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University of Southern California Dissertations and Theses
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Alpha-ketoglutarate, an endogenous metabolite, extends lifespan and compresses morbidity in aging mice
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Alpha-ketoglutarate, an endogenous metabolite, extends lifespan and compresses morbidity in aging mice
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Content
ALPHA-KETOGLUTARATE, AN ENDOGENOUS METABOLITE, EXTENDS LIFESPAN
AND COMPRESSES MORBIDITY IN AGING MICE
by
Azar Asadi Shahmirzadi
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
BIOLOGY OF AGING
May 2020
ii
Acknowledgments
I see my time as a PhD student in the biology of aging program like a box full of adventure, pain,
excitement, hope, despair and joy! On top of these feelings are my passion for science and the
gratitude for all the people who helped me along the way to grow not only as a PhD student but
as a better human being.
To my best friend and brother, Arash, who supported me to grow my ambition and passion.
I have always looked up to you, thank you for always believing in me. To my beautiful mother
and artist sister for their never-ending love and affection, and to the kindest and the most loving
person I know, my uncle Mansoor you have been a father to me since I was six and my life is
more beautiful because of you. Thanks for always being there for us.
I would like to especially thank my mentor, Dr. Gordon Lithgow, who gave me the most
valuable thing that you can give any student, trust and the freedom to explore my passion and do
research. I cannot thank Gordon enough as this journey would not have been possible without
him. You will always be an academic father to me. Thank you for always believing in me.
I would like to thank Dr. Julie Andersen for her support and attention. Thanks for being there
when Gordon was too busy. You are a great example of a strong woman in science.
To Dr. John J Tower, first for your wonderful lectures including my favorite one: inheritance of
maternal mitochondria and aging, and also for your great scientific inputs into my project. Many
thanks to Dr. Brian Kennedy for his continual guidance and support on the mouse project. I also
would like to thank Dr. Christian Pike for his input and agreement to be on my committee.
Thanks to Garbo Gan, for not only helping me to correct my English, but also for her great
assistance throughout the mice project. Dipa Bhaumik, you are one of the most beautiful people
iii
in my life, I feel lucky to have you as a friend, mentor and lab mate. I also want to thank Dr.
Daniel Edgar with whom I started the project and got experienced with mice work. Thanks to all
the Lithgow lab members especially Dr. Suzanne Angeli, your passion for science and integrity
is amazing! and thanks to all the Buck employees for the friendly atmosphere. Oh, I forgot to
thank the deer, you girls and your beautiful twins made my days. At last, to all those scientists
(especially graduate students and post docs) who have led monotonous lives, in hope of
experiencing the delights and joy of creation and breakthrough.
iv
TABLE OF CONTENTS
ACKNOWLEDGMENT ii
LIST OF FIGURES viii
LIST OF TABLES x
ABBREVIATIONS xi
DEFINING TERMINOLOGY xiv
ABSTRACT xvii
CHAPTER 1: INTRODUCTION 1
Aging and Metabolism 1
α-ketoglutarate 4
Overview of α-ketoglutarate as an endogenous metabolite 4
AKG and HIF-1 regulation 9
AKG and collagen synthesis 9
AKG and epigenetics 10
AKG and the immune system 11
AKG and the urea cycle 13
Extracellular AKG 13
α-ketoglutarate and aging 15
v
Stem cell proliferation 16
Oxidative stress 17
Tumor and cancer 18
Muscle protein synthesis 19
Bone loss 20
Skin 21
Healthspan and aging 22
Frailty Index as a biomarker of healthspan 26
Inflammation 27
Immune system 27
Inflammation and aging 28
Sex and the immune system 32
Cellular senescence 33
Role of C. elegans 35
Limitations of C. elegans 36
Role of M. musculus 37
Sexual Dimorphism 39
Limitations of Mouse Models 41
CHAPTER 2: RESULTS 42
vi
α-ketoglutarate supplementation extends lifespan and decreases mortality in mice 45
α-ketoglutarate supplementation improves healthspan and decrease morbidity in aging mice 50
α-ketoglutarate supplementation affects the metabolism of aging mice 68
α-ketoglutarate prevents age-associated hair discoloration 71
α-ketoglutarate supplementation does not affect mTOR activity in tissues of aged mice 78
α-ketoglutarate supplementation suppresses inflammaging 80
DISCUSSION 94
MATERIAL AND METHODS 101
C .elegans lifespan 101
Animal housing and diet 101
Mouse survival 102
Baselining and grouping of animals 103
Aging index (Frailty Index or FI) 103
Statistical analyses 104
Metabolic data 104
Transthoracic echocardiography 105
vii
Treadmill exhaustion test 105
Western blot analysis 106
Skin collection and melanocyte stem cell synchronization 106
Immunohistochemistry 107
Flow Cytometry 108
Inflammatory cytokines and chemokines 109
Cell culture 109
ELISA 109
RT PCR 110
REFERENCES 112
APPENDIX 148
viii
LIST OF FIGURES
Figure 1. Schematic representation of AKG as a key metabolite in Krebs cycle. 6
Figure 2. 2-Oxoglutarate-dependent dioxygenase reaction cycle and cofactors. 8
Figure 3. AKG is an endogenous metabolite which is involved in multiple
fundamental biology processes 14
Figure 4. The effect of AKG treatment on median lifespan in different nematode strains 42
Figure 5. AKG and AKG combination treatment can extend the lifespan of C. elegans. 44
Figure 6. Experimental Design. 47
Figure 7. AKG extends lifespan and decrease mortality in mice 48
Figure 8. effects of aging in mouse 51
Figure 9. AKG extends health span and alleviates age-associated frailty 54
Figure 10. The graphic illustration of morbidity 55
Figure 11. Compression of morbidity by AKG administration 57
Figure 12. Total Frailty Score has strong correlation with life expectancy in aging mice 58
Figure 13. AKG administration alleviates multiple age-associated frailty 60
Figure 14. AKG alleviates multiple age-associated frailty phenotypes (including those that
significantly change with age) 64
Figure 15. AKG supplementation improves locomotion in aged mice (Cohort-2 data) 66
Figure 16. AKG supplementation does not improve heart function 67
Figure 17. AKG preserves body weight in male animals (Cohort-2 data) 69
Figure 18. AKG decreases the metabolic rate of aged mice (Cohort-2 data) 70
Figure 19. AKG strongly prevents age-associated hair discoloration in female mice 72
ix
Figure 20. AKG treatment helps to preserve the melanocyte population in aged hair follicles 74
Figure 21. AKG treatment does not affect stem cell or their differentiation population
in mouse airway system 76
Figure 22. Figure 23. mTOR activity is not changed in tissues of mice receiving AKG
in the diet 79
Figure 23. AKG reduces inflammation in aged mice 81
Figure 24. Old female mice exhibit higher levels of inflammation compared to males,
which is significantly suppressed by AKG supplementation 82
Figure 25. AKG does not affect the senescence growth arrest in different tissues
of aging mice 84
Figure 26. AKG reduces inflammation and lowers the proinflammatory SASP
without preventing the senescence associated growth arrest 85
Figure 27. Schematic illustration of different blood leucocyte populations and
surface markers 88
Figure 28. Different leucocyte population in blood; Female mice receiving AKG have
higher abundance of T-cells 89
Figure 29. A representative flow plots and sorting strategies for re-stimulated splenocyte 92
Figure 30. AKG increases intercellular IL-10 in stimulated female T-cells 93
x
LIST OF TABLES
Table 1. Frailty index as a biomarker of health; focusing on pharmacological interventions 23
Table 2. Age related inflammatory phenotypes in human 31
Table 3. The effect of AKG supplementation on lifespan 49
Table 4. List of all 31 aging phenotypes and their interaction with aging (time) in females 62
Table 5. List of all 31 aging phenotypes and their interaction with aging (time) in males 63
Supplemental table 1. Statistical summary for splenocytes- Flow Cytometry data 148
Supplemental table 2. Statistical summary for intracellular signaling for ex vivo stimulated
splenocytes 149
Supplemental table 3. Statistical summary for negative cells (Dump channel) 150
xi
ABBREVIATIONS
ACK: Ammonium-Chloride-Potassium
AKT: Protein kinase B
AMP: Adenosine monophosphate
AMPK: 5' adenosine monophosphate-activated protein kinase
ANOVA: Analysis of variance
ATP: Adenosine triphosphate
BSA: Bovine serum albumin
C. elegans: Caenorhabditis elegans
CCSP: Clara cell secretory protein
CoA: acetyl coenzyme A
DAPI: 4′,6-diamidino-2-phenylindole
DCT: Dopachrome tautomerase also known as tyrosine-related protein 2
DMEM: Dulbecco's Modified Eagle's Medium
DMSO: dimethyl sulfoxide
DNA: deoxyribonucleic acid
EDTA: Ethylenediamine tetraacetic acid
FADH2: Flavin adenine dinucleotide
FoxP3+: forkhead box P3
H2O2: hydrogen peroxide
Hep3B: Hepatocellular Carcinoma Cell Line
IFN-g: interferon-gamma
IL: Interleukin
xii
IMR-90: Human fetal lung fibroblasts
Jmjd3: Jumonji domain-containing protein 3
LLC: Lewis lung carcinoma
LPS: Lipopolysaccharides
MITF: Melanocyte Inducing Transcription Factor
mL: milliliter
mM: millimolar
NAD+: Nicotinamide adenine dinucleotide
NF-κB: nuclear factor kappa-light-chain-enhancer of activated B-cells
O2.- : superoxide
P16
INK4A
: p16 cell cycle inhibitor of kinase 4A
P4H: prolyl 4-hydroxylases
P5C: pyrroline-5-carboxylate
PAX3: paired box gene 3
PBS: Phosphate-buffered saline
PCR: polymerase chain reaction
pH: potential hydrogen
PI3K: Phosphatidylinositol-4,5-bisphosphate 3-kinase
qPCR: quantitative polymerase chain reaction
RIPA: Radioimmunoprecipitation assay
RNAi: ribonucleic acid interference
rtPCR: reverse transcriptase polymerase chain reaction
S6K: S6 kinase
xiii
SDS-PAGE: sodium dodecyl sulfate polyacrylamide gel electrophoresis
SDS-PAGE: sodium dodecyl sulfate polyacrylamide gel electrophoresis
SEM: Standard error of the mean
ß-gal: β-galactosidase
SUMOylation: the covalent binding of Small Ubiquitin-like modifier (SUMO) to target proteins
TNF-α: Tumor Necrosis Factor alpha
Tris: trisaminomethane
TRP-2: tyrosine-related protein 2, also known as Dopachrome tautomerase
Trp63: Tumor Protein P63
UVB: ultraviolet B
VEGF: Vascular endothelial growth factor
°C: degree Celsius
µL: Microliter
µm: Micrometer
µM: micromolar
xiv
DEFINING TERMINOLOGY
I have applied a group of terms that may deviate from the meanings these words have in other
contexts and in everyday language. Here I define meaning and concept I am referring to in this
thesis.
Health/Healthy (animal): The condition of an animal, taking into consideration the frailty
phenotypes; the absence of the frailty phenotypes
Health/Healthy (human): The state of being free from illness and being physically fit
Healthspan: The length of a person’s or animal’s life during which they are healthy
Lifespan: The length of time for which an animal is alive
Metabolite: A small molecule that is an intermediate product of cellular regulatory processes
including metabolism
Morbidity/Morbid: The quality of being unhealthy independent of a particular disease
Mortality: The state of being subject to death
Resilience: The ability of an individual to recover from an acute event (disease or a dysfunction)
xv
Supplementation/Supplement: The addition of an extra element to something. I used these two
terms to explain addition of a-ketoglutarate to the diet
Treatment: Administration of a dose of a chemical. In this study the molecule is a-ketoglutarate
xvi
ABSTRACT
Aging and metabolism are tightly connected and interference in nutrient-sensing pathways can
enhance longevity in laboratory animals. Here, I demonstrate beneficial effects of α-ketoglutarate
(AKG), delivered in food in the form of a calcium salt (CaAKG), a key metabolite in the
tricarboxylic acid (TCA) cycle, on longevity in aged mice.
AKG is involved in various fundamental processes including protein synthesis, hypoxic
response, collagen synthesis and epigenetic changes (Zdzisinska, Zurek, & Kandefer-Szerszen,
2017). Due to its broad roles in multiple biological processes, AKG has been a subject of interest
for researchers in many fields. AKG also influences several age-related processes, including
stem cell proliferation and osteoporosis. It has been shown that supplementation of AKG to adult
Caenorhabditis elegans (C. elegans) can extend the lifespan and delays aging (Chin et al., 2014).
AKG also been shown to consistently extend the lifespan of multiple different
Caenorhabditis strains across different research centers, including our lab (Lucanic et al., 2017).
A variety of genetic and pharmacological interventions, mostly in invertebrate laboratory
animals, have been identified that enhance lifespan. Whether, these interventions extend
healthspan, the disease-free and functional period of life, is not always tested and is often a
matter of debate (Bansal, Zhu, Yen, & Tissenbaum, 2015; Hansen & Kennedy, 2016). Human
aging indices have been developed to assess elements of functional decline with aging (e.g.
sarcopenia, cognitive function) (Fried et al., 2001; Rockwood et al., 2005). However,
corresponding comprehensive indices in laboratory animals including mice are seldom applied to
aging studies. To probe the relationship between healthspan and lifespan extension in mammals,
xvii
I performed a series of longitudinal, clinically relevant healthspan measurements. To determine
its influence on mammalian aging, we administered AKG to mice beginning at 18 months of age,
which corresponds to ~55 human years, until death and determined its effect on the onset of
frailty and survival. My results show that a metabolite, delivered in food, increases lifespan and
improves healthspan in aging mice. Healthspan was determined longitudinally throughout life,
using a recently developed metric with 31-clinically relevant non-invasive measurements
(Searle, Mitnitski, Gahbauer, Gill, & Rockwood, 2008; Whitehead et al., 2014). AKG conferred
a significant reduction in several individual frailty metrics including the appearance of tremors,
gait disorders, deterioration of body condition, piloerection, and body weight loss. Among the
biggest effects of AKG were suppression of changes in fur color and improvement of coat
condition, where reversal of hair graying was detected. We assessed frailty changes not only by
lifespan but also by proportion of lifespan: My results indicate that AKG supplementation can
decrease the proportion of life in which the animal is frail and increases the healthy days of life
independent of how long the animal lives. Data from longitudinal analyses of clinically relevant
health measurements leads me to propose that AKG compresses morbidity, making it a strong
candidate for human clinical intervention in the process of aging.
Inflammaging, a mild systemic inflammatory state, is a significant risk factor for morbidity and
mortality in adults and is considered an essential contributor to many age-related pathologies
(Franceschi & Campisi, 2014). Studies have shown a relationship among inflammatory
cytokines and adverse health outcomes in several chronic diseases in older adults. Plasma levels
of IL-6 and TNF-a have been identified as predictors of 10-year mortality from all causes
(Varadhan et al., 2014) and an indicator of survival (Larbi et al., 2008). Recent studies have
shown imbalanced expression and production of both pro-inflammatory cytokines and anti-
xviii
inflammatory cytokines, such as IL-8 and IL-10 can contribute to different diseases (Zhen, Chu,
Zhou, Qi, & Shu, 2015).
My findings in mice also confirm that aging increases systemic inflammation which can be
suppressed by AKG administration. In my study, females showed more chronic inflammation
compared to males upon aging, which was inhibited to larger extents by chronic administration
of AKG. This observation is consistent with our lifespan and morbidity data, as female mice
responded more robustly to AKG supplementation.
Extracted T-cells from the spleens of female AKG treated mice significantly produced higher IL-
10 compared to control mice; IL-10 is a potent anti-inflammatory cytokine that plays a central
role in limiting host immune response (Ip, Hoshi, Shouval, Snapper, & Medzhitov, 2017). I
believe that induction of IL-10 by AKG treatment can be a potential mechanism for suppression
of systemic inflammation.
I observed no significant adverse effects of the metabolite. The only phenotypes that had a
higher incidence in AKG-treated animals (both female and male) were cataracts and corneal
opacity, although these did not reach statistical significance. AKG is Generally Recognized As
Safe (GRAS) under the Food and Drug administration law. Given its GRAS status, my findings
point to a potential intervention that may impact important elements of aging and improve
quality of life if applied to the elderly population.
1
CHAPTER 1: INTRODUCTION
Aging and Metabolism
Aging and metabolism are tightly connected. The aging process is characterized by loss of
homeostasis (Barzilai, Huffman, Muzumdar, & Bartke, 2012) and deregulation of nutrient
sensing pathways (Lopez-Otin, Galluzzi, Freije, Madeo, & Kroemer, 2016) which affects
metabolism.
Research over the last decades has uncovered several evolutionarily-conserved pathways
involved in regulation of metabolism including nutrient sensing genes: Insulin-like growth factor
1 (IGF1) (Junnila, List, Berryman, Murrey, & Kopchick, 2013), the sirtuins (SIRTs) (Kennedy,
Austriaco, Zhang, & Guarente, 1995), AMPK (Salminen & Kaarniranta, 2012), target of
rapamycin (TOR) (Selman et al., 2009) and forkhead box O (FOXO) transcription factors (Greer
& Brunet, 2005). These sensors can regulate metabolism of the organism and control
fundamental aging processes such as DNA repair (Vazquez, Thackray, & Serrano, 2017),
mitochondrial biogenesis and function, stress resistance (Lithgow, White, Melov, & Johnson,
1995), stem cell and telomere maintenance, chromatin modifications (Lopez-Otin, Blasco,
Partridge, Serrano, & Kroemer, 2013), autophagy (Alers, Loffler, Wesselborg, & Stork, 2012),
and inflammation (Gillum et al., 2011).
Aging researchers have found several molecules that can activate these metabolic pathways and
extend lifespan. Rapamycin, a drug discovered to reduce organ transplant rejection, inhibits
mTOR and extend lifespan (D. E. Harrison et al., 2009). Another longevity drug is metformin
2
(Martin-Montalvo et al., 2013), the frontline therapy for type 2 diabetes, which activates AMPK
(Onken & Driscoll, 2010).
Consistent with the relevance of deregulated metabolism as a hallmark of aging, caloric
restriction (CR) is known as the gold standard for delaying aging and extending lifespan
(Fontana, Partridge, & Longo, 2010). Very interestingly, scientists have been able to design
drugs or engineer transgenic animals to mimic the physiological effects of calorie restriction. For
example, SIRT-activating compounds such as resveratrol and SRT2183 (Pacholec et al., 2010)
can pharmacologically induce some of the protective effects of calorie restriction in various
model organisms (Wood et al., 2004). Mammals have 7 SIRTs enzymes (SIRT1–7), which are a
family of NAD
+
-dependent deacylases. SIRTs are major effectors in the cellular response to
metabolic, oxidative and genotoxic stress (Michan & Sinclair, 2007). They play an important
role in regulation of genome homeostasis under different forms of stress (Mostoslavsky et al.,
2006). Due to their fundamental protective role, SIRTs have extensively been studied in aging
and metabolic disorders (Giblin, Skinner, & Lombard, 2014). Remarkably, mice over expressing
SIRT1 or SIRT6 or treated with STACs have shown lifespan extension with improved organ
function (Bonkowski & Sinclair, 2016).
Recent studies have attempted to link longevity with various metabolic parameters. For instance,
plasma lipidome studies of offspring of nonagenarians reveal favorable lipid metabolism
associated with familial longevity. There is a positive correlation between longevity and
sphingomyelin metabolites. Also the plasma of long lived population have a higher ratio of
monounsaturated (MUFA) over polyunsaturated (PUFA) fatty acids (Gonzalez-Covarrubias et
3
al., 2013). Other studies show that the concentration of different metabolites such as NAD
+
(Clement, Wong, Poljak, Sachdev, & Braidy, 2019), glutathione (H. Liu, Wang, Shenvi, Hagen,
& Liu, 2004) and α-ketoglutarate (A. P. Harrison & Pierzynowski, 2008) decrease upon aging.
