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.
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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 CMR glc by FDG-PET.........19
2.6.2 Animal Anesthesia System Development ..................................................................20
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2.6.3 Unreported CMR glc data...........................................................................................22
2.6.4 Unreported CMR glc 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 CMR glc ...................................................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 CMR glc 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
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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
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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
2 DERIVATION OF THE COMPETITIVE REACTIONS OF GLUCOSE AND 18FDG................ 139
3. FINDING THE PHOSPHORYLATION RATE OF GLUCOSE AND 18FDG ........................... 141
4. LINKING THE PHOSPHORYLATION RATE OF GLUCOSE AND 18FDG ........................... 144
5. ESTIMATION OF 18FDG KINETIC CONSTANTS .......................................................... 145
6. ESTIMATION OF THE LUMPED CONSTANT (LC) ........................................................ 146
BIBLIOGRAPHY ......................................................................................................... 149
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Dedication
This work is dedicated to my wife and parents.
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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 HL09293301, R21 NS062048-01 and Mouse Metabolic Phenotyping Center, MMPC U24 DK76169.
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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 (CMR glc )
decreases linearly (9% per 1mM blood ketone body increase) in rats with diet-induced
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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 γaminobutyric 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.
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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 (CMR glc ) 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 CMR glc 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
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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
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List of Tables
Table 2.1 Unpublished data of meta-analysis of the studies on CMR glc during ketosis. 31
Table 2.2 Unpublished data on KG and STD rat CMR glc , with hyperoxia (100% O 2
anesthesia) . ....................................................................................................................... 32
Table 3.1 Physiological Parameters .................................................................................. 58
Table 3.2 CMR glc 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
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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
13
Carbon-13
CAC
Citric Acid Cycle (Same as TCA, or tricarboxyl acid cycle)
CBF
Cerebral Blood Flow
CIT
Citrate
CMR
Cerebral Metabolic Rate
CMR glc
Cerebral Metabolic Rate of Glucose
C
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CMR ket
Cerebral Metabolic Rate of Ketone Bodies
CMR o2
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
18
Fluorine-18
FDG
18
FDG-6-P
18
FUM
Fumarate
FW
Formula Weight (or molecular weight per mole)
G-6-P
Glucose-6-phosphate
GABA
γ-aminobutyric acid
F
[F]-2-Fluoro-Deoxy-Glucose
[F]-2-Fluoro-Deoxy-Glucose-6-P
xv
GAD
Glutamate acid decarboxylase
GC-MS
Gas Chromatography Mass Spectrometry
GLC
Glucose
GLN
Glutamine
GLU
Glutamate
2
Deuterium
H
HPLC
High-Performance Liquid Chromatography
HIF
Hypoxia-Inducible Factors
HMG-CoA
Hydroxymethylglutaryl-coA
IS
Internal Standard
KB
Ketone bodies
KG
Ketogenic diet
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
15
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
N-Acetyl-Aspartate
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 (CMR glc ). 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
CMR glc 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 CMR glc , 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 GCMS 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 CO 2 ) 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 35 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 CMR glc (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 (C 4 H 8 O 3 , FW=104) and AcAc (C 4 H 6 O 3 , 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 AcAccoA 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). Dietinduced 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 13 hours (15, 55-58) can cause human hyperketonemia. It is also known that infusion of
KB can reset the coupling of CBF and CMR glc and CMR ket , 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 CO 2
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-6phosphate (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 HMGCoA(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 CMR glc 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,
CMR ket , is defined as the rate of AcAc oxidation to AcAc-coA, in micromole per 100g
wet tissue per minute (μmol/100g/min). For rats, CMR ket is about 1-20 times less than
CMR glc (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 CMR glc 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; V u 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 , C A
and C V 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 CMR glc = CBF× (C A -C V ),
divided by brain sample weight. This measurement scheme served as standard for years,
and it worked for CMR glc , CMR ket , and CMR o2 . However, this method had obvious
drawbacks: i) the brain arterial and venous sampling is highly invasive ii) measurement
would be global CMR glc , does not allow regional CMR glc measurement.
2.5.2 Compartmental Modeling method (Measurement of reaction)
More than two decades later, Sokoloff et al published seminal works on estimating the
CMR glc by studying the phosphorylation rate, using a trapping tracer 2-14[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 V m
and K m held constant ratios between the tracer (DG) and tracee (glucose), a lumped
constant (LC) was assumed. The CMR glc thus can be estimated if tissue and blood (or
plasma) activities are known during the study period. CMR glc 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 CMR glc , CMR ket and CMR o2
estimations.
CMR glc 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 2tissue 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 CMR glc .
