiology Endocrinology and metabolism. 2009 Apr;296(4):E796-
801. PubMed PMID: 19176356.
79. Occhipinti R, Puchowicz MA, LaManna JC, Somersalo E, Calvetti D. Statistical analysis of metabolic pathways of brain metabolism at steady state. Annals of biomedical engineering. 2007 Jun;35(6):886-902. PubMed PMID: 17385046.
162
80. Cremer JE, Heath DF. The estimation of rates of utilization of glucose and ketone bodies in the brain of the suckling rat using compartmental analysis of isotopic data. The
Biochemical journal. 1974 Sep;142(3):527-44. PubMed PMID: 4464840. Pubmed
Central PMCID: 1168317.
81. Gjedde A. Calculation of cerebral glucose phosphorylation from brain uptake of glucose analogs in vivo: a re-examination. Brain research. 1982 Jun;257(2):237-74.
PubMed PMID: 7104768.
82. Patlak CS, Blasberg RG, Fenstermacher JD. Graphical evaluation of blood-to- brain transfer constants from multiple-time uptake data. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and
Metabolism. 1983 Mar;3(1):1-7. PubMed PMID: 6822610.
83. Patlak CS, Blasberg RG. Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and
Metabolism. 1985 Dec;5(4):584-90. PubMed PMID: 4055928.
84. Gunn RN, Gunn SR, Cunningham VJ. Positron emission tomography compartmental models. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. 2001
Jun;21(6):635-52. PubMed PMID: 11488533.
163
85. Roy M, Nugent S, Tremblay-Mercier J, Tremblay S, Courchesne-Loyer A,
Beaudoin JF, et al. The ketogenic diet increases brain glucose and ketone uptake in aged rats: a dual tracer PET and volumetric MRI study. Brain research. 2012 Dec 7;1488:14-
23. PubMed PMID: 23063891.
86. Nakashima K, Ito K, Nakajima Y, Yamazawa R, Miyakawa S, Yoshimoto T.
Closed complex of the D-3-hydroxybutyrate dehydrogenase induced by an enantiomeric competitive inhibitor. Journal of biochemistry. 2009 Apr;145(4):467-79. PubMed PMID:
19122202.
87. Des Rosiers C, Montgomery JA, Garneau M, David F, Mamer OA, Daloze P, et al.
Pseudoketogenesis in hepatectomized dogs. The American journal of physiology. 1990
Mar;258(3 Pt 1):E519-28. PubMed PMID: 2316645.
88. Kim SG, Rostrup E, Larsson HB, Ogawa S, Paulson OB. Determination of relative CMRO2 from CBF and BOLD changes: significant increase of oxygen consumption rate during visual stimulation. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic
Resonance in Medicine. 1999 Jun;41(6):1152-61. PubMed PMID: 10371447.
89. Xu F, Ge Y, Lu H. Noninvasive quantification of whole-brain cerebral metabolic rate of oxygen (CMRO2) by MRI. Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in
164
Medicine. 2009 Jul;62(1):141-8. PubMed PMID: 19353674. Pubmed Central PMCID:
2726987.
90. Mintun MA, Raichle ME, Kilbourn MR, Wooten GF, Welch MJ. A quantitative
model for the in vivo assessment of drug binding sites with positron emission
tomography. Annals of neurology. 1984 Mar;15(3):217-27. PubMed PMID: 6609679.
91. Wu HM, Bergsneider M, Glenn TC, Yeh E, Hovda DA, Phelps ME, et al.
Measurement of the global lumped constant for 2-deoxy-2-[18F]fluoro-D-glucose in normal human brain using [15O]water and 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography imaging. A method with validation based on multiple methodologies. Molecular imaging and biology : MIB : the official publication of the
Academy of Molecular Imaging. 2003 Jan-Feb;5(1):32-41. PubMed PMID: 14499160.