For some metabolites, restoring the levels by gene therapy or exogenous supplementation can
extend lifespan.
NAD
+
is the most well-studied longevity metabolite (S. J. Lin, Defossez, & Guarente, 2000).
NAD
+
is an energy-sensing metabolite that is vital for a wide variety of cellular processes including
metabolism, cell death, DNA repair, gene expression and mitochondrial function (Gomes et al.,
2013; Verdin, 2015). It functions as a coenzyme in various redox reactions in energy production
pathways in the mitochondria. Furthermore, NAD
+
serves as a substrate for (ADP-ribose)
polymerases (PARPs) (Menissier de Murcia et al., 2003) and SIRTs (Verdin, 2015). The discovery
of SIRT2 NAD-dependent deacetylase drew attention towards the potential anti-aging effects of
NAD
+
(Imai, Armstrong, Kaeberlein, & Guarente, 2000). As humans and mice age, levels of
NAD
+
decline, which may affect the activities of SIRTs and their downstream genes (Clement et
al., 2019). Boosting endogenous NAD
+
levels by administrating NAD
+
precursors or by inducing
its biogenesis can increase lifespan (Bonkowski & Sinclair, 2016). As NAD
+
is impermeable to
the plasma membrane, NAD
+
precursors, such as nicotinamide mononucleotide (NMN),
nicotinamide (NAM), nicotinic acid (NA), and nicotinamide riboside (NR), are utilized to increase
plasma levels of NAD
+
in mice and humans (Nikiforov, Dolle, Niere, & Ziegler, 2011). NAD
+
-
boosting molecules can serve as a new class of SIRT-activating compounds and has gained much
attention recently; multiple clinical trials have been undertaken using NMN and NR (Martens et
al., 2018).
4
α-ketoglutarate (AKG) is another interesting metabolite which has not been tested for longevity
effects in mammals. Studies in C.elegans have shown that endogenous AKG increases upon
fasting (Chin et al., 2014). Findings in our lab also show that supplemented AKG can
reproducibly increase lifespan in different strains of nematode (Lucanic et al., 2017). In humans,
AKG plasma levels increase after exercise (Brugnara et al., 2012). Unpublished yeast data
generated by the Kennedy lab also show that cells lacking glutamate dehydrogenase (GDH) 1
and 3 have higher replicative lifespan. Gdh-1 and 3 are responsible for converting AKG to
glutamate. Unlike NMN and NR that are contained in natural food such as cow’s milk
(Trammell, Yu, Redpath, Migaud, & Brenner, 2016), AKG is not found in the normal diet. This
makes supplementation the only feasible way to restore its levels. Considering the broad
physiological roles of AKG and also the conserved longevity effects of this metabolite in yeast
and C. elegans, we decided to further study the molecule in mice. Although lifespan has been the
major outcome of aging research, we aimed to have a special focus on healthspan as an improved
quality of life is considered a primary goal when translating findings to humans.
α-ketoglutarate
Overview of α-ketoglutarate as an endogenous metabolite
α-ketoglutaric acid (AKG; also known as 2-oxoglutaric acid, and less commonly 2-
oxopentanedioic acid) is a key intermediate metabolite in the tricarboxylic acid cycle (TCA; also
known as the Krebs Cycle). Aerobic organisms generate energy from the oxidation of acetyl-
CoA, which is derived from carbohydrates, fats and proteins in the TCA cycle. The cycle is a
series of eight enzymatic reactions where acetyl-CoA becomes oxidized and leads to production
of CO2 and reduced coenzymes (NADH and FADH2) (Krebs & Johnson, 1980). These
5
coenzymes are further oxidized by reactions in the electron transport chain (ETC) to provide a
pH gradient across the inner mitochondrial membrane, which leads to energy production in the
form of adenosine triphosphate (ATP) (Slater, 1967; Whitehead et al., 2014). In the TCA cycle,
AKG is generated from isocitrate by oxidative decarboxylation and then converted to succinyl-
CoA. It can also replenish the cycle at this junction from glutamate (Fig. 1) AKG is synthetized
from glutamate by transamination, or through the action of glutamate dehydrogenase (Slater,
1967). Due to the reversible nature of these enzymes, AKG can also be used for the synthesis of
other amino acids (e.g. proline and arginine, Fig. 1). As a TCA cycle metabolite, AKG is
important for biosynthesis and breakdown of amino acids (He et al., 2015). AKG also regulates
and is regulated by the NAD
+
/NADH ratio (Owen, Kalhan, & Hanson, 2002) A high ratio of the
NAD
+
/NADH leads to decarboxylation of AKG and formation of succinyl-CoA. However, in the
case of increased levels of NADH, AKG is converted to glutamate by glutamate dehydrogenase,
which can further lead to the formation of glutamine (Zdzisinska et al., 2017). While all these
reactions take place in the mitochondria, AKG can freely diffuse through channels or
transporters into the cytoplasm. One of these transport systems is known as the
oxoglutarate/malate antiporter (Chappell, 1968; Zdzisinska et al., 2017).
6
Figure 1. Schematic representation of AKG as a key metabolite in Krebs cycle.
AKG is a key intermediate metabolite in the tricarboxylic acid cycle and is generated from
isocitrate by oxidative decarboxylation. It can also replenish the cycle at this junction from
glutamate. AKG is associated with the production of glutamate and glutamine through
reversible reactions. Various transaminases can convert AKG to other amino acids. Not only
AKG help collagen synthesis by increasing the pool of proline via glutamate, but it also
serves as a mandatory co-factor for the conversion of proline to hydroxyproline, which is
responsible for the triple helix folding of matured collagen.
Krebs cycle
7
2-oxoglutarate dependent dioxygenases (2-OGDD) are a large family of enzymes that are
responsible for hydroxylation of a diverse range of substrates. AKG is a mandatory co-substrate
for 2-OGDD (Islam, Leissing, Chowdhury, Hopkinson, and Schofield (2018). This family of
enzymes require oxygen (O2) and Fe (II) as cofactors, as well as ascorbic acid (Vitamin C) for
recovery. One oxygen atom from O2 is transferred to a hydroxyl group in the substrate while the
other one leads to decarboxylation of AKG and production of CO2 and succinate. The complete
OGDD reaction cycle and cofactors is illustrated in Figure 2 (Kuiper & Vissers, 2014). The 2-
OGDD family consists of more than 60 different enzymes, some of them involved in
fundamental biological processes including hypoxic response (Bruick & McKnight, 2001),
collagen biosynthesis, nucleic acid modification/repair, fatty acid metabolism (Hausinger, 2004),
transcriptional and epigenetic regulation (Tsukada et al., 2006). Here I explain the role of AKG
in various fundamental 2-OGDD reactions.
8
Figure 2. 2-Oxoglutarate-dependent dioxygenase reaction cycle and cofactors.
(a) Simplified view of the active site of prolyl hydroxylase, a fundamental human AKG
dependent dioxygenase that is involved in oxygen sensing. (b) Schematic illustration of AKG
dependent dioxygenases. (b')The first step involves the binding of AKG and substrate to the
active site. AKG coordinates as a bidentate ligand to Fe (II), while the substrate is held by
noncovalent forces in close proximity. Subsequently, molecular oxygen binds end-on to Fe
cis to the two donors of the AKG. (b'') The uncoordinated end of the superoxide ligand
attacks the keto carbon on AKG, lead to release of CO
2
and forming Fe (IV) oxo-intermidiate.
This conversion is coupled with oxidation of AKG into succinate and carbon dioxide. (b''')
The formed Fe=O then oxidase the substrate: converting C-H bond of substrate to C-OH.
(b'''') The hydroxylated product is released. Ascorbic acid works as a reducing agent, AKG
dependent dioxygenases activities relays on it.
9
AKG and HIF-1 regulation: AKG regulates hypoxia-inducible factors (HIFs). HIFs are
transcription factors that respond to modulation of intracellular oxygen levels. HIFs are
heterodimer enzymes that consist of one O2-labile a subunit and another stable ß subunit. The a
O2-labile subunit consists of 3 isoforms. The first isoform, HIF-1a, is consecutively expressed in
all cell types. Under aerobic conditions, prolyl hydroxylase domain protein 2 (PHD2,) a 2-
OGDD enzyme for which AKG is a co-substrate, hydroxylates the proline (Pro402 and Pro564)
residue of HIF-1a. This hydroxylation initiates the recognition of the subunit by Von Hippel-
Lindau (VHL) protein and leads to HIF-1a ubiquitination and its rapid degradation by the
proteasome. In hypoxic conditions or low levels of cytoplasmic AKG, PHD2 activity is
attenuated, which results in HIF-1a stabilization in the cytoplasm. HIF-1a can then enter the cell
nucleus and dimerize with the stable subunit HIF-1ß. This complex can then bind to HIF-
responsive elements (HREs) and induce transcription of downstream hypoxia survival genes
(Iommarini, Porcelli, Gasparre, & Kurelac, 2017).
Mutations in succinate dehydrogenase complex-related genes can lead to a build-up of succinate
and also result in HIF-1a stabilization. Pseudo-hypoxia, which is associated with different types
of cancer, occurs as succinate to AKG levels increase and lead to HIF-1a stabilization without
any changes in oxygen levels (Iommarini et al., 2017; Zdzisinska et al., 2017).
AKG and collagen synthesis: AKG is also a co-factor for prolyl-4-hydroxylase (P4H), a 2-
OGDD enzyme, which is located in the endoplasmic reticulum (ER). P4H is responsible for the
hydroxylation of proline into 4-hydroxyproline which increases the conformational stability of
the secondary structure of collagen. Hydroxylation of proline is a crucial process for the
10
formation of both connective tissue and bone matrix (Gerber & Altman, 1961). AKG also
contributes to collagen synthesis by adding to the pool of glutamate that can be converted to
pyrroline 5-carboxylate (P5C) and ultimately proline (Kristensen, Jungvid, Fernandez, &
Pierzynowski, 2002), (Fig.1.1). Although the major source of proline is through recycling, P5C
significantly regulates collagen metabolism pathways (Vasta & Raines, 2018). Research in this
regard have shown that AKG supplementation can increase the blood levels of proline by 45%
and 20% in pigs (Kristensen et al., 2002).
AKG and epigenetics: Epigenetics mechanisms result in changes in the levels of gene
expression, DNA repair and replication, without altering the DNA sequence itself. Two basic
methods of epigenetic regulations are DNA methylation and histone modification (chromatin
modification). The post-translational modification of histone includes acetylation, methylation,
phosphorylation, ubiquitination, biotinylation, and SUMOylation. (Ito et al., 2010; Tsukada et
al., 2006). Through its ability to alter gene expression, epigenetics has important roles in cell
differentiation, growth, proliferation, and stress responses.
AKG is an important molecule that connects metabolism to epigenetic changes. AKG influences
epigenetic gene expression by affecting the activity of ten-eleven translocation (TET1-3) family
of enzymes which promotes reversal of DNA methylation. TET enzymes oxidize the methylation
found on the 5-carbon position of cytosine (5mC) and convert it into a hydroximethylation
(5hmC). The further oxidation of 5hmC produces 5-formylcytosine (5fC) and 5-carboxylcytosine
(5caC) which promotes DNA demethylation through different mechanisms (Ito et al., 2010; Ito
et al., 2011).
11
AKG can also impact on histone modifications by enhancing the activities of Jumonji C (JmjC)
domain-containing demethylases (Tsukada et al., 2006). Like TET enzymes, JHDM enzymatic
activity requires AKG and Fe (II) (Chisolm & Weinmann, 2018; Tsukada et al., 2006). Current
data suggest the balance between AKG, 2-hydroxyglutarate (2HG), succinate or fumarate in the
cells defines the levels of histone or DNA methylation (Tsukada et al., 2006).
AKG and the immune system: AKG plays an important role in regulating immune function
through different mechanisms, many of which involve enhancing the pool of glutamine and
production of intracellular reactive oxygen species (ROS). Glutamine is known as an immune-
enhancing nutrient and it can regulate the innate immune response by enhancing phagocytosis
and ROS production in monocytes and neutrophils (Ogle et al., 1994). Furthermore, glutamine is
a fuel for lymphocyte function, proliferation, and cytokine production, all of which can enhance
the adaptive immune response (Ardawi, 1988; Wells, Kew, Yaqoob, Wallace, & Calder, 1999).
It has been shown that intracellular AKG levels have fundamental roles in T-cell differentiation.
Upon nutrient deprivation, specifically that of glutamine, the decrease in the amount of AKG is
the main reason for the shift between different generations of T-cells; there is induction in
generation of FoxP3+ regulatory T instead of T helper cells (Klysz et al., 2015). In addition, the
metabolite leads to production of intracellular ROS which can act as a second messenger for T-
cell signaling and activation (Chang, Yang, & Shaio, 1999; Kew et al., 1999).
AKG itself can act as a glutamine homologue and affect both innate and adaptive immune
responses, especially during stress. In stressed rats, ornithine α-ketoglutarate (OKG) improves
immune status through enhancing polymorphonuclear neutrophil (PMN) function. Findings
demonstrate increase in chemotaxis, respiratory burst, and migration via production of nitric
12
oxide (NO
.
) upon AKG supplementation (Moinard et al., 2002). In vitro, the metabolite can
enhance intracellular production of O2
·
and myeloperoxidase activity in PMNs (Muhling et al.,
2010).
It has been shown that AKG affects macrophage function at multiple levels. Macrophages are
essential components of the innate immune response. Beyond increasing inflammation and
stimulating the immune system, they can induce anti-inflammatory responses depending on
various cues (Shapouri-Moghaddam et al., 2018). M1 macrophages are induced by infection,
tissue damage, or liposaccharides (LPS) and can cause inflammation and injured tissues (Wang,
Liang, & Zen, 2014). Alternatively, M2 activation is induced by interlukin-4 (IL-4) and IL-13
and elicits anti-inflammatory responses and tissue repair (Wang et al., 2014). The switch
between these two extreme phases is regulated by a set of signaling pathways, transcriptional and
post-transcriptional regulatory networks. Recently researchers have found that AKG (via
glutaminolysis or supplementation) can facilitate M2 polarization by Jmjd3-dependent epigenetic
reprogramming of M2 genes. In addition, supplementation of dimethyl-AKG (a lipophilic, cell-
permeable form of AKG) can increase the ratio of intracellular AKG/succinate levels and
promote M2 polarization and anti-inflammatory responses. Low AKG/succinate ratio will
activate M1 macrophage polarization and inflammation (P. S. Liu et al., 2017). This is a very
important finding as the imbalance between M1 and M2 phases is associated with various
inflammatory conditions and identification of the molecules modulating the dynamic changes is
critical for therapeutic strategies (Wang et al., 2014). Moreover, OKG can enhance the
macrophage cytotoxicity in stressed mice (Moinard et al., 2000) and in rats with tumors
(Moinard et al., 1999).
13
The metabolite can inhibit the nuclear factor kappa B (NF-κB)-mediated pathway and prevent
inflammation in the intestine of LPS-challenged piglets. AKG supplementation can reverse
adverse effects of LPS-induced inflammation through modulating the interaction between
pregnane X receptor (PXR)--also known as the steroid and xenobiotic sensing nuclear receptor
(SXR)--and NF-κB (He et al., 2017).
AKG and the urea cycle: Amino acid catabolism results in the formation of the waste product
ammonia. The urea cycle converts ammonia to a far less toxic form; urea. Transaminases are
responsible for transfer of amino groups to AKG, one of the fundamental nitrogen transporters
involved in metabolic pathways. This can help to decrease the nitrogen overload in case of
excess ammonia and nitrogen levels or any urea cycle disorders (Barmore & Stone, 2019).
Extracellular AKG: Not only AKG can function intracellularly, it can also act as an
extracellular ligand for the G protein-coupled receptor 2-oxoglutarate receptor 1 (OXGR1), also
known as GPR99. This pathway uses Ca
2+
as second messenger and regulates a wide range of
vital functions including metabolism, inflammation, growth and differentiation (Kanaoka,
Maekawa, & Austen, 2013). Other ligands for GPR99 include cysteinyl leukotrienes (CysLTs),
in particular leukotriene E4 (LTE4), which is extensively studied in the context of allergy and
asthma (Peters-Golden, Gleason, & Togias, 2006).
14
Figure 3. AKG is an endogenous metabolite which is involved in multiple fundamental
biology processes
15
α-ketoglutarate and aging
AKG is mainly found within cells (in mitochondria and the cytoplasm) but it can also be detected
in the bloodstream. Interestingly, human plasma levels of AKG decline 10 folds between the
ages of 40 and 80. Data also show that AKG concentrations increases upon exercise (A. P.
Harrison & Pierzynowski, 2008; Wagner, Donnarumma, Wintersteiger, Windischhofer, & Leis,
2010). In animal models (C. elegans and pigeons), starvation can enhance the physiological
levels of AKG (Kaminsky, Kosenko, & Kondrashova, 1982). It has been shown that
supplementation of AKG in adult C. elegans can extend the lifespan and delay aging (Chin et al.,
2014). AKG has been tested as part of the Caenorhabditis Intervention Testing Program (CITP),
a multicenter research program that tests pharmacological interventions in diverse genetic
backgrounds. Using multiple replicates across different centers, AKG was found to be one of the
compounds that reproducibly extended lifespan in three different Caenorhabditis strains (N2,
MY16 and JU775) (Lucanic et al., 2017). Nematode studies suggest that AKG binds to ATP
synthase β subunit (complex V of ETC) and inhibits its function. ATP synthesis inhibition leads
to reduced ATP content and oxygen consumption, which mimics dietary restriction (DR). AKG
supplementation was not able to further increase the lifespan of eat-2 mutants, which are
considered to be a genetic model of DR in worms (slower pharyngeal pumping rate that restricts
the amount of food intake). The longevity effects of AKG in nematodes requires the let-363
gene, which is an orthologue of the mammalian target of rapamycin (mTOR) kinase (Chin et al.,
2014). mTOR is an evolutionarily conserved nutrient sensing kinase that integrates both
intracellular and extracellular signals. mTOR serves as a central regulatory system for
metabolism, cell growth, proliferation and survival. Genetic or pharmacological inhibition of
mTOR can extend lifespan in diverse model organisms such as yeast, fruit flies and mice (S. C.
16
Johnson, Rabinovitch, & Kaeberlein, 2013). There are no published aging studies on the effects
of AKG on lifespan or healthspan in mammals. However, AKG is reported to influence several
age-related processes in mammals including inflammation (He et al., 2017; P. S. Liu et al.,
2017), stem cell proliferation (Carey, Finley, Cross, Allis, & Thompson, 2015; Song et al.,
2018), oxidative stress (S. Liu, He, & Yao, 2018), protein synthesis (J. Chen et al., 2018;
Wernerman, Hammarqvist, von der Decken, & Vinnars, 1987), cancer, and osteoporosis
(Dobrowolski et al., 2008). Here, I explain briefly the role of AKG in each age-related process.
Stem cell proliferation: Stem cells need to preserve their differentiation and pluripotent
properties over time for long-term maintenance of tissue homeostasis. Much evidence has shown
that aging has adverse effects on stem cells. As an organism ages, stem cells gradually lose their
renewal and differential capacities (Ahmed, Sheng, Wasnik, Baylink, & Lau, 2017). It has been
suggested that the loss in stem cell capacity plays fundamental roles in the pathology of many
age-related diseases (Childs, Durik, Baker, & van Deursen, 2015). Different concepts of
potential age-related stem cell dysfunction mechanisms have been developed (Boyette & Tuan,
2014), among which the role of metabolism in regulating stem cell function has been widely
studied. The majority of mammalian stem cells require glutamine to proliferate as a source for
nitrogen and for replenishing the TCA cycle (Eagle, Oyama, Levy, Horton, & Fleischman, 1956;
Lunt & Vander Heiden, 2011). Interestingly, recent research has shown that mouse embryonic
stem cells (ESCs) are able to maintain naïve pluripotency in the absence of glutamine as long as
they can maintain high levels of AKG (Carey et al., 2015). In the absence of glutamine, ESCs
can utilize glucose to obtain an elevated AKG/succinate ratio, in order to regulate multiple
epigenetic changes that are essential for pluripotency-associated gene expression capacity.