CMR ket is more difficult to measure than CMR glc because of the lack of a trapping
tracer. Significant estimation error arises when the labeled tracer administered to the
subject loses in CO 2 (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 CMR ket ; on the other hand, it may have been the
tracer loss to CO 2 from the non-trapping tracer measured by PET or other reaction-based
methods, such that severe underestimation made the apparent CMR ket 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 pseudoketogenesis, 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).
CMR o2 is a key index in studying the brain metabolism. Essentially, all oxidative fuel
metabolism study in the brain relies on the assumption about the CMR o2 . Alternatively,
the CMR o2 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 CMR o2 shares the same principles for CMR ket and CMR glc
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 H 2 O had been reported (90) . Due to the technical demands for a dedicated onsite 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 K 1 * , K 2 * , and K 3 * estimation:
Nonlinear fitting method requires good initial guess to obtain a good estimate. It is
crucial that K 1 * , K 2 * be in the range of 0.1-1, while K 3 * should be one magnitude lower.
Alternatively, graphic method to estimate the combination of K 1 * , K 2 * and K 3 * can be
used. In both cases, the steady state CMR glc 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 CMR glc 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 CO 2 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 CO 2 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 CO 2 . Assuming ideal non compressible gas for CO 2 at room temperature, using
Avogadro's constant such that 1mol of CO 2 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 CO 2 , 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 CMR glc 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 CMR glc 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
Pa O2 , 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 CMR glc 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)
Year
Journa
l
Al
Mudall
al
1995
Neurol
Chang
1993
Can J
Physio
Phar
Corddr
y
1982
J
Neuro
chem
Crane
1985
JCBF
M(101
)
same
as
above
Dalqui
st
1976
Pediat
r Res
same
as
above
same
as
above
Same
as
above
Hassel
bach
1994
JCBF
M
Hassel
bach
1996
AJP
Hawki
ns
1986
AJP
Hawki
ns
1971
Bioche
mJ
same
speci
es
An
est
hes
ia
Tech
Method
ketosis
method
Rats
Y
2DG
KG diet
NS
Dogs
Y
Kety
Schmidt
BHB
Infusion
NA
Rats
N
2DG
3day fast
or BHB
Infusion
N
Rats
Y
and
N
modified
uptake
method
Diffusion
and Kety
Schmidt
2day fast
Change
87.30
83.91
Comments
0.11
0.66
KG diet has calorie restriction; KG diet for
three weeks but calory restriction.
N/A
5
0.48
2.34
Cerebellum; N.S decrease. Only look at
frontal cortex
Not
Repo
rted
reduction to 63% after 5 days in
pentobarbital anesthetized rats;
Hemispheres
Not
Repo
rted
reduction to 78.5% in hemispheres and
frontal cortex
Not
Rep
orte
d
Not
Rep
orte
d
NS
NS
2day fast
Not
Reported
Not
reported
157.14
0.95
unit: umol/mg DNA /min; In adults. This
result is weird
2day fast
Not
Reported
Not
reported
62.50
1.58
unit: umol/mg DNA /min; In adults This is
also sort of weird
3 day
fast
Not
Reported
Not
reported
80.95
2.44
unit: umol/mg DNA /min; In adults
Not
Reported
Not
reported
75.00
2.00
unit: umol/mg DNA /min; In adults
Yes
Yes for
global, but
N.S for
regional
No change
74.19
0.28
3.20
LC no change. Kety's method: -24%
39.22
67.98
0.30
Not
Rep
orte
d
2.40
BHB utilization up 5 folds also
NA
Only measured Cmrket contributes 3%
0.23
2.81
Did not measure CMRglc or CMRket.
Only a-v concentrations
Infant
rat
Y
adult
rat
Y
Diffusion
and Kety
Schmidt
Diffusion
and Kety
Schmidt
Infant
rat
Y
Diffusion
and Kety
Schmidt
3 day
fast
Hum
an
N
FDG
PET
3.5 day
Fast
Hum
an
N
FDG
PET +
Kety
Rats
Y
modified
uptake
BHB
infusion
Starve 2
or 4
days. No
ctrl
Y
Diffusion
and Kety
Schmidt
Fast
2day
NA
NA
NA
fast 3
day
3.03
fast 4
day
3.34
Infuse
acac
1.40
Infuse
acac 2
7.28
same
same
same
suckli
ng
rats
Hypoxia Vs. Normoxia study, did not
measure CMRglc. Only the extraction
fraction measured.
NS
Y
62.96
Ctrl
KG
Total
keton
e
NS
adult
rat
Adult
rats
CMRglc
changed?