92. Dienel GA. Brain lactate metabolism: the discoveries and the controversies.
Journal of cerebral blood flow and metabolism : official journal of the International
Society of Cerebral Blood Flow and Metabolism. 2012 Jul;32(7):1107-38. PubMed
PMID: 22186669. Pubmed Central PMCID: 3390802.
93. Lear JL, Ackermann RF. Regional comparison of the lumped constants of deoxyglucose and fluorodeoxyglucose. Metabolic brain disease. 1989 Jun;4(2):95-104.
PubMed PMID: 2755416.
165
94. Strohl KP, Thomas AJ, St Jean P, Schlenker EH, Koletsky RJ, Schork NJ.
Ventilation and metabolism among rat strains. Journal of applied physiology. 1997
Jan;82(1):317-23. PubMed PMID: 9029232.
95. Orzi F, Schuier FJ, Rutscheidt AP, Diana G, Carolei A, Fieschi C. Cerebral blood
flow and plasma volume during hyperglycemia in the conscious rat. Italian journal of
neurological sciences. 1990 Oct;11(5):459-63. PubMed PMID: 2272780.
96. Wise DR, Ward PS, Shay JE, Cross JR, Gruber JJ, Sachdeva UM, et al. Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of alpha-ketoglutarate to citrate to support cell growth and viability. Proceedings of the National Academy of
Sciences of the United States of America. 2011 Dec 6;108(49):19611-6. PubMed PMID:
22106302. Pubmed Central PMCID: 3241793.
97. Epstein SK, Singh N. Respiratory acidosis. Respiratory care. 2001 Apr;46(4):366-
83. PubMed PMID: 11262556.
98. Sibson NR, Dhankhar A, Mason GF, Rothman DL, Behar KL, Shulman RG.
Stoichiometric coupling of brain glucose metabolism and glutamatergic neuronal activity.
Proceedings of the National Academy of Sciences of the United States of America. 1998
Jan 6;95(1):316-21. PubMed PMID: 9419373. Pubmed Central PMCID: 18211.
99. Wu B, Zhang G, Zhang Y, Shuang S, Choi MM. Measurement of glucose concentrations in human plasma using a glucose biosensor. Analytical biochemistry.
2005 May 1;340(1):181-3. PubMed PMID: 15802146.
166
100. Takei H, Fredericks WR, London ED, Rapoport SI. Cerebral blood flow and
oxidative metabolism in conscious Fischer-344 rats of different ages. Journal of neurochemistry. 1983 Mar;40(3):801-5. PubMed PMID: 6827277.
101. Crane PD, Pardridge WM, Braun LD, Oldendorf WH. Two-day starvation does not alter the kinetics of blood--brain barrier transport and phosphorylation of glucose in rat brain. Journal of cerebral blood flow and metabolism : official journal of the
International Society of Cerebral Blood Flow and Metabolism. 1985 Mar;5(1):40-6.
PubMed PMID: 3972922.
102. Cherel Y, Burnol AF, Leturque A, Le Maho Y. In vivo glucose utilization in rat tissues during the three phases of starvation. Metabolism: clinical and experimental. 1988
Nov;37(11):1033-9. PubMed PMID: 3185286.
103. Hasselbalch SG, Knudsen GM, Jakobsen J, Hageman LP, Holm S, Paulson OB.
Blood-brain barrier permeability of glucose and ketone bodies during short-term starvation in humans. The American journal of physiology. 1995 Jun;268(6 Pt 1):E1161-
6. PubMed PMID: 7611392.
104. Xu K, Puchowicz MA, Sun X, LaManna JC. Decreased brainstem function following cardiac arrest and resuscitation in aged rat. Brain research. 2010 Apr
30;1328:181-9. PubMed PMID: 20211610. Pubmed Central PMCID: 2877401.
105. Tokugawa J, Ravasi L, Nakayama T, Schmidt KC, Sokoloff L. Operational lumped constant for FDG in normal adult male rats. Journal of nuclear medicine : official
167
publication, Society of Nuclear Medicine. 2007 Jan;48(1):94-9. PubMed PMID:
17204704.