17
(Ryall, Cliff, Dalton, & Sartorelli, 2015). In vitro, direct manipulation of intracellular AKG via
supplementation with cell-permeable AKG has been shown to increase the activity of histone
demethylases and TET-dependent DNA demethylation enzymes and to support self-renewal
(Carey et al., 2015). In addition, the same group showed that supplementation with cell-
permeable succinate can decrease the AKG/succinate ratio and inhibit proliferation while
promoting differentiation. These findings reveal a critical mechanistic role for AKG in
transcriptional and epigenetic regulation of stem cells that affects their pluripotency and
differentiation (Carey et al., 2015).
Oxidative stress: The oxygen molecule, O2, a vital element for all aerobic organisms, is used to
generate energy out of food (glycolysis) but can also lead to generation of free radicals (ROS)
and non-radical oxidants within the body (Wickens, 2001). Dioxygen is a strong oxidizing agent
because of its two unpaired electrons. Overwhelming tissues with oxidants can cause oxidation
of lipid membranes, proteins or even damage to nucleic acids (Speakman & Selman, 2011).
AKG has an antioxidant capacity and can participate in non-enzymatic oxidative decarboxylation
(Sokolowska, Oleszek, & Wlodek, 1999). In mice, CaAKG or NaAKG supplementation
significantly increases activity of superoxide dismutase, glutathione peroxidase activity, and
decreases the activity of thiobarbituric acid reactive substances (TBARS). These data suggest
that AKG protects the animals from ROS (Niemiec et al., 2011). In the model of induced
hepato-carcinogenesis in rats, AKG administration can restore circadian patterns of lipid
peroxidation and antioxidant activities back to normal (Velvizhi, Dakshayani, & Subramanian,
2002). The molecule can also act as a direct H2O2 scavenger, which leads to its conversion to
succinate (Long & Halliwell, 2011).
18
One of the most interesting features of AKG is its antagonist properties against cyanogens.
Cyanogens are toxic chemical compounds containing (CN)2 groups. Cyanogens can undergo
reduction to form cyanide, which inhibits cytochrome c oxidase complex activity and interrupts
the ETC. Inhibiting mitochondrial activity via cyanide can lead to lactic acidosis and cell death
(Bhattacharya, Rao, & Vijayaraghavan, 2002; Bhattacharya, Satpute, Hariharakrishnan, Tripathi,
& Saxena, 2009). The carbonyl group on AKG can readily react with cyanide to reduce the
levels of lethal cyanide by forming cyanohydrin. AKG also can restore cyanide-induced
reductions in glutathione and protect different organs from cyanohydrin-induced ROS
(Tulsawani et al., 2005).
Tumor and cancer: The rate of cancer changes exponentially with age. More than half of cancer
incidences in the United States occurs in individuals older than 70 (Siegel, Miller, & Jemal,
2018) . Aging and cancer share many fundamental hallmarks including epigenetic alteration,
genomic instability, telomere attrition and senescence (Aunan, Cho, & Soreide, 2017). Most of
the studies on anti-tumor/anti-cancer properties of AKG are based on the reduction of the HIF-1α
subunit and inhibition of angiogenesis in hypoxic conditions. As explained earlier, AKG is a
mandatory co-factor for PHD2, which hydroxylates HIF-1α and leads to its degradation by the
proteasome. As a tumor grows, its demand for oxygen and nutrition increases and cells start to
run out of oxygen inducing the hypoxic response. In a hypoxic state, HIF-1α enhances the
transcription of genes necessary for blood vessel formation such as vascular endothelial growth
factor (VEGF) and PDGF-B (platelet-derived growth factor, type B), epidermal growth factors
and angiopoietin (Nishida, Yano, Nishida, Kamura, & Kojiro, 2006). The anti-angiogenic
properties of AKG have been confirmed in many in vitro studies, e.g. in the Hep3B and LLC cell
19
line, AKG can inhibit VEGF and erythropoietin production (Matsumoto et al., 2006; Matsumoto
et al., 2009). The same group studied the anti-tumor properties of intraperitoneal injection of
AKG alone and in combination with 5-fluorouracil, an antineoplastic agent used to treat multiple
solid tumors. Interestingly AKG alone or in combination inhibited tumor growth and
angiogenesis in tissues of mice with transplanted tumors (Matsumoto et al., 2009). These results
suggest AKG as a strong therapeutic candidate as an antineoplastic agent. AKG is lipophobic
and has low cell permeability; some in vitro studies applied a cell permeable form of AKG, e.g.
dimethyl-AKG, octyl-AKG and 1-trifluoromethyl benzyl-AKG, which have increased
hydrophobicity. These derivatives were also able to decrease the levels of HIF-1α in vitro
(MacKenzie et al., 2007).
Moreover, in a clinical study, AKG in combination with 5-hydroxymethylfurfurale (5-HMF) was
used as a pre-operative solution in patients with lung cancer. The results show significant
reduction of complications during surgery and better conditions before and after surgery (Matzi
et al., 2007).
Muscle protein synthesis: Aging is accompanied by loss of muscle mass and strength. Muscle
loss in elderly patients is believed to lead to a loss in functional capacity and to chronic
metabolic diseases (Breen & Phillips, 2011). AKG is important for the biosynthesis and
breakdown of amino acids. Glutamate dehydrogenase (GDH) and glutamine synthetase can
convert AKG to glutamine. Proline and arginine are other amino acids which can be synthesized
from AKG as well (Xiao et al., 2016). Moreover, in trauma patients who were highly catabolic
and hypermetabolic, the ornithine salt of α-ketoglutarate (OKG) has the capacity to induce
protein synthesis via the secretion of anabolic hormones: insulin, growth hormone (GH), and
20
insulin-like growth factor (IGF)-1 (Jeevanandam & Petersen, 1999). Many clinical and animal
studies have used OKG supplementation to improve protein metabolism in stressed subjects. In
these studies, OKG was found to inhibit proteolysis, glutamine loss, myofibril degradation, and
to increase protein synthesis (Cynober, Lasnier, Le Boucher, Jardel, & Coudray-Lucas, 2007;
Vaubourdolle et al., 1991). Clinical studies have shown that OKG supplementation in
malnourished older individuals results in a significant improvement in their overall health and
motor function (Brocker, Vellas, Albarede, & Poynard, 1994; Kovacs, Zelko, & Balogh, 2016;
Walrand, 2010). OKG administered orally, or as an enteral and parenteral nutrition has been used
repeatedly in different clinical studies to improve protein metabolism and restore glutamine
pools (Cynober et al., 2007). It can also restore the nitrogen imbalance and help with protein
catabolism in patients after severe burns, surgery or acute infections (Coudray-Lucas, Le Bever,
Cynober, De Bandt, & Carsin, 2000; Donati, Ziegler, Pongelli, & Signorini, 1999; Hammarqvist,
Wernerman, Ali, von der Decken, & Vinnars, 1989).
Bone loss: Aging causes deterioration in bone composition, micro-architecture and function, all
of which predispose the bone to osteoporosis (Raisz & Rodan, 2003). Although the mechanism
behind age-related osteoporosis is not fully understood, there is increasing evidence
(translational and clinical) showing a significant effect of age on driving osteoporosis in both
men and women (Raisz & Seeman, 2001). Both longitudinal and cross-sectional studies have
shown a slow rate of decline in bone mineral density (BMD) in both sexes starting at the age of
40 (Khosla & Riggs, 2005). So far, there are no interventions available to stop but only to slow
age-related bone loss. There are some evidence that AKG supplementation can help to slow bone
loss (Demontiero, Vidal, & Duque, 2012). As described previously, AKG can contribute to the
21
pool of amino acids necessary for collagen synthesis, the main protein of the bone matrix. AKG
can also play a role in bone quality by affecting proline and hydroxyproline formations. Another
mechanism by which AKG influences bone tissue is by impacting on the endocrine system.
Ornithine and arginine, which can be synthetized from AKG, can stimulate growth hormones
(GH) secretion and the insulin signaling (IGF-1) axis, thereby effecting bone loss. GH and IGF-1
stimulate proliferation of osteoblastic differentiation and bone formation (Giustina, Mazziotti, &
Canalis, 2008; Rosen, 1994). Glutamate synthesized from AKG can interact with glutamate
receptors (GluR) on the osteoblast and impact bone metabolism (Spencer, McGrath, & Genever,
2007). Furthermore, in an experimental osteopenia model induced by gastrectomy, AKG
supplementation has a positive impact on calvaria and trabecular bone, but failed to affect bone
mineral density (Dobrowolski et al., 2008). Study in menopausal women also showed that 24
weeks of CaAKG administration significantly increases the serum C-terminal cross-linked
telopeptide of type I collagen (beta-CTX) and helped with preserving bone mass density in the
lumbar in comparison to group receiving only Ca (Filip et al., 2007). Beta-CTX is derived from
the degradation of bone collagen and provides an indirect estimate of bone resorption (Okuno et
al., 2005).
Skin: The role of AKG in collagen synthesis also affects the skin. The contribution of AKG to
collagen biogenesis in skin has been tested in human cells and also in UVB-irradiated hairless
mice. In vitro, 10 μM AKG stimulates procollagen production in human fibroblasts and increases
the activity of prolidase, an important enzyme involved in collagen metabolism. Interestingly,
long term topical administration of AKG on the skin of UVB-induced rats increases collagen
production and inhibits wrinkle formation (Son et al., 2007).
22
Healthspan and aging
Since the 1950s, the average age of the global population has been increasing, due to a decline in
mortality that is associated with early life diseases. Discoveries of drugs for the treatment of
different diseases, better vaccinations, improved lifestyle, and more accessibility to healthcare
have also contributed to demographic changes and a dramatic rise of the percentage of the aged
population compared to the total. Aging manifests as a decline in health, multiple organ
dysfunction, and increased vulnerability to different diseases, which degrades the quality of life.
The common co-morbidities of aging have often proven refractory to clinical interventions.
Modern aging research arguably began in the 1930’s when it was shown that restricting access to
calories resulted in lifespan extension in laboratory rats. However, it did not become a growing
field until the discovery of single gene mutations that modulated lifespan in the late 1980’s.
What has emerged over the last thirty years is the principle that there are underlying biological
processes which drive death, aging and age-associated diseases. Intervening in these processes
increases lifespan, while delaying associated co-morbidities. Survival has been the primary focus
of aging research and multiple genetic and pharmacological interventions has been identified that
can enhance lifespan (Friedman & Johnson, 1988; D. E. Harrison et al., 2009; Howitz et al.,
2003; Kenyon, Chang, Gensch, Rudner, & Tabtiang, 1993; K. Lin, Dorman, Rodan, & Kenyon,
1997; Wood et al., 2004). Whether these interventions extend healthspan, the disease-free and
functional period of life, has only recently been tested and is often a matter of debate (Bansal et
al., 2015; Hahm et al., 2015). Currently the field is evolving towards incorporation of health to
aging studies. Recent research has addressed the efficacy of some of the longevity molecules in
extending both lifespan and healthspan in mammals (Bitto et al., 2016; Martin-Montalvo et al.,
2013; Mitchell et al., 2018). Here I present a summary chart focusing on mouse intervention
23
studies with small molecules that have applied different healthspan measurements as a
determination of the efficacy of a longevity compound.
Table 1. Frailty index as a biomarker of health; focusing on pharmacological interventions
(Palliyaguru, Moats, Di Germanio, Bernier, & de Cabo, 2019)
Interventio
n
Dosing Mouse
strains
Age at the
onset of
Administration
Health
measuremen
ts
Reference
s
Resveratrol 2 doses of RSV
(5.2 and 22.4
mg/kg) per day,
added to high fat
diet for 6 months
C57BL/6Nia 24 weeks-old Increased
endurance/mot
or function
(Baur et
al., 2006)
Resveratrol Added to high
fat diet for 6
months 25, 50 or
125 mg/kg/day
for 21 days
ICR 6 weeks-old Increased in
endurance
swimming test
for 25
mg/kg/day dose
(R. E. Wu
et al.,
2013)
Resveratrol Diet
supplemented
with 25 mg/kg
RSV for 4 weeks
C57BL/6J 64 weeks-old Increased in
grip strength
and endurance
swimming test
(Kan et al.,
2016)
Resveratrol Added to high
fat diet for 6
months 100
mg/kg
C57BL/6J 72 weeks-old Decreased in
frailty score
(Kane et al
2016)
Rapamycin Oral delivery of
microencapsulate
C57BL/6J 96 weeks-old Decrease in
muscle fatigue
and kyphosis
(Flynn et
al., 2013)
24
d rapamycin (14
ppm)
Rapamycin Diet
supplemented
with rapamycin
(14 ppm)
C57BL/6Nia 76 weeks-old Better motor
function, gait
Increased grip
strength and
spontaneous
activity in
females
(Y. Zhang
et al.,
2014)
Rapamycin Oral delivery of
microencapsulate
d rapamycin (14
ppm)
C57BL/6J 12 weeks-old No difference
in stride length
or age-related
hearing loss
Worsening of
motor function
in males
(Fischer et
al., 2015)
Rapamycin i.p.injection of 8
mg/kg
rapamycin for 90
days
C57BL/6Nia 80-84 Weeks-
old
Significant
increase in
muscle
function
(Bitto et
al., 2016)
Metformin Diet
supplemented
with 0.1%
metformin
C57BL/6 54 weeks-old Improved
physical
performance
(Martin-
Montalvo
et al.,
2013)
Metformin High fat diet
supplemented
with 1%
metformin for
six months
C57BL/6 48 weeks-old elped with
decline in
motor function
(Allard et
al., 2016)
25
Metformin Diet
supplemented
with 1%
metformin every
other week
C57BL/6 104 weeks-
old
Rotarod and
forelimb grip
strength tests
were performed
No difference
between
treatment
groups
(Alfaras et
al., 2017)
Nicotinamid
e Riboside
(NR)
i.p. injection of
NR 1000 mg/kg
twice daily for 5
days prior to
noise exposure
and two weeks
after the
exposure
BALB/c,
C57BL/6J,
CBA
(C57BL/6J
background)
8-10-weeks
old
Protection
against hearing
loss
(Brown et
al., 2014)
NR and
NMN
Dissolved in
water for
concentration of
(12mM)
Nampt
knockout
18 weeks-old Restored
exercise
performance
and endurance
in KO mice
(Frederick
et al.,
2016)
Senolytics
17-DMAG
Oral gavage 10
mg/kg for 3
days/week
(every 3 weeks)
INK-
ATTAC
mice on a
(C57BL/6J
x BALB/c)
background
6 weeks-old Reduced
incidence of
grip strength
loss, kyphosis,
poor coat
condition, gait
disorder, and
poor body
composition
(Fuhrmann
-
Stroissnig
g et al.,
2017)
26
Selective
Sirtuin
(SIRT1)
activator
SRT2104
100 mg/kg,
supplemented
diet oral delivery
C57BL/6J 24 weeks-old Higher
endurance on
treadmill and
rotaod
performance
(Mercken
et al.,
2014)
Selective
Sirtuin
(SIRT1)
activator
SRT1720
100 mg/kg,
supplemented
diet
oral delivery
C57BL/6J 24 weeks-old Significant
reduction in
cataracts
formation
(Mitchell
et al.,
2014)
Frailty Index as a biomarker of healthspan: The quality of life in old age is strongly linked to
functionality of different organs and to mobility, which are conditions of healthy aging (Searle et
al., 2008). In humans, the health status of old adults are very heterogeneous and many indices
have been developed to assess elements of functional decline with aging (e.g. sarcopenia,
cognitive function). A composite frailty index, which encompasses different aspects of frailty, is
classified as one of the most important risk factors for mortality and health status in older adults
(Kane, Ayaz, Ghimire, Feridooni, & Howlett, 2017). Although the biological mechanisms
driving frailty are poorly understood, it can be studied to measure a state of high vulnerability
and to poor health. Aging interventions conducted on mice add valuable knowledge that can be
applied to human aging studies. However, corresponding comprehensive indices in mice have
only recently been proposed and are seldom applied. Different frailty indices have been
generated to assess health in aging mice. Susan E. Howlett’s laboratory were amongst the first to
27
develop a mouse Frailty Index (FI) (Parks et al., 2012). The initial FI measures health-related
variables that are linked to the function of different systems that are known to change with age in
the inbred C57BL/6 mouse model. The parameters include the animal’s physical activity levels
(determined with a video tracking system), hemodynamic measures (e.g. blood
pressure, pulse, heart rate), body composition and basic metabolic status (e.g. pH, glucose,
sodium, potassium, and chloride). Although these indices provided useful information, they only
covered part of the phenotypes related to human aging and they required invasive procedures
(i.e. blood draw). Two years later, the same laboratory developed a FI which used simplified,
non-invasive methods to quantify 31 clinically relevant frailty phenotypes in aging C57BL/6J
mice. Changes in the FI of aging mice over time was further compared with human data (n=
30,025) and showed similar age-associated exponential changes (Whitehead et al., 2014). These
31 phenotypes have the same characteristic of human phenotypes and are indicators of age-
associated health deterioration. The revised indices covered a broader range of factors related to
frailty including physical/musculoskeletal, vestibulocochlear/auditory, respiratory system,
ocular/nasal, integument, digestive/urogenital, and aspects of physical discomfort. In order to
probe the relationship between healthspan and lifespan extension in mammals, in my study I
conducted blinded longitudinal clinically-relevant healthspan measurements every eight weeks
using the revised FI developed by Whitehead’s group.
Inflammation
Immune system
Immune cells known as leucocytes are generated from hematopoietic stem cells in the bone
marrow. Initially, pluripotent hematopoietic stem cells give rise to two main categories of white
28
blood cells: the lymphoid progenitor and the myeloid progenitor. The myeloid progenitor is the
precursor of granulocytes, monocytes and dendritic cells. Granulocytes have enzyme-containing
secretory granules and consist of neutrophils, basophils, or eosinophils. Neutrophils are the most
abundant and important cellular component of the innate immune system. Monocytes can
maturate to macrophages in human tissues, which play an important role in innate immunity.
The common lymphoid progenitor cells give rise to the lymphocytes. Two major types of
lymphocytes are B lymphocytes or B-cells (which mature in the bone marrow) which have
membrane immunoglobulin (mIG) antigen receptor and secrete antibodies and T lymphocytes or
T-cells (which mature in the thymus) which express T-cell antigen receptor. B and T cells are
functional inactive until they encounter antigen, which is necessary to trigger their proliferation
and subsequent differentiation. The third lineage of lymphoid cells are called natural killer (NK)
cells, which lack antigen-specific receptors and are part of the innate immune system.
Lymphoid organs contain a large number of lymphocytes and consist of two types: central (bone
marrow and thymus) where lymphocytes are generated and maturated and peripheral (spleen, the
lymph nodes and the mucosal-associated lymphoid tissues) where lymphocytes are maintained,
and adaptive immune response is initiated. Pathogens enter the body from different routes and
are eventually carried out by macrophages and dendritic cells to peripheral lymphoid tissues,
where antigens encounter lymphocytes. As adaptive immune response is initiated, lymphocytes
differentiate and proliferate and enter the blood stream. In our study, I used spleen as a
fundamental lymphoid tissue to further understand the immune response.
Inflammation and aging
Almost all age-related diseases are accompanied by chronic inflammation, which is referred to as
“Inflammaging” (Franceschi & Campisi, 2014). Inflammaging is a low-grade, systemic
29
inflammation in the absence of infection and is a significant risk factor for morbidity and
mortality in adults (Franceschi et al., 2000). There are several mechanisms which are responsible
for induction of chronic inflammation during aging. Some of these mechanisms are senescent
cells (Franceschi & Campisi, 2014) the inflammasome (Youm et al., 2013), the microbiota
(Bodogai et al., 2018) and the activation of microglia in the brain (Spittau, 2017).
I should highlight the fact that hundreds of association studies have shown a relationship among
inflammatory cytokines, adverse health outcomes and several chronic diseases in older adults.