Change
after the
effect, %
30
Hassel
bach
1995
AJP
Owen
1967
J Clin
Invest
Pan
2002
JCBF
M
Redie
s
1989
AJP
Ruder
man
1974
Bioche
mJ
Linde
2005
JCBFM
Mans
1987
Metab
olic Br
Diseas
e
Linde
1999
Acta
Physiol
Scand
Prins
2009
J
Neurot
rauma
Jiang
2011
JCBFM
Bentou
rkia
2009
AJP
Issad
1987
Bioche
mJ
Cherel
1988
Metab
olism
same
as
above
Hum
an
Hum
an
(Obe
se)
N
Kety
Schmidt
3.5 day s
fast
NA
N
Kety
Schmidt
5-6
weeks
fast
NA
Hum
an
N
NMR
2 hr BHB
infusion
NA
Hum
an
N
FDG
PET +
Kety
20-24
Day fast
Yes
No change
Kety
Schmidt
1-2 days
fast
NA
N/A !
Kety
Schmidt
Ketone
Infusion
2 days
fast
Yes
No
NA
Did not induce ketosis. New CBF measure
method
NA
KG diet as therapeutic (Not protective)
Lactate up and recovered from the trauma
Rats
Rats
Y
Y
and
N
Rats
N
modified
Autoradio
graphy
Rats
N
Kety
Schmidt
Rats
Y
Autoradio
graphy
Rats
Y
NMR
KG diet, 7
days
Fast
1.5d ,
then inf
BHB
Rats
Y
C11 PET
KG diet
and fast
2day
Gjedde
1975
AJP
2day fast
NS
Rats
Y
Autoradio
graphy
up to 3
day fast
NS
up to 8.5
up to 12
days fast
Kety
Schmidt
7.83
Did not measure CMRglc or CMRket
Unk
now
n
2.25
Did not measure CMRglc
55.17
0.05
4.27
LC decreased by 25% in ketosis
83.00
0.15
2.58
Only reports A-V diff; only significant for
2days fast; Lactate down in fast rats. This is
glucose oxidation, not uptake or utilization
86
0.23
Not
Rep
orte
d
Lactate Raised in the awake, but not
anesthetized. No CMRglc change
0.64
88.00
50.00
0.33
4.20
1.35
9.40
Unsu
re
NA
Autoradio
graphy
Y
No change of Glucose influx
(unidirectional), did not measure CMRglc
29.00
NA
N
Rats
3.17
NA
64.81
Rats
same
as
above
No change
whole body
CMRglc
decreased
40%
0.33
Lacks real control animal
Pure Oxygen Anesthesia; only has CMRket
1.95
Not significant different in the brain
Too small
to tell
1.30
glucose utilization index, not CMRglc
NS
83.33
1.15
NS
66.67
0.17
5 day fast
94.23
Lactate unchanged.
0.10
weird
Only measured BUI
Table 2.1 Unpublished data of meta-analysis of the studies on CMR glc during ketosis.
NS: not significant. NA: not available.
31
Age
Weight
grams
FDG Dose Injected
Dose per g
uCi
Rat1
Rat2
Rat3
Rat4
Rat5
Rat6
Rat7
P56
P60
P61
P65
P75
P79
P62
229
Died 140min
post-surgery
267
270
292
294
276
325
654
784
808
659
729
734
2.45
2.90
2.77
2.24
2.64
2.26
13.5
19
19
19
18
18.5
17.5
2.4
2.2
2.3
N/A
1.1
1.1
0.4
N/A
N/A
N/A
N/A
N/A
4.7
6.6
5.78
N/A
N/A
N/A
N/A
42-44
41-43
43-45
45-48
43-45
45-47
Yes
Delay 40sec, Heart
Input Function
H0mi
n=42
Very
good
H10=
47
Very
good
yes
Very
good
uCi/g
Time btw fast & injct
hrs
Pre-Img [BHB]
mM
Pre-Img [Glc] in whole blood
mM
Pre-Img [Glc] in plasma (Cp)
mM
Hematocrit (%)
Hematocrit stable Through
Imaging?
Yes
PET
Heart
Input function quality
Brain Image TAC quality
Breathe Rate at steady state
b/min
Steady state sampling time min
post injection
Plasma glucose At steady state
mM
[BHB] At steady state
L-Lactate at steady state
mM
mM
Haemoglobin Oxygen Saturation
at steady State %
pH at steady state
Pco2 at steady state
mmHg
Po2 at steady state
mmHg
CMRglc,trapping,ODE method
(K1-k3) umol/100g/min
CMRglc,nontrapping,ODE (K1k4) umol/100g/min
CMRglc, trapping, Patlak (K1-k3)
umol/100g/min
97%-18%
H90min=3
9%
Very
Good
Wokeup
@82min
51
32
41
35
42
37
48
51,60
52
55
45
46
7.37
5.48
6.95
5.41
7.33
9.53
3.2
2.2
1.7
2.1
2.2
0.9
1.55
1.05
1.15
1
0.99
0.85
99
98.9
99.05
97.95
97.6
7.31
7.35
7.3
N/A
N/A
55
56
45
N/A
N/A
314(3
7C°)
152(25c°)
104(25C°)
N/A
N/A
99.09
7.18(Wr
ong?)
has
Error
333
(wrong?