106. Blomqvist G, Thorell JO, Ingvar M, Grill V, Widen L, Stone-Elander S. Use of R-
beta-[1-11C]hydroxybutyrate in PET studies of regional cerebral uptake of ketone bodies
in humans. The American journal of physiology. 1995 Nov;269(5 Pt 1):E948-59.
PubMed PMID: 7491948.
107. Gu L, Zhang GF, Kombu RS, Allen F, Kutz G, Brewer WU, et al. Parenteral and
enteral metabolism of anaplerotic triheptanoin in normal rats. II. Effects on lipolysis,
glucose production, and liver acyl-CoA profile. American journal of physiology
Endocrinology and metabolism. 2010 Feb;298(2):E362-71. PubMed PMID: 19903863.
Pubmed Central PMCID: 2822475.
108. Deng S, Zhang GF, Kasumov T, Roe CR, Brunengraber H. Interrelations between
C4 ketogenesis, C5 ketogenesis, and anaplerosis in the perfused rat liver. The Journal of
biological chemistry. 2009 Oct 9;284(41):27799-807. PubMed PMID: 19666922.
Pubmed Central PMCID: 2788830.
109. Des Rosiers C, Montgomery JA, Desrochers S, Garneau M, David F, Mamer OA, et al. Interference of 3-hydroxyisobutyrate with measurements of ketone body
concentration and isotopic enrichment by gas chromatography-mass spectrometry.
Analytical biochemistry. 1988 Aug 15;173(1):96-105. PubMed PMID: 3189805.
168
110. Kirsch JR, D'Alecy LG. Hypoxia induced preferential ketone utilization by rat
brain slices. Stroke; a journal of cerebral circulation. 1984 Mar-Apr;15(2):319-23.
PubMed PMID: 6422588.
111. Yudkoff M, Daikhin Y, Nissim I, Lazarow A, Nissim I. Ketogenic diet, amino acid metabolism, and seizure control. Journal of neuroscience research. 2001 Dec
1;66(5):931-40. PubMed PMID: 11746421.
112. McKenna MC. The glutamate-glutamine cycle is not stoichiometric: fates of glutamate in brain. Journal of neuroscience research. 2007 Nov 15;85(15):3347-58.
PubMed PMID: 17847118.
113. Bartnik-Olson BL, Oyoyo U, Hovda DA, Sutton RL. Astrocyte oxidative metabolism and metabolite trafficking after fluid percussion brain injury in adult rats.
Journal of neurotrauma. 2010 Dec;27(12):2191-202. PubMed PMID: 20939699. Pubmed
Central PMCID: 2996847.
114. Yudkoff M, Daikhin Y, Nissim I, Horyn O, Lazarow A, Luhovyy B, et al.
Response of brain amino acid metabolism to ketosis. Neurochemistry international. 2005
Jul;47(1-2):119-28. PubMed PMID: 15888376.
115. Patel AB, de Graaf RA, Mason GF, Rothman DL, Shulman RG, Behar KL. The contribution of GABA to glutamate/glutamine cycling and energy metabolism in the rat cortex in vivo. Proceedings of the National Academy of Sciences of the United States of
169
America. 2005 Apr 12;102(15):5588-93. PubMed PMID: 15809416. Pubmed Central
PMCID: 556230.
116. Mason GF, Rothman DL, Behar KL, Shulman RG. NMR determination of the
TCA cycle rate and alpha-ketoglutarate/glutamate exchange rate in rat brain. Journal of
cerebral blood flow and metabolism : official journal of the International Society of
Cerebral Blood Flow and Metabolism. 1992 May;12(3):434-47. PubMed PMID: 1349022.