Several studies in mice and humans have shown elevated levels of C-reactive protein (CRP) and
pro-inflammatory cytokines such as IL-6 and TNF-a (Bartlett et al., 2012). Furthermore, plasma
levels of IL-6 and TNF-a have been identified as predictors of 10-year mortality from all causes
(Varadhan et al., 2014) and an indicator of survival (Larbi et al., 2008). Recent studies have
shown imbalanced expression and production of both pro-inflammatory cytokines and anti-
inflammatory cytokines, such as IL-8 and IL-10 can contribute to different diseases (Zhen et al.,
2015). Interestingly, inflammation is absent in many healthy long-lived centenarians and they do
not experience elevations in cytokine levels (Franceschi, Monti, Sansoni, & Cossarizza, 1995).
Many studies in mice and humans have shown age-associated changes in effectiveness of both
the innate and adaptive immune systems to respond to newly encountered pathogens.
The aging immune system contains fewer B-cells with specifically smaller numbers of memory
B-cells (Gibson et al., 2009). In addition, B-cells in aged mammal are less efficient in responding
to new pathogens and produce fewer antibodies (S. A. Johnson, Rozzo, & Cambier, 2002).
Thymus size decreases 3% per year shortly after birth, and continue to shrink as humans age
(Steinmann, Klaus, & Muller-Hermelink, 1985). Shrinkage of thymus affects the number of
30
peripheral T-cells in the blood. Although fewer numbers of T-cells enter the blood in the aged
population, the T-cell pool stays the same. This homeostatic mechanism requires T-cells to live
longer or proliferate more which affects their efficacy (Hadden, Malec, Coto, & Hadden, 1992).
In addition, the aged thymus has a higher rate of production of dysfunctional T-cells (Aspinall &
Andrew, 2000). The aged T-cell population also has a slow differentiation rate (Shanley, Aw,
Manley, & Palmer, 2009). For instance, aged mice express higher levels of CD122 cytokine
receptor, which do not differentiate into efficient effector T-cells (Messaoudi, Warner, &
Nikolich-Zugich, 2006). Another phenotype that is associated with the aging immune system is
an inverted ratio of CD4/CD8 (Strindhall et al., 2013). CD4
+
cells are helper and immune
inducing cells while CD8
+
have cytotoxic functionality. CD4
+
cells help to coordinate the
immune response by stimulating other immune cells including macrophages, B lymphocytes and
CD8
+
T lymphocytes (Taniuchi, 2018). The normal ratio of CD4/CD8 is usually between 1.5 and
2.5, however different factors (sex, age, genetics, exposures and infections, (Strindhall et al.,
2013) can impact on this value (Howard, Fasano, Frey, & Miller, 1996). A low or inverted
CD4/CD8 ratio is an immune risk phenotype and is associated with altered immune function,
immune senescence, and chronic inflammation (Appay & Sauce, 2008; Wikby et al., 2005).
The number of NK cells also increases in aged individuals as their efficacy decreases (Solana et
al., 2012). The number of neutrophils, macrophages and dendritic cells have been reported to
remain the same in the aged human population. A summary of well-studied age-associated
inflammatory phenotypes in human population can be found in the Table 2.2 (Gubbels Bupp,
2015).
One important contributor to inflammaging is cellular senescence which will be discussed in
detail later in this section.
31
Table 2. Age related inflammatory phenotypes in human
32
Sex and the immune system
Females and males have different immune systems. Immunologic responses change more
robustly after puberty when the effects of sex hormones are initiated. Females have a more
intense innate and adaptive immune response than males (Amadori et al., 1995; Scotland,
Stables, Madalli, Watson, & Gilroy, 2011). In females, the macrophage population is larger and
more efficient (Scotland et al., 2011). Antigen-presenting cells (APCs) express higher levels of
MHC class II which leads to higher efficacy in females (Weinstein, Ran, & Segal, 1984). APC
cells also secrete higher levels of IL-12 that drives naïve T-cell differentiation into T helper type-
1 cells, which enhances the function of macrophages following IFN-g secretion (Metzger, 2010).
Another piece of evidence for the robust adaptive immunity in females is the response to
immunization. Women upregulate more Toll-like receptor (TLR)-associated genes after viral
vaccination (Klein, Jedlicka, & Pekosz, 2010). The number, differentiation state, and function of
lymphocytes differ between sexes. For instance, studies have shown higher levels of
immunoglobulin, CD4 T lymphocytes (CD4+) and in the CD4/CD8 T-cell ratio in females than
to males (Amadori et al., 1995). Aging mostly affects the immune system similarly in both males
and females. Chronic inflammation and inefficacy of innate and adaptive immune response, as
discussed earlier, are hallmarks of aging in both sexes (Gubbels Bupp, 2015). However, the risk
for developing chronic inflammatory diseases like atherosclerosis and type II diabetes are higher
in men ages of 40-60 years old (Group, 2003). Very interestingly, after menopause women show
an increased risk for atherosclerosis and type II diabetes when compared to men. Aging men
usually have a lower risk for developing autoimmune disease, but again after menopause women
become less susceptible for developing auto-immune diseases (Cooper & Stroehla, 2003). This
strongly suggests the effects of sex hormones on inflammatory responses, as women are exposed
33
to the highest amount of estrogen right before menopause and estrogen levels significantly
decrease after menopause (Gubbels Bupp, 2015). Some studies suggest that estrogen has
protective effects on chronic inflammation (Elhage et al., 2005).
Overall aging is a complex process that proceeds at a different pace in men and women. More
studies need to be done to unravel the complex relationships between immune responses and sex
hormones.
Cellular senescence
Cellular senescence is historically recognized as a potent anti-tumor mechanism that leads to
permanent cell cycle arrest (Campisi & d'Adda di Fagagna, 2007). In addition to their
irreversible arrest, senescent cells also acquire widespread changes in chromatin organization
and gene expression that lead to pro-inflammatory properties which can detrimentally impact the
surrounding tissues (van Deursen, 2014). Different stimuli that can provoke cellular senescence
include telomere shortening, mitogenic signals, genomic damage, mitochondrial dysfunction and
activation of tumor suppressor genes (either or both p53/p21 and P16
INK4a
) which are increased
during aging (Campisi, 2013). In vivo findings have shown an increase in senescent markers in
various tissues of aging mice including skeletal muscle, eye, kidney, lung, heart, liver and spleen.
Moreover, it has been shown that senescent cell removal benefits longevity (Baker et al., 2016).
Senescent cells contribute to organism aging and can drive age-related phenotypes through
different mechanisms. Arguably the most important mechanisms for driving age-associated
pathology by senescence is through acquiring a senescence-associated secretory phenotype
(SASP) (Campisi, 2001). The SASP is a major contributor to alterations observed in the
microenvironment and surrounding cells. Its components include inflammatory chemokines,
34
cytokines, growth factors and proteases. Despite initial findings suggesting that senescent cells
only have anti-tumor properties, some SASP components including amphiregulin, growth
regulated oncogenes (GRO), and VEGF can cause hyperplasia. Many SASP components
including IL-6, IL-8, MCPs (monocyte chemoattractant proteins), GM-CSF
(granulocyte/macrophage colony-stimulating factor) and MIPs (macrophage inflammatory
proteins) can induce inflammation (Coppe, Desprez, Krtolica, & Campisi, 2010). Chronic
inflammation can impact stem cell proliferation and regenerative capacity. IL-6 and IL-8
specifically can stimulate or inhibit WNT, which drives stem cells to differentiation or arrest
(Elzi, Song, Hakala, Weintraub, & Shiio, 2012; D. Y. Zhang, Wang, & Tan, 2011). There are
different markers for the identification of senescent cells, including histochemical staining for
cytoplasmic beta-galactosidase (SA-betagal) which was the first identified and still most
common marker utilized (Dimri et al., 1995). Other markers include p16
INK4a
and p53/P21
expression, which are low or undetectable in most cells but increase during senescence and with
aging (Serrano, Lin, McCurrach, Beach, & Lowe, 1997). Other markers include DNA-SCARS
(DNA segments with chromatin alterations reinforcing senescence), SAHF (senescence
associated heterochromatin foci), DEC1 (deleted in esophageal cancer), Decoy Receptor 2 and
lamin B1. Although not all senescent cells express all of these senescent markers, they are often
identified by combined expression of several of these (Campisi, 2013). In my study, I used SA-
betagal staining and p16
INK4a
and p53/P21 expression levels to identify senescent cells and to
study the effect of AKG intervention.
35
Role of C. elegans
C. elegans was used as a genetic model for the first time by Sydney Brenner nearly 50 years ago
to answer basic questions in biology (Brenner, 1974). Over the ensuing years, the worm’s short
lifespan, small size (~1 mm in length), transparent body, economic propagation (E. coli as a food
source) and well-annotated genome have made the animal an invaluable tool for addressing
biological questions. Being a self-fertilizing hermaphrodite with a short life cycle and high
progeny number (300/nematode), they allow the production of thousands of genetically identical
animals (WormBook, ed. The C. elegans Research Community). The transparency of the worm
allows visualization of individual cells and tissues in vivo in live animals: different fluorescent
tagged proteins can be used to study different cellular processes, to screen for mutants, for cell
isolation, and to assess in vivo protein interactions (Chalfie, Tu, Euskirchen, Ward, & Prasher,
1994; Feinberg et al., 2008). For all these reasons, the nematode has been widely used for aging
studies and led to the discovery of the first aging gene. About 30 years ago, a mutation in the
genetic homologue of mammalian phosphatidylinositol-3-OH kinase (PI3K), called age-1, was
found to extend both the average (+65%) and maximal lifespan (+110%) of the nematode
(Friedman & Johnson, 1988). Additional studies in C. elegans led to the identification of another
long-lived mutant called DAF-2 (Kenyon et al., 1993). This mutation was subsequently
identified as the homologue of mammalian insulin/insulin-like growth factor (IGF)-1 receptor
and led to the discovery of the downstream life-extending daf-16 gene (Kimura, Tissenbaum,
Liu, & Ruvkun, 1997). Daf-16 was later identified as the homologue of the mammalian
forkhead/winged-helix transcription factor (FOXO), a critical stress-responsive and energy-
sensitive master regulator that controls a plethora of cellular defensive mechanisms (Lin,
Dorman et al. 1997). These findings highlight the fundamental role that C. elegans has played in
36
aging research. In addition, C. elegans has also emerged as a tool for drug discovery. Different
organ systems and multi-cellular complexity existing in a whole organism improves the chances
of identifying a drug that will have efficacy in humans versus use of cells in culture (O'Reilly,
Luke, Perlmutter, Silverman, & Pak, 2014). The same properties that make them versatile tools
for genetic investigations and aging studies—small size, short lifespan, short generation time and
genetic amenability—together with the availability and simplicity in application of genetic tools
(e.g., RNAi-feeding libraries), make C. elegans an excellent candidate for whole organism-based
high-throughput small molecule screening (HTS) (O'Reilly et al., 2014). C. elegans homologs
have been identified for ~70% of human genes including those involved in many human-related
diseases including Alzheimer’s (Wittenburg et al., 2000), Parkinson’s (Braungart, Gerlach,
Riederer, Baumeister, & Hoener, 2004) and diabetes (Ogg et al., 1997) , all of which are not
completely reproducible in in vitro or in unicellular models.
Limitations of C. elegans
Despite all the many positive attributes that the C. elegans model offers for aging research, there
are some drawbacks in using the nematode to model human aging. The nematode lacks specific
organs including liver, blood, fat tissue etc., limiting the understanding of tissue-specific
signaling and gene expression (Artal-Sanz, de Jong, & Tavernarakis, 2006). As an invertebrate,
they are considered evolutionarily distant from humans and some aging-specific pathways are
absent in these animals (Antebi, 2007). In addition, the larvae of C. elegans is capable of
entering a specific dauer state which enables the animal to undergo long term survival in harsh
environments, a state which is absent in mammals.
As a drug discovery tool, C. elegans has an inefficient drug uptake caused by an impermeable
cuticle and limited number of receptors in the intestine (Zheng, Ding, Li, Wu, & Luo, 2013). The
37
nematode’s laboratory food source, E. coli, can metabolize and change the efficacy of
compounds delivered to the worms (Garcia-Gonzalez et al., 2017). Lacking specific organs such
as a liver also limits pharmacokinetics studies which can be performed in mammalian systems
(Artal-Sanz et al., 2006).
Role of M. musculus
Laboratory rodents and mostly mice are another common model for aging studies. The wealth of
existing physiological knowledge, convenience of use, well annotated genome, genetic similarity
to humans, availability of transgenic lines, relatively short lifespan, and low cost have made
them ideal tools for various research including age related studies.(Martin-Montalvo et al., 2013;
Vanhooren & Libert, 2013). All the pharmacological or genetic interventions for aging found in
other invertebrate models should be tested in the mammalian system before moving forward to
humans. Although mice have their own limitations and do not precisely replicate human
physiology, many researchers argue that the mouse model system is necessary to fully
understand aging. Furthermore, clinical trials require data from mammalian models, mostly
mice, to assess safety and efficacy (Mitchell, Scheibye-Knudsen, Longo, & de Cabo, 2015).
Caloric restriction (CR) is the gold standard longevity intervention. The potential longevity
effects of CR were initially found in rats (McCay, Crowell, & Maynard, 1989). Later, multiple
mouse strains were used to extensively study the various levels of CR and its elusive longevity
mechanism (Weindruch, 1996).
Although invertebrate models have led to the discovery of many conserved aging pathways,
further studies carried out in mice have offered valuable insights into life-extending
interventions. For instance, resveratrol which activates mammalian SIRT2 as well as its homolog
38
SIRT1, later was discovered to extend the lifespan of mice receiving high-fat diet (Baur et al.,
2006). This finding lead to the synthesis of compounds with higher specificity and potency for
SIRT1 that can extend the lifespan of mice on a regular diet. These pre-clinical mouse studies
were followed by clinical trials using two of SIRT1 activators (STAC): SRT1720 and SRT2104
(Mercken et al., 2014; Mitchell et al., 2014). Because of the protective effect of STACs, the NIH
is now evaluating the safety and tolerability of SRT2104 in type 2 diabetes patients and in
healthy cigarette smokers. Using oxidative stress, platelet activation and inflammatory markers
as a read out, this study is now in a phase one clinical trial (SRT2104 Clinical Trial:
NCT01031108). Findings in mice also set the groundwork for clinical metformin studies in
healthy older adults which is now in a phase four clinical trial (Metformin Clinical Trial:
NCT02432287).
Although survival has been the main focus of aging research, healthy aging is an ultimate goal of
aging interventions. Mouse models have been used to study the beneficial impact of longevity
interventions on health. Several comparable aging phenotypes between mice and humans have
enabled aging researchers to identify compounds that can increase healthspan (Kane & Sinclair,
2019). Comprehensive aging indices have been described and used in several aging studies in
mice (Palliyaguru et al., 2019). Interestingly, the healthspan effects of longevity interventions
such as metformin, rapamycin, and nicotinamide were discovered utilizing aged mice (Fischer et
al., 2015; Martin-Montalvo et al., 2013; Mitchell et al., 2018).
39
Sexual Dimorphism
Females and males have different lifespan and rates of aging across different species, with
females outliving males in most species including humans (Barford, Dorling, Davey Smith, &
Shaw, 2006; Holden, 1987). The hypothesis that explains these differences center around two
main topics: inheritance of the X chromosome and the mitochondrial genome. Other hypotheses
are based on sex-specific selection (influence of sex hormones and receptors) and the
fundamental trade-off between reproduction and survival in both sexes, which can drive sexual
dimorphism (Maklakov & Lummaa, 2013).
The role of the X chromosome in lifespan relies heavily on the fact that males are more prone to
the danger of recessive deleterious mutations occurring on X (or Y) chromosomes, as they are
not guarded by alleles on the remaining chromosome. Hormonal influences on sexual
dimorphism is the direct outcome of genotypic sex. Sex chromosomes determine the phenotype
of the gonads, and gonads in turn are responsible for production of the circulating sex hormones.
Different hormone levels at specific times in XX and XY individual life drives not only many
phenotypic changes (appearance and body size) but susceptibility to certain diseases (Carroll et
al., 2010; Sinauer Associates, 2001).
The next most cited hypothesis is a consequence of maternal inherence of mitochondrial genome,
which can lead to the accumulation of male-specific deleterious mutations in the mitochondrial
DNA (mtDNA) (Birky 1995). This can evoke a sex-specific selection for changes that align best
with female nuclear genes (Frank 1996, Camus, Clancy et al. 2012) (Innocenti, Morrow et al.
2011). Therefore, mutations that have a neutral, or in some instances, positive impact on females
will be selected for. On the other hand, the same mutations can lead to a mitochondrial burden
and act to accelerate the aging process in males. Maternal inheritance of mitochondrial genome
40
can also lead to more efficient mitochondrial function in females, especially in tissues with a
high metabolic rate (Roy and Chatterjee 1983). The exact molecular basis of sexual dimorphism
is still elusive; researchers have shown that 60% of autosomal gene expression is sexually
dimorphic in different tissues. It is believed that master transcriptional factors (e.g. Forkhead
Box P1/P4 and the breast cancer 1 gene) are strong drivers of sexually dimorphic gene
expression (Chen, Lopes-Ramos et al. 2016).
Sexual dimorphism also affects the occurrence rate of age-related diseases in men versus
women. Men are at a higher risk for developing Parkinson’s disease, type II diabetes, cancer
(Clocchiatti, Cora et al. 2016), ischemic heart disease, and hypertension (Freeman 2001).
However, women are much more susceptible to developing AD, osteoporosis, and rheumatoid
arthritis (Ostrer 1999, Kaminsky, Wang et al. 2006).
Sexual dimorphism impacts interventions affecting longevity in different model systems. For
instance, SIRT6 overexpression in male mice, but not females, extends lifespan (Kanfi et al.,
2012). Similarly, pharmacological interventions have different results on males versus females:
nordihydroguaiaretic acid and aspirin significantly increase life span in heterogeneous male, but
not female, mice (Strong et al., 2008). Understanding the mechanisms behind the diverse
responses to longevity interventions between sexes can have large implications in aging studies.
Due to these differences, aging studies should include both sexes when determining the success
of any translational interventions.
41
Limitations of Mouse Models
Mice provide invaluable insights into the therapeutic safety and efficiency of drugs in humans,
but they also have their drawbacks. The high failure rate in clinical trials (more than 80%) is
proof of the remaining challenges in translational research and imperfection of the use of mouse
models (Perrin, 2014).
Inbred mice have been extensively used for the study of aging and age-related diseases. Genetic
similarity between the offspring minimizes genetic variables in the experiments that might affect
the outcome. However, the genetic uniformity of inbred strains is not representative of the
human population. C57BL/6 mice, upon which 70% of published animal studies have relied on,
show high prevalence of lymphoma and increased susceptibility to metabolic diseases (Ward,
2006). It also has been argued that laboratory mice are metabolically obese and eat roughly 20%
more than mice in the wild (Martin, Ji, Maudsley, & Mattson, 2010) This makes interventions
like CR more effective in these animals (Mitchell et al., 2015). As discussed previously, mice
generally have similar aging phenotypes to humans (cognitive decline, tremor, weight loss, etc.).
However, some inbred strains of mice display premature aging for some phenotypes including
hearing and vision loss (Tremblay, Zettel, Ison, Allen, & Majewska, 2012). In addition, mice are
not known to naturally develop some age-related diseases including Alzheimer’s disease (AD)
(Do Carmo & Cuello, 2013). Given the enormous expense and time in developing a drug, it is
important that the models we use provide the strongest possible basis for validating likely
outcomes in humans. Part of the solution may be testing interventions in a range of species
including non-human primates.