)
75.8
61.09
42.43
81.89
94.8
60.96
64.94
96
67.57
63.73
43.49
77.06
Table 2.2 Unpublished data on KG and STD rat CMR glc , with hyperoxia (100% O 2
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 (CMR glc ) and degree or duration of ketosis remains
uncertain. To investigate if CMR glc decreases with chronic ketosis, 2-[18F]fluoro-2deoxy-D-glucose in combination with Positron Emission Tomography, was applied in
anesthetized young adult rats fed three weeks of either standard or ketogenic diets.
CMR glc (µmol/min/100g) was determined in the cerebral cortex and cerebellum using
Gjedde-Patlak analysis. The average CMR glc 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 CMR glc 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 CMR glc 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 (CMR glc ) 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 βhydroxybutyrate (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 lowcarbohydrate) 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 CMR glc 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 CMR glc with 3-5 days of fasting in humans(15, 17, 103)while in other studies
there were no significant changes in CMR glc (46, 51, 75, 102).
The goal of this study was to estimate CMR glc in chronic ketotic rats and to determine if
ketosis induces a metabolic adaptation through changes in glucose phosphorylation rates.
The effects of ketosis on CMR glc 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 PETFDG 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
described.31 Arterial blood gas parameters (pH, P aO2 and P aCO2 ) were measured at t=0, 45
min (ABL5 Radiometer, Copenhagen, Denmark); 45 minutes was considered the end
point where CMR glc 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, microcapillary 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 premeasured as 8.3μl/37mm, therefore by measuring the length of the whole blood portion,
whole blood activity per volume (C wb *), 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 (C p *) 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 C wb *, was converted to C p * by a factor R. This
follows
R=
C *p (t = 3.5)
*
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
CMR glc . 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 K i , which
follows:
43
K i* =
k1*k3*
k 2* + k3*
While k 1 * is the 18FDG transport rate constant (/min) to the brain tissue, k 2 * is the 18FDG
reverse transport rate constant from tissue to the plasma (/min) and k 3 * is the 18FDG
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, C p , was used to generate the final CMR glc ,
which follows: (26, 27)
CMRglc =
K i*C 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 CMR glc (µmol/100g/ min) measured in both cerebral hemispheres
and cerebellums are shown in Table 2. There were no significant differences in CMR glc
between the left and right hemispheres The PET analysis revealed that diet induced
ketosis resulted in a significant decrease in the average CMR glc in both cerebral
hemispheres and cerebellum compared to STD group. CMR glc was significantly lower in
the left and right cerebral hemispheres compared to the cerebellum, in both dietary
groups.
45
The CMR glc 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 CMR glc
decreased with increasing ketosis. The calculated CMR glc 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, (CMR glcright = -2.9×
([BHB]+[AcAc]) + 34.9; R² = 0.59); whereas the cerebellar region was significantly
higher (CMR glc = -3.7× ([BHB]+[AcAc]) + 43.9; R² = 0.59) compared to Cerebral Cortex.
These data highlight the proportional change in CMR glc with increasing ketosis; thus for
every 1mM increase in total plasma ketone bodies CMR glc decreases by ~9%.
3.4.3 Meta-analysis of CMRglc in Ketotic Subjects
Meta-Analysis of CMR glc reduction in ketotic subjects (human or rats) was shown in
Figure 2. All data were collected from previously reported studies where CMR glc was
measured and level of ketosis was reported. CMR glc 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 CMR glc 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 CMR glc following 3.5 days of fasting (45), in humans
that were fasted for 3 weeks the authors reported a 46% decrease in CMR glc 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 CMR glc 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 CMR glc
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 (CMR ket ) replaces CMR glc
following three weeks of diet-induced ketosis.
Previous studies measuring CMR glc in ketotic subjects report either changes in CMR glc
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 CMR glc
during “metabolic adaptation” to ketosis has not been clearly described. Using PET-FDG
imaging, the focus of this study was to determine if CMR glc decreases with increasing
ketosis in adult anesthetized diet-induced ketotic rats. CMR glc 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 CMR glc (51). The study failed to detect significant changes in CMR glc
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
CMR glc with ketosis.
