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Metabolic consequences of obesity-associated inflammation during puberty and perinatal development
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Metabolic consequences of obesity-associated inflammation during puberty and perinatal development
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1
Metabolic consequences of obesity-associated inflammation during
puberty and perinatal development
Brandon David Kayser
A dissertation presented to the faculty of the
University of Southern California Graduate School
In partial fulfillment of the requirements for the degree
Doctor of Philosophy
(Integrative and Evolutionary Biology)
August 2014
2
Table of Contents
ACKNOWLEDGEMENTS ................................................................................................ 4
ABSTRACT ...................................................................................................................... 5
CHAPTER 1 - INTRODUCTION AND BACKGROUND .................................................. 6
Obesity and insulin resistance in children and adolescence ................................................... 6
Adipose tissue inflammation and macrophage recruitment .................................................... 7
Obesity, inflammation, and insulin resistance in pediatric populations ............................... 11
Early-life Programming to obesity and metabolic disease ..................................................... 13
References ................................................................................................................................... 17
CHAPTER 2 - TEMPORAL TRENDS OF ADIPOCYTOKINES AND ASSOCIATIONS
WITH FAT DISTRIBUTION, INSULIN SENSITIVITY, AND Β-CELL FUNCTION IN
OBESE HISPANIC ADOLESCENTS. ............................................................................ 27
Abstract ....................................................................................................................................... 27
Introduction ................................................................................................................................. 28
Research Design and Methods .................................................................................................. 30
Results ......................................................................................................................................... 33
Discussion ................................................................................................................................... 35
Appendix ...................................................................................................................................... 39
References ................................................................................................................................... 47
CHAPTER 3 - PERINATAL NUTRITIONAL PROGRAMMING OF ADIPOSE TISSUE
INFLAMMATION AND METABOLIC DYSFUNCTION IN DIET-INDUCED OBESITY . 52
Abstract ....................................................................................................................................... 52
Introduction ................................................................................................................................. 53
Research Design and Methods .................................................................................................. 55
Results ......................................................................................................................................... 59
Discussion ................................................................................................................................... 63
Figure Legends ........................................................................................................................... 71
3
References ................................................................................................................................... 73
CHAPTER 4 - SUMMARY, PROSPECTIVE STUDIES, AND CONCLUSION .............. 78
Chapter 2 Summary and Conclusion ........................................................................................ 78
Chapter 3 Summary and Conclusion ........................................................................................ 80
Prospective Studies .................................................................................................................... 82
Conclusion .................................................................................................................................. 85
References ................................................................................................................................... 89
List of Figures
FIGURE 1-1: SUMMARY OF ADIPOSE TISSUE INFLAMMATION .............................................................................. 9
FIGURE 2-1: ADIPOCYTOKINES ACROSS AGE ................................................................................................. 43
FIGURE 2-2: BASELINE MCP-1 AND IL-6 MODIFY THE CHANGE IN SI DURING PUBERTY .................................... 44
FIGURE 2-3: COMPARATIVE ADIPOCYTOKINE VALUES IN LEAN CHILDREN ......................................................... 45
FIGURE 2-4: COMPARATIVE ADIPOCYTOKINE VALUES IN ADULTS ..................................................................... 46
FIGURE 3-1: EFFECTS OF SL REARING AT WEANING ....................................................................................... 66
FIGURE 3-2: BODYWEIGHT AND ADIPOSITY OUTCOMES IN ADULTHOOD ............................................................. 67
FIGURE 3-3: METABOLIC OUTCOMES IN ADULTHOOD ....................................................................................... 68
FIGURE 3-4: HISTOLOGY AND FLOW CYTOMETRY OF WAT IN ADULTHOOD ....................................................... 69
FIGURE 3-5: WAT AND SERUM CYTOKINE LEVELS IN ADULTHOOD .................................................................... 70
FIGURE 4-1: SUMMARY OF SMALL LITTER EXPERIMENTS ................................................................................. 81
FIGURE 4-2: PROPOSED RELATIONSHIP BETWEEN AGE AND THE PATHOPHYSIOLOGICAL IMPORTANCE OF
INFLAMMATION TO DIABETES RISK .......................................................................................................... 86
FIGURE 4-3: PROPOSED RELATIONSHIP BETWEEN PERINATAL OBESITY AND INFLAMMATION AND DIABETES RISK . 87
List of Tables
TABLE 2-1: BASELINE CHARACTERISTICS OF THE SOLAR COHORT ................................................................. 41
TABLE 2-2: ADIPOCYTOKINES ACROSS ADOLESCENCE: COEFFICIENTS FROM LINEAR MIXED EFFECTS
REGRESSION MODELS .......................................................................................................................... 42
4
Acknowledgements
I have had the rare and wonderful opportunity to be trained by three talented mentors:
Drs. Michael Goran, Sebastien Bouret and Casey Donovan. You have all contributed
immensely to my development as a scientist. Michael, thank you for giving me the
opportunity to develop such a diverse and fruitful research project. You have taught me
that research projects should be as rigorous and ambitious as one can imagine.
Sebastien, thank you for your time and guidance – I could not have developed such a
project without you. It has been an inspiration working with a team conducting such a
high caliber of science. And Casey, I cannot thank you enough for your initial
mentorship and facilitating my transition to the work that has become this dissertation.
Trouble-shooting a radioenzymatic assay probably taught me more about science than
any other single experience.
Bérengère Coupé and Sophie Croizier, I will never forget your support and
encouragement at the bench. Merci et à bientôt !
I would like to thank my mother, Bonnie Kayser. I could not have done all of this without
you. Thank you helping me pursue my dreams; for being there in the difficult times, and
in the good times. To my late father, Dr. David Kayser, I wish I could have shared my
science with you, but I am proud to have pursued a similar path as you.
And of course, I am grateful to my wife, Rachel Bodsky. It has been an incredible
journey, and this was only the beginning. Thank you for all of your support through the
long days and nights. And thank you for letting me talk on and on about my experiments,
when all you want to do is have dinner. I love you so much.
5
Abstract
The prevalence of overweight and obesity has increased in all ages, including
neonates and adolescents. Childhood obesity is complicated by insulin resistance, and
understanding the pathophysiology of this link may help alleviate the increased diabetes
risk in this population. Chronic low-grade inflammation is an important cause of insulin
resistance, and may be driving obesity-associated insulin resistance in children.
Adipose tissue is central to the inflammatory phenotype, where adipocytes and recruited
macrophages produce inflammatory cytokines that directly impair insulin signaling. The
purpose of this dissertation is to examine the relationships between obesity,
inflammation, and diabetes risk during periods of development.
Previous studies have shown that obese children have increased inflammatory
biomarkers, but it is unclear if inflammation itself is associated with metabolic outcomes
in these individuals. In this dissertation, we report that most circulating cytokines
actually decreased during the adolescent period. Some of these cytokines were
associated with a greater fall in insulin sensitivity during puberty. There were no
associations with β-cell function. Changes during very early development may have a
more profound impact on inflammation.
Perinatal nutrition is known to have a lasting impact on adult metabolism and
disease risk, including sensitization to obesity-induced insulin resistance. Using an
animal model of early postnatal over nutrition, we report that rapid early weight gain did
not cause adipose tissue inflammation in weanling pups. However, perinatal over
nutrition greatly exacerbated obesity-induced adipose tissue inflammation, ectopic fat
deposition, and insulin resistance in adulthood.
This dissertation concludes by summarizing the data presented within and
proposing several prospective experiments, and discusses the hypothesis that obesity-
induced inflammation contributes relatively little to insulin resistance at younger ages,
but that its contribution gradually increases in adulthood. In addition, while the
contemporaneous relationships between obesity, inflammation, and insulin resistance
during childhood may be weak, very early life obesity appears to critically determine the
inflammatory, and therefore metabolic, phenotype of adult obesity.
6
Chapter 1 - Introduction and Background
Obesity and insulin resistance in children and adolescence
The prevalence of overweight and obesity in U.S. adults remains at an all time
high, with approximately 1/3 of the population being classified as overweight and
another 1/3 as obese (1). Obesity in adulthood is associated with an array of chronic
diseases, including cardiovascular disease, type 2 diabetes (T2D), osteoarthritis, and
even some cancers (2). Childhood obesity has risen since the 1960’s. Using data from
the National Health and Nutrition Examination Survey (NHANES), Ogden and Carroll
estimate that 16.9% of boys and girls aged 2-19 years are obese. What is more,
children from minority ethnicities have disproportionately higher obesity rates, with
Mexican-American boys and African-American girls at roughly 28% prevalence (3).
Obesity is linked to insulin resistance and T2D in both adults and children.
The progression to T2D requires insulin resistance and the eventual inability of
the pancreas to secrete sufficient insulin to compensate for this defect. Most of insulin-
stimulated glucose disposal occurs in skeletal muscle, and insulin resistance is defined
as decreased sensitivity of insulin to mediate this disposal (4, 5). T2D is also
characterized by hepatic insulin resistance, which leads to excess gluconeogenesis,
and in the presence of systemic insulin resistance, raises fasting glucose levels (6).
Insulin resistance occurs at the cellular level in adipocytes, myocytes, and hepatocytes
and involves changes in insulin receptor and post-receptor mechanisms. However, the
pathogenesis of T2D also requires the failure of the β-cell to adequately compensate to
insulin resistance i.e. decreased β-cell function (BCF).
Insulin resistance alone is insufficient to cause T2D. For example, mice with
selective insulin receptor defects in skeletal muscle and adipose tissue initially exhibit
profound hyperinsulinemia but maintain normal glucose concentrations until there is a
relative defect in β-cell’s ability to secrete insulin (8). A similar observation is observed
in mice with a genetic and liver-specific ablation of the insulin receptor. These mice
develop profound hyperinsulinemia and maintain normal blood glucose concentrations
until the β-cells are chemically lesioned by streptozotocin
(9). Therefore, the
development of T2D requires a “two-hit” pathogenesis involving both insulin resistance
7
and β-cell failure (10, 11). Understanding the mechanisms behind insulin resistance and
decreased BCF is therefore necessary to understand the pathogenesis of T2D in this
population.
Obese children are more likely to develop glucose intolerance, components of
the metabolic syndrome, and even frank diabetes (12, 13). For example, 21% and 25%
of children and adolescents with an age- and sex-adjusted BMI percentile greater than
95
th
percentile had impaired glucose tolerance, which was most strongly associated with
insulin resistance (14). 4% (4/100) of the children in that study presented with silent T2D
that was accompanied by a severe insulin secretory defect, corroborating the “two-hit”
mechanism identified in adults (14). In addition to insulin resistance due to obesity,
susceptible adolescents may be even more likely to transition to diabetes because
insulin sensitivity declines during puberty (15, 16). Obese Hispanic adolescents with a
family history of T2D exhibit decreased BCF during this period, and thus enter
adulthood with a lower BCF (17). In addition, lower BCF during puberty was associated
with a greater likelihood of pre-diabetes in this population (18). The mechanistic link
between obesity, insulin resistance and diabetes risk in children remains unclear, but
may be related to adipose tissue inflammation.
Adipose tissue inflammation and macrophage recruitment
White adipose tissue (WAT) is no longer considered a mere storage depot, but is
now regarded as an endocrine and immunological organ that undergoes inflammatory
changes in obesity. These inflammatory changes were first observed 20 years ago,
when it was shown that obesity increased the expression of the potent inflammatory
cytokine Tumor Necrosis Factor–α (TNF-α) (19). Blocking the action of TNF-α improved
insulin sensitivity in obese mice, suggesting that inflammation could link obesity to
insulin resistance (19, 20). Since the initial observations with TNF-α, WAT inflammation
has been well characterized and involves the recruitment and activation of a network of
leukocytes within the WAT.
In the lean and insulin sensitive state, WAT is populated by “alternatively
activated”, or M2, macrophages that are identified as CD301
+
cells that reside between
adipocytes and secrete anti-inflammatory factors (21). With progressive fat accretion,
8
macrophages infiltrate the WAT and surround dead and dying adipocytes forming
“crown-like structures” (CLS) (22, 23). These infiltrative macrophages are considered
“classically activated” or M1 macrophages that express the dendritic cell marker CD11c
+
(24). As much as 40% of cells within WAT of obese mice are macrophages – by far the
most abundant leukocyte in the tissue – and as such are considered the critical effector
cells of inflammation induced insulin resistance (22, 23, 25).
In the lean state, M2 macrophages can maintain a low-inflammation and insulin
sensitive environment through the secretion of anti-inflammatory cytokines, such as IL-
10 (24). But with progressive obesity and insulin resistance, mouse models have shown
that circulating monocytes are recruited to WAT by chemokine signaling, with the CCL2
(MCP-1)-CCR2 and CCL5 (RANTES)-CCR5 axes being particularly important (26)
(27).