42
CHAPTER 2: RESULTS
AKG was previously tested in the Caenorhabditis Intervention Testing Program (CITP) which
utilizes a set of wild-derived nematode species as aging models. CITP is a multi-center research
program that tests pharmacological interventions across 3 different labs in diverse genetic
backgrounds. As part of this program, we identified several compounds that displayed
reproducible positive longevity effects across the different laboratories. Depending on the
compound, these effects appeared to be differentially influenced by genetic background (Lucanic
et al., 2017). AKG was one of the most consistent and robust chemicals we tested, as it
Figure 4. The effect of AKG treatment on median lifespan in different nematode strains
Treatments is shown for six different Caenorhabditis strains. The percent difference in
median lifespan was determined by calculating the median lifespan for each plate population
(single plate lifespan assays starting with 35–40 animals, each site at least 6 plates in at least
2 biological replicates). Each point represents the percent difference in median lifespan
between one plate and the control. Points are color coded to indicate the lab the data was
collected in. Middle bar represents the mean with small bars indicating the s.e.m. Asterisks
represent P-values from the Cox proportional-hazards model; ****P<0.0001 (Lucanic et al.,
2017).
43
significantly and reproducibly extended lifespan in 3 out of the 6 strains tested, with only HK104
responding negatively to treatment (Fig. 4, (Lucanic et al., 2017).
The potent and robust longevity effects that AKG had on different Caenorhabditis strains
suggests that the molecular mechanism targeted by our compound is likely a conserved aging
mechanism. However, the failure to extend C. briggsae lifespan showed that conservation may
not be universal. To further test the conservation of the effect, we chose to test efficacy of the
intervention on an evolutionary distant species, namely laboratory mice, to study effects of AKG
on mammalian aging.
As a part of our study, we were also interested to look into combination interventions for
synergistic effects on longevity. The hypothesis came from previous work in the application of
genetic tools for synergistic lifespan extension. Chen et al. generated daf-2 rsks-1 double mutants
which exhibited a 5-fold life span extension as compared to wild type. This synergistic effect
requires expression of DAF-16 (FOXO) via AMPK (D. Chen et al., 2013). The goal of our study
was to determine the right combinations of compounds that would have synergestic effects in C.
elegans, that may be more potent than individual compounds. In these studies, AKG positively
affected all combination treatments it was a part of (Fig. 5a). We next moved our combination
treatments to mice. Suprisingly, AKG alone had the most robust effect on mamalian lifepsan
(Fig.5b) versus that of any combination treatament. These findings resulted in AKG becoming
the primary candidate for more thorough aging studies including health and mechanstic studies
in mice.
44
Figure 5. AKG and AKG combination treatment can extend the lifespan of C. elegans.
(a) Lifespan of wild type N2 animals exposed to different compounds and their combinations
beginning as young day 1 adults. Each survival curve consists of 3 plates in 3 biological
replicates. Each plate was initiated with n=35 animals. (b) Survival graphs for female mice
receiving different compounds and their combinations added to their regular diet beginning at
540 days old. Survival graphs are shown as days alive post treatment and each treatment
group consist of 21 ± 3 female animals.
45
α-ketoglutarate supplementation extends lifespan and decreases mortality in mice
For our mammalian study, aged C57Bl/6 mice were used. Two independent cohorts of mice were
purchased from Jackson Laboratories at 14 months of age. Animals were aged in our vivarium
facility on a regular diet (18% protein and 6% fat diet-Teklad 2918) which is very similar to their
diet at Jackson Laboratories; 5K52 (18-19% protein and 6-7% fat). At 18 months of age, mice
were divided into treatment and control groups: while control mice were kept on a standard-2918
diet, the treatment group was subjected to a lifelong 2% (w/w) AKG supplementation on the
standard-2918 diet (Fig. 6). In order to increase the number of animals and test for
reproducibility of lifespan data, we assessed two independent cohorts of mice. The first cohort
was started on June 2016 and consisted of 89 animals. The second cohort was started on January
2018 and consisted of 93 animals (45± 2 females and 45± 2 males for each cohort). The first
cohort was used for non-invasive health related measurements as described in (Fig. 6). Since any
invasive measurements would have affected the survival of the animals, I designed two
sacrificial groups, the first consisting of 12 animals and the second consisting of 20 animals. The
first sacrificial group consisted of only females treated for 3 months with CaAKG. The second
sacrificial group was treated for 6 months and both sexes were represented. Tissue collected
from these animals were used for mechanistic studies (please refer to Fig. 6 for an illustration of
the overall study plan).
Dietary supplementation of AKG was found to increase survival in these two independent
cohorts of aged mice (Fig. 7). In the first cohort of female mice, median lifespan and survival
(age at 90th percentile mortality) were significantly extended (by 16.6% and 19.7%,
respectively) as measured from the inception of CaAKG feeding. These findings were replicated
46
in the second cohort of mice: the female median lifespan and survival were significantly
extended (in this case by 10.5% and 8%, respectively, Fig. 7.a, b and Table 3). Improved
survival for males displayed a trend but was not statistically significant in either cohort (Fig 7d,
e). Median lifespan was extended by 9.6% and 12.8% from the inception of treatment in the first
and second cohort respectively (Table 3).
47
Figure 6. Experimental Design
The mice were fed AKG or standard diet at 18
months of age. The study consists of two
cohorts ( n=182) for survival data and two sacrificial groups (n=12 and n=20). Cohort-1
mice were used for all the frailty index measurments and lifespan. Cohort-2 mice were
used for replication of survival data, metabolic studies and complementary aging studies.
We started the diets for all groups at the same age (18 months).
48
Figure 7. AKG extends lifespan and decrease mortality in mice
Post treatment survival plots graphed separately for Cohort-1 and Cohort-2. Comparing
control mice to those fed AKG in the diet starting at 18th months of age. Arrows indicate the
start of the treatment. (a, b) female (Cohort-1, n=43), (Cohort-2, n=45) and (c) Survival for
pooled female. (c, d) male and (Cohort-1, n=46), (Cohort-2, n=47) and (f) Survival for pooled
male. Survival curves comparison were performed using Log-rank test, *P < 0.05. Maximum
lifespan extensions were calculated using fisher’s exact test statistics, **P <0.05 for female
Cohort-1.
49
Table 3. The effect of AKG supplementation on lifespan
50
α-ketoglutarate supplementation improves healthspan and decrease morbidity in aging
mice
In order to assess whether AKG treatment has an effect on healthspan, we applied measurements
based on a clinically relevant frailty index (Searle et al., 2008; Whitehead et al., 2014).
The Frailty Index (FI) consists of 31 phenotypes that are indicators of age-associated health
deterioration. The complete description of how each phenotype is scored can be found in the
supplemental section of the original manuscript by Whitehead, J.C., et al. In our study, each
phenotype is scored on a 0, 0.5 or 1 scale based on its severity (Fig. 8), except for temperature
and body weight. Briefly, for temperature and body weight, new scaling scores were used;
average and standard deviations (STDEV) were calculated for each sex using our own baseline
data. Our baseline data was collected right before the start of the treatment of animals at 18-
months. A decrease in temperature or body weight within one STDEV was scored as a 0, a
decrease bigger than one STDEV but smaller than 2 STDEV was scored as a 0.5 and any
decrease more than 2 STDEV was scored as a 1. All scorings were conducted blinded and were
undertaken by the same person throughout the animal’s life. These measurements were repeated
approximately every eight weeks, providing us with eight and seven sets of data, respectively,
for male and female groups. The total frailty score which is the sum of 31 frailty phenotypes was
calculated for each mouse at a given timepoint. The “total frailty score” and “total score” terms
were used interchangeably. The complete list of the phenotypes is shown Fig. 8.
51
Figure 8. Effects of aging in mouse
52
We used the total frailty score (total score) to indicate the state of increased vulnerability to
adverse heath outcomes which is comparable to morbidity. We observed that in both female and
male animals, AKG decreased incidence and severity of different aging phenotypes and
postponed morbidity (Fig. 9a, b). Females showed significant improvements after 9 months of
AKG supplementation (P<0.001, Fig. 9a). Male animals began to show significant health
improvement after 11 months of AKG supplementation and these improvements persisted until
the last measurement at 33 months of age (P<0.001, P<0.01, Fig. 9b). Since our experimental
design takes repeated measurements on the same experimental units (same mice) over time, our
analysis of the data should take into account the probability that measurements for a given
experimental unit (given mouse) will be correlated overtime in some way. I took further step to
analyze the data longitudinally. I applied Mixed Models to analyze our longitudinal data (Fig. 9).
In the current Mixed Model, subjects (every mouse with a unique ID) were treated as a random
factor. Treatment and time were treated as fixed factors (L. Wu, 2010). Further, the chi-square
statistic was calculated for comparing the fit of the current Mixed Model to a simpler ANOVA
which is not accounting for repeated measures. The very small P value (P<0.0001) for chi-square
indicates that our current analysis model was very effective (Fig. 9a, b). Our results show that, in
both female and male animals, CaAKG decreases incidence and severity of aging phenotypes
and postpones morbidity (Fig. 9).
53
54
Since the age of onset of age-related phenotypes was quite heterogeneous in our study, we
plotted frailty datasets not only as a function of chronological time (age), but also in proportion
to the lifespan of each mouse. In order to do this, we calculated the percent of lifespan against
each frailty measurement time point for each animal (Fig .10). This allowed us to test whether
AKG decreased the proportion of the life period in which the animal is frail and vulnerable to
adverse health outcomes independent of how long the animal lives. We plotted our data by
binning scores within ten percentiles in each group. (e.g. scores collected between 60% and 70%
of the animal’s lifespans were binned and plotted together) (Fig. 11). This approach allowed us
to align assessments with respect to the biologic age of the animal. Our findings show that AKG
treatment decreases the proportion of the lifespan spent in a morbid state. This improvement in
healthy days of life is disproportionately larger than the increase in lifespan (determined as the
area under the frailty curve and calculated at a 46% reduction for females and 41% for males,
Fig. 11a, b). Our results also suggest that AKG modulates the rate of frailty changes with age in
females; Mixed Model was applied not only for the total score against the percentage of lifespan,
but also for the interaction between total score and lifespan percentage allowing us to examine
Figure 9. AKG extends health span and alleviates age-associated frailty
Separately graphed (a) female and (b) male total Frailty Index (FI) scores during lifespan,
comparing control mice (blue) to those fed AKG in the diet (pink) starting at 18th month.
Each dot is the total score of one animal at specific age as indicated. Data are mean ±s.e.m. of
each group. n= all animals alive at each measurement time. Mixed Model was used to
analyze the data longitudinally. In the current Mixed Model, subjects (every mouse with a
unique ID) were treated as a random factor. Treatment and time were treated as fixed factors.
The low P value for Chi-square for significant matching effect indicate that the pairing was
effective; Comparing the fit of the current Mixed Model to a simpler ANOVA,
****P<0.0001.
For the comparison in each time point Two tailed t-test was used; *P <0.05, **P< 0.01,
***P< 0.01
55
the impact of AKG treatment on the relationship between biological age and the total frailty
score. Our findings demonstrate that AKG can compress morbidity significantly in females
(Fig.11).
Figure 10. The graphic illustration of morbidity
In this example, mouse (1) lives up to 32 months of age and mouse (2) lives up to 24 months.
When mouse (1) is 24 months old, its at 75% of its lifespan. However when mouse (2) is 18
months old, it is at 75% of its lifespan. For graphing our data we pooled the scorings for mice
with the same percentage of lifespan together ( In this case, 24
th
and 18
th
months old control
mice (1) and (2) were graphhed togethr at 75% timepoint). In the AKG supplemented group
mouse (3) and (4) were plotted togetehr at 95% of lifespan (they were 30 and 23 months old).
As the animal ages and gets closer to death (higher percentage of lifespan) it manifests
several aging phenotypes and will be at its highest multi-morbidity risk. My data show that
feeding AKG can compress this morbidity period.
56
57
To determine whether there is a correlation between applied Frailty Index and life expectancy,
we graphed the total score of each animal against its remaining days of life. Our data show that
higher scores for control mice correlates negatively with life expectancy and can be considered
as a risk factor (Fig. 12). Data also were fitted with a simple linear regression line to further
assess the effect of AKG treatment. AKG treatment can significantly decrease the slope of the
regression line in both males and females (Fig. 12a, b).
Figure 11. Compression of morbidity by AKG administration
As the animal ages and gets closer to death (higher percentage of lifespan) it manifests
several aging phenotypes and will be at its highest multi-morbidity risk. Total scores of
31-phenotype (FI), are considered as morbidity scores. Separately graphed (a) female
and (b) male mice total frailty scores by the proportion of their lifespan. AKG
supplementation postpones the occurrence of aging phenotypes during lifespan and
compresses the morbidity risk into fewer days of life in both sexes. Each dot is the total
score of one animal. Lines are mean ±s.e.m. of the group. n= all animals alive at each
time. Area Under the Curve (AUC) was calculated seprately for females and males,
baselining at 18
th
months old. Mixed Model was used to analyze the data longitudinally.
In the current Mixed Model, subjects (every mouse with a unique ID) were treated as a
random factor. Treatment and time were treated as fixed factors. The low P value for
Chi-square for significant matching effect indicate that the pairing was effective;
Comparing the fit of the current Mixed Model to a simpler ANOVA, ****P<0.0001.
58
Figure 12. Total Frailty Score has strong correlation with life expectancy in aging mice
a, b) The total scores for each mouse were plotted against remaining life (life expectancy).
Pearson correlation coefficients (r), and associated P-values have been indicated. There are
negative correlations between total score and life expectancy in both female and male
animals. However, AKG supplementation abolished this correlation in male animals.
Lines of best fit for each treatment group have been graphed. The equation of each regression
line is shown in colors corresponding to the data points (y= bx+a). Where x is the
explanatory variable, b is the slope of the line, and a is the intercept. The reported p-value is
the result of analysis of covariance (ANCOVA) for regression lines. AKG adminstration can
significantly decrease the rate of linear relationship between life expectancy and total score in
both males and females.
59
To determine which Frailty phenotypes were the most affected by our treatment, we compared
individual frailty indicators at different time points (Fig. 13). AKG treatment significantly
decreased the severity of multiple aging phenotypes in females, including piloerection, grimace
(pain assessment), alopecia, loss of fur color, poor coat condition, grip strength loss, gait
disorder, rectal prolapse and loss of body weight (Fig. 13a). In males, grip strength loss, gait
disorder, balance loss (vestibular disturbance), grimace, loss of menace reflex (Miller & Leach,
2015), hearing loss, eye discharge, poor coat condition, poor body condition, tail stiffening and
abnormal breathing rate were significantly decreased (Fig. 13b). The improvement in health of
both sexes was most prominent around the median lifespan of the animal (27-29 months old).
As in almost all longitudinal studies, the missing values have caused data fluctuations during the
course of our study. The main contributor to the fluctuation is the death of the morbid animal
between measurement time points. When the morbid animal dies and is omitted from the group,
the total frailty score of the group is improved (lower scores). As remaining mice might exhibit
the aging phenotype in later times, again the total score of the group will increase (Fig.13). To
overcome this issue for the readers, the total number of animals measured at each time points are
indicated (Fig. 13). For instance, a continued decrease in vestibular disturbance in males (Fig.
13b) from months 23-27 is a consequence of death of a subset of animals in this period. As the
animals in the group continue to age, additional mice in the cohort will be affected with
vestibular disturbance, resulting in change of the group scoring for this parameter. The only
reversible aging phenotype noted in the AKG-treated group was hair discoloration while the drug
was found to slow the progress of other aging phenotypes.
60
Reversal in both prolapse and dermatitis were due to vivarium-mandated treatments of these
conditions rather than the effects of AKG treatment (Material and Methods: Animal housing).
Figure 13. AKG administration alleviates multiple age-associated frailty
Separately graphed (a) female and (b) male individual frailty phenotypes comparison. Data
are mean ±s.e.m. of the group, n= all animals alive at each measurement time. *P <0.05, **P
< 0.01, P<0.001, ***P< 0.001 and ****P <0.0001 (Two tailed t-test).
61
Whitehead and colleagues used young adult (5 months), middle aged (19 months) and aged (28
months) mice to establish the frailty index. Their findings show that as the animal age from 5
months to 28 months, the frailty score increases significantly. The mice we used for frailty were
in an age range from 18 to 33 months. The choice of older animals in our studies was intended to
determine whether aging significantly affects the elements of frailty used in our study. When
testing each individual aging phenotype against time using one-way ANOVA, not all frailty
indices showed age-associated effects. Therefore, data has also been graphed which only include
phenotypes determined in our study to change with age. Our data set shows significant increases
in the incidences of 19 and 23 frailty phenotypes which change upon aging in females and males
respectively. All 19 phenotypes that showed changes upon aging in females are also detected in
males (Table 4 and 5). Our data show the same significant trends for total score and morbidity.
Interestingly, most of the phenotypes that were improved by AKG were also those affected by
aging. In females, AKG was shown to improve the occurrences of piloerection, grimace, grip
strength loss, loss of fur color, poor coat condition, gait disorder, rectal prolapse and loss of body
weight (Fig. 14a). In males, grip strength loss, gait disorder, tremors, vestibular disturbance,
grimace, loss of menace reflex, hearing loss, eye discharge, poor coat condition, poor body
condition, tail stiffening and abnormal breathing rate were all significantly improved (Fig. 14b).
62
Table 4. List of all 31 aging phenotypes and their interaction with aging (time) in
females
F and P values are the result of one-way ANOVA for changes in frailty as a function of time
for females, *P <0.05, **P <0.01 and ***P <0.001.
63
Table 5. List of all 31 aging phenotypes and their interaction with aging (time) in males
P value is the result of one-way ANOVA for changes in frailty as a function of time for males,
*P <0.05, **P <0.01 and ***P <0.001.
64
Figure 14. AKG alleviates multiple age-associated frailty phenotypes (including those
that significantly change with age)
Individually graphed frailty phenotypes that significantly change with age comparing control
with AKG treated mice for (a) female and (b) male. Data are mean ±s.e.m. of the group, n=
all animals alive at each measurement time. *P <0.05, **P < 0.01, ***P<0.001 (Two tailed t-
test).
65
In the elderly population, loss of mobility is considered one of the most important risk factors for
chronic diseases and has been linked to a higher mortality rate (Bergland, Jorgensen, Emaus, &
Strand, 2017; A. B. Newman et al., 2003). With advancing age, walking capability may be
jeopardized by sensory impairments, neuromuscular and cardiovascular dysfunction. Walking
speed or gait speed is a characteristic phenotype of frailty and a slower ‘up-and-go’ predicts
health and cognitive declines (Robinson et al., 2013).
In our mammalian study, gait or walking ability declined significantly with age (Table 4 and 5).
Interestingly, AKG treatment in both females and males improved gait in comparison to the
untreated control group (Fig. 14). In order to study gait speed and locomotor activity, we used
metabolic cages which can detect and record the animal’s overall movements via measurement
of beam breaks (locomotor activities) and also the total distance traveled over time. Consistent
with our scoring data, automated cages detected enhanced locomotor activities for both female
and male in the AKG-treated versus untreated groups (Fig. 15). In order to further study heart
and motor function, we performed a treadmill exhaustion test. In the treadmill exhaustion test,
the animals were challenged with an acceleration in speed. Air puffs were used as stimuli to
keep the animal running. The maximal speed and distance were recorded up to the point prior to
when the mice were unable to stay on the treadmill (considered the point of exhaustion). Our
data showed no improvement in maximum muscular and cardiovascular capacity of animals
upon treatment (Fig. 16i-l). In order to study heart function, we utilized transthoracic
echocardiography. We evaluated cardiac morphometry, systolic function, and mean baseline
myocardial performance index, none of which displayed improvement in the AKG treated group
(Fig. 16a-h).
66
Figure 15. AKG supplementation improves locomotion in aged mice (Cohort-2 data)
(a, b) Locomotor activity and pedestrian locomotion was measured utilizing metabolic cages
at the median life (28 months old) of control (n=5) and AKG (n=6) female mice. Total
locomotor activity refers to any movement made by the animal that is picked up by the
sensors. The pedestrian locomotion is refered to walking. Data are mean±s.e.m, *P
value=0.014, **P value=0.00097 (two tailed t-test).