49
The most striking information obtained from our study was the correlative finding that
CMR glc 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 CMR glc in ketotic subjects, as our meta-analysis (Figure 3.2) also showed the
same linear association between level of ketosis and corresponding changes in CMR glc .
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 CMR glc with a small degree of ketosis. This was the case with our
previous study in diet-induced ketotic rats where CMR glc 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 CMR glc (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 CMR glc .
In summary, CMR glc 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 CMR glc with ketosis
was reported. Nevertheless, the maximum percent ketone bodies that can replace glucose
oxidation still need to be determined. A quantitative understanding of CMR glc and
CMR ket 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 (CMR glc ) 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 CMR glc in each
region was calculated with Gjedde-Patlak analysis and plotted as a function of the
measured plasma total ketone body concentrations; the equation CMR glc = [slope ×
53
plasma total ketone concentrations + CMR glc 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 CMR glc 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 CMR glc reduction in ketotic subjects (human or rats).
All data were collected from previously reported studies where CMR glc was measured
and level of ketosis was reported. Data were normalized (%) against control state (nonfasted, 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 CMR glc , (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, CMR glc , was
indirectly calculated by O 2 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 CMR glc reduction, (h) Data from Ruderman et al, (45)1-2 days fasted rats, AV 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 CMR glc 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 CMR glc .
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
358
±
33
360
±
26
pH
7.35
±
0.04
7.32
±
0.03
PaO 2 (mm Hg)
112
±
22
104
±
20
53
±
5
50
±
5
Physiological Parameters
Breath Rate (Br/min)
Hematocrit (%)
Heart Rate (Beats/min)
Plasma Metabolic Parameters b
63
48
378
±
±
±
3
2
61
63
47
365
±
±
±
5
2
37
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)
D-Glucose (mM)
1.00
11.51
±
±
0.10
1.08
0.77
10.71
±
±
0.18*
1.87
Weight (g)
Blood Gas Parameters
a
PaCO 2 (mm Hg)
b
*
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 CMR glc .
58
Table 3.2 CMR glc in the volumes of interest (VOI)
VOI
Left Hemisphere
STD diet (n=9)
33.5 ± 4.9
KG diet (n=10)
23.2 ± 4.8*
Right Hemisphere
Hemispheres
Average
Cerebellum
32.3 ± 4.7
22.8 ± 5.2*
32.9 ± 4.7
23.0 ± 4.9*
41.2 ± 6.4**
29.3 ± 8.6*, **
*P<0.05 compared to STD diet group, **P<0.05 compared to hemispheres
CMR glc (µmol/100g/min)
Cerebral metabolic rate for glucose (CMR glc ) by positron emission tomography and 2[18F] fluoro-2-deoxy-D-glucose in rats fed standard or ketogenic diets. CMR glc (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
MacroNutrients
Starch % by weight
D glucose % by
weight Fructose %
by weight
Sucrose % by
weight Lactose %
Saturated % by weight
Monounsaturated % by
weight Polyunsaturated %
Protein % by weight
Fat % by weight
Carbohydrates % by
weight
Protein % by energy
Fat % by energy
carbohydrates % by energy
STD diet
(Labdiet 5ANE
RMH3000)
(Research Diets D12369B)
32.53
0.12
0.16
0.97
0.00
0.00
0.00
0.00
<1%
0.00
1.60
1.61
1.85
22.5
5.5
51.6
4.2
26.0
14.3
59.7
19.45
33.04
14.56
17.3
67.0
<1%
8.7
10.4
89.1
0.5
60
KG diet
Minerals
Ca %
P%
Mg %
K%
S%
Na %
Cl %
Cr ppm (STD) or %(KG) *
Cu ppm (STD) or %(KG) *
I ppm (STD) or % (KG) *
Fe ppm (STD) or % (KG) *
Mn ppm (STD) or % (KG) *
Se ppm (STD) or % (KG) *
Zn ppm (STD) or % (KG) *
F ppm
Co ppm
Vitamins
Carotene ppm
Vitamin A IU/g
Vitamin D3 IU/g
Vitamin E IU/g
Vitamine K ppm
Thiamin Hydrochloride
ppm
Riboflavin ppm
Niacin ppm
Pantothenic Acid ppm
Folic acid ppm
Pyridoxine ppm
Biotin ppm
Vitamin B12 mcg/kg
Choline Chloride ppm
Ascorbic Acid ppm
STD diet
KG diet
RMH3000)
(Research Diets D12369B)
1.06
0.76
0.24
0.93
0.33
0.21
0.37
0.91
14
0.98
375
99
0.38
116
18.3
0.4
0.90
0.69
0.09
0.62
0.06
0.17
0.28
0.00035
0.00104
0.00003
0.00779
0.01022
0.00003
0.00502
0
0
1.2
18
2.4
75
1.9
0
4000 **
1000 **
50 **
312.5 **
10
14.3
60
13
1.2
8.17
0.4
77
1999
0
6000 **
6000 **
30000 **
16000 (calcium salt) **
2000 **
7000 **
2.0 **
10 **
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- 13 C]
glucose or [U- 13 C] acetoacetate for 60 min. The measured percent contribution of
glucose or ketone bodies to oxidative metabolism was analyzed by measuring the 13Clabel 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- 13 C] glucose or [U- 13 C]
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-[ 18 F]-Fluorodeoxyglucose