The WAT environment, rather than the circulating milieu, in obesity then favors the
polarization of these monocytes into the M1 phenotype, resulting in a “phenotypic
switch” from M1 to M2 (24, 26). M1 macrophages contribute to insulin resistance in
adipose tissue, skeletal muscle, and the liver, as ablation of CD11c
+
cells restores
insulin sensitivity in these target tissues (28). There are likely many signaling pathways
involved, but one of the key determinants of the phenotypic switch in WAT is ligand
binding to Toll-like receptor 4 (TLR4). TLR4 is expressed on infiltrating M1
macrophages and free fatty acid (FFA)-TLR4 signaling induces the c-Jun N-terminal
kinase (JNK) cascade and Nuclear Factor-κB (NF-κB) activation, resulting in increased
cytokine production (29, 30). Ablation of TLR4, JNK1, or NF-κB activation in
hemapoietic cells mitigates insulin resistance in diet-induced obese mice
(31-33),
demonstrating that this pathway is critical for mediating inflammation-induced insulin
resistance. Furthermore, gene silencing of the cytokines TNF-α and osteopontin
selectively in adipose tissue macrophages improves glucose tolerance in obesity,
providing experimental evidence that the macrophages within WAT itself are affecting
whole body glucose homeostasis (34). There are two primary mechanisms by which
WAT inflammation may affect whole body insulin sensitivity (Fig. 1).
1. Inflammatory factors secreted by macrophages may directly cause insulin resistance
in adipocytes, resulting in impaired lipid storage and ectopic fat deposition. M1
macrophages produce proinflammatory signals such as TNF-α, IL6, and iNOS, and
9
conditioned media from M1, but not M2, macrophages causes insulin resistance in
cultured adipocytes (21, 35). Furthermore, adipocyte-derived FFAs exacerbate
macrophage activation, which causes a positive-feedback loop between adipocytes
and macrophages (36). Escape of FFA from the insulin resistant WAT could drive
ectopic fat deposition and lipotoxicity (37).
2. Inflammatory cytokines may directly induce insulin resistance in peripheral tissue by
endocrine action. Both adipocytes and macrophages produce cytokines in obesity
that may spill-over into the circulation due to elevated tissue concentrations (38-40).
Cytokines like TNF-alpha, IL-6, and MCP-1 can directly impair insulin signaling in
adipocytes, myocytes, and hepatocytes, showing proof of principle for an endocrine
mechanism (41-43).
Figure 1-1: Summary of adipose tissue inflammation
10
Additional Mechanisms in WAT inflammation
The mechanism of WAT inflammation provided above – macrophage recruitment
due to FFA-TLR4 signaling – suggests that WAT inflammation is an aberrant response
to the excess FFA found in obesity. Other researchers, however, have attempted to
describe the etiology of WAT inflammation as an unresolved compensatory response to
obesity.
In response to energy surplus, WAT expands through hyperplasia and
hypertrophy of adipocytes, which results in endoplasmic reticulum stress and the
generation of inflammatory signals (44). One hypothesis is that the expanding
adipocytes become hypoxic, as the local vasculature is incapable of supplying the
rapidly expanding tissue (45). Adipocyte hypoxia, along with subsequent oxidative and
endoplasmic reticulum stress, may directly induce inflammation in an attempt to
increase vasculature and oxygen perfusion in the tissue (40). Hypoxia could also
induce extracellular fibrosis, resulting in physical stress on the adipocytes as they
attempt to expand within the fibrotic matrix, ultimately leading to necrosis and
inflammation (46). The hypoxia hypothesis is consistent with a recent experiment
demonstrating that over-expression of the angiogenic factor VEGF-1 in adipose tissue
of diet-induced obese mice increased WAT angiogenesis, reduced hypoxia signaling,
and ameliorated the anticipated metabolic impairments (47). The hypoxia hypothesis
and the FFA-TLR4 hypothesis both have considerable evidence and are not mutually
exclusive. It is possible that both are redundant mechanisms to induce inflammation and
subsequent tissue remodeling in order to adapt to the increasing size of the WAT in
obesity. Why this inflammation does not resolve, and why the inflammatory processes
seems to be overwhelmingly pathological (in terms of insulin resistance) remain
unanswered questions.
WAT macrophages are critically important in inflammation-induced insulin
resistance, and are the focus of this dissertation. However, other leukocytes have been
identified in inflamed WAT and are described for completeness. WAT contains
numerous CD3
+
lymphocytes, including CD4
+
IFN-γ-producing T-helper-1 (T
H
1) cells,
CD4
+
GATA-binding protein-3 (T
H
2) cells, and the potent immune-modulating
11
CD4
+
CD25
+
Foxp3
+
T-regulatory (T
Reg
) cells. Similar to the phenotypic switch of
macrophages, WAT inflammation also exhibits a predominance of T
H
1
relative to T
H
2
cells, and a relative or absolute decrease in the number of T
reg
cells (48-50). Animal
models have also shown an obesity-induced increase in cytotoxic CD8+ T cells (51),
natural killer T cells(52), neutrophils (53) and dendritic cells (54). Interestingly, loss of
function experiments in all of these cell types ameliorates obesity-induced insulin
resistance. One possibility is that these cells act in a synergistic manner to perpetuate
inflammation and insulin resistance, and thus removal of any one type could affect the
entire network (25). For example, macrophages have recently been shown to act as
antigen presenting cells in WAT, thus facilitating the recruitment of CD4
+
cells and their
subsequent action (55). Understanding the function of these other adipose tissue
leukocytes remains a productive area of inquiry, but given the relative uncertainty of
their functions and the known importance of adipose tissue macrophages, the work
presented below focuses on the latter.
Obesity, inflammation, and insulin resistance in pediatric populations
Obese children exhibit similar metabolic comorbidities as adults, including insulin
resistance and dyslipidemia; therefore it is likely that similar mechanism linking obesity
to insulin resistance in adulthood also work in pediatric populations. Because WAT
inflammation is thought to be one of these mechanisms, several studies over the past
decade have attempted to find evidence for subclinical inflammation in children.
Furthermore, studying obesity-linked inflammation in children may also offer potential
insight into the more general epidemiology of inflammation, as the potential for reverse
causality is likely to be reduced in children because frank inflammatory diseases have
note yet developed (56). Cross-sectional studies indicate underlying inflammatory
processes in childhood obesity.
Non-specific markers of inflammation are elevated in overweight and obese
children, which may be driven by total adiposity as much as any particular region. Cook
et al. demonstrated that total adiposity in 9 to 11 year olds is associated with sub-
acutely elevated levels of the acute phase protein C-reactive protein (CRP) (56). An
12
analysis of the Northern Finland Birth Cohort 1986 Study revealed that both overall and
abdominal obesity increased the risk of having elevated CRP and leukocytes – has
much as a 5-fold higher likelihood of having elevated levels in the highest visceral
obesity group. The obesity-inflammation link has been documented throughout
childhood, from ages 5-9 (57, 58), 9-11 (56), and 6-16 (59). Given the importance of
WAT inflammation, other studies have investigated markers that may be more specific
to WAT biology.
As described above, WAT secretes a host of adipokines, cytokines, and
chemokines (adipocytokines) that change with inflammation and may be detectable in
the circulation. Adipokines are secreted by adipocytes and can have inflammatory
(leptin, visfatin, retinol binding protein-4) and anti-inflammatory actions (adiponectin)
(60-62). Cytokines and chemokines are a class of inflammatory or anti-inflammatory
factors that may be secreted by WAT or adipocytes themselves, but are not exclusive to
adipocytes; MCP-1 and CCL5 are important examples (26, 27, 40, 63). Inflamed WAT
has increased secretion of many inflammatory factors, including TNF-alpha, IL-1β, IL-6,
and IL-8, therefore there is considerable interest in measuring these factors in serum
(19, 64). The advent of multiplexed ELISA kits has allowed simultaneous quantification
of many of these factors in children.
Obese adolescents were reported to have roughly 50% and 25% greater
circulating IL-6 and MCP-1, respectively, as well as elevated IP-10 and IL-1Ra (59). IL-6
and TNF-α were approximately two-fold higher in obese vs. lean 5-8 year olds and
positively correlated with BMI-z score; these obese children also had elevated IL-20,
MIF, RBP-4, and the adhesion molecules P-selectin and ICAM-1 (57). Elevations in IL-
6, IL-8, and the anti-inflammatory cytokine IL-10 have also been reported (57). But
despite the repeated documentation of increased biomarker levels in children, there is
little evidence showing that inflammation is independently associated with or mediates
the relationship between obesity and insulin resistance (65, 66). Furthermore, there are
limited longitudinal data, which is more likely to detect a relationship between
inflammation and insulin resistance.
13
To date, there have been no comprehensive longitudinal analyses of obesity-
associated inflammation in children. Skinner et al. performed a serial cross-sectional
analysis in 1 to 17 year olds derived from the NHANES, and they reported that 1) the
hazard ratio for elevated CRP (≥1.0mg/L) increases with overweight/obesity to 3-5 at
older ages and 2) that the risk for elevated absolute neutrophil counts is increased with
obesity by 6-9 years, peaks at 9-11 years, and nearly normalizes by 15-17 years (67).
Boys and girls who transitioned from a lean to an obese BMI had greater IL-6, IL-8, and
IL-10 than did those who maintained a lean phenotype or transitioned to a lean BMI
(68). Finally, several weight loss intervention studies have shown some decrease in
circulating inflammatory markers with weight loss, but these studies measured a limited
number of analytes and cannot evaluate the evolution of inflammation throughout
childhood (66). The dearth of longitudinal data analyses is a crucial gap in our
understanding of the pathophysiology of childhood obesity. In addition, little is known
about how obesity in very early life affects inflammation in adulthood.
Early-life Programming to obesity and metabolic disease
The Fetal Origins of Disease hypothesis was proposed to describe the
epidemiological relationships between very early life nutrition and later adult disease. It
was nearly 30 years ago when Barker and Osmond found that areas in England and
Wales with the highest infant mortality – a statistic tied to severe poverty and
undernutrition – had as much as a 10-fold increase in the rates of ischemic heart
disease among adults (69). Similar findings were made regarding glucose metabolism;
adults who were in gestation during the Dutch famine had higher prevalence rates of
impaired glucose tolerance and T2D compared to adults that were born before or after
the famine (70). The epidemiological evidence has been confirmed in experiments using
rodents and sheep, and have demonstrated that severe in-utero nutrient restriction
causes altered glucose metabolism and increased mortality in adulthood, but
importantly, that this effect generally requires rapid “catch-up” growth immediately after
birth (71, 72). This early rapid growth is also found with over nourishment, which is likely
a prevalent exposure given that most obese children have excessive growth prior to the
14
age of 5
(73). Indeed, an accelerated early growth rate in children is associated with
higher fasting insulin levels during adolescence compared to more normal growth rates
(74). Rodent models have provided important insights into the role of perinatal nutrition
and growth on later metabolic disease.
Reports from as early as the 1920’s document an inverse relationship between
rodent litter size and pre- and post-weaning weight gain (75). This effect can be induced
experimentally in rodents by selective litter culling around postnatal day 3 (P3) in order
to generate small litters (SL, 3-4 pups) relative to normal size litters (NL, 7-12
depending on species) (Fig. 2). The SL early obesity paradigm has been demonstrated
across species, including both Swiss and B6D2F
2
mice (76, 77) and both Wistar and
Sprague-Dawley rats(78, 79), and induces accelerated pre-weaning growth with a
weaning weight that is approximately 15-25% heavier than normal litter counterparts
(80). Importantly, these animals defend a modest but significant increase in weight
across the rest of the life span despite feeding on regular laboratory chow in many (79-
82), but not all studies (77, 78). The defense of higher adiposity into adulthood is
hypothesized to be a result of early and persistent leptin resistance, as SL animals have
been shown to have lower basal hypothalamic Ob-Rb and STAT-3 expression (83) and
lower basal p-STAT3 signaling (84). In addition to increased body weight, SL rodents
also exhibit altered metabolic profiles.
Selective litter culling can cause components of the metabolic syndrome. SL
rodents develop elevated fasting glucose and insulin levels (79, 85-87), as well as
increased triglycerides and FFAs (85, 86, 88). These whole-body changes are related to
impaired insulin signaling in peripheral tissues. SL mice have been reported to have
Figure 1-2: Small litter manipulation
15
decreased insulin-mediated phosphorylation of IRS-1 and Akt in epididymal WAT and
decreased protein levels of the insulin receptor, IRS-1, and Akt in the liver (89). SL
rearing increases hepatic triglyceride and FFA uptake that may explain the changes in
insulin signaling phosphorylation patterns, but SL animals do not appear to develop fatty
liver when maintained on regular chow (76, 89). However, while many studies have
shown that rodents from SL have impaired glucose homeostasis, these findings have
not been replicated in all studies (82-84, 90). These discrepancies may be attributed to
differences in rodent species and strain, and likely represent the relatively small effect
size of SL rearing in chow fed animals. On the other hand, SL animals are consistently
sensitized to the consequences of diet-induced obesity.
To date, 3 studies have shown that SL rodents become more obese, glucose
intolerant, and insulin resistant when fed a high fat diet (HFD) compared to their NL
counterparts (82, 87, 89). These studies have identified several potential mechanisms
for this metabolic programming. Boullu-Ciocca et al. observed greater alterations in
glucocorticoid metabolism in visceral WAT of SL and SL-HFD rats, which is known to be
related to visceral obesity and metabolic decline (87). Glavas et al. reported both
greater hepatic steatosis and central leptin resistance in SL-HFD mice, indicating that
perinatal overnutrition may sensitize HFD-induced insulin resistance through both
peripheral and hypothalamic alterations (82). And the most recent report, by Liu et al.,
reported that SL rearing amplified HFD-induced insulin resistance and impaired lipid
storage in WAT and increased lipogenesis in skeletal muscle, suggesting increased
ectopic fat deposition and lipotoxicity secondary to impaired lipid storage (89). With
regard to inflammation, two of these reports also demonstrated increased WAT cytokine
expression, including TNF-α and IL-6, suggesting a potential role of WAT inflammation.