67
Figure 16. AKG supplementation does not improve heart function
(a-h) Echocardigraphy test was performed to measure cardiovascular function close to
animal median life, age=29 months old, n= all female animals alive at the time of study,
data are mean±s.e.m. No significant change was observed for any of the measurements,
two tailed t-test). (i-l)Treadmill exhaustion tests were performed to measure cardiovascular
system and motor function for (i,j) male and (k,l) female, age= 29 month old. n= all
animals alive at the time of study. No significant change (t-test two tailed).
68
α-ketoglutarate supplementation affects the metabolism of aging mice
Advanced age-related weight loss has been reported in elderly humans and rodents and is
associated with morbidity (Alley et al., 2010). Interventions that help to preserve body weight
have also been associated with increased survival (Martin-Montalvo et al., 2013; Pearson et al.,
2008). Data from our study confirms age-related weight loss in both female and male animals. In
the first cohort, AKG preserved body weight in both genders (Fig. 13a). However, in the second
cohort, a significant improvement in weight was observed only in the males (Fig. 17b, d).
Utilizing metabolic cages, body composition and total food consumption were additionally
measured in the second cohort of animals. We did not detect any difference between the groups
in these parameters (Fig. 17).
Metabolism was monitored for about four consecutive days (92 hrs). Measurements were
undertaken at two separate ages (19 and 23 months old) using the same cohort of animals for
both runs. Interestingly, despite increased locomotor activities, the total levels of oxygen
consumption, carbon dioxide production and energy expenditure were significantly lower in the
AKG-treated group in comparison to untreated controls. The decrease in carbon dioxide
production was found to be preserved later in life (Fig. 18).
69
Figure 17. AKG preserves body weight in male animals (Cohort-2 data)
(a) Food consumption was measured for 3 consecutive days at different times during lifespan,
control (n=6) and AKG fed (n=5) mice. The arrows at 19, 23 and 28 months show the age at
which food consumption was measured. Data are mean±s.e.m, no significant change detected
(two tailed t-test). (b, d) Longitudinal male and female body weights, n = all live animals in
the study at each time points, data are mean±s.e.m. Two way ANOVA tests of independent
variables including time and treatment (AKG) affect male and female body weight. The
comparison provided evidence of significant effects of both treatment and time on (b) male
body weight. ***p <0.0001 and ***p <0.001 and time on (d) female body weight ***p
<0.001. (c, e) Male and female body composition, n = all live animals in the study, data are
mean±s.e.m.
70
Figure 18. AKG decreases the metabolic rate of aged mice (Cohort-2 data)
Oxygen consumption, carbon dioxide production and energy expenditure decrease upon
AKG administration. Mice were monitored for about four consecutive days (92 hrs).The
measurements were done at two separate time points during lifespan (19 and 23 months old)
using the same animals for both runs. Plots were generated using CalR, and data was adjusted
to bodyweight. Control (n=5) and AKG (n=5). Data are mean±s.e.m. *p < 0.05 and ***p <
0.001 (Two way ANOVA tests).
71
α-ketoglutarate prevents age-associated hair discoloration
Fur-related phenotypes including age-dependent hair graying, coat condition, piloerection and
alopecia were significantly attenuated in AKG-treated animals. Strikingly, the first cohort of
females showed a reversal of age-dependent hair-graying after 9 months of AKG consumption,
although the second cohort of mice only displayed its prevention (Fig. 19). Since the prevention
of hair-graying was one of the strongest phenotypes, further exploration of the potential
mechanism involved was pursued.
Picture 1. Animals in AKG group have black coat and less alopecia compared to control
animals
AKG treated mouse on the left and aged matched control animals on the right, mice are 28-
month-old females and have been on treatment for 10 months.
72
Figure 19. AKG strongly prevents age-associated hair discoloration in female mice
AKG treated mice on the left and the aged-matched control on the right (27 months of age).
(a, c) Overall assessment of changes in fur color index of mice in each treatment group after 9
months of treatment. Control (n= 15) and AKG (n=18). Data are mean±s.e.m. ****P<0.0001
and **P <0.01 (t-test, two tailed). (b, d) Each dot is a single mouse and connecting lines tie
the base line score for each mouse to its scoring after 9 months of treatment. Aging caused an
increase in gray hair in control mice. AKG grouped mice had more gray hairs at baseline (18
months of age) and AKG supplementation could reverse the hair discoloration in the first
cohort and prevent the hair discoloration in the second cohort of mice.
73
Hair follicles are sensitive organs that go through different phases of cyclical transformation
including quiescence (telogen), rapid growth (anagen) and apoptosis-driven regression (catagen)
(Al-Nuaimi, Baier, Watson, Chuong, & Paus, 2010; Paus, Handjiski, Czarnetzki, & Eichmuller,
1994). The activity of melanocyte stem cells (MSC), responsible for production of melanocytes
(MC) and melanin and therefore hair pigmentation, change at different phases of hair follicle
transformation (Fig. 20a). In order to synchronize all the hair follicles to the anagen phase, hair
ablation technique` was utilized. As demonstrated in previous findings, even subtle shifts in the
hair cycle can have drastic effects (Muller-Rover et al., 2001). One of the ways to distinguish
MSCs from MCs is by their location. MSCs reside within a specific anatomic niche in the bulge
region of the hair follicle (Fig. 20a). As MSCs mature and differentiate to MCs, they migrate to
the hair bulb. Osawa and his colleges beautifully characterized specific markers for MSCs and
MCs. MCs express Dct, Pax3, Tyr, Si, Tyrp1, Kit, Mitf, Sox10 and Lef1. In contrast, expression
of Tyr, Si, Tyrp1, Kit, Mitf, Sox10 and Lef1 are undetectable within MSCs and only Dct and
Pax3 are expressed in these cells (Osawa et al., 2005). For the current study, I initially used Dct
and Pax3 to find MSC population. Because of technical difficulties and the age of the samples
(24 months old), I was unable to locate most of the MSCs and as a result I could not fully
address the possible changes in the stem cell population. However, the MCs which are located in
the bulge region of the hair follicle were detectable upon Dct staining. Therefore, Dct was used
as a marker to characterize MCs during the anagen phase in our experiments (Fig. 20c). Six
months of AKG treatment increased the population of MCs (Fig.20d-f).
74
Figure 20. AKG treatment helps to preserve the melanocyte population in aged hair
follicles
(a) Schematic presentation of different hair follicle cycles. (b) Schematic presentation of the
melanocyte stem cells and melanocyte in anagen phase of the hair. (c) Confocal image of the
hair follicle during anagen phase of the hair.
75
In vitro published data show that direct manipulation of intracellular AKG via supplementation
can affect epigenetic regulation of stem cells and impact their pluripotency and support self-
renewal (Carey et al., 2015). In order to determine if AKG could prevent age-related loss of stem
cell activities, we utilized the mouse airway epithelia. This is a well-studied organ for stem cell
function and contains both the undifferentiated stem cell population and basal cells (BCs) which
differentiate into either ciliated or secretory cells. BCs are characterized by Keratin (Krt5) and
Tumor protein 63 (Trp63) expression and become activated and undergo transition into basal
luminal progenitors (BLPs), which express both Krt5 and Krt8. BLPs can differentiate into
Ciliated cells expressing acetylated tubulin (Actub) or Clara cells which express Clara cell
secretory protein (CCSP) (Fig. 21). Since the balance between self-renewal and differentiation
ensures the long-term maintenance of stem cell pools and regeneration capacity of a tissue
(which is challenged during aging), we studied both stem cells and differentiated cell
populations. Our findings however showed no significant changes in any of the cell populations
upon AKG treatment in the mouse airway system (Fig. 21 b-f).
(d, e) Mice were fed AKG for 6 months, starting at 18 months of age, skins were collected and
stained for a melanocyte and melanocyte stem cell marker (Dct). DAPI is shown in blue. (f)
Quantitative analysis of melanocytes. Data are percent of hair follicles positive for melanocyte
staining, Data are shown as mean±s.e.m. Each dot is representative of one skin section, each
animal has 2 or 3 different skin sections. Total of 3 mice for each group (color coded).
76
Figure 21. AKG treatment does not affect stem cell or their differentiation population in
mouse airway system
The mouse airway system or trachea has both undifferentiated cells (stem cells) and basal cells
(BCs), which differentiate into either ciliated or secretory cells. (a) Schematic presentation of the
basal cell (BC) lineage in the tracheal epithelium.
Krt5 (Basal cells)
77
(b) Confocal images of the proximal tracheal epithelium. Mice were fed AKG for 3 months,
starting at 18 months of age, trachea were collected and stained for a BC markers (Trp63, white &
Krt5, red), ciliated cells (Actub, green) and Clara cells (CCSP, white). DAPI is shown in blue. (c-
f) Quantitative analysis of BC and differentiated cell population. Data are mean±s.e.m. Each dot
is representative of average cell population in one single animal. Control (n= 5) and AKG (n=5).
Animals are 21 months old at the time of measurement. No significant difference between treated
and untreated group (t-test, two tailed).
78
α-ketoglutarate supplementation does not affect mTOR activity in tissues of aged mice
Studies in C. elegans suggest that the longevity effects of AKG requires the let-363 gene, an
orthologue of the mammalian target of rapamycin (mTOR) kinase. AKG was reported to reduce
mTOR activity in worms (Chin et al., 2014). To gain a better mechanistic insight on the
longevity effects of AKG in the mammalian system, we harvested tissues following 3 months of
AKG treatment for analysis of mTOR activity. We utilized the mTORC1 (mTOR complex 1)
downstream kinase protein S6K which becomes phosphorylated at two sites upon mTORC1
activation. We also probed Akt which becomes phosphorylated upon mTORC2 (mTOR complex
2) activation. Unlike the data in worms, we detected heterogeneous mTOR activities in different
tissues and found no consistent decrease in mTOR signaling (Fig. 22). It is possible that 3
months of AKG treatment is insufficient to affect mTOR activity. However, other studies have
indicated that dietary supplementation with AKG can activate mTOR signaling. AKG
supplementation was reported to alleviate mucosal damage and improves the absorptive function
of the small intestine via activation of mTOR in young pigs (Hou et al., 2010).
Baar and her colleges comprehensively assessed the effect of age on mTORC1and mTORC2 in
different tissues of C57BL/6J mice. According to their data, aging was not found to result in
increased mTOR signaling in most tissues. mTOR signaling has been reported to vary upon
aging depending on the tissue type and the sex. For instance, increased mTORC1 activity has
been reported in the liver and heart tissue of young female mice (Baar, Carbajal, Ong, &
Lamming, 2016). All in all, although our mTOR data should be repeated with higher number of
animals and a longer period of treatment, there is a possibility that mTOR signaling is not
affected by AKG treatment in mice.
79
Figure 22. Figure 23. mTOR activity is not changed in tissues of mice receiving AKG
in the diet
(a-f) Western blots of mTORC1 (indicated by p-S6/S6) and mTORC2 (indicated by p-
Akt/Akt) activities in multiple tissues of mice receiving AKG for 3 months. Overall three
months AKG treatment does not change mTORC1 and mTORC2 activities
80
α-ketoglutarate supplementation suppresses inflammaging
Inflammaging, a low-grade, systemic inflammation, is a significant risk factor for morbidity and
mortality in adults and is considered an essential contributor to many age-related pathologies. In
order to study the effects of dietary supplemented AKG on inflammaging, we collected plasma
from female mice from the survival study. These mice were 28 months old and had been on
AKG diet for 10 months. We looked at the levels of 24 inflammatory cytokines using cytokine
values from 18-month-old untreated mice as a reference. In untreated mice, the levels of most
cytokines increased between 18 and 28 months; However AKG fed animals were resistant to
these changes (Fig 23b). There was a general trend towards suppression of all plasma cytokines
assayed in AKG-treated animals and our data showed significant changes specifically for TNFα
and MIP-1β (Fig 23a).
The immune system of males and females differs in significant ways with females generally
demonstrating a heightened immune response (Gubbels Bupp, 2015). I next asked whether the
robust effects of AKG on chronic inflammation was sex specific. In this current study, AKG
supplementation was found to significantly affect the lifespan of females. Although the median
lifespan for males was increased upon AKG treatment, the life extension was not as robust as
that of females and never reached statistical significance (Fig 7 and table 3). Since the effects of
AKG on longevity was sex specific, I speculated that anti-inflammatory properties would be
more robust in females. In order to address this, I collected blood from a new cohort of mice
which had been on AKG treatment for 6 months (24 months old on the day of blood collection).
I used 18 months old female and male mice as references to adjust the values in a gender specific
manner. My findings show a higher abundance of chronic inflammation markers in old female
81
mice compared to age-matched males. Very interestingly, AKG suppresses inflammation in both
sexes, but to a higher extent in females (Fig. 24).
Figure 23. AKG reduces inflammation in aged mice
(a) Heat map of 24 inflammatory cytokines and chemokines from plasma of middle aged
(female, age=18 months, n=11), aged control and AKG fed (female, 28 months old, n=5)
animals. Inflammatory cytokines show a general trend of reductions in AKG treated group
comparing to aged control. Fold changes of all cytokines were calculated using the untreated
18 months old animals as reference for each treatment group. Values were all added together
and was compared with paired t-test. ****p <0.0001.
(b) Level of TNF-a and MIB-1B significantly increase in old animals in comparison to young,
AKG treated nimals do not show an increase in cytokines levels when compared to young
mice. Data are mean ±s.e.m. of the group. *P<0.05 and **P< 0.01 (unpaied t-test, two tailed).
82
Figure 24. Old female mice exhibit higher levels of inflammation compared to males,
which is significantly suppressed by AKG supplementation
Separately graphed sex-specific heat map of 24 inflammatory cytokines and chemokines from
plasma of female (a) and male (c) animals. Sex matched middle aged (18 months old, n=5),
aged control and AKG fed (24 months old, n=10) animals. Animals were receiving AKG for
6 months. For each group, fold changes of all cytokines were calculated sex specifically using
the untreated 18 months old animals as reference. Values were all added together and were
compared. Cytokines show a general trend of reductions in (b) female AKG group but not in
(d) males. *p< 0.05 (paired t-test, two tailed).
83
As I explained earlier, aging leads to accumulation of senescent cells, a permanent cellular arrest
as a potent anti-tumor mechanism (Campisi & d'Adda di Fagagna, 2007). Findings in mice, have
shown an increase in senescent markers in various tissues including skeletal muscle, eye, kidney,
lung, heart, liver and spleen upon aging. Moreover, senescent cells removal benefits longevity
(Baker et al., 2016). Arguably the most important mechanisms for driving age-associated
pathology by senescence is through acquiring senescence-associated secretory phenotype
(SASP) (Campisi, 2001). Interestingly, recent findings have shown that senescent cells can
secrete SASP into the blood stream and drive age-related pathologies (Tanaka et al., 2018; Wiley
et al., 2019). Considering the fundamental role of senescent cells in aging and inflammation, the
next question was if AKG supplementation could affect the senescence and SASP production.
Sustained activation of the p16
Ink4a
and/or p53–p21 pathways represents the progression from a
transient to a stable cell-cycle arrest. These two markers are extensively used as markers for
identification of senescent cells (van Deursen, 2014). In our study, we used the combination of
p21
CIP1/WAF1
and p16
INK4a
to detect senescent cells and did not observe any significant changes in
the levels of these proteins in different tissues of aged mice upon AKG administration (Fig. 25).
As in vivo data can be quite heterogeneous, we next decided to utilize IMR-90 cells (human
fibroblasts) to study the direct effects of AKG on senescence formation. Our in vitro data
confirm our mice findings that AKG cannot prevent the formation of senescent cells (Fig. 26a).
However, in cell culture, AKG could inhibit SASP and cytokine production. The senescence was
induced in vitro by radiation (Rodier et al., 2009) and AKG reduced IL-1b, IL-6, CCL2 and
MMP3 levels. There were however no changes in the senescent associated B-gal assay and in the
levels of p21. Inhibition of SASP is a possible mechanism for AKG action in aging mice,
although more studies need to be done to confirm this notion.
84
Figure 25. AKG does not affect the senescence growth arrest in different tissues of aging
mice
qRT-PCR analysis showing expression of senescence-associated markers for different tissues
from aged females (upper panel) and males (lower panel). Data are mean±s.e.m, No
significant changes (t-test, two tailed).
85
Figure 26. AKG reduces inflammation and lowers the proinflammatory SASP without
preventing the senescence associated growth arrest
Ionizing radiation (IR) was used to induce senescence in IMR-90 fibroblasts. Cells were
concurrently treated with PBS (control) or 1 mM AKG and were either mock (0 Gy) or
irradiated (10 Gy). All assays were performed 10 days post-irradiation. (a) Cells were stained
for senescence-associated ß-galactosidase activity (left panel) or EdU incorporation (right
panel). (b) IL-6 levels in conditioned media were determined by ELISA, normalized to cell
number. (c,d) qRT-PCR analysis showing expression of senescence-associated secretory
phenotype (SASP) genes, normalized to actin. Each dot is one independent experiment. Data
are mean±s.e.m, *p <0.05, **p<0.01 (t-test two tailed).
86
Since the anti-inflammatory effects of AKG was initially detected in plasma, we decided to
further study the blood to understand the effects of AKG on immune system. Immune cells use
cytokines to communicate with other cells and increases in specific leucocyte populations can
affect cytokine production. On the other hand, changes in cytokine levels can affect leucocyte
differentiation (Parham, 2018).
I collected blood from 24-month-old female and male animals (total of 20 animals), which had
been receiving AKG for 6 months, and used fluorescent activated cell sorting (FACS) to study
the different population of leucocytes in the blood. The Figure 27 summarizes the specific
antigens applied for each cell type to detect and sort. I mainly focused on alterations in T cell
population and I used broader antibodies to detect the unique surface markers of different T cell
populations. One of the major sources of cytokines and chemokines are T cells, and changes in T
cell population are well studied and most robust within an aging immune system (Salam et al.,
2013). According to my findings, only alpha beta presenting T cells were more abundant in
females receiving supplementary AKG (Fig. 28a). Natural killer T cells were the population of
cells mostly affected in females receiving AKG. There were also trends for higher abundance of
CD8+ T cells in treated female animals (Fig.28c). However, there were no change in CD4/CD8
ratio, upon AKG treatment. CD4/CD8 ratio has been strongly linked to aging immune system
and immune senescence in both human and mice (Wikby, Mansson, Johansson, Strindhall, &
Nilsson, 2008). No differences were detected in blood leucocyte populations for male mice (Fig.
28d).
A steady decline in the production of fresh naïve T cells, more restricted T cell receptor (TCR)
repertoire, weak activation and increase in levels of memory T cells are a few of the established
phenotypes of aging immune system (Yan et al., 2010). However, we did not detect any
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improvements in these phenotypes upon our treatment. Since the data obtained from blood did
not provide any strong evidence supporting the changes in the immune response of AKG fed
mice, I decided to look at spleen as the major lymphoid tissue.
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Figure 27. Schematic illustration of different blood leucocyte populations and surface
markers
The whole immune cells known as leucocytes are generated from hematopoietic stem cells.
Initially pluripotent hematopoietic stem cells give rise to the two main categories: the lymphoid
progenitor and the myeloid progenitor. The myeloid progenitors are the precursor of the
granulocytes, monocytes and dendritic cells. Granulocytes consist of neutrophil, basophil, and
eosinophil. The common lymphoid progenitor cells give rise to the lymphocytes. There are three
major types of lymphocyte: B lymphocytes, B-cells and natural killer cells. There are different
surface markers for each population of immune cells; all the surface markers specifically used in
our experiments are shown in purple. We used CD11b and Gr-1 aka/Ly-6G for detection of
Monocyte and Granulocytes cells respectively. NK1.1 (homolog of human CD56) were used to
identify natural killer cells. CD19 were used for B-cells. Alpha/beta T-cell receptors were used
to detect all T-cell populations. T-cells may be either CD4+ or CD8+. A broad generalization
segregates helper function to CD4+ cells and cytotoxic functionality to CD8+ cells. Naïve T-
cells are not activated (CD62L) once they encounter antigen and get activated, they start
proliferating and express CD69 surface marker, which are known as effector cells. Memory T-
cells are the surviving effector cells which express CD44 and can proliferate. Memory T-cells
are usually the surviving effector cells that have previously encountered and responded to their
cognate antigen and produce faster and stronger response in the second encounter. Regulatory
T-cells which were detected in our study using the CD25 marker are a subpopulation of T-
cells that modulate the immune system, maintain tolerance to self-antigens, and prevent
autoimmune disease.