( 18 FDG) 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, 13Cglucose 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- 13 C]glu- cose
or [U- 13 C]AcAc and fed either standard (STD) or ketogenic (KG) diets. [U- 13 C] glucose
(99.8 %) was solved in 0.9 % NaCl solution to a final concentration of 38.7 mM. [U13C]AcAc was derived from [U- 13 C] ethyl-acetoacetate, as previously described ( 1 0 9 )
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- 13 C] 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 background 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 dietinduced 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
(CMR o2 ) stays relatively constant in ketosis, the reported reduction of CMR glc
(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 CMR ket 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 12h12h 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 Sigma82
Aldrich. (St. Louis, MO, USA, Cat# CX1474), as previously described (118) and
concentrated to 137 mM (107). All other reagent chemicals were purchased from SigmaAldrich. 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 GasChromatography 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 selfturning, 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 CMR glc reduction (phosphorylation rate) in dietinduced ketotic rats, where we showed approximately 9% decrease of CMR glc for each
1mM of total ketone body increaseand a maximum of ~35% of CMR glc 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 U13CAcAc, 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 glutamateglutamine (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/U13CGlucose(n=4)
KG/U13CGlucose(n=6)
STD/U13CAcAc(n=7)
KG/U13CAcAc(n=3)
81
±
12
69
±
7
68
±
6
79
±
1ǂ
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
Age
Physiological Parameters
Breath Rate (/min)
62
±
3
67
±
5
68
±
4
70
±
1
Hematocrit (%)
45
±
1
44
±
2
42
±
2
48
±
2ǂ
BHB (mM)
0.29
±
0.17
2.28
±
0.54*
0.25
±
0.10
2.24
±
0.81ǂ
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
Plasma Parameters
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/U13CGlucose(n=4)
KG/U13CGlucose(n=6)
STD/U13CAcAc(n=7)
KG/U13CAcAc(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: βhydroxybutyrate.
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, βhydroxybutyrate; 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 (CMR o2 that come from both CMR glc and CMR ket ), 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 CMR glc decreases in aged human and
animals (100, 130), with more recent publications in 2012 (85) pointing out that the
global glucose utilization may decrease (CMR glc 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
[1,2-13C 2 ]GABA from PDH activities and [3,4-13C 2 ]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 glutamateglutamine 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 (CMR glc )
at steady state measurement by FDG-PET method.
We have recently reported that the diet-induced ketosis reduces the CMR glc 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 CMR glc . 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 CMR glc estimation significantly
and undermine our interpretations. As of 2013, the LC had never been reported in dietinduced ketotic rats. To validate our previous CMR glc 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 CMR glc 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 CMR glc by FDG-PET, one would need to assume an appropriate value of
CMR FDG to CMR glc ratio, which requires a Lumped Constant (LC; CMR glc =CMR FDG /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 CMR glc 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 CMR glc 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 CMR glc
indeed decreases during diet-induced ketosis; if LC increases, then our previous CMR glc
data would be an overestimation, i.e, diet-induced ketosis reduce the CMR glc more; lastly,
if LC decreases, then our previous CMR glc overestimates, and thus our thought that
CMR glc 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 LCMS 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.
Subject
Phy/Path
models
Induction
Method
Trace
r
Blood
Ketone
range
Baselin
e LC
studied
LC
Values
1977
Rat
Normal
N/A
DG
Unknown
0.48
N/A
(27)
1979
Human
Normal
N/A
FDG
Unknown
0.42
N/A
(100)
1983
Rat
12-24 month
old
N/A
DG
Unknown
0.50
decreased
to 0.42
(137)
1988
Rat
Glioma
N/A
DG
Unknown
0.52
1.17
(17)
1989
Human
Ketosis
3 week
fast
FDG
Up to
4.3mM
0.57
Decrease
d to 0.43
(135)
1990
Rat
Hypoglycemia
Insulin
infusion
DG
Unknown
0.48
Increased
to 1.20
(136)
1990
Rat
Hyperglycemi
a
Glucose
infusion
DG
Unknown
0.48
decreased
to 0.36
(15)
1994
Human
Ketosis
Fasted
3.5 days
FDG
Total up
to 3.2mM
0.70
No
change
(56)
1996
Human
Ketosis
Ketone
infusion
FDG
Total up
to 2.4mM
N/A
N/A
(140)
1998
Human
Malignant
tumor
N/A
FDG
Unknown
0.86
increased
to 1.40
(105)
2006
Rat
Normal
N/A
FDG
Unknown
0.71
N/A
Referenc
e No.