However, all 3 reports showed that SL-HFD animals had greater visceral WAT than NL-
HFD, therefore the cytokine production may be do to the greater visceral obesity.
Furthermore, cytokine gene expression is not sufficient to describe WAT inflammation,
as these changes could be related to altered adipocyte physiology rather than
macrophage recruitment and frank inflammation. One other study used NL and SL rats
on regular chow and showed that SL rats have an exaggerated cytokine and febrile
response to lipopolysaccharide (LPS) injection, along with higher adipose tissue gene
16
expression of Tlr4 and Cd68 (81). Increased Tlr4 expression in WAT and sensitivity to
the TLR-4 ligand LPS suggests that perinatal overnutrition may be sensitizing the WAT
to greater TLR-4 mediated inflammation i.e. FFA induced inflammation described
above. Given that WAT inflammation is a substantial contributor to HFD-induced insulin
resistance in mice, it remains a critical question as to whether SL rearing sensitizes to
greater HFD-induced WAT inflammation.
17
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27
Chapter 2 - Temporal trends of adipocytokines and associations with fat
distribution, insulin sensitivity, and β-cell function in obese Hispanic
adolescents.
Abstract
To determine the longitudinal associations between inflammatory biomarkers and
changes in fat distribution, insulin sensitivity (SI), insulin secretion (AIR), and β-cell
function (BCF) in a high-risk pediatric cohort. 158 overweight/obese Hispanic
adolescents were followed from 11.1 years of age for a median of 4 years. Puberty was
assessed by Tanner method. Serum adipocytokines were measured using Luminex
technology. SI, AIR, and BCF, determined from the Disposition Index (DI), were derived
from an intravenous glucose tolerance test and Minimal Modeling. Total fat mass (TFM)
was measured by DEXA and visceral adipose tissue (VAT) by MRI. IL-8 and IL-1β
decreased significantly by 6.5% per year, IL-6 and TNF-α by 5% per year, but MCP-1
was unchanged. Gaining 1-SD of VAT was associated with a 2% and 5% increase in
MCP-1 and IL-8. When comparing differences by pubertal status, each 1-SD increase in
MCP-1 or IL-6 at baseline was independently associated with a 16% and 21% greater
decline in SI during puberty vs. pre-puberty. These associations with SI corresponded to
a 9% and 17% increase in AIR, respectively, and no associations were found with DI. A
1-SD increase in MCP-1 from baseline was also associated with a 9% decline in SI, a
7% rise in AIR, and a 5% increase in fasting insulin. No associations were found with DI
or fasting glucose. Several adipocytokines decreased during adolescence and were
weakly associated with VAT. Circulating adipocytokines appear unrelated to BCF, but
MCP-1 and IL-6 were associated with greater insulin resistance and compensatory
insulin secretion.
28
Introduction
The prevalence of obesity in children and adolescents has risen over the past
several decades and remains at an all time high, especially in Hispanics who have a
prevalence rate as high as 22.4% (1). As many as one-fourth of obese children present
with impaired glucose tolerance, with some even progressing to type 2 diabetes (2).
Furthermore, childhood obesity and metabolic dysfunction are likely to persist into
adulthood, increasing the likelihood of developing overt metabolic disease in adulthood
(3).
As with adults, elevated fat mass during childhood is thought to cause insulin
resistance and subsequently increase diabetes risk (4). However, this pathophysiology
is complicated by pubertal development, which is associated with dynamic increases in
lean and fat masses, as well as a temporary fall in insulin sensitivity (SI) (5). Our group
has shown that during this physiological period of insulin resistance, β-cell function
(BCF) progressively declines during puberty in overweight and obese Hispanic youth
with a family history of type 2 diabetes (6). In adults, the deterioration of BCF predicted
the incidence of type 2 diabetes in both Pima Indian populations and in Hispanic women
with a history of gestational diabetes (7, 8). And while the transition to diabetes was rare
in our cohort, the persistence of pre-diabetes in these high-risk adolescents was
associated with lower BCF (9). Therefore, understanding the physiological mediators of
both insulin resistance and impaired BCF is critical to alleviating obesity-related co-
morbidities in adolescents.
Obesity is a state of chronic low-grade inflammation (10), which has also been
demonstrated in pediatric populations (11). In obesity, macrophages and other
leukocytes are recruited into adipose tissue, and along with adipocytes, secrete an
array of proinflammatory cytokines, including TNF-α, IL-6, and MCP-1 (12). Unlike
general markers of inflammation such as C-reactive protein (CRP), circulating levels of
these adipose-derived cytokines, or “adipocytokines,” may more accurately reflect
adipose tissue inflammation in obesity. In addition, these cytokines can also mediate
inflammation-induced insulin resistance by directly impairing insulin signaling in
adipocytes and skeletal muscle (13, 14). Several studies have reported increased
29
adipocytokine levels in overweight or obese children (15-19), and these inflammatory
factors are positively associated with fasting indices of insulin resistance (20-23).
However, in studies that controlled for adiposity, the relationship between inflammatory
biomarkers and insulin resistance largely disappears, suggesting that obesity-
associated inflammation may not mediate insulin resistance in children and adolescents
(20, 24). These studies, though, were limited to cross-sectional designs and did not
incorporate more precise measures of adiposity or glucose homeostasis, therefore the
independent relationships between adipocytokines and diabetes risk remain unknown.
The purpose of this study is to clarify the independent relationships between
circulating adipocytokines and diabetes risk in obese youth using intensive measures of
insulin sensitivity and secretion, BCF, and fasting indices (glucose and insulin) in a
longitudinal design. The specific aims of this analysis were: 1) to model the temporal
trends of 5 relevant adipocytokines (MCP-1, TNF-α, IL-1β, IL-6, and IL-8) from
childhood to adolescence, 2) to determine whether changes in total fat mass (TFM) and
visceral fat (VAT) were differentially associated with circulating adipocytokines, and 3)
to test whether higher serum adipocytokines were associated with greater declines in
insulin sensitivity, insulin secretion, and BCF.
30
Research Design and Methods
Subjects. Data were obtained from the Study of Latino Adolescents at Risk (SOLAR)
project at the University of Southern California, which is a longitudinal cohort from 2001
to 2013 that aims to study the progression of T2D risk in susceptible youth across the
pubertal transition. Details of the cohort have been described previously {(27, 28).
Briefly, inclusion criteria for the SOLAR study were as follows: 1) age 8-13 years of age,
2) body mass index (BMI) ≥ 85
th
percentile for age and sex according to the Centers for
Disease Control and Prevention (CDC) guidelines, 3) Hispanic ancestry (all four
grandparents self-reported Hispanic ancestry), and 4) family history of T2D in at least
one parent, sibling, or grandparent. Patients in this analysis completed an inpatient
overnight visit for DEXA, MRI, and a frequently sampled intravenous glucose tolerance
test (FSIVGTT). This current analysis consists of a total of 158 children (83 males, 75
females) who completed at least 2 inpatient visits. The Institutional Review Board,
Health Science Campus, at USC approved the SOLAR study. Informed consent and
assent were obtained from all parents and children, respectively.
Adiposity and Metabolic Measures. A DEXA scan was performed to determine whole
body composition using a Hologic QDR 4500W (Hologic, Bedford, MA). Visceral
Adipose Tissue (VAT) cross-sectional area was measured using a 1.5 Signa LX-
Ecospeed 1.5 Tesla magnet (Waukesha, Wisconsin, General Electric) with a single-
slice axial view at the level of the umbilicus.
A FSIVGTT was performed in the morning following an overnight visit in the
General Clinical Research Center, as described previously (27). Plasma glucose and
insulin data were analyzed with the MINMOD MILLENIUM 2002 computer program
(Version 5.16, Richard N. Bergman) to determine Insulin Sensitivity (SI), the Acute
Insulin Response to glucose (AIR), and the Disposition Index (DI), which is the product
of SI and AIR, as a measure of β-cell function (29)
Adipocytokines. Baseline serum samples from the FSIVGTT (-15min and -5min) were
pooled in order to minimize fluctuations in analyte concentrations resulting from pulsatile
secretion and stored at –80
°
C. Adipocytokines (IL-1β, IL-6, IL-8, MCP-1, and TNF-α)
31
were assayed in duplicate using a commercially available magnetic bead-based
multiplex ELISA (#HADK2MAG-61K-08, EMD-Millipore) on a Luminex MAGPIX
according to the manufacturer’s instructions. This kit has reported intra-assay and inter-
assay variability of <15% and <20%, respectively. To prevent inter-assay variability from
contaminating intra-subject variability, all samples from a single subject were assayed
on the same plate.
Statistics
1
st
Model Series: Changes in adipocytokines with age/puberty and relationships to fat
distribution
Fixed effects: Linear mixed effects regression models were used to analyze the
changes in adipocytokines across time. A linear age-as-time model was used because
there was no evidence for a quadratic trend. TFM and VAT are time-varying covariates
and were therefore modeled as baseline (x
i1
) and change-from-baseline (x
ij
– x
i1
). The
baseline estimate represents a standard cross-sectional estimate of the association
between x and y at baseline. Change-from-baseline is a longitudinal estimate that is not
confounded by genetic make-up or other unmeasured time-invariant covariates, and is
interpreted as the association between a change in x from baseline and the concomitant
change in y over the same period i.e. change over change (30). The latter estimate is
unique to the longitudinal design of this study and is therefore the primary interest. Each
model was also adjusted for sex.
Variance-covariance: The correlation structure of these models included random
intercepts and an exponentially decaying serial correlation, which outperformed random
intercept and slope models. Blocking occurs when subjects are analyzed on the same
plate, so a plate-specific random intercept was also included in the models. Box-Cox
transformations were performed on each adipocytokine to better approximate normality
and homoscedasticity.
2nd models series: Changes in diabetes risk across age or pubertal status and
relationships to adipocytokines
Fixed effects: SI, AIR, and DI were first modeled using age-as-time mixed models to
32
directly study the rate of change per year in these outcomes (similar to the model
described above). A linear model for age was used for AIR, whereas SI and DI required
a quadratic model. Time was also modeled by pubertal status (as our group has
previously done) to explicitly test whether adipocytokine concentrations would modify
the effect of puberty on SI, AIR, and DI (i.e. an adipocytokine by pubertal status
interaction). Pubertal status was defined as pre-pubertal (Tanner 1), pubertal (Tanners
2-4), and post-pubertal (Tanner 5). The models that included pubertal status were
analyzed by ANCOVA. In the presence of a significant pubertal status x adipocytokine
interaction, post-hoc comparisons across pubertal status at low (-1SD) and high (+1SD)
levels of the adipocytokine were conducted to help interpret the interaction. These
models were adjusted for sex, and baseline and changes in VAT and TFM.
Variance-covariance. Metabolic outcomes were log transformed to meet model
assumptions. The variance-covariance of AIR and DI were modeled by a random-
intercept and an exponentially decaying serial correlation, and an estimate of
measurement error was also included for SI.
Restricted Maximum Likelihood was used to estimate model parameters.
Statistical significance of fixed effects was determined using conditional t-statistics and
a probability of type I error set to 0.05. Data were analyzed using R 2.15.2 with the
nlme, car, and effects packages.
33
Results
53% of participants were male and the mean ± SD age at baseline was 11.3 ±
1.8 years. Over half of the children were in Tanner stages 1 or 2 at baseline, and the
remaining 33% were between stages 3 and 5. The mean baseline age- and sex-
adjusted BMI percentile was 96.3 ± 5.6 and waist circumference was 87.1 ± 13.0cm.
Adiposity variables from DEXA and MRI, fasting glucose and insulin, metabolic
outcomes, and serum adipocytokine values are provided in Table 1. There was a
median of 4 years of follow-up per subject with a range from 2 to 7 visits.
In the first series of models, each adipocytokine was regressed onto age,
TFM
BASELINE
, VAT
BASELINE
, ∆TFM, ∆VAT, and sex, using linear mixed effects models.
Independent of changes in adiposity, TNF-α, IL-6, IL-1β, and IL-8 decreased at annual
rates of 0.39pg/ml (6.5%), 0.28pg/ml (6.5%), 0.25pg/ml (5%), and 0.23pg/ml (5%),
respectively (p<0.001, each). However, there was no statistically significant change in
MCP-1 over time (P=0.09). As shown in Figure 1, average plasma levels of
adipocytokines TNF-α, IL-6, IL-1β, and IL-8 decreased from 8 to 18 years of age.
Baseline and change in TFM and VAT were also examined in the first series of
models to determine the effects of fat distribution on these circulating adipocytokines.