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Figure 28. Different leucocyte population in blood; Female mice receiving AKG have
higher abundance of T-cells
Detecting different leucocyte populations in the blood of aged mice using flow cytometry.
Blood from aged control and AKG fed mice (24 months old, 5 animals for each sex per
treatment) were collected and lecucytes extractin were undertaken. Total lecuocytes were
stained with antibodies for different surface markers; B-cells, T-cells, T-cell subsets,
granulocytes, natural killer cells and monocytes.(a,b) Different cell population were
determined by flow cytometry for each sex seprately. Female mice have higher abundance of
circulatory T-cells, (c) including natural killer T-cells. (b,d) AKG does not affect the
leucocyte population in the blood of male mice. Data are frequencies of cells detected by flow
cytometry shown as percentage of absolute number of parent cells. Data are summarized as
bar graphs mean±s.e.m. *P<0.05 and ***P <0.001 (t-test, two tailed).
90
To study the leucocyte population more broadly, I chose to look at the spleen as the major
peripheral lymphoid tissue where proliferation and differentiation are initiated. After extraction
of splenocytes from the whole spleen, we used antibodies against specific populations of
leucocytes. We could not detect any significant differences in splenocyte populations between
AKG treated and control mice.
Next we decided to stimulate the splenocytes in culture to assess differentiated T cell cytokine
secretion profiles (Fig. 29). Cells prepared in this manner were stained with different antibody
panels, some with separate surface and intracellular staining steps. The full list of the markers
and antibodies used is summarized in method section. Very interestingly, our data show
significant differences between sexes. The sexual dimorphism of aged immune system was
remarkable (Supplemental tables 1-3).
Our findings show that female AKG treated mice have higher IL-10 secretion (Fig. 30). IL-10
is an important immunoregulatory cytokine produced by diverse cell populations and plays an
essential role in the control and resolution of inflammation (Ip et al., 2017). IL-10 is involved in
regulating differentiation and proliferation of immune cells such as T-cells, B-cells, natural killer
cells, antigen-presenting cells, mast cells, and granulocytes. The exact mechanisms involved in
the inhibitory effects of IL-10 are controversial (Asadullah, Sterry, & Volk, 2003). In response to
acute inflammation, IL-10 inhibits the production of a broad range of inflammatory mediators
mostly from activated macrophages and dendritic cells (Murray, 2006). In the context of chronic
inflammation, the source of IL-10 is largely shifted to T-cells and, in particular, regulatory T-cell
subtypes (O'Garra, Vieira, Vieira, & Goldfeld, 2004). In addition, studies show T cell-specific
IL-10 mutant recapitulate the immune phenotype of complete IL-10 deficiency (Roers et al.,
2004). Therefore T-cell-mediated IL-10 production is critical in chronic inflammatory
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conditions. Very interestingly, the IL-10 homozygous knock-out (KO) mice (IL-10
tm/tm
) has
been used as a model of frailty (Walston et al., 2008). These mice show frailty phenotypes
including increase in several pro-inflammatory cytokines including interleukin (IL)-6, IL-1β,
TNF-α, CXCL-1 and IL-12 (Ko et al., 2012). Considering the critical role of T-cell mediated IL-
10 in chronic inflammatory conditions (O'Garra et al., 2004), we believe that induction of IL-10
by AKG treatment can be a potential mechanism for suppression of chronic inflammation.
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Figure 29. A representative flow plots and sorting strategies for re-stimulated
splenocyte
Splenocytes were harvested from spleen of AKG and control mice (24 months old, 5 animals
for each sex per treatment). Harvested cells were plated and stimulated ex vivo for 4 hours
with PMA + Ionomycin + Brefeldin. Representative flow cytometry dot plots that show two
parameters data. Each dot corresponds to a single event that has been detected above the
threshold. These plots are also a density plot where each color represent the collection with
the same signal intensity. No probes were used with excitation properties in PB (Pacific
Blue) and BV510 (Brilliant Violet 510) channels. These two fluorescence output channels
were used to gate out the auto-fluorescent cells, before further analysis. The exact same
gating strategies were used to isolate the specific set of events from a larger data set for all
samples. Showing gating startegies for (a) CD4/CD8 expression and (b) intracellular
presence of IL-10, (c) TNF-a and (d) IL-17 in gated CD4 + /CD8 + cells after re-stimulation.
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Figure 30. AKG increases intercellular IL-10 in stimulated female T-cells
A representative flow dot plots and gating with total quantification for intracellular presence
of IL-10 in ex vivo stimulated CD8 and CD4 T-cells. Splenocytes were harvested from spleen
of AKG and control mice after 6 months of treatment (24 months old, 5 animals for each sex
per treatment). Harvested cells were plated and stimulated ex vivo for 6 hours with PMA +
Ionomycin + Brefeldin. IL-10 production was detected using intracellular staining. The gating
strategy is shown for CD4 and CD8 positive T cells in (b) female and (c) male. Summary of
data plotted as bar garphs show positive IL-10 cells as percent of total CD4/CD8 T cells. Data
are mean ±s.e.m., *p<0.05, **p<0.01 (two-tailed t-test).
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DISCUSSION
This study is, to my knowledge, the first to identify an endogenous metabolite that can be added
to the food to extend the lifespan and healthspan of mammals. Here we demonstrate that a-
ketoglutarate (AKG), a key metabolite of the TCA cycle, has longevity effects consistent with
compressed morbidity in a long-term study in aging mice. Interestingly, in human plasma AKG
levels decline 10 fold between the ages of 40 and 80 (A. P. Harrison & Pierzynowski, 2008). The
molecule is not available in the human diet, making direct supplementation the only feasible
route to restore levels during aging.
In order to increase reproducibility, one of the biggest challenges in all areas of science, we used
two independent cohorts of mice each consist of 45 females and 45 males (total of 180
animals). Noting the importance of sexual dimorphism in aging studies, all data, when possible,
were analyzed in a gender-specific manner.
Georoscience is based on the principle that there are underlying biological processes driving
aging and that intervening in those processes will increase health and function, while delaying
associated co-morbidities. Such interventions usually target fundamental aging processes and
may hold a great promise to treat aging (Goldman et al., 2013). However, testing the efficacy of
these interventions in delaying aging process in humans is very challenging. Using lifespan by
itself is not a feasible outcome as the duration of the study make these experiments impractical.
It is unmanageable and very expensive to control all the variables during the individual’s entire
life. Another important drawback for using the lifespan as the fundamental readout is the fact
that longevity with poor health and compromised function is not desirable. Although lifespan by
95
itself may not be the outcome of choice, mortality should be included among a composite of
measurements (J. C. Newman et al., 2016).
Researchers argue that health and functional abilities are the fundamental outcomes to be
measured in human aging studies. One way to evaluate health is to measure aging symptoms like
frailty (Goldman et al., 2013). The concept of frailty has been initially developed to describe the
conditions of aged people with increased vulnerability to adverse health outcomes (Fried et al.,
2001). The most widely used frailty scales are “Fried frailty phenotype” and the “Rockwood
frailty index”(Rockwood et al., 2005). Fried’s frailty has been initially designed for clinical
assessment of frailty in elderlies, and to develop interventions for frailty based on a standardized
ascertainment. Fried’s frailty defines frailty based on five phenotypic criteria: weakness,
slowness, low level of physical activity, self- reported exhaustion, and unintentional weight loss
(Fried et al., 2001). In the other hand, Rockwood frailty index defined frailty originally as
cumulative deficits identified in a comprehensive geriatric assessment (consisting of more than
70 parameters). These parameters are relevant to everyday activities, also comprising
physiological problems, mental capabilities, concomitant features of co-morbidities, etc.,
(Rockwood et al., 2005). New frailty indices have been developed in recent years to assess health
in human. However, agreement on a standard instrument to identify frailty in humans has not yet
been achieved (Hoogendijk et al., 2019).
Pioneers in the field believe that current frailty
measurements can be more optimized by addition of more measurable outcomes. For instance,
different elements can be added to the geriatric assessments such as gait speed, grip strength,
mobility stress test (Sanders et al., 2014), cognitive test (Holtzer, Wang, Lipton, & Verghese,
2012), time to incidence of a second or third age-related disease or impairment, the time between
disability and death and the end-of-life functionality (A. B. Newman et al., 2003). Trials of
96
resilience can also add invaluable information to health assessments such as antibody titers
following vaccination or length of stay after elective surgery (J. C. Newman et al., 2016).
There is a general agreement in the aging field that we need to apply current understanding of the
human aging process and the clinical assessments of health to our animal studies when testing
longevity interventions. This will be beneficial in developing a translational pipeline to move
candidate compounds through animal models to clinical trials.
One of the assessments which can be added to mammalian studies is non-invasive frailty
measurements. Scientists have applied some of the health assessments (i.e. gait speed, grip
strength, memory tests, mobility) in aging studies. However, the longitudinal and repeated health
assessments which can measure the functionality period is missing. Considering the value of
coordinated healthspan with lifespan extension, in our study health was measured repeatedly
throughout the lifespan using a non-invasive frailty index (FI). The FI consists of 31 clinically-
relevant aging phenotypes which share many characteristics of human aging and are based on the
principle of deficit accumulation with age (Whitehead et al., 2014). These measurements were
repeated approximately every eight weeks and provided us with eight and seven sets of
healthspan data sets, respectively, for male and female mice during their lifespan. This gave me
the rigorous analytical ability to look at the impact on period of morbidity. We used “morbidity”
to describe the condition of being ill or unhealthy using total frailty score as a morbidity
indicator. Our results reveal a longevity effect consistent with an overall decrease in frailty in
aged mice.
The FI used in our study could be expanded and improved. The most important missing elements
of our study are assessments for cognitive functions such as any memory, behavioral and
conditioning tests. Some of the individual frailty phenotypes can be translated to human (tumors,
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kyphosis, gait, grip strength, body condition, loss of hair, cataracts, corneal opacity, vision loss
and etc.,), some others do not have translational potential. However, the non-human relevant
phenotypes (distended abdomen, tail stiffening, dermatitis, loss of whiskers, coat condition,
piloerection, malocclusion, menace reflex and etc.,) are valuable when applied as a composite
score, since they are informative for evaluation of the animal’s overall health. The applied Frailty
Index also lacks any power to capture any social interactions or to test resilience; the ability to
rebound back to baseline functional and health status after a disease or an acute event which is an
important indicator of health.
Almost all age-related diseases are accompanied by chronic systemic inflammation (Franceschi
& Campisi, 2014), a significant risk factor for morbidity and mortality in aged adults (Franceschi
et al., 2000). Recent studies have identified inflammation-associated biomarkers for frailty and
adverse health outcomes. In human, plasma levels of IL-6 and TNF-a have been identified as
predictors of 10-year mortality from all causes (Varadhan et al., 2014). Studies also have shown
a positive correlation between pro-inflammatory cytokine levels and frailty in aging mice.
However, levels of the pro-inflammatory cytokines in aging females differs from aging males;
IL-6, IL-9, and interferon-γ were associated with higher FI scores in aging females, while levels
of IL-12 p40 rose as FI scores increased in aging males (Kane, Keller, Heinze-Milne, Grandy, &
Howlett, 2018) . There are many evidences showing that males and females differ in immune
responses (Amadori et al., 1995; Scotland et al., 2011; Yan et al., 2010).
In my study, plasma levels of the inflammatory cytokines increased in aging females and males.
Interestingly, female mice showed more chronic inflammation than males, which was inhibited
to larger extents by chronic administration of AKG. This observation is consistent with our
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lifespan data, as female mice were shorter lived compared to males and responded more robustly
to AKG supplementation.
Senescent cells are one of the known mechanisms which promotes age-related inflammation
(Franceschi & Campisi, 2014). Considering their fundamental role, I chose to study the effects of
AKG supplementation on senescence formation and SASP production. I found no changes in the
senescent formation but inhibition of SASP was detected as a possible mechanism for AKG
action in aging mice.
The peripheral immune cells undergo age-related changes which can lead to the release of
inflammatory cytokines. I chose to mainly focus on alterations in T-cell population as these
population of cells exhibit the most robust age-associated changes compared to other leucocyte
populations (Salam et al., 2013; Strindhall et al., 2013). Furthermore, there has been an
increasing focus on the role of T-cells during ageing because of their impact on the overall
immune responses (Salam et al., 2013; Yan et al., 2010). I first studied the blood to understand
the effects of AKG on peripheral immune system. However, the data obtained from blood did
not provide strong evidence supporting the changes in the immune response of AKG fed mice. I
next decided to look at peripheral lymphoid tissue, where the differentiation and maturation of
lymphocytes is initiated. Our findings show that T-cells from the spleens of AKG treated mice
significantly produce higher IL-10; this effect was sex-specific with higher levels in AKG treated
female mice. IL-10 is a potent anti-inflammatory cytokine that plays a central role in limiting
host immune response (Ip et al., 2017). IL-10. Homozygous knock-out (KO) mice (IL-10
tm/tm
)
has been used as a model of frailty (Walston et al., 2008). Interestingly, these mice show frailty
phenotypes including loss in body strength, higher mortality and increase in several pro-
inflammatory cytokines (Ko et al., 2012). Considering the critical role of T-cell mediated IL-10
99
in chronic inflammatory conditions (O'Garra et al., 2004; Roers et al., 2004), we believe that
induction of IL-10 by AKG treatment can be a potential mechanism for suppression of systemic
inflammation
Remarkably, the effect of sex on T-cell population and activation was far more robust than our
treatment affect. Once again, our findings in mice highlight the importance of sexual dimorphism
in aging immune system.
We observed no significant adverse effects of AKG administration. The only phenotypes that
had a higher incidence in AKG-treated animals (both female and male) were cataracts and
corneal opacity, although these did not reach statistical significance. Higher incidence of
cataracts has also been reported to occur following rapamycin treatment (Wilkinson et al., 2012).
AKG has also been used in human clinical disease studies without any observable adverse effects
(Filip et al., 2007; Jeevanandam & Petersen, 1999; Riedel, Nundel, & Hampl, 1996). AKG is
Generally Recognized As Safe (GRAS) under the Federal Food, Drug, and Cosmetic. Given its
GRAS status and human safety record, our findings point to a potential safe intervention that
may impact important elements of aging and improve quality of life in the elderly population.
It is important that CaAKG administration started at 18 months of age (equivalent to 50-60 years
old human) still had robust effects since human clinical studies are likely to be initiated at a
similar relative time point during aging. If translatable to humans, this effect would indicate the
ability of AKG to not only extend lifespan but, more importantly, to reduce the debilitating
period of functional decline and disease management that plague most aging individuals.
This is arguably an important discovery as it implies that aging interventions could provide
significant health benefits. With the current demographic challenge of increased burden of age-
related chronic disease, the idea that we could intervene and promote healthy aging is not only of
100
interest to specialists but should be important to every scientist who studies chronic disease and
also every social scientist thinking about demographic change and healthcare.
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MATERIAL AND METHODS
C .elegans lifespan
Synchronized N2 Bristol (wild type) populations of worms were cultured at 20°C and transferred
as young day 1 adults to control or 8 mM AKG plates (Lucanic et al., 2017). All plates were
supplemented with 10μg/μl 5-fluoro 2-deoxyuridine (FUdR) to prevent progeny production.
Animals that crawled off the plates or died due to internal gut or vulval extrusions were censored
from the population. Log rank (Mantel-Cox) statistics were used for lifespan analyses in Prism.
Animal housing and diet
All mice were housed on a 12-h light/dark cycle and kept at 20–22 °C. Two independent cohorts
of C57BL/6J mice were purchased from Jackson Laboratories at 14 months of age. Animals
were aged on a regular mouse diet (Teklad Irradiated 18% protein and 6% fat diet-2918) which is
very similar to their diet at Jax 5K52 (18-19% protein and 6-7% fat) prior to arrival at 18 months
of age when treatment commenced. AKG treated animals were subjected to a lifelong 2% (w/w)
AKG supplementation on the 2918 diet, while control animals were kept on standard 2918. Pure
calcium 2-oxoglutarate (Carbosynth) was homogeneously mixed during manufacture of the 2918
diet prior to irradiation and pelleting. Mice were housed in groups (5 per cage at a maximum)
and aggressive male mice were isolated to prevent fighting. All lifespan and healthspan
experiments were initiated at ~18 months of age. Mice were inspected daily and treated for non-
life-threatening conditions as directed by the veterinary staff. The only conditions that received
treatment were dermatitis and prolapse (topical solution three times per week). A total of 8
control mice and 3 in the AKG supplemented group were treated for dermatitis or prolapse. The
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Buck Institute is an AAALAC accredited facility. Each room contains sentinel mice (one CD-1
sentinel female every 75-100 cages of experimental mice). Health screening is performed 4 times
per year at 3 months intervals. Diagnostics consist of serological screening and fecal and fur
analysis for internal and external parasites.
Mouse survival
The principle endpoint of our lifespan study was natural death. We recorded the age at which
mice were found dead or selected for euthanasia (a procedure for mice deemed unlikely to
survive for the next 48 hours and in discomfort). The criteria for euthanasia were based on
independent assessments by a veterinarian according to AAALAC guidelines (D. E. Harrison et
al., 2009). Animals with any of the following symptoms were euthanized: severe lethargy, rapid
weight loss (>20% over two weeks), severe distended abdomen, poor body condition, signs of
pain (grimace), inability to move despite stimuli, severe ulcers or bleeding tumors, severe
temperature loss, or abnormal breathing rate. Animals found dead or that were euthanized were
necropsied for pathology scores. No invasive measurements were performed on this population
prior to death (n=180 animals, two cohorts of 90 animals). Two sacrificial groups were
purchased at 14
th
months of age and baselined the following week. The mice (n=12 and n=20)
either received Teklad 2918 or 2% (w/w) AKG supplemented 2918 diet. Animals were sacrificed
and tissues were collected following 3 months of treatment. The Institutional Animal Care and
Use Committee (IACUC) at the Buck Institute approved all animal experimental procedures,
housing and diets for this current study. Body weight and food intake were measured on a
biweekly and bimonthly basis for the duration of the study.
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Baselining and grouping of animals
Mammals age heterogeneously and 18 months old mice already manifest some age-associated
deterioration of healthy phenotypes. All the animals were scored before grouping and all 31 FI
scores were applied in order to assign animals into different groups. A balanced partitioning of
mice was performed: for any given mouse in any given group, similar mice based on their FI
scores were placed in all other groups. This allowed any outcome of the study to be related to the
treatment rather than an inherent property of a particular group, sometimes called a “cohort
effect”.
Aging index (Frailty Index or FI)
One can find the complete protocol for the FI in Whitehead et al., 2014.
For the purpose of assessment, all measurements were completely in a blinded fashion to remove
observer bias.
These assessments assess age-associated deterioration of health and include evaluation of the
musculoskeletal system, the vestibulocochlear/auditory systems, the ocular and nasal systems,
the digestive system, the urogenital system, the respiratory system, signs of discomfort, body
weight and body surface temperature. 0 is assigned if no sign of frailty is observed and the
animal is healthy for each phenotype. A moderate phenotype or a severe phenotype were scored
0.5 or 1, respectively. Loss of temperature and body weight were scored using standard
deviation.
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Statistical analyses
Python Software was used to extract all of the healthspan data and to create files compatible with
R software for analysis. Data were analyzed using R, GraphPad Prism 7 and OASIS 2 software.
Log-rank (Mantel–Cox) tests were used to analyze Kaplan–Meier curves and a Fisher’s exact
test was performed for maximum lifespan analysis (at 90% survival). Two-tailed Student’s t-tests
were used for analyses of scoring at each time point between control and AKG treated groups.