Year
(26)
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]
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
value[nCi/cc]
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
brain and eventually lost to CO 2 .
18
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 p ,Ce : Plasma and intracellular glucose concentrations (mM)
Cm : Glucose-6-P concentration (mM)
137
C *p ,Ce* : Plasma and intracellular labeled FDG concentrations (nCi/ml)
Cm* : FDG-6-P concentration (nCi/ml)
Transport and metabolic processes
Dynamic molar balances of intracellular endogenous glucose and glucose-6-P lead to
(1.1)
dCe
= k1C p − k2Ce − R(Ce , Ce* ) + k4Cm
dt
(1.2)
dCm
= R(Ce , Ce* ) − k4Cm − k5Cm
dt
Where R(Ce ,Ce* ) characterizes the forward competitive reaction rate to form glucose-6-P.
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
(1.3)
dCe*
= k1*C *p − k2*Ce* − R* (Ce ,Ce* )
dt
(1.4)
dCm*
= R* (Ce ,Ce* )
dt
138
Where R* (Ce ,Ce* ) characterizes the forward competitive reaction rate to form 18FDG-6-P:
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-chemicalengineering-topics-i-introduction-to-biocatalysis-fall-2004/lecture-notes/lecture4.pdf)
(2.1)
k1


→[SE] k
→[E] + [PS ]
[S] + [E] ←
k2
(2.2)
k3


→[P ]
[I] + [E] ←
I
k4
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 P s .
The reaction rate equations are
139
d[S ]
=
−k1[ S ][ E ] + k2 [ SE ];
dt
(2.3)
d [ PS ]
== k[ SE ]
dt
d [ PI ]
d[I ]
=
−k3 [ I ][ E ] + k4 [ PI ] =
−
dt
dt
For the substrate and the inhibitor at equilibrium, we set the derivatives equal to zero and
obtain the equilibrium constants:
(2.4)
[ E ][ S ] k2
Km =
=
[ SE ]
k1
(2.5)
[ I ][ E ] k4
[ E ][ I ]
Ki =
= ⇒ [ PI ] =
[ PI ]
k3
Ki
⇒
[ E ][ S ]
[ SE ] =
Km
Therefore the total concentration of compounds that contains enzyme would be
(2.6)
[ E0 ] =[ E ] + [ SE ] + [ PI ] =[ E ](1 +
[S ] [ I ]
+ )
K m Ki
from (2.4) and (2.6) we find the intermediate concentration :
(2.7)
[ SE ] =
[ E0 ]
[S ]
K m (1 + [ S ] / K m + [ I ] / K i )
From (2.7) and (1.3) we arrive the product (P s ) production rate
(2.8)
d [ Ps ]
[ E0 ]
k[ E0 ][ S ]
[S ]
= k=
=
[ SE ] k
dt
K m (1 + [ S ] / K m + [ I ] / K i ) K m + K m [ I ] / K i + [ S ]
140
The maximum reaction rate occurs when
gets very large:
 d [ Ps ] 
 dt  ≈ k[ E0 ] ≡ Vm

 max
so that
(2.9)
d [ Ps ]
Vm [ S ]
=
dt
K m + K m [ I ] / Ki + [S ]
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:
CeVm
K m + C K m / K m* + Ce
(3.1)
R(Ce ,Ce* ) =
(3.2)
Ce*Vm*
R (Ce ,C ) = *
K m + Ce K m* / K m + Ce*
*
*
e
*
e
Here K m and K m * are half-maximum rate concentrations for glucose and 18FDG,
respectively. The V m and V m * are the maximum phosphorylation rates for glucose
and 18FDG, respectively.
141
For glucose, if K m >> Ce* K m / K m* + Ce (meaning the enzyme affinity is very low) , then
the reaction is approximated as first order:
(3.1a)
Here we have defined a first order rate constant k 3 to relate the glucose concentration to
the phosphorylation rate. Similarly, for 18FDG when K m* >> Ce K m* / K m + Ce* ,
Ce*Vm*
(3.2a) R (Ce , Ce ) ≈ *
Km
*
*
⇒
R* (Ce , Ce* ) Vm*
=
≈ *
k
Ce*
Km
*
3
We here define k 3 * to relate the 18FDG phosphorylation rate to a first order constant.