Overall, ∆VAT was positively associated with both MCP-1 (β=0.29, P =0.040) and IL-8
(β=0.010, P =0.027); a 1-SD gain in VAT from baseline was associated with a 2% and
5% increase in MCP-1 and IL-8, respectively. However, none of the adipocytokines
were associated with TFM
BASELINE
,
VAT
BASELINE
, or ∆TFM. Neither baseline nor change-
from-baseline in TFM or VAT modified the change in any adipocytokine across the
study period, as there were no statistically significant interactions between the adiposity
covariates and age. TNF-α was the only adipocytokine associated with sex and was
1.12pg/ml higher, on average, in boys than girls (P <0.001).
Since insulin sensitivity and BCF are known to decrease with sexual maturation,
we examined changes in metabolic parameters across puberty to determine whether
greater adipocytokine levels exacerbated pubertal-declines in insulin sensitivity and
BCF. Indeed, higher levels of MCP-1
BASELINE
(P<0.05) and IL-6
BASELINE
(P<0.01) resulted
in greater declines in SI during puberty, which returned to pre-pubertal levels during
34
post-puberty. Specifically, 1-SD higher concentrations of MCP-1
BASELINE
or IL-6
BASELINE
were associated with a 16% or 22% decrease, respectively, in SI during puberty
compared to pre-puberty (P<0.05, each; Fig. 2A and 2C). For AIR, elevated IL-6
BASELINE
further increased the AIR seen during puberty (P<0.05) while higher MCP-1
BASELINE
showed a tendency for a similar effect (P=0.057), and in both cases, AIR returned to
pre-pubertal levels during post-puberty. Specifically, each 1-SD increase in MCP-
1
BASELINE
or IL-6
BASELINE
was associated with a 9% and 17% rise in AIR from pre-puberty
to puberty (Fig. 2B and 2D). Neither MCP-1
BASELINE
nor IL-6
BASELINE
altered the decrease
in DI that occurred during puberty (Fig. 2C and 2D). In addition, there were no
statistically significant interactions between adipocytokine levels and pubertal status for
either fasting glucose or fasting insulin. However, TNF-α
BASELINE
was positively
associated with fasting insulin (β=0.020, P=0.032), where 1-SD higher TNF-α
at
baseline
was associated with 6% higher fasting insulin.
In addition to the population average trends described above, we also examined
whether changes-from-baseline of circulating adipocytokines within individuals tracked
with changes in metabolic parameters across time. ∆MCP-1, but not ∆IL-6 or ∆ TNF-α,
was inversely associated with SI (β=-0.0016, P<0.001) and positively associated with
AIR (β=1.711, P=0.003). Specifically, a 1-SD increase in MCP-1 from baseline was
associated with a 9% fall in SI and a 7% rise in AIR during the same period. Consistent
with these relationships, ∆MCP-1 was not associated with DI. ∆MCP-1 was also
positively associated with fasting insulin, whereby fasting insulin increased by 5% per 1-
SD increase in MCP-1 from baseline. Fasting glucose was unrelated to baseline or
changes in adipocytokine levels.
35
Discussion
Inflamed adipose tissue in obesity secretes an array of adipocytokines that
perpetuate inflammation and induce insulin resistance (12). Studies in adults have
shown that chronic low-grade inflammation in obesity increases the risk for developing
type 2 diabetes (10, 30). Inflammatory biomarkers are also elevated in obese children
(11, 15-19), but there is limited evidence that inflammation is contributing to insulin
resistance in youth, particularly in high-risk minority youth with a family history of type 2
diabetes. In the current study we found that TNF-α, IL-6, IL-1β, and IL-8 declined, while
MCP-1 was unchanged during adolescence in obese Hispanics. Contrary to our
hypothesis, only MCP-1 and IL-6 were weakly associated with increases in VAT. At the
same time, higher baseline levels of MCP-1 and IL-6, as well as longitudinal increases
in MCP-1, were associated with decreases in SI during puberty. This insulin resistance
was met with appropriate β-cell compensation, as these same adipocytokines were
associated with similar increases in AIR. Our results suggest that inflammation may play
less of a role in the pathogenesis of insulin resistance and diabetes in youth than it does
in adults.
Higher levels of circulating inflammatory markers predict the incidence of type 2
diabetes in adults (31). Given that BCF, a predictor of type 2 diabetes incidence, is
known to decline in our cohort (6), the most striking finding of this analysis is that 4 of
the 5 adipocytokines decreased with increasing age, while MCP-1 did not, on average,
change over time. The different trajectory of MCP-1 is likely explained by its inverse
relationship with SI, which itself decreased with increasing age. The general decline in
these inflammatory markers is consistent with a serial-cross-sectional study from
NHANES suggesting that the obesity-associated elevations in CRP and absolute
neutrophil count peak during early adolescence but begin to decline in the later teen
years (32). While it is difficult to compare cytokine levels across studies due to
considerable differences between assays and serum vs. plasma (33), the decline in
adipocytokines we observed is consistent with lower levels in adults. For example,
mean IL-6 at baseline in our study was 7.4pg/ml, and has been reported between
1.4pg/ml and 1.7pg/ml in lean and obese adults, respectively (30, 34). On the other
hand, MCP-1 remains at relatively high concentrations in adults, ranging from
36
approximately 200pg/ml to 430pg/ml in lean vs. morbidly obese subjects, respectively,
consistent with the absence of a decline in our study beginning from 223pg/ml at
baseline (34, 35). The mechanism behind the age-related decrements in these
adipocytokines warrants further investigation.
The greater abundance of adipose tissue itself, particularly VAT, is thought to
contribute to greater circulating markers of inflammation in obesity. We were specifically
interested in changes in TFM and VAT during the study period because such
longitudinal estimates are less likely to be confounded and reflect modifiable changes
that occur during the period of interest i.e. adolescence. Given that MCP-1 and IL-8
were related to changes in VAT, but not TFM, our data is consistent with the notion that
visceral adiposity is more detrimental than total adiposity. However, even visceral fat
appears to be a relatively minor determinant of adipocytokine levels in already obese
adolescents, particularly when compared to the effect of age. The sparse and weak
associations with adiposity detected in our analysis were unexpected, as several reports
have found relationships between BMI or WC and cytokines in children, including
Latinos (15, 19, 22, 36). However, other studies have shown no associations between
obesity and these same adipocytokines, including: IL-6 (8), TNF-α (8, 20), IL-8 (18), and
MCP-1 (16, 18, 20). One possibility is that we did not observe sufficient changes, or
enough subjects with sufficient change, in TFM or VAT during the study period to detect
a change in adipocytokine levels (37). Furthermore, longitudinal estimates frequently
differ from cross-sectional estimates (29), especially when cross-sectional estimates are
highly influenced by genetic differences, which may be the case for obesity-associated
inflammation in children (38).
The final aim of this study was to examine the independent contribution of
circulating adipocytokines to changes in metabolic parameters across puberty. Higher
baseline MCP-1 and IL-6 were each associated with a further decline in SI during
puberty that fully recovered by post-puberty, suggesting that higher levels of these
cytokines did not have a lasting influence on SI during this period. The exaggerated
decreases in SI with higher MCP-1 and IL-6 were accompanied by compensatory
increases in AIR, which corresponded to no modifying relationship between
adipocytokines and DI. In addition, MCP-1 (i.e. ∆MCP-1) was the only adipocytokine
37
measured that was independently and inversely associated with SI, AIR, and fasting
insulin across time. The independent contribution of inflammatory markers to insulin
resistance in obese children is often not tested (37), or the associations between
inflammatory biomarkers and insulin resistance are nearly entirely explained by
adiposity (20, 24). Thus, a major strength of our analysis is that our findings are
independent of total and visceral adiposity. Interestingly, Herder et al. similarly reported
that MCP-1 was only one of seven inflammatory markers to be independently
associated with HOMA-IR (20). The potential importance of MCP-1 may be attributable
to its potent biological actions. MCP-1 is primarily produced by adipose tissue and binds
to chemokine receptor-2 on circulating monocytes to induce macrophage recruitment
and activation in adipose tissue (39). Furthermore, in differentiated human muscle cells,
MCP-1 was capable of blunting insulin signaling via ERK1/2 activation at
physiologically-relevant concentrations as low as 20pg/ml (14). Our findings are largely
consistent with the existing literature in pediatric populations where, unlike adults,
inflammation may contribute minimally to the increased diabetes risk seen in obese
youth. Of course, our results must be interpreted in the context of several limitations.
By design, the SOLAR cohort is restricted to overweight and obese adolescents.
Including lean participants may have allowed us to detect more substantial effects of
adiposity on markers of inflammation. On the other hand, not all obese individuals
demonstrate a strong inflammatory phenotype. A previous study by our group reported
that approximately 50% of obese Hispanic young adults had biopsy confirmed adipose
tissue inflammation (40). Assuming a similar prevalence among the adolescents in our
population, it is expected that this high-risk sample would provide adequate
representation of healthy individuals and those with active inflammation. Thus, our
design may have limited findings with adiposity while strengthening the ability to detect
a relationship between inflammation and metabolic parameters. In addition, biopsies
were not taken to directly measure adipose tissue inflammation. These adipocytokines
may primarily act through paracrine mechanisms within adipose tissue and liver,
therefore circulating levels may be less relevant than tissue concentration (12). Lastly,
SI primarily reflects glucose disposal into muscle, so we cannot determine the
importance of MCP-1, or the other adipocytokines, to hepatic insulin resistance.
38
In conclusion, adipocytokines relevant to adipose tissue inflammation and
metabolic dysfunction mostly decline during adolescence in obese Hispanic youth. Fat
mass, either total or visceral, appears to be only weakly associated with circulating
inflammatory markers in already obese adolescents. Lastly, while higher levels of MCP-
1 and IL-6 were associated with lower SI and greater β-cell compensation during
puberty, the fall in BCF in this high-risk cohort is unrelated to circulating adipocytokines.
These data suggest that adolescence may be a period of reduced inflammatory tone
and extends others’ cross-sectional findings that after controlling for adiposity,
circulating adipocytokines are poorly associated with diabetes risk in pediatric
populations.
39
Appendix
The SOLAR cohort is limited to overweight and obese children, which prevents
us from comparing the values in our study to normal weight children directly. However,
we can compare and contrast to previous reports in children to gain an impression of
how the values in our study relate to lean children. The relationships between values
from our studies and those aggregated from other studies are displayed in Fig. 3 As
expected, circulating levels of IL-6 and TNF-α were each approximately 65% higher in
our cohort of obese children. These two cytokines are the most frequently measured,
and therefore likely the most accurate to compare. On the other hand, MCP-1 and IL-1β
varied little from our measurements; MCP-1 differed by no more than 3% between our
estimates and the median of previous studies, while IL-1β in our study was only 14%
higher than the one previous study. Taken from only two studies, IL-8 was 5-fold lower
in our study compared to previous studies. However, there is a 10-fold difference in IL-8
levels between the two previous studies. Given that our estimate was closer to
4.85pg/ml than 40pg/ml, it is possible that technical differences may preclude
comparison with the higher values. When comparing to these previous studies, any
observed difference is unlikely attributed to age, as the baseline age in our study was
11.1 years, whereas the median age was 12.4 in the comparative studies. These
comparisons reveal that the adipocytokines measured in our study were at least
comparable to those in normal weight children, and the most frequently studied
cytokines TNF-α and IL-6 were indeed elevated in our cohort of obese children.
Another question related to the absolute concentration of these adipocytokines is
how they relate to adult levels. Our analysis revealed that, with the exception of MCP-1,
these adipocytokines declined rapidly during adolescence. To address this, we
extracted cytokine values from previous studies that measured adults. These studies
included both normal weight and non-diabetic obese subjects so as to minimize a
potential rebound effect where adipocytokines levels could be much higher in obese
adults (Fig. 4). Consistent with our findings that adipocytokines decline with age during
adolescence, TNF-α, IL-6, and IL-1β were approximately 70%, 65%, and 95% higher in
our cohort with a baseline age of 11.1 years compared to levels in adults with a median
age of 46 years. The comparison with IL-1β should be made with caution, however, as
40
this measurement was only found in one study. Conversely, MCP-1 and IL-8 were 65%
and 35% below the estimated adult level; although the values from the SOLAR study for
these latter two cytokines approximated the range found in previous studies (Figure 2).
Overall, these data are consistent with our findings that many adipocytokines, such as
IL-6 and TNF-α, decrease from adolescence into adulthood and plateau at a value
below that of childhood.
While these comparisons offer important insight into the absolute concentrations
observed in our study, several limitations are worth noting. All of the studies included
varied in regards to the analytical technique (ELISA vs. Luminex technology vs. other
techniques) and used kits from different companies (Linco vs. Millpore), all of which has
been shown to substantially influence the reported values of circulating adipocytokines
(41). Furthermore, values of the same adipocytokines can also vary depending upon
sample matrix (plasma vs. serum) or preservation type (42-43). Given the complications
of comparing values across studies, there is considerable need to measure these
adipocytokines in lean and obese children and in adults under the same conditions to
confirm the relationship between aging, obesity, and circulating biomarkers of
inflammation.