The area under curve (AUC) of mortality graphs were measured for baselining at the initiation of
AKG treatment at 18
months of age. Changes in AUC were used to calculate the percent
compression of morbidity. Using R scripts, Mixed Models was used to analyze the data
longitudinally. In the current Mixed Model, subjects (every mouse with a unique ID) were
treated as a random factor. Treatment and time were treated as fixed factors
Metabolic data
Metabolism was measured applying indirect calorimetry. We utilized a Promethion Metabolic
Cage system (Sable System International). The system is equipped with Promethion GA-3 small
mammal gas analyzers for measurements of O2 (consumption) and CO2 (production). Energy
expenditure, food intake, water consumption, body weight, physical activity and volunteer
exercise were simultaneously recorded over 4 consecutive days (96 hours). Mice were housed
individually in metabolic cages and accustomed to their environment for a day before the start of
recording. Data were analyzed using Sable System Expedata-P Data Analysis Software.
Subsequently, we applied CalR software, a free web tool for analysis of experiments using
indirect calorimetry (Mina et al., 2018), to analyze our raw data, generate some of our plots and
run statistical analysis (https://calrapp.org). Whole-body composition analysis was conducted
105
using a quantitative nuclear magnetic resonance machine (EchoMRI-2012, Echo Medical
Systems).
Transthoracic echocardiography
Echocardiography examination was performed using a high resolution (32-55 MHz)
Visualsonics Vevo 2100 micro‐ultrasound system with the echocardiography probe (MS‐400).
Each mouse was placed on a heating pad (37°C) and minor sedation (0.5% isoflurane oxygen)
was used to paralyze the animal (to minimize any cardiac suppression side effects) during the
measurement time. Doppler imaging, 2D and M-mode echocardiography were performed to
evaluate cardiac morphometry, systolic function, and mean baseline myocardial performance
index (MPI).
Treadmill exhaustion test
We modified the protocol of Castro and Kuang (Castro & Kuang, 2017) Given the age of the
animals (28 months), the initial speed and acceleration were adjusted for our study. All mice
were trained and adapted to the environment for three consecutive days for 10 min at 5m/min
before the actual experiment. On the day of the experiment, mice were acclimated for 3 min at 5
m/min after which the speed was accelerated by 1.5 m/min
-2
. We used air puff as a stimuli to
keep the animal running. Maximal speed and distance were recorded once the mice showed signs
of exhaustion (heavy breathing, hunched back and unwillingness of the animal to mount the
treadmill belt despite administration of 10 puffs of air).
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Western blot analysis
Mouse were fasted overnight and the next morning different tissues were dissected and
immediately frozen in liquid nitrogen; heart, lung, kidney and adipose tissue including visceral
fat in females isolated along the epididymis and uterus and skin (back skin, on the spine midway
between the head and the tail). Tissues were homogenized using an Omni TH homogenizer
(Omni International) on ice in radio-immunoprecipitation assay (RIPA) buffer, 300 mM NaCl,
1.0% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, 50 mM Tris (pH 8.0), protease inhibitor
cocktail (Roche) and phosphatase inhibitor (Sigma). Samples were centrifuged at 13,200 rpm for
10 min, 4°C. The protein content of the supernatants was assessed using the detergent
compatible (DC) protein assay (Bio-Rad). Equal amounts of protein were resolved by SDS-
PAGE (4%– 12% Bis-Tris gradient gel, Invitrogen), transferred to nitrocellulose membranes, and
incubated with protein/phosphoprotein-specific antibodies. Antibodies against phosphorylated
S6
S240/244
(5364), Akt
S473
(4058), S6 (2217), Akt (4691), and glyceraldehyde 3-phosphate
dehydrogenase (GAPDH; 2118) were purchased from Cell Signaling Technology. Protein bands
were revealed using an Amersham enhanced chemiluminescence (ECL) detection system (GE
Healthcare) and quantified by ImageJ software.
Skin collection and melanocyte stem cell synchronization
Mice were waxed in the dorsal area (area of 1.5 inches×2 inches) to initiate the hair cycle and to
initiate a homogenous re-entry into the anagen stage. Seven days later, skin samples were
collected and immersed in 4% paraformaldehyde/PBS (pH 7.4) followed by 30% sucrose until
the samples sank to the end of the tubes. Fixed skin was embedded in OCT compound and snap-
frozen (Nishimura et al., 2002). For double or triple immunofluorescent staining, 14 uM
cryosections were acquired.
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Immunohistochemistry
Skin: After treatment with a blocking solution containing 5% skim milk (Difco), 1% donkey
serum and 0.1% Triton X-100 for 20 in PBS, skin sections were incubated with primary
antibodies diluted in the blocking solution. The primary antibodies used were as follows: rabbit
polyclonal TRP2 (abcam), goat polyclonal PAX3 (R&D systems) and mouse monoclonal MITF
(abcam). The sections were then washed three times in PBS containing 0.1% Triton X-100, and
incubated with an appropriate combination of the following secondary antibodies diluted in
blocking solution containing TO-PRO3 (Molecular Probes): Alexa488-conjugated donkey anti-
rabbit IgG, Alexa547-conjugated donkey anti-goat and Alexa646-conjugated donkey anti-mouse
IgG. After washing three times with PBS, the slides were mounted with a ProLong Antifade kit
(Molecular Probes) and observed under a confocal microscope (Bio-Rad Radiuns 2100 or Zeiss
LSM510 Meta).
Trachea: Mice were sacrificed and the whole trachea along with the left long was dissected and
immediately fixed overnight at 4°C in 4% paraformaldehyde. The next day, tissues were
dehydrated and then paraffin-embedded before sectioning (5 μM). Primary antibodies were anti-
Trp63 (mouse, 1:100 CM163B, Biocare Medical and mouse, 1:100 ab735, Abcam), anti-Krt5
(rabbit, 1:200 ab52635, Abcam), CCSP (goat, 1:100 sc-9772, Santa Cruz Biotechnology) and
AcTub (mouse, 1:5000 T7451, Sigma). Secondary antibodies were Alexa Fluor conjugates
(1:500, Life Technologies) processed with ProLon Gold antifade reagent with DAPI (P36931,
Invitrogen) for mounting. Quantification of BCs and other cell types were performed manually in
in FIJI (NIH Image J). Six images were taken along the length of each trachea to calculate the
average number of specific cells per mouse trachea.
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Flow Cytometry
Blood leukocytes were prepared by collection ~50 microliters of whole blood via distal tail
incision, directly into 1.5 mL of cold PBS/2 mM EDTA, followed by centrifugation (4 minutes,
4000 RPM in a refrigerated microcentrifuge), removal of the supernatant, and erythrocyte lysis
by ACK buffer treatment.
Leukocyte suspensions were prepared from mouse spleens by crushing, dissociation of cells by
pipetting, straining through 40 micron nylon mesh. Cells were washed twice with PBS
containing 1mM EDTA and 2% FBS prior to lysing red blood cells with ACK lysis buffer (made
in house). For analysis of cytokine expression, cells were cultured in RPMI/10% FCS for 4
hours post-isolation, with 50ng/ml PMA (Sigma), 0.5μM ionomycin (Sigma), and 0.5μg/ml
Brefeldin A (Sigma) prior to staining. Surface staining with fluorochrome-conjugated antibodies
was performed for 30 minutes on ice, at 1 microgram/mL, in PBS with 2% FCS and 2mM
EDTA, followed by either fixation in PBS/1% PFA or fixation/permeabilization with the
eBioscience (ThermoFisher) FOXP3 intracellular staining kit. Intracellular staining for cytokines
or transcription factors was performed for 1 hour on ice in eBioscience FOXP3 Perm/wash
buffer. Samples were analyzed using a BD LSR II flow cytometer.
All antibodies for flow cytometry were obtained from Biolegend. These included the following:
CD4-BV650, clone GK1.5; CD8α-Alexa488, clone 53-6.7, TCRβ-PerCP-Cy5.5 or PE,
cloneH57-597; IL-10-PE, clone JES5-16E3; TNF-α-APC, clone MP6-XT22; LY-6g-FITC, clone
1A8; CD11b-PerCP-Cy5.5, clone M1/70; CD62L-APC, clone MEL-14; CD44-APC-Cy7, clone
IM7; CD25-Pacific Blue, clone PC61; CD69-BV711, clone H1.2F3; CD45-BV510, clone 30-
F11; F4/80-BV510, clone BM8; CD11c-Pacific Blue, clone N418; Class II MHC ( I-A
I/E)
-APC-
Cy7, clone M5/114.15.2; NK1.1-BV650, clone PK136.
109
Inflammatory cytokines and chemokines
Blood were from the jugular vein of middle-aged (18 month old), aged control and AKG fed (29
month old) animals. The samples were sent to Eve Technologies (Calgary, Alberta, Canada) for
measurement of soluble cytokines and chemokines in serum using multiplex lase bead array
technology (MD31).
Cell culture
IMR-90 fetal lung fibroblasts were obtained from ATCC and were cultured at 37° C in 3% O2
and 5% CO2. Dulbecco's modified Eagle's media (DMEM) supplemented with 10% fetal bovine
serum and streptomycin/penicillin were used. Media was changed every 2 days during the
experiment. For damage-induced senescence, cells were irradiated with doses of either 0 or 10
Gy of ionizing radiation (IR). Cells were concurrently treated with PBS (control) or 1 mM AKG
for 10 days, changing media every 2 days. All assays were performed 10 days post irradiation.
An EdU (5-ethynyl-2´-deoxyuridine) Proliferation Kit (iFluor 488) ab219801 was used to detect
cell proliferation. Cells were stained for the senescence-associated β-gal (SA-β-gal) marker as
described (Dimri et al., 1995). Non-senescent cells (having undergone fewer than 35 population
doublings) were made quiescent by washing with PBS and incubating in DMEM containing
0.2% serum for 4 day. Cultures that had > 80% SA-β-gal positive cells and ≤ 4% EdU positive
cells were considered senescent.
ELISA
Conditioned media was prepared by washing cells 3 times in PBS and incubating them in serum-
free DMEM containing penicillin/streptomycin for 24 h. Conditioned media was removed and
110
cells were trypsinized for performance of cell counts. The CM was then centrifuged to remove
cellular debris, and supernatants were used for ELISA. IL-6 ELISAs were performed using kits
and procedures from R&D (#D06050). The resultant data were normalized to cell number.
RT PCR
For cell culture experiments, RNA was isolated using an ISOLATE II RNA mini kit (Bioline
#BIO-52073). RNA quality and quantity were assessed using NanoDropTM 1000
Spectrophotometer measurements (Thermo Scientific). Total cDNAs were synthesized from
500ng of RNA using random primers and iScript RT reagents following the manufacturer's
Superscript II protocol (Invitrogen, Carlsbad, USA). Gene expression was measured from cDNA
using the Roche Universal Probe Library system (Indianapolis, IN, USA). All values were
normalized to beta-actin.
For in vivo study, tissues were collected from 12 animals from the sacrificisl group. Tissues were
homogenized in 1 ml Invitrogen TRIzol™ Reagent using metal beads combined with high-speed
shaking (Tissuelyser Qiagen at 20 Hrtz, for 6 min). Skin samples were crushed with a pestle and
in liquid nitrogen prior to the homogenization step. Chloroform extraction and
ethanol precipitation were performed on homogenized tissues to extract RNA. RNA quality and
quantity were assessed and cDNA synthesized as described. Gene expression was quantified via
real-time quantitative PCR using the Roche Universal Probe Library system (Indianapolis, IN,
USA). The primer sets (0.1 μM) were as follows: 1) p16 F:5'-AACTCTTTCGGTCGTACCCC-3'
and R: 5'-TCCTCGCAGTTCGAATCTG -3' with Custom designed probe : 5'-/56-FAM/AGG
TGA TGA/ZEN/TGATGGGCAACGTTCAC/3IABkFQ -3'. 2) p21 R: 5'-
111
TTTGCTCCTGTGCGGAAC -3' and F:5'-TTGCCAGCAGAATAAAAGGTG -3' with probe #9.
Transcript levels were normalized to Beta-glucuronidase (GUSB) as an endogenous control.
112
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APPENDIX
Supplemental table 1. Statistical summary for splenocytes – Flow Cytometry data
Female Male
Sex specific
Differences (female
VS males)
Control AKG P-Value Control AKG P-Value
P-Value
Control
P-Value
AKG
Single Cells 100 100 100 100
TCRß 33.475 29.860 0.333 27.270 28.580 0.753 0.221 0.682
CD4 18.314 14.940 0.223 12.080 11.910 0.934 0.041* 0.161
CD4/CD25
pos (Treg)
4.373 4.010 0.648 1.890 2.030 0.748 0.004* 0.008*
CD4/CD69
pos (Treg)
0.844 0.550 0.103 0.350 0.370 0.901 0.004* 0.227
CD4/CD44
(Memory)
15.711 12.540 0.206 8.230 6.600 0.085 0.008* 0.001*
CD4/CD62
(Naïve)
1.461 1.110 0.355 3.200 4.580 0.311 0.084 0.011*
CD8 10.838 10.380 0.756 13.080 14.180 0.687 0.412 0.072
CD8/CD25
(Treg)
1.368 1.640 0.164 1.050 1.410 0.387 0.352 0.477
CD8/CD69
pos (Treg)
0.589 0.480 0.340 0.520 0.620 0.568 0.719 0.222
CD8/central
memory
4.889 4.220 0.619 6.830 8.630 0.413 0.427 0.007*
CD8/effector
memory
3.105 3.300 0.734 2.720 2.180 0.312 0.401 0.086
CD8/Naive 0.466 0.340 0.455 2.190 2.470 0.800 0.071 0.029*
Female Male
Sex specific
Differences (female
VS males)
Control AKG P-Value Control AKG P-Value
P-Value
Control
P-Value
AKG
Single Cells 100 100 100 100
iNKT cells 0.945 0.609 0.282 0.327 0.346 0.865 0.037* 0.172
iNKT
cells/nk1.1hi 0.227 0.167 0.322 0.085 0.072 0.730 0.030* 0.039
iNKT
cells/nk1.1lo 0.695 0.426 0.290 0.230 0.256 0.753 0.046* 0.272
Single
Cells/other 66.110 70.870 0.229 70.545 68.377 0.640 0.429 0.414
γδ T-cells 1.273 0.556 0.326 0.256 0.296 0.492 0.167 0.126
149
Supplemental table 2. Statistical summary for intracellular signaling for ex vivo stimulated
splenocytes –Flow Cytometry data
Female Male
Sex specific
Differences (female
VS males)
Control AKG P-Value Control AKG P-Value
P-Value
Control
P-Value
AKG
Single Cells 100 100 100 100
CD4 17.040 12.660 0.218 12.380 11.910 0.791 0.150 0.735
CD4/foxp3 6.530 4.160 0.086 3.830 3.160 0.149 0.040* 0.138
CD4/Tbet 0.165 0.140 0.807 0.250 0.250 0.885 0.267 0.149
CD8 10.055 9.010 0.561 13.310 15.360 0.429 0.247 0.007*
CD8/foxp3 0.117 0.110 0.903 0.190 0.160 0.411 0.114 0.144
CD8/Tbet 0.212 0.330 0.450 1.320 1.170 0.710 0.010* 0.018*
Female Male
Sex specific
Differences (female
VS males)
Control AKG P-Value Control AKG P-Value
P-Value
Control
P-Value
AKG
Single Cells 100 100 100 100
CD4 13.049 11.600 0.612 10.429 11.063 0.625 0.132 0.825
CD4/ IFN-γ 5.644 6.562 0.728 2.620 2.178 0.467 0.014* 0.077
CD4/ IL4 0.160 0.163 0.958 0.049 0.074 0.264 0.027* 0.101
CD8 10.555 12.026 0.549 12.362 13.492 0.631 0.526 0.466
CD8/ IFN-γ 5.133 6.421 0.614 3.353 4.421 0.211 0.313 0.293
CD8/ IL4 0.126 0.315 0.016 0.107 0.139 0.497 0.651 0.018*
Female Male
Sex specific
Differences (female
VS males)
Control AKG P-Value Control AKG P-Value
P-Value
Control
P-Value
AKG
Single Cells 100 100 100 100
CD4 14.262 11.391 0.350 8.282 8.899 0.663 0.025 0.289
CD4/TNF-α 7.280 5.472 0.209 4.549 5.877 0.320 0.062 0.766
CD8 10.423 11.364 0.699 13.511 14.693 0.631 0.317 0.112
CD8/ TNF-α 4.322 4.325 0.999 5.296 6.003 0.623 0.621 0.193
150
Supplemental table 3. Statistical summary for negative cells (Dump channel) – Flow
Cytometry data
Female Male
Sex specific
Differences (female
VS males)
Contr
ol AKG P-Value Control AKG P-Value
P-Value
Control
P-Value
AKG
Single Cells 100 100 100 100
Dump negative
23.31
9 34.316 0.159 18.040 16.513 0.693 0.135 0.028*
macrophages 2.852 5.304 0.080 1.317 1.543 0.714 0.005* 0.012*
macrophages
CD11c hi 0.276 0.323 0.543 0.192 0.103 0.169 0.212 0.014*
macrophages
cd38 1.052 1.534 0.168 0.655 0.791 0.784 0.057 0.199
macrophages
class II 0.277 0.360 0.211 0.154 0.162 0.894 0.013 0.023*
Granulocytes 0.931 2.799 0.191 0.918 0.709 0.543 0.971 0.105
myeloid/other
11c hi/ Class II
hi 0.110 0.160 0.021* 0.073 0.071 0.928 0.093 0.0001*
Abstract (if available)
Abstract
Aging and metabolism are tightly connected and interference in nutrient-sensing pathways can enhance longevity in laboratory animals. Here, I demonstrate beneficial effects of α-ketoglutarate (AKG), delivered in food in the form of a calcium salt (CaAKG), a key metabolite in the tricarboxylic acid (TCA) cycle, on longevity in aged mice. ❧ AKG is involved in various fundamental processes including protein synthesis, hypoxic response, collagen synthesis and epigenetic changes (Zdzisinska, Zurek, & Kandefer-Szerszen, 2017). Due to its broad roles in multiple biological processes, AKG has been a subject of interest for researchers in many fields. AKG also influences several age-related processes, including stem cell proliferation and osteoporosis. It has been shown that supplementation of AKG to adult Caenorhabditis elegans (C. elegans) can extend the lifespan and delays aging (Chin et al., 2014). AKG also been shown to consistently extend the lifespan of multiple different Caenorhabditis strains across different research centers, including our lab (Lucanic et al., 2017). ❧ A variety of genetic and pharmacological interventions, mostly in invertebrate laboratory animals, have been identified that enhance lifespan. Whether, these interventions extend healthspan, the disease-free and functional period of life, is not always tested and is often a matter of debate (Bansal, Zhu, Yen, & Tissenbaum, 2015
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Asset Metadata
Creator
Asadi Shahhmirzadi, Azar
(author)
Core Title
Alpha-ketoglutarate, an endogenous metabolite, extends lifespan and compresses morbidity in aging mice
School
Leonard Davis School of Gerontology
Degree
Doctor of Philosophy
Degree Program
Biology of Aging
Publication Date
02/25/2020
Defense Date
02/21/2020
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
aging,AKG,alpha-ketoglutarate,frailty index,frailty phenotype,healthspan,IL-10,Inflammation,lifespan,morbidity,OAI-PMH Harvest,senescence associated secretory phenotype
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Lithgow, Gordon J. (
committee chair
), Andersen, Julie (
committee member
), Pike, Christian (
committee member
), Tower, John G. (
committee member
)
Creator Email
asadisha@usc.edu,Azaasadi@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c89-272376
Unique identifier
UC11673252
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272376
Document Type
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Asadi Shahhmirzadi, Azar
Type
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Source
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(contributing entity),
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The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...
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Tags
AKG
alpha-ketoglutarate
frailty index
frailty phenotype
healthspan
IL-10
lifespan
morbidity
senescence associated secretory phenotype