117. Kunnecke B, Cerdan S, Seelig J. Cerebral metabolism of [1,2-13C2]glucose and
[U-13C4]3-hydroxybutyrate in rat brain as detected by 13C NMR spectroscopy. NMR in biomedicine. 1993 Jul-Aug;6(4):264-77. PubMed PMID: 8105858.
118. Kombu RS, Brunengraber H, Puchowicz MA. Analysis of the citric acid cycle intermediates using gas chromatography-mass spectrometry. Methods in molecular biology. 2011;708:147-57. PubMed PMID: 21207288.
119. Fernandez CA, Des Rosiers C, Previs SF, David F, Brunengraber H. Correction of
13C mass isotopomer distributions for natural stable isotope abundance. Journal of mass
spectrometry : JMS. 1996 Mar;31(3):255-62. PubMed PMID: 8799277.
120. Olstad E, Olsen GM, Qu H, Sonnewald U. Pyruvate recycling in cultured neurons from cerebellum. Journal of neuroscience research. 2007 Nov 15;85(15):3318-25.
PubMed PMID: 17304574.
170
121. Brekke E, Walls AB, Norfeldt L, Schousboe A, Waagepetersen HS, Sonnewald U.
Direct measurement of backflux between oxaloacetate and fumarate following pyruvate carboxylation. Glia. 2012 Jan;60(1):147-58. PubMed PMID: 22052553.
122. Lebon V, Petersen KF, Cline GW, Shen J, Mason GF, Dufour S, et al. Astroglial contribution to brain energy metabolism in humans revealed by 13C nuclear magnetic resonance spectroscopy: elucidation of the dominant pathway for neurotransmitter glutamate repletion and measurement of astrocytic oxidative metabolism. The Journal of neuroscience : the official journal of the Society for Neuroscience. 2002 Mar
1;22(5):1523-31. PubMed PMID: 11880482. Pubmed Central PMCID: 2995528.
123. Cerdan S, Kunnecke B, Seelig J. Cerebral metabolism of [1,2-13C2]acetate as detected by in vivo and in vitro 13C NMR. The Journal of biological chemistry. 1990
Aug 5;265(22):12916-26. PubMed PMID: 1973931.
124. Sonnewald U, Westergaard N, Schousboe A, Svendsen JS, Unsgard G, Petersen
SB. Direct demonstration by [13C]NMR spectroscopy that glutamine from astrocytes is a precursor for GABA synthesis in neurons. Neurochemistry international. 1993
Jan;22(1):19-29. PubMed PMID: 8095170.
125. Waagepetersen HS, Qu H, Hertz L, Sonnewald U, Schousboe A. Demonstration of pyruvate recycling in primary cultures of neocortical astrocytes but not in neurons.
Neurochemical research. 2002 Nov;27(11):1431-7. PubMed PMID: 12512946.
171
126. Olstad E, Qu H, Sonnewald U. Glutamate is preferred over glutamine for
intermediary metabolism in cultured cerebellar neurons. Journal of cerebral blood flow
and metabolism : official journal of the International Society of Cerebral Blood Flow and
Metabolism. 2007 Apr;27(4):811-20. PubMed PMID: 17033695.
127. Amaral AI, Teixeira AP, Hakonsen BI, Sonnewald U, Alves PM. A comprehensive metabolic profile of cultured astrocytes using isotopic transient metabolic flux analysis and C-labeled glucose. Frontiers in neuroenergetics. 2011;3:5. PubMed
PMID: 21941478. Pubmed Central PMCID: 3171112.
128. Lapidot A, Gopher A. Cerebral metabolic compartmentation. Estimation of glucose flux via pyruvate carboxylase/pyruvate dehydrogenase by 13C NMR isotopomer analysis of D-[U-13C]glucose metabolites. The Journal of biological chemistry. 1994
Nov 4;269(44):27198-208. PubMed PMID: 7961629.
129. Tallian KB, Nahata MC, Tsao CY. Role of the ketogenic diet in children with intractable seizures. The Annals of pharmacotherapy. 1998 Mar;32(3):349-61. PubMed
PMID: 9533066.