Consequently, the model equations for endogenous glucose (1.1) (1.2) simplify as:
(3.3)
dCe
= k1C p − k2Ce − k3Ce + k4Cm
dt
(3.4)
Similarly, (1.3) and (1.4) leads to
(3.5)
dCe*
= k1*C *p − k2*Ce* − k3*Ce*
dt
and the approximation for the cerebral metabolic rate of FDG:
142
(3.6)
CMRFDG

dCm*
;
= k3*Ce*
dt
If the FDG is constantly infused for a sufficient long period of time, then
becomes
constant:
dC *p
dt
=0
⇒ C *p (∞)
{ }
The Laplace transform C * (s) = L C * (t) applied to the variables of Eq.(3.5) yields
(3.7)
sCe* (s) = k1*C p* (s) − (k2* + k3* )Ce* (s)
Omit the following equation, which is not needed:
sCm* (s) = k3*Ce* (s)
From equation (3.7), when s ==> 0 corresponding to t ↑ ∞ , we find
0 =k1*C *p ( s ) − (k2*Ce* ( s ) + k3*Ce* ( s ))
so that
(3.8)


k*
lim  sCe* (s) = * 1 * sC p* (s) 
s→0
k 2 + k3


⇒
143
Ce* (∞) =
k1*
C *p (∞)
*
*
k 2 + k3
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:
=
CMRglc
(4.1)
dCm
≈ Ce k3 − Cm k4 = Ce k3φ
dt
where φ = 1− Cm k4 Ce k3 . If the rate of loss of the phosphorylated glucose is sufficiently
small, then φ ≈ 1 or approximately a constant close to one.
For the endogenous glucose at steady state (equation 3.3 equal to zero)
k1C p − k2Ce = k3Ce − k4Cm = Ce k3φ
At steady state (ss), we can relate brain glucose concentration to plasma concentration as:
Ce ( ss ) = k1C p ( ss ) /(k2 + φ k3 )
(4.3)
From (4.2) & (4.3) ,
(4.4)
CMRglc =
k1k3φ
C (ss)
k 2 + φ k3 p
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:
λ≡
(4.6)
k1φ
k1*
/
*
*
k 2 + k3 k 2 + φ k3
then substitution of Eqs. (4.5) and (4.6) into 4.4) yields
(4.7)
CMRglc =
k1*k3* φ C p ( ss )
k1*k3*
k1φ  k3* 
=
=
C
s
C p ( ss )
s
)
(
  p
k 2 + φ k3  f 
k2* + k3* λ f
(k2* + k3* ) LC
where (LC) is assumed to be a constant:
LC ≡
(4.8)
λf
φ
and is called a “Lumped Constant”. Equation (4.7) is used as an operational equation for
the estimation of CMR glc .
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:
(3.5)
dCe*
= k1*C *p − k2*Ce* − k3*Ce* 3
dt
(3.6)
dCm*
= k3*Ce*
dt
With the initial conditions C m *(0) =C e *(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:
(6.1)
dCm
dt
= CMRglc(ss) = CBF(C A − CV )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 C A and C V .
Similarly, at the steady-state, the FDG metabolic reaction and uptake rates are equal:
(6.2)
dCm*
= CMRFDG (ss) = CBF(C A* − CV* )ss
dt ss
The ratio of these steady-state rates eliminates CBF:
(6.3)
dCm* / dt
CMRFDG (ss) (C A* − CV* )ss
=
=
dCm / dt ss CMRglc(ss) (C A − CV )ss
From Eqs. (3.6) and (4.1) for cerebral metabolic rates and (4.5), we obtain
 Ce*k3* 
 fCe* 
(C A* − CV* )ss  dCm* / dt 
=
=
=





(C A − CV )ss  dCm / dt  ss  φCe k3  ss  φCe 
ss
At steady state, Ce* = Ce* (∞) and Ce = Ce (ss) so that substituting Eqs. (3.8) and (4.3)
yields
k1*
C *p (∞)
*
*
*
*
*
*
fC *p (∞)
(C A − CV ) ss
fCe (∞)
k 2 + k3
1 C p (∞ )
)
= =
=
= (
k1
φλ
ss
(C A − CV ) ss φ Ce ( ss ) φ
(
)
C
LC
C p ( ss )
p
C p ( ss )
k 2 + φ k3
f
(6.4)
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 PET procedure. Then, using Eq. (4.7), we can estimate CMRglc(ss) by injecting 18FDG
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
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