41
Table 2-1: Baseline Characteristics of the SOLAR cohort
Table 1 Baseline Characteristics of the SOLAR cohort
Variable Value
Male, n (%) 83 (53)
Female 75 (47)
Tanner 1 60 (38)
2 45 (28)
3 15 (9)
4 23 (15)
5 15 (9)
Age (y) 11.3 ± 1.8
BMI (kg/m
2
) 28.2 ± 5.3
BMI - Percentile 96.3 ± 5.6
BMI - Z Score 2.0 ± 0.5
WC (cm) 87.1 ± 13
Body Fat (%) 38.1 ± 5.9
Lean Mass (kg) 37.5 ± 10.7
Fat Mass (kg) 25.0 ± 10.2
VAT (cm
2
) 46.9 ± 21
Fasting Glucose (mg/dl) 93.1 ± 5.7
Fasting Insulin (µU/ml) 21.1 ± 12.4
SI (10
-4
min
-1
/µU/ml) 2.1 ± 1.5
AIR (µU/ml x 10min) 1740 ± 1260
DI 2600 ± 1400
MCP-1 (pg/ml) 223.5 ± 80.4
TNF-α (pg/ml) 7.4 ± 2.9
IL-6 (pg/ml) 6.9 ± 7.9
IL-1β (pg/ml) 4.2 ± 3.7
IL-8 (pg/ml) 3.7 ± 2.3
Table 1. Unless specified otherwise, values are reported as mean ± standard deviation.
BMI = body mass index, WC = waist circumference, VAT = visceral adipose tissue area,
SI = insulin sensitivity, AIR = acute insulin response to glucose, DI = disposition index
42
Table 2-2: Adipocytokines Across Adolescence: Coefficients from Linear Mixed Effects
Regression Models
MCP-1 TNF-α IL-6 IL-1β IL-8
β* P β P β P β P β P
Age -2.31 0.090 -0.39 <0.001 -0.28 0.001 -0.25 <0.001 -0.23 <0.001
TFM
BASELINE
-0.32 NS 0.04 NS 0.07 NS 0.05 NS 0.01 NS
∆TFM 0.96 0.071 0.02 NS 0.00 NS 0.02 NS -0.01 NS
VAT
BASELINE
0.45 NS 0.00 NS 0.00 NS -0.01 NS 0.00 NS
∆VAT 0.29 0.040 0.01 NS 0.00 NS 0.00 NS 0.01 0.027
†Sex 10.37 0.077 1.12 <0.001 -0.41 NS -0.09 NS 0.25 NS
Table 2. *Coefficients are reported back-transformed from the Box-Cox
transformations. †Coded as male=1 and female=0. ∆TFM and ∆VAT are
change-from-baseline in total fat mass and visceral adipose tissue area,
respectively.
43
Figure 2-1: Adipocytokines across age
Figure 1. Mean change in adipocytokines across age, adjusted for sex, and baseline and
change in TFM and VAT. Re-scaled as percent from baseline (age 8). The effect of age was
statistically significant for all adipocytokines other than MCP-1.
44
Figure 2-2: Baseline MCP-1 and IL-6 modify the change in SI during puberty
Figure 2. A-C: Estimated marginal means for insulin sensitivity (SI; A), acute insulin response
(AIR; B), and the disposition index (C) at each pubertal stage for high and low levels of baseline
MCP-1. D-F: SI (D), AIR (E), and the disposition index (F) for high and low levels of baseline IL-
6. Back-transformed estimates are adjusted for years elapsed, gender, baseline and change-
from-baseline in TFM and VAT. 1-SD corresponds to 84 and 8pg/ml for baseline MCP-1 and IL-
6, respectively.
45
Figure 2-3: Comparative adipocytokine values in lean children
MCP-1 IL-6 TNF-α IL-1β IL-8
0
10
20
30
40
Herder et al.
Kim et al.
Breslin et al.
Aygun et al.
Warnberg et al.
Herder et al.
Kim et al.
Nemet et al.
Balagopal et al.
Aygun et al.
Warnberg et al.
Herder et al.
Breslin et al.
Reinehr et al.
Nemet et al.
Aygun et al.
Herder et al.
Breslin et al.
+
+
+
+
+
pg/ml
Adipocytokines in Normal Bodyweight Children
+"Median'of'other'studies" Kayser'et'al.'
Aygun'AD,'Gungor'S,'Ustundag'B,'Gurgoze'MK,' Sen'Y:'Proinflammatory'cytokines'and'lepDn'are'increased'in'serum'of'
'prepubertal'obese'children.'Mediators*Inflamm'2005:180K183,'2005'
Balagopal'P,'George'D,'PaMon'N,'Yarandi'H,'Roberts'WL,'Bayne'E,'Gidding'S:'LifestyleKonly'intervenDon'aMenuates'the'
'inflammatory'state'associated'with'obesity:'a'randomized'controlled'study'in'adolescents.' J*Pediatr'146:342K348,'
'2005'
Breslin'WL,'Johnston'CA,'Strohacker'K,'Carpenter'KC,'Davidson'TR,'Moreno'JP,' Foreyt'JP,'McFarlin'BK:'Obese'Mexican'
'American'children'have'elevated'MCPK1,'TNFKalpha,'monocyte'concentraDon,'and'dyslipidemia.' Pediatrics'
'129:e1180K6,'2012'
Herder'C,'Schneitler'S,'Rathmann'W,'Haastert'B,'Schneitler'H,'Winkler'H,'Bredahl'R,'Hahnloser'E,'MarDn'S:'LowKgrade'
'inflammaDon,'obesity,'and'insulin'resistance'in'adolescents.' J*Clin*Endocrinol*Metab'92:4569K4574,'2007'
Kim'J,'BhaMacharjee'R,'KheirandishKGozal'L,'Khalyfa'A,'Sans'Capdevila'O,'Tauman'R,'Gozal'D:'Insulin'sensiDvity,'serum'
'lipids,'and'systemic'inflammatory'markers'in'schoolKaged'obese'and' nonobese'children.'Int*J*Pediatr'
'2010:846098,'2010'
Nemet'D,'Wang'P,'Funahashi'T,'Matsuzawa'Y,'Tanaka'S,'Engelman'L,'Cooper'DM:'Adipocytokines,'Body'ComposiDon,'and'
'Fitness'in'Children.'Pediatric*Research'53:148K152,'2003'
Reinehr'T,'StoffelKWagner'B,'Roth'CL,'Andler'W:'HighKsensiDve'CKreacDve'protein,'tumor'necrosis'factor'alpha,'and'
'cardiovascular'risk'factors'before'and'acer'weight'loss'in'obese'children.' Metabolism'54:1155K1161,'2005'
Wärnberg'J,'Nova'E,'Moreno'LA,'Romeo'J,'Mesana'MI,'Ruiz'JR,'Ortega'FB,'Sjostrom'M,'Bueno'M,'Marcos'A:'Inflammatory'
'proteins'are'related'to'total'and'abdominal'adiposity'in'a'healthy'adolescent'populaDon:'the'AVENA'Study.'Am*J*
*Clin*Nutr'84:505K512,'2006'
'
Sources"
*'
*MCPK1'was'divided'by'a'factor'of'10'to'be'on'the'same'scale'as'the'other'cytokines'
46
Figure 2-4: Comparative adipocytokine values in adults
MCP-1 IL-6 TNF-α IL-1β IL-8
0
10
20
30
40
Le et al.
Kloting et al.
Pradhan et al.
Kloting et al.
Fabbrini et al.
Fabbrini et al.
Mirza et al.
Testelmans et al.
Engeli et al.
Le et al.
Mirza et al.
Pradhan et al. Engeli et al.
Mirza et al.
Le et al.
Mirza et al.
Pradhan et al.
+
+
+
+
+
pg/ml
Adipocytokines in Adults
+"Median'of'other'studies " Kayser'et'al.'
Lê'KA,'Mahurkar'S,'Alderete'TL,'Hasson'RE,'Adam'TC,'Kim'JS,'Beale'E,'Xie'C,'Greenberg'AS,'Allayee'H,'Goran'MI:'
'Subcutaneous'adipose'Issue'macrophage'infiltraIon'is'associated'with'hepaIc'and'visceral'fat'deposiIon,'
'hyperinsulinemia,'and'sImulaIon'of'NFO kappaB'stress'pathway.'Diabetes'60:2802O2809,'2011'
Engeli'S,'Feldpausch'M,'Gorzelniak'K,'Hartwig'F,'Heintze'U,'Janke'J,'Möhlig'M,'Pfeiffer'AFH,' Lu['FC,'Sharma'AM:'
'AssociaIon'between'adiponecIn'and'mediators'of'inflammaIon'in'obese'women.' Diabetes'52:942O947,'2003'
Fabbrini'E,'Cella'M,'McCartney'SA,'Fuchs'A,' Abumrad'NA,'Pietka'TA,'Chen'Z,'Finck'BN,'Han'DH,'Magkos'F,'Conte'C,'Bradley'
'D,'Fraterrigo'G,'Eagon'JC,'Pacerson'BW,'Colonna'M,'Klein'S:'AssociaIon'between'specific'adipose'Issue'CD4+'TO
'cell'populaIons'and'insulin'resistance'in'obese'individuals.' Gastroenterology'145:366O74.e1O3,'2013'
KlöIng'N,'Fasshauer'M,'Dietrich'A,'Kovacs'P,' Schon'MR,'Kern'M,'Stumvoll'M,'Bluher'M:'Insulin'sensiIve'obesity.' Am1J1
1Physiol1Endocrinol1Metab'2010'
Mirza'S,'Hossain'M,'Mathews'C,'MarInez'P,'Pino'P,'Gay'JL,'Renfro'A,'McCormick'JB,'FisherOHoch'SP:'Type'2Odiabetes'is'
'associated'with'elevated'levels'of'TNFOalpha,'ILO6'and'adiponecIn'and'low'levels'of'lepIn'in'a'populaIon'of'
'Mexican'Americans:'a'crossOsecIonal'study.' Cytokine'57:136O142,'2012'
Pradhan'AD,'Manson'JE,'Rifai 'N,'Buring'JE,'Ridker'PM:'COreacIve'protein,'interleukin'6,'and'risk'of'developing'type'2'
'diabetes'mellitus.'JAMA'286:327O334,'2001'
Testelmans'D,'Tamisier'R,'BaroneORochece 'G,'Baguet'JP,'RouxOLombard'P,'Pepin'JL,'Levy'P:'Profile'of'circulaIng'cytokines:'
'impact'of'OSA,'obesity'and'acute'cardiovascular'events.' Cytokine'62:210O216,'2013'
Sources"
*'
*MCPO1'was'divided'by'a'factor'of'10'to'be'on'the'same'scale'as'the'other'cytokines'
47
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52
Chapter 3 - Perinatal nutritional programming of adipose tissue
inflammation and metabolic dysfunction in diet-induced obesity
Abstract
Obesity causes white adipose tissue (WAT) inflammation and insulin resistance
in some, but not all individuals. Here, we used a mouse model of early postnatal
overfeeding to determine the role of neonatal nutrition in lifelong WAT inflammation and
metabolic dysfunction. C57BL/6J mice were reared in small litters of 3 (SL) or normal
litters of 7 pups (NL) and fed either regular chow or a 60% high fat diet (HFD) from 5 to
17 weeks. At weaning, SL mice did not develop WAT inflammation despite increased fat
mass, although there was an up-regulation of WAT Tlr4 expression. On HFD, adult SL
mice had greater inguinal fat mass compared to NL mice, however both groups showed
similar increases in visceral fat depots and adipocyte hypertrophy. Despite the similar
levels of visceral adiposity, SL-HFD mice displayed greater impairments in glucose
homeostasis and more pronounced hepatic steatosis compared to NL-HFD mice. In
addition, WAT from SL mice fed a HFD displayed greater crown-like structure formation,
increased M1 macrophages, and higher cytokine gene expression. Together, these data
suggest that early postnatal overnutrition may be a critical determinant of fatty liver and
insulin resistance in obese adults by programming the inflammatory capacity of adipose
tissue.
53
Introduction
The prevalence of overweight and obesity has increased at an alarming rate in
countries that have adopted a Western lifestyle, which includes overconsumption of
energy-rich and nutrient-poor food (1, 2). Such lifestyle changes also affect children,
which raises major health concerns because obese children and adolescents are more
likely to become obese adults (3). Obesity is the primary risk factor for the development
of type 2 diabetes by causing inulin resistance, which results in a greater demand of the
pancreas to secrete insulin and eventually β-cell failure in susceptible individuals (4).
However, obesity is not always sufficient to cause insulin resistance, as 30-40% of
individuals with a Body Mass Index greater than 35kg/m
2
have normal insulin sensitivity
determined by the hyperinsulinemic-euglycemic clamp (5). Differences in fat distribution
(6), ectopic fat deposition (7), and inflammation (8, 9) may determine whether an obese
individual becomes insulin resistant. Identifying the environmental determinants and
biological processes of these physiologic mediators is critical to understanding the
pathophysiology of obesity-induced insulin resistance.
During the past few decades, evidence has accumulated that suggests that
alterations in the perinatal environment can substantially contribute to deleterious
metabolic outcomes in the developing offspring. In particular, epidemiological and
animal studies have revealed that changes in the hormonal and nutritional environments
during critical periods of development may increase the susceptibility for the
development of obesity later in life. A primary importance has been given to the
nutritional environment before birth in part because of epidemiological and animal
studies that demonstrated that severe undernutrition during pregnancy results in adult
metabolic disturbances in the offspring (10, 11). However, the early postnatal
environment also contributes to obesity and metabolic disease risk in adulthood (12,
13). For example, offspring from dams fed a high fat diet (HFD) during the suckling
period, but not during gestation, develop leptin resistance, glucose intolerance, and
impaired β-cell innervation that persist into adulthood (14, 15). Another valuable model
to study postnatal overfeeding is the small litter size model. Pups raised in small litters
(SL) have increased energy intake and subsequently gain more weight before weaning
(13). SL rodents remain overweight and hyperinsulinemic into adulthood (16-18), and
54
also develop more pronounced insulin resistance and hepatic steatosis when fed a
high-fat diet (HFD) (16, 19, 20). This latter observation suggests that early-life nutrition
may determine whether an obese individual subsequently develops insulin resistance or
remains metabolically normal. However, the biological processes linking perinatal
overnutrition and insulin resistance in adulthood remain largely unknown, but might
involve adipose tissue inflammation
Obesity in adults is associated with chronic low-grade inflammation that
predisposes to insulin resistance (21). White adipose tissue (WAT), in particular,
contributes to this state of metabolic inflammation or “metainflammation,” and
undergoes considerable changes in leukocyte composition and cytokine and adipokine
production in obesity (21). Adipose tissue macrophages are central contributors to
metainflammation (22), whereby obesity leads to an influx of proinflammatory type 1
macrophage (M1) that overcome the decreasing proportion of resident and anti-
inflammatory type 2 macrophages (M2) (23-25). The recruited M1 macrophages secrete
an array of cytokines and chemokines that perpetuate inflammation and impair
adipocyte function (26-28). Increased WAT macrophage content has been suggested to
explain, at least in part, the discrepancy between metabolically normal and abnormal
obesity in humans (8, 9), indicating that environmental factors that modify
metainflammation are important drivers of insulin resistance and diabetes risk.
Although the importance of the obesogenic environment during adult life
on metainflammation is now well established, the relative contribution of neonatal
nutrition in this biological process is not well understood. In the present study, we used
the small litter size model to evaluate the contribution of early postnatal overnutrition to
adipose tissue inflammation and insulin resistance in adulthood.
55
Research Design and Methods
Mice. Offspring of C57BL/6 mice (Jackson Laboratories), produced in our mice colony,
were used in these studies. Mice were housed under specific pathogen-free conditions
and maintained in a temperature-controlled room with a 12 hr light/dark cycle. On post-
natal day 1 (P1), litters were adjusted to 7 pups to normalize nutrition. At P3, litters were
culled to 3 pups (small litters; SL) while normal litters (NL) remained at 7 pups. A subset
of male mice were sacrificed at P21, whereas all other males were weaned onto ad
libitum normal chow and water in pairs matched for the same litter size treatment. At 5
weeks of age, both NL and SL mice were either given 60% high-fat diet (HFD; Research
Diets) or remained on regular chow (Chow) until sacrifice 12 weeks later (week 17 of
life). Animal usage was in compliance with and approved by the Institutional Animal
Care and Use Committee of the Saban Research Institute of the Children’s Hospital of
Los Angeles.
Physiological measures. Animals were weighed every two days between P4 and P20
and weekly from P25 through ~P120 (n= 19-25 per group from ≥ 5 litters). At P21, all
data are from n=4-5 per group from ≥ 4 litters, while sample sizes for adult mice are
specified below. Epididymal (eWAT) and subcutaneous (sWAT) adipose tissue was
collected at P21, and eWAT, retroperitoneal (rWAT), and inguinal (iWAT) fat depots
were collected at 17 weeks of age and weighed (n = 9-13 per group from ≥ 6 litters).
Insulin tolerance tests (ITT) were performed at 15 weeks of age (n = 4-8 per group from
≥ 4 litters) by an i.p. administration of 0.75U/kg (Humalin R) after a 6-hour fast, and then
the blood glucose levels were measured 0, 15, 30, 45, 60, 90, 120 min following insulin
challenge. Glucose tolerance tests (GTT) were performed at 16 weeks of age (n = 5-10
per group from ≥ 5 litters) by an i.p. administration of glucose (1.5mg/g bodyweight)
after overnight fasting, and then the blood glucose levels were measured 0, 15, 30, 45,
60, 90, 120, and 150 min following glucose challenge. For both tests, blood was taken
via a small incision at the tip of the tail. The incremental (and inverted for ITT) area
under the glucose curve (iAUC) was calculated using the trapezoidal rule. Total
triglyceride (TG) content was assayed in the liver of 17-week-old mice (n = 5-11 per
56
group from ≥ 5 litters) using a Triglyceride Assay Kit (Sigma) as previously described
(29).
Serum measurements. Blood was collected by cardiac puncture. Serum was isolated
by storing blood on ice for 60 minutes and then centrifugation for 15 minutes at 3000
r.c.f. at 4°C. Serum IL-6, MCP-1, and resistin were assayed at 17 weeks of age (n = 4-8
per group from ≥ 4 litters) on a Luminex-MAGPIX using a commercially available
multiplex ELISA panel (MADKMAG-71K, EMD Millipore). TNF-α and insulin were
assayed using ELISA kits (EMD Millipore).
Immunohistochemistry and image analysis. Fat pads were sectioned at 1mm thick,
fixed in 1% paraformaldehyde and processed for immunofluorescence using standard
procedures. Briefly, samples were incubated overnight in primary antibodies, washed,
and incubated in secondary antibodies. Samples were counterstained using Hoechst
33342 (Invitrogen) to visualize cell nuclei and immersed in buffered glycerol (pH 8.5).
Primary antibodies used were rat anti-F4/80 for CLS (1:1000; Abcam), rat anti-perilipin
(1:1000; Sigma) for adipocyte sizing, Armenian hamster anti-CD11c to visualize M1
(1:500; AbD Serotec), and conjugated CD301-Alexa647 (1:200; AbD Serotec) to
visualize M2 macrophages. Secondary antibodies were goat anti-rat Alexa 568, anti-
rabbit Alexa 488, and anti-hamster Alexa 647 (1:200; Invitrogen). For quantification,
images were acquired using a Zeiss LSM 710 confocal microscope system equipped
with a 10X or 20X (for P21) objective. Determination of mean size (µm
2
) was measured
semi-automatically using the FIJI distribution (30) of Image J software (NIH,
ImageJ1.47i). The average adipocyte size and isolated macrophage counts from 3
fields in each mouse was used for statistical comparisons. The sum total of CLS from 3
fields per mouse were manually counted using Image J analysis software.
Isolation of stromal vascular cells and flow cytometry. 17 week-old mice (n = 7-8
per group from ≥ 4 litters) were perfused with 15 ml of PBS, and one epididymal fat pad
57
was placed in Hank’s Balanced Salt Solution (HBSS; Invitrogen) supplemented with 1%
BSA. Adipose tissue was minced and incubated at 37°C in 1mg/ml collagenase (type
IV; Worthington Biochemical, Lakewood, NJ). The cell suspension was filtered through
a 100 µm filter and centrifuged. The pellet of stromal vascular cells (SVC) was re-
suspended in 500 µl of RBC lysis buffer (BioLegend), followed by dilution with PBS
containing 1 mM EDTA, 25 mM HEPES and 1% heat-inactivated fetal bovine serum. A
minimum of 1x10
5
cells were aliquoted into single-stain controls, fluorescence minus
one controls, and sample tubes, then incubated in Fc Block (rat anti-mouse
CD16/CD32) followed by conjugated antibodies. DAPI was used to discriminate
live/dead cells. Flow data were acquired on a FACSAria-I (BD Bioscience) and analyzed
using Cytobank (31). FMO controls were used to establish polygonal gates. The
following fluorochrome conjugated antibodies were used: CD45 Apc-Cy7 for leukocytes,
CD64 PerCp-Cy5.5 for macrophages, CD11c PE-Cy7 for M1 macrophages (BioLegend,
San Diego, CA), and CD301 Alexa 647 for M2 macrophages (AbD Serotec, Raleigh,
NC).
Quantitative real-time PCR. sWAT of P21 and eWAT of 17 weeks-old mice (n = 5-8
per group from ≥ 5 litters) was rapidly dissected and frozen. Total RNA was isolated
using the RNeasy Lipid Tissue Kit (Qiagen, Valencia, CA). cDNA was generated using a
High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Carlsbad, CA).
Quantitative real time PCR analysis was performed using TaqMan Fast universal PCR
Mastermix and recommended primer/probe sets (Life Technologies). mRNA expression
was calculated using the 2
-∆∆CT
method after normalization with Gapdh as an internal
control. Inventoried TaqMan® Gene expression assays Il6 (Mm 00446190_m1), Tlr4
(Mm00445273_m1), Tnfa (Mm 00443260_g1), Itgax (Mm00498698_m1, Il10
(Mm00439614_m1), Arg1 (Mm00475988_m1), Ccl2 (Mm00441242_m1) and Gapdh
(Mm99999915_g1) were used. Assays were performed with a Prism 7900HT Sequence
Detection System (Applied Biosystems).
58
Statistical analysis. Terminal samples at weaning were derived from mice born in
different litters, and were therefore independent statistical units analyzed by unpaired T-
tests. Terminal samples in adult mice contain data from mice born to the same litter,
which results in statistical dependence between siblings; therefore linear mixed models
were used to account for within-litter correlation (random intercept for litter) and the
within-mouse correlation from repeated-measurements (random intercept for litter +
random intercept for mouse + serial correlation) in growth curve, ITT, and GTT
analyses. Repeated measurements were analyzed by 3-way ANOVA, while terminal
data were analyzed by 2x2 ANOVA. Following a significant interaction (P<0.10), post-
hoc comparisons between litter sizes were stratified by diet. Variance weights were
estimated to mitigate the severe heteroscedasticity caused by the large treatment effect
of the HFD. CLS counts were analyzed by generalized estimating equations using a
Poisson distribution and the Jackknife estimate of the standard errors (32). Statistical
significance was considered P<0.05, and for post hoc comparisons, P values were
adjusted by the Holm-modified Bonferroni correction (33). Data were analyzed using R
2.15.2 with packages nlme, car, geepack, and phia.
59
Results
Small litter rearing causes rapid weight gain without inducing marked
inflammation at weaning
To study the consequences of early postnatal overnutrition, we used a mouse
model of divergent litter size. As expected, SL rearing was associated with changes in
pre-weaning growth, as revealed by a significantly higher body weight in SL compared
to NL mice starting at P4 (Fig. 1A). At weaning SL pups remained 20% heavier
compared to NL pups (P<0.001 at P20; Fig 1A). In addition, epididymal (eWAT) and
subcutaneous fat (sWat; i.e., inguinal + paracostal) masses were 4.5-fold and 3.6-fold
increased, respectively, in P21 mice compared to control NL animals (Fig. 1B). This
increase in fat mass in weanling SL mice was accompanied by a 3-fold increase in
adipocyte area (P<0.01; Fig. 1C-E). We next investigated adipose tissue macrophage
infiltration using immunostaining for the macrophage marker F4/80. A 2.3-fold increase
in the number of F4/80-positive cells was found in eWAT (P<0.05) and sWAT (P<0.01)
of P21 SL mice as compared to control NL mice (Fig. 1D-F). However, CLS were
undetected in both groups. Because obesity induces a phenotypic switch in adipose
tissue macrophage polarization from an M2-polarized state to an M1 pro-inflammatory
state (23), we also assessed M1- and M2-related gene expression in sWAT of SL and
NL at P21. mRNA expression of the anti-inflammatory gene Arg1 was 5.4-fold increased
(Fig. 1G; P<0.05) in SL animals whereas Il10 gene expression was undetectable (Fig.
1H). There were no differences in the expression of the proinflammatory genes Itgax,
Tnfa, or Il6, although TLR4 (P<0.05) was expressed 2-fold higher in SL mice (Fig 1G-
H). Consistent with the idea that neonatal overnutrition does not cause marked WAT
inflammation at weaning, SL rearing had no effect on random-fed circulating levels of
TNF-α, glucose, or insulin (Fig. 1I-K).
Neonatal overnutrition exacerbates HFD-induced weight gain and alters fat
distribution
To determine whether neonatal overnutrition programs diet-induced obesity, we
fed SL and NL a high-fat diet starting at 5 weeks of age. Body weight was higher in NL-
60
HFD mice compared to chow fed controls as early as 4 weeks after diet manipulation
(Fig. 2A). However, exposure of HFD to SL mice resulted in an even greater increase in
bodyweight compared to NL-HFD mice (P
Size X Diet X Week
<0.01; Fig. 2A). Differences in
body weight were detected as early as 2 weeks of high fat feeding (P<0.05), and
persisted throughout the HFD exposure (P<0.05; Fig. 2A). The elevated bodyweight
observed in SL animals was associated with an increase in body length (P
Size
<0.01; Fig.
2B). Moreover, HFD increased eWAT and rWAT weights by nearly 6-fold (P<0.001,
each) with no additional effect of litter size (Fig. 2C). However, there was 1.5-fold
increase in iWAT weight in SL-HFD animals compared to NL-HFD mice (P
Size X
Diet
<0.01
and P<0.01 for pairwise comparison; Fig. 2C). High fat feeding also caused adipocyte
hypertrophy as revealed by a 3.7-fold, 4-fold, and 3.8-fold increase in adipocyte size in
eWAT, rWAT, and iWAT, respectively (P
Diet
<0.001, each; Fig. 2D-E). However, rWAT
adipocyte size was reduced by 13% in SL mice compared to NL animals on either diet
(P
Size
<0.05; Fig. 2D-E).
Neonatal overnutrition further impairs glucose homeostasis and hepatic steatosis
in diet induced obesity
To examine the effect of neonatal overfeeding on glucose homeostasis, we
performed glucose (GTT) and insulin (ITT) tolerance tests and measured various fasting
parameters in SL and NL mice fed a chow diet or a HFD. Fasting glucose and insulin
levels were significantly elevated in SL-HFD mice compared to NL-HFD animals (Fig.
3C-D). In addition, when exposed to a glucose challenge, SL-HFD mice displayed
impaired glucose tolerance as compared to NL-HFD mice across all time points (P
<0.01; Fig. 3A). HFD exposure increased the mean iAUC in the GTT (P
Diet
<0.003),
however, there was only a trend for a higher iAUC in SL mice (P
Size
=0.067; Fig. 3A
inset). An ITT was performed to better evaluate whole-body insulin action. During the
ITT, blood glucose in SL-HFD mice was statistically significantly higher than NL-HFD
animals at 60, 90, and 120 min post insulin injection (P<0.001, 0.001, and 0.01,
respectively; Fig. 3B); and the mean ITT-derived iAUC of the SL-HFD group was one-
third that of the NL-HFD group (P<0.001; Fig. 3B inset). In addition, SL animals exposed
61
to HFD displayed a 2-fold increase in the mean hepatic triglyceride content and
enhanced hepatic steatosis compared to NL-HFD mice (P<0.01; Fig. 3E-F).
Neonatal overfeeding triggers HFD-induced adipose tissue inflammation.
We next evaluated WAT inflammation in various fat pads of adult SL and NL
mice fed a chow or a HFD. We first performed F4/80 staining to detect macrophage
infiltration and the presence of CLS (Fig. 4A-B). Consistent with the low-inflammatory
potential of low-fat feeding, CLS were rare in the eWAT, rWAT, and iWAT of chow fed
NL and SL (Fig. 4A). Moreover, there was no marked difference in the number of CLS
between NL-Chow and SL-Chow (Fig. 4A). However, when fed a HFD, SL mice
displayed 3-8 times greater CLS counts in eWAT (P<0.001), rWAT (P<0.001), and
iWAT (P<0.05) compared to NL-HFD mice (Fig. 4B-C). To further confirm macrophage
infiltration in SL-HFD mice, we quantified total CD45
+
CD64
+
macrophages in eWAT
using flow cytometry. As expected, the total number of macrophages was not different
between SL-chow and NL-chow mice (Fig. 4F). However, on HFD, SL mice displayed
twice as many CD45
+
CD64
+
cells compared to NL-HFD mice (P
Size X Diet
<0.01; pairwise
P<0.05; Fig. 4F). Histological examination confirms that CLS predominately contain
CD11c
+
M1 macrophages, while CD301
+
macrophages are identified as more diffuse
isolated cells (Fig. 4E). To better characterize the phenotype of adipose tissue
macrophages, we next sorted CD45
+
CD64
+
macrophages based on heterogeneous
expression of CD11c and CD301. The number of CD11c
+
macrophages was 3.8-fold
higher in SL-HFD mice compared to NL-HFD (P<0.01; Fig. 4F). In contrast, the number
of CD301
+
macrophages was reduced by 40% in the HFD groups (P
Diet
<0.01), with no
additional effect of litter size (Fig. 4F). These findings confirmed that the increased
number of macrophages observed in the eWAT of SL-HFD mice is attributed to an
increased number of M1 macrophages. Consistent with these findings, mRNA
expression of pro-inflammatory genes, such as Il6, Tnfa, and Ccl2 (MCP-1) were up-
regulated by 4.5 (P<0.05), 3.6 (P<0.05), and 5.1 (P<0.01) times, respectively, in eWAT
of SL-HFD compared to NL-HFD mice (Fig. 5A). Similar to the P22 animals, Tlr4
expression in SL-HFD was 1.7 times that of NL-HFD (P<0.05; Fig. 5A). In addition, Arg1
62
mRNA expression was 6-fold increased in SL-HFD animals (P<0.01), but surprisingly,
Il10 mRNA expression was not different between SL-HFD and NL-HFD mice (Fig. 5B).
Similarly, circulating concentrations of IL-6, TNF-α, MCP-1, and resistin were 2-, 1.1-,
1.7-, and 3.3-fold increased in HFD animals compared to chow fed mice (P
Diet
<0.001;
Fig. 5C). However, there were no additional effects of litter size on these circulating
cytokines or resistin (Fig. 5C).
63
Discussion
Epidemiological and animal studies have indicated that changes in growth and
nutrition during early life can have lasting effects on adult metabolism. In the present
study, we employed a well-established animal model of divergent litter size to study the
role of early postnatal overnutrition on adipocyte inflammation and metabolic
programming. Despite the early rapid weight gain, SL rearing alone did not cause WAT
inflammation at weaning or in adults when fed regular chow. However, SL mice were
sensitized to greater obesity-induced macrophage recruitment and cytokine signaling in
WAT, as well as greater ectopic fat deposition and impaired glucose homeostasis.
Importantly, all of these differences occurred despite comparable levels of visceral
adiposity between NL-HFD and SL-HFD groups. These experiments demonstrate that
early postnatal nutrition influences the inflammatory phenotype of adipose tissue in diet-
induced obesity.
Litter size has been known to influence weight gain in rodents for nearly a
century (34). The accelerated growth of SL pups from selectively culled litters is
primarily attributed to increased energy intake of the suckling pups (35), and therefore
provides an accurate model for perinatal programming by early overnutrition. Confirming
the importance of perinatal nutrition, numerous studies have shown that SL rodents
maintain increased fat mass and develop components of the metabolic syndrome in
adulthood, despite being fed regular chow (13, 18, 36). Several studies have further
shown that litter size reduction causes greater sensitivity to the metabolic
consequences of diet-induced obesity, including greater insulin resistance and hepatic
steatosis (16, 19, 20). Boullu-Ciocca et al. correlated the exaggerated metabolic
impairments to enhanced WAT glucocorticoid signaling (20), while a more recent report
by Liu et al. showed further impairments in muscle and WAT insulin signaling (19). Both
studies demonstrate higher cytokine gene expression in WAT from SL-HFD compared
to NL-HFD, but these findings were confounded by increased fat mass and adipocyte
size in the fat pads of interest. Our study confirms and extends these reports in several
important ways. First, we employed several different techniques, including flow
cytometry, to comprehensively characterize WAT inflammation and macrophage
recruitment. Second, using 12 weeks of a 60% HFD in the C57BL/6 mouse strain, a
64
common model for metainflammation studies, we demonstrated that SL rearing
exacerbates inflammation independent of differences in adiposity. Finally, by examining
NL and SL mice at weaning, we showed that the increased propensity to HFD-induced
inflammation in adulthood is not attributed to an early development of inflammation.
Together, these findings implicate adipose tissue inflammation as an important
contributor to the metabolic programming induced by perinatal overfeeding.
WAT inflammation is characterized by changes in numerous leukocyte
populations, particularly macrophages, and increased production of inflammatory
cytokines (37). Previous studies have shown that ablation of CD11c
+
cells (25) or
reduction of their cytokine production (28) mitigates insulin resistance in obesity,
suggesting that at least part of the metabolic impairment we observed in SL-HFD mice
is attributed to the large increase in M1 macrophage recruitment and subsequent
cytokine production. Proinflammatory cytokines from the adipose tissue of SL-HFD
could enter the circulation and directly cause insulin resistance in muscle or liver (38,
39). However, circulating concentrations of IL-6, TNF-α, and MCP-1 were comparable
between NL-HFD and SL-HFD, suggesting that this was not the primary mechanism.
On the other hand, macrophage-derived cytokines can induce adipocyte insulin
resistance through paracrine signaling (26), which could impair adipocyte function,
resulting in ectopic fat deposition and lipid-induced insulin resistance (40). Our findings
showing elevated WAT cytokine gene expression and hepatic triglyceride accumulation
are consistent with this hypothesis. Future studies that experimentally reduce
macrophage recruitment or improve adipose tissue lipid storage in SL-HFD mice will
help to clarify the relative contribution of WAT inflammation to the programmed
phenotype.
As early as 3 weeks of life, SL mice already displayed greater fat mass and
adipocyte hypertrophy compared to NL mice. Yet the juvenile SL mice did not develop
overt WAT inflammation, as demonstrated by the absence of CLS and normal Itgax
(CD11c) expression, but instead, demonstrated an M2 phenotype, with higher numbers
of isolated macrophages and an increase in Arg1 expression. A robust M2 polarization
with increasing fat mass may be unique to developing adipose tissue, as inflammation
can be detected with similar levels of fat accretion in mature animals fed a HFD for 2
65
week (41). However, WAT from weanling SL mice also displayed an increase in Tlr4
expression. Toll-like Receptor 4 is an important mediator of adipose tissue inflammation
in diet-induced obesity (42), and could potentially explain the increased sensitivity of SL
mice to HFD. Future studies will be required to test this hypothesis.
Epidemiological data confirms the relevance of early life obesity to later
metabolic health in humans. Obesity rates have increased in children younger than 5
years of age (43), and this excessive early growth is associated with greater propensity
for obesity (44) and insulin resistance (45) in later life. Similar to the discordance in
inflammation seen between NL-HFD and SL-HFD mice in the current study, our group
(46), as well as others (9), has shown that macrophage infiltration in WAT is associated
with greater insulin resistance among similarly obese patients. However, the factors that
determine whether an obese patient subsequently develops this inflammation are poorly
understood. Given the profound inflammatory and metabolic differences between NL
and SL mice on HFD, our findings offer proof of principle that perinatal nutrition may be
an important environmental contributor to metabolically abnormal obesity, possibly by
exacerbating WAT inflammation.
In conclusion, our study shows that SL rearing results in greater fat mass
accretion before weaning without inducing early-onset WAT inflammation. When
exposed to an obesogenic environment, mice raised in a SL displayed much greater
macrophage recruitment and cytokine gene expression compared to NL mice,
independent of differences in visceral fat. This greater propensity to develop adipose
tissue inflammation paralleled more severe hepatic steatosis and impairments in
glucose homeostasis. Together, these data suggest that the early postnatal
environment may be a critical modifier of adipose tissue inflammation and insulin
resistance in diet-induced obesity.
66
Figure 3-1: Effects of SL rearing at weaning
67
Figure 3-2: Bodyweight and adiposity outcomes in adulthood
68
Figure 3-3: Metabolic outcomes in adulthood
69
Figure 3-4: Histology and flow cytometry of WAT in adulthood
70
Figure 3-5: WAT and serum cytokine levels in adulthood
71
Figure Legends
Figure 1. Neonatal overfeeding promotes rapid weight gain and increases
adiposity without causing WAT inflammation at weaning. A: Pre-weaning growth
curves (body weights) of mice raised in normal litters (NL) or small litters (SL) (n = 19-25
per group from ≥ 9 litters). B-C: Mass (B) and mean adipocyte areas (C) of epididymal
(eWAT) and subcutaneous (sWAT) adipose tissue of P21 SL and NL mice (n = 4-5 per
group from ≥ 5 litters). D-E: Representative images showing adipocyte morphology
(immunostained for perilipin, green fluorescence) and F4/80-immunoreactive cells (red
fluorescence) in eWAT (D) and sWAT (E) of NL and SL mice at P21. F: Quantification of
F4/80-immunoreactive cells in eWAT (D) and sWAT (E) of NL and SL mice at P21 (n =
4-5 per group from ≥ 4 litters). G-H: Relative gene expression of macrophage markers
(G) and cytokines (H) in sWAT at P21. I-K: Plasma levels of TNF-α (I), glucose (J), and
insulin (K) in NL and SL mice at P21 (n = 4-5 per group from ≥ 4 litters). *P<0.05 and
**P<0.01 versus NL. Scale bar, 100 µm.
Figure 2. Neonatal overfeeding increases HFD-induced weight gain and alters fat
distribution. A-B: Post-weaning bodyweights (A) and naso-anal length (B) of mice
raised in normal litters (NL) or small litters (SL) and fed a chow or a high-fat diet (HFD)
starting at 5 weeks of age (n = 9-13 per group from ≥ 5 litters). C-E: Mass (C) and
mean adipocyte areas (E) of epididymal (eWAT), retroperitoneal (rWAT), and inguinal
(iWAT) adipose tissue in adult SL and NL mice fed a chow or a HFD (n = 7-8 per group
from ≥ 4 litters). Representative images illustrating adipocyte morphology
(immunostained for perilipin, green fluorescence) in adult NL and SL mice fed a chow or
a HFD (D). *P<0.05 and ***P<0.001 versus NL matched for diet; ∆∆∆ P<0.001 for Diet
main-effect; Σ P<0.05, ΣΣ P<0.01 for Litter Size main-effect. Scale bar, 100 µm.
Figure 3. Neonatal overnutrition perturbs glucose homeostasis and causes
hepatic steatosis in diet-induced obesity. A-B: Glucose and (A) insulin (B) tolerance
tests and incremental area under the curves/inverted incremental area under the curves
of adult SL and NL mice fed a chow or a high-fat diet (HFD) (n = 4-10 per group from ≥
72
4 litters). C-E: Plasma levels of glucose (C), insulin (D), and hepatic triglyceride content
(E) of adult SL and NL mice fed a chow or a HFD (n = 5-11 per group from ≥ 5 litters). F:
Representative images showing Oil Red-O stain in the liver of adult SL and NL mice fed
a chow or a HFD. *P<0.05, **P<0.01 and ***P<0.001 versus NL matched for diet; ∆∆
P<0.01 for diet main-effect. Scale bar, 100 µm.
Figure 4. Neonatal overnutrition exacerbates HFD-induced adipose tissue
inflammation. A: Representative images of F4/80 immunoreactivity (red fluorescence)
in the epididymal adipose tissue of NL and SL mice fed a chow diet. B: Representative
images of F4/80 immunoreactivity (red fluorescence) in the epididymal, retroperitoneal,
and inguinal adipose tissue of NL and SL mice fed a high-fat diet (HFD). C:
Quantification of crown-like structures (CLS) in the epididymal (eWAT), retroperitoneal
(rWAT), and inguinal (iWAT) adipose tissue of adult NL and SL mice fed a HFD (n = 9-
13 per group from ≥ 6 litters). D: Representative scatterplots showing CD301 and
CD11c heterogeneity in CD45
+
CD64
+
macrophages from eWAT of adult NL and SL fed
a chow or a HFD. E: Histological illustration of antibodies used for flow cytometry. F:
Quantification of CD45
+
CD64
+
total macrophages, CD45
+
CD64
+
CD11c
+
M1
macrophages and CD45
+
CD64
+
CD301
+
M2 macrophages in eWAT of SL and NL fed a
chow or a HFD (n = 7-8 per group from ≥ 4 litters). *P<0.05, **P<0.01 and ***P<0.001
versus NL matched for diet; ∆ P<0.05 for diet main-effect. Scale bar, 100 µm.
Figure 5. Neonatal overnutrition exacerbates HFD-induced expression of pro-
inflammatory genes. A-B: Relative gene expression pro-inflammatory (A) and anti-
inflammatory (B) markers in eWAT of NL and SL fed a high-fat diet (HFD) (n = 5-8 per
group from 5-8 litters). C: Serum concentrations of adipokines/cytokines (n = 4-8 per
group from ≥ 4 litters). *P<0.05 and **P<0.01 versus NL-HFD; ∆∆ P<0.01, ∆∆∆ P<0.001
for Diet main-effect.
73
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78
Chapter 4 - Summary, Prospective Studies, and Conclusion
The final chapter in this dissertation summarizes the results from the preceding
chapters and synthesizes these findings into a broader framework. Several important
questions remain following the animal experiment presented in chapter 3, therefore a
formal presentation of follow-up experiments in presented.
Obesity is a major cause of insulin resistance, and therefore type 2 diabetes
(T2D) as well. But despite obesity’s important role in insulin resistance, many obese
individuals remain insulin sensitive, suggesting that elevated fat mass per se does not
impair insulin action. Inflammation, primarily derived from the adipose tissue, appears to
be a critical determinant of obesity-induced insulin resistance. An abundance of work in
animal models has shown that inflammatory macrophages recruited to the white
adipose tissue (WAT) in diet-induced obesity causes insulin resistance in adipose
tissue, skeletal muscle, and liver. WAT inflammation has also been observed in obese
and insulin resistant patients, and importantly, is able to distinguish metabolically normal
from metabolically abnormal obesity. But while much has been learned about metabolic
inflammation in adult obesity, little attention has been given to earlier periods in the life
span. The purpose of this dissertation was to fill this knowledge gap.
Chapter 2 Summary and Conclusion
The rise in childhood obesity has resulted in an increase in the number of insulin
resistant and glucose intolerant children and adolescents, with some of these pediatric
patients transitioning to T2D. Weight reduction is the most desirable approach in
treating this population, but this is often difficult to attain. Understanding the
pathophysiology of insulin resistance during adolescence may provide therapeutic
targets to prevent the transition to pre-diabetes or T2D during the metabolically stressful
period of puberty. Our study demonstrated that, with the exception of MCP-1, the
biologically important adipocytokines TNF-α, IL-6, IL-8, and IL-1β actually decline during
the teenage years. Furthermore, only MCP-1 and IL-8 were positively and weakly
79
associated with increases in visceral adiposity, suggesting that circulating inflammatory
markers are relatively insensitive to changes in adiposity in already obese adolescents.
Lastly, higher baseline MCP-1 and IL-6 were associated with insulin resistance during
puberty. However, this latter effect was only transient, and furthermore, no
adipocytokines were related to changes in DI. There are two interpretations of these
findings.
One possibility is that inflammation is an important cause of insulin resistance in
adolescents, but circulating biomarkers poorly reflect the inflammatory state in tissues.
This may be the case because many inflammatory cytokines are thought to act primarily
in a paracrine fashion (1). Furthermore, and despite being obese, children may have
lower levels of tissue inflammation compared to adults, so there may be even greater
discordance between circulating and tissue levels of inflammatory cytokines in pediatric
populations.
The second interpretation is that inflammation is a minor contributor to pediatric
insulin resistance. Studies that have obtained subcutaneous fat biopsies did not find a
relationship between obesity and adipose tissue macrophages in children, suggesting
that frank WAT inflammation may not occur in children (2, 3). Walker et al. did report
that children positive for crown-like structures (CLS) had greater liver inflammation
scores, but CLS did not associate with more moderate metabolic outcomes such as
hepatic steatosis or fasting estimates of insulin resistance and β-cell function (3). Thus,
adipose tissue inflammation in children may occur with the most severe metabolic
abnormalities, but may not explain the early deteriorations in glucose homeostasis.
Obtaining omental adipose tissue biopsies in lean and obese children would provide
more conclusive evidence regarding the importance of WAT inflammation, as visceral
fat is thought to be more inflammatory than the subcutaneous depots. However, given
the difficulty in obtaining these types of samples in children, this question may not be
readily addressed. Analyzing inflammatory biomarkers in healthy versus obese
adolescents with T2D would also provide valuable insight into whether inflammation
plays a larger role in the final transition to diabetes, rather than at the earlier stages of
insulin resistance.
80
Chapter 3 Summary and Conclusion
The experiments in chapter 3 investigated whether metabolic programming by
perinatal overnutrition was characterized by increased WAT inflammation. The first
experiment examined WAT inflammation and the metabolic phenotype of small litter
(SL) and normal litter (NL) mice at weaning to determine whether WAT inflammation
was an early phenomenon. In contrast to our hypothesis, WAT from SL mice at weaning
showed no increase in proinflammatory M1 macrophage recruitment or cytokine
production despite considerable fat accretion. SL mice may have been protected from
inflammatory processes due a much higher number of M2 macrophages. These data
show that SL rearing does not simply result in the early incidence of WAT inflammation.
The second experiment exposed NL and SL mice to regular or high fat diet
(HFD) chow in order to determine the effects of perinatal overnutrition on the
inflammatory phenotype in adulthood. Consistent with the phenotype at weaning, we did
not observe increased inflammation in SL mice when they were maintained on normal
chow. This is consistent with the hypothesis that adipose tissue inflammation requires a
persistent stimulus, such as saturated free fatty acids (FFA) or hypoxia due to rapid
tissue expansion. In contrast, when mice were fed a high fat diet, SL rearing caused a
substantial increase in M1 macrophage recruitment, cytokine expression, and ectopic
fat deposition despite comparable levels of visceral adiposity (Figure 4-1). Thus, the
development of inflammation in adult obesity is critically dependent upon early life
nutrition.
81
Figure 4-1: Summary of small litter experiments
Our findings in SL mice have important implications for the phenomenon of
metabolically normal and abnormal obesity. As many as 65% of patients with a BMI
between 30-34.9 and 35% of patients with a BMI above 35 remain insulin sensitive (4).
Increased WAT macrophage and lymphocyte recruitment and hepatic steatosis appears
to distinguish those obese individuals who become insulin resistant (5-7). However, the
genetic or environmental determinants of metabolically abnormal obesity have not been
determined, therefore it is difficult to establish means of prevention. Our study provides
proof of principle that perinatal nutrition could largely determine the inflammatory and
metabolic phenotype of obesity. These findings will need to be confirmed in humans.
The ideal study would recruit adult patients who have participated in birth cohorts with
comprehensive early postnatal growth data, so that adipose tissue biopsies can be used
to determine inflammation or in vitro sensitivity to inflammation in those that grew the
most rapidly during early postnatal life. In addition, several future experiments will help
to address mechanistic questions related to the animal model developed in chapter 3.
82
Prospective Studies
1) How much does inflammation causally contribute to the programmed phenotype?
Rationale: SL rearing could exacerbate obesity-induced insulin resistance through a
number of mechanisms; therefore it is critical to determine how much WAT inflammation
contributes to this programmed phenotype.
Design: MCP-1 is largely produced in WAT and MCP-1 KO mice exhibit dramatically
reduced macrophage recruitment into WAT (8). After litter size allocation and at 5
weeks of age, NL-WT, SL-WT, and SL-MCP-1KO mice will be put onto 60% HFD for the
following experiments:
1. A small sample of each group will be sacrificed at weeks 4, 8, and 12 to
determine the evolution of WAT macrophage recruitment using flow cytometry,
histology, and gene expression of WAT depots.
2. Once it is determined when NL-WT and SL-MCP-1KO mice have the same level
of WAT macrophage recruitment, an expanded sample will be included at this
time point to comprehensively examine the metabolic phenotype using insulin
and glucose tolerance tests, and measures of ectopic fat deposition.
Interpretation:
1. The first experiment will allow us to study the evolution of WAT inflammation in
programmed mice, and will also allow us to expand our analysis to other WAT
leukocytes such as T
H
1 and T
reg
cells. Furthermore, this longitudinal evaluation
will allow us to identify a time point in which NL-WT and SL-MCP-1-KO mice
have similar levels of macrophage recruitment in order to control for
inflammation.
2. By establishing comparable levels of WAT inflammation between NL-WT and SL-
MCP-1-KO mice, the second experiment will allow us to determine the relative
contribution of inflammatory mechanisms to the programmed metabolic response
(the difference between SL-WT and SL-MCP-1-KO outcomes) and the
contribution of non-inflammatory mechanisms (the remaining difference between
NL-WT and SL-MCP-1KO, which have the same levels of inflammation).
83
2) The mechanism of perinatal programming of WAT inflammation
Rationale: SL mice do not develop WAT inflammation at weaning or when put onto
regular chow, indicating the programming effect was due to a change in sensitivity of
the inflammatory response. Tlr4 gene expression was up regulated in the WAT of SL
mice at weaning, and given this receptor’s important role in mediating WAT
inflammation, increased TLR-4 signaling may be the molecular link for increased
inflammatory sensitivity in SL mice.
Design:
1. To confirm that SL rearing induces early and functional TLR-4 responsiveness,
ex vivo culture of WAT explants from P21 mice will be conducted. WAT explants
will be exposed to control-media, or also incubated with lipopolysaccharide
(LPS), oleate (non-inflammatory fatty acid), or palmitate. Cytokine production
(TNF-α, IL-6, and MCP-1 in media) and NF-κB activation (phosphorylation of IκB-
α in tissue by immunoblot) will be determined.
2. To test the role of TLR-4 in vivo, NL-WT, SL-WT, and SL-TLR4-KO will be fed a
60% HFD for 12 weeks. Macrophage recruitment and metabolic outcomes will be
evaluated as described above.
Interpretation:
1. With respect to the in vitro experiments, these results will demonstrate that SL
rearing causes early sensitivity to TLR-4-mediated WAT inflammation in a
functional manner (i.e. increased NF-κB activation and cytokine response in WAT
from SL). Furthermore, by isolating the effect in WAT, these experiments will
determine whether this effect is tissue autonomous.
2. The in vivo experiment will confirm whether TLR-4 is at least partially responsible
for the higher WAT inflammation observed in SL-HFD compared to NL-HFD
mice.
84
3) Do early changes in the gut microbiota lead to the SL-induced phenotype and can
these alterations be therapeutically manipulated?
Rationale: The programmed phenotype in SL-HFD mice may be due to changes in
WAT biology per se, but another possibility is that early postnatal overnutrition causes
persistent alterations in gut flora. Obesity and insulin resistance increase gram-
negative bacterial populations in the gut, and LPS produced by these bacteria can
induce endotoxemia through TLR-4 activation (9).
Design:
1. The experiment from Chapter 3 will be repeated, but stool samples will be
collected at P3 (before SL exposure), P21 (weaning), and after 12 weeks of
regular chow or HFD in order to perform metagenomic sequencing of the gut
flora.
2. To test the causal contribution of LPS-producing bacteria