130. Leenders KL, Perani D, Lammertsma AA, Heather JD, Buckingham P, Healy MJ, et al. Cerebral blood flow, blood volume and oxygen utilization. Normal values and effect of age. Brain : a journal of neurology. 1990 Feb;113 ( Pt 1):27-47. PubMed PMID:
2302536.
172
131. Schwenk WF, Berg PJ, Beaufrere B, Miles JM, Haymond MW. Use of t-
butyldimethylsilylation in the gas chromatographic/mass spectrometric analysis of
physiologic compounds found in plasma using electron-impact ionization. Analytical biochemistry. 1984 Aug 15;141(1):101-9. PubMed PMID: 6496921.
132. Marin-Valencia I, Good LB, Ma Q, Malloy CR, Patel MS, Pascual JM. Cortical metabolism in pyruvate dehydrogenase deficiency revealed by ex vivo multiplet (13)C
NMR of the adult mouse brain. Neurochemistry international. 2012 Dec;61(7):1036-43.
PubMed PMID: 22884585.
133. Lapidot A, Haber S. Effect of endogenous beta-hydroxybutyrate on brain glucose metabolism in fetuses of diabetic rabbits, studied by (13)C magnetic resonance spectroscopy. Brain research Developmental brain research. 2002 Apr 30;135(1-2):87-99.
PubMed PMID: 11978397.
134. Lapidot A, Haber S. Effect of endogenous beta-hydroxybutyrate on glucose metabolism in the diabetic rabbit brain: a (13)C-magnetic resonance spectroscopy study of [U-(13)C]glucose metabolites. Journal of neuroscience research. 2001 Apr
15;64(2):207-16. PubMed PMID: 11288149.
135. Suda S, Shinohara M, Miyaoka M, Lucignani G, Kennedy C, Sokoloff L. The lumped constant of the deoxyglucose method in hypoglycemia: effects of moderate hypoglycemia on local cerebral glucose utilization in the rat. Journal of cerebral blood
173
flow and metabolism : official journal of the International Society of Cerebral Blood
Flow and Metabolism. 1990 Jul;10(4):499-509. PubMed PMID: 2347881.
136. Schuier F, Orzi F, Suda S, Lucignani G, Kennedy C, Sokoloff L. Influence of
plasma glucose concentration on lumped constant of the deoxyglucose method: effects of
hyperglycemia in the rat. Journal of cerebral blood flow and metabolism : official journal
of the International Society of Cerebral Blood Flow and Metabolism. 1990
Nov;10(6):765-73. PubMed PMID: 2211874.
137. Kapoor R, Spence AM, Muzi M, Graham MM, Abbott GL, Krohn KA.
Determination of the deoxyglucose and glucose phosphorylation ratio and the lumped
constant in rat brain and a transplantable rat glioma. Journal of neurochemistry. 1989
Jul;53(1):37-44. PubMed PMID: 2723662.
138. Ng CK, Holden JE, DeGrado TR, Raffel DM, Kornguth ML, Gatley SJ.
Sensitivity of myocardial fluorodeoxyglucose lumped constant to glucose and insulin.
The American journal of physiology. 1991 Feb;260(2 Pt 2):H593-603. PubMed PMID:
1996702.
139. Hertz L, Zielke HR. Astrocytic control of glutamatergic activity: astrocytes as stars of the show. Trends in neurosciences. 2004 Dec;27(12):735-43. PubMed PMID:
15541514.
140. Spence AM, Muzi M, Graham MM, O'Sullivan F, Krohn KA, Link JM, et al.
Glucose metabolism in human malignant gliomas measured quantitatively with PET, 1-
174
[C-11]glucose and FDG: analysis of the FDG lumped constant. Journal of nuclear
medicine : official publication, Society of Nuclear Medicine. 1998 Mar;39(3):440-8.
PubMed PMID: 9529289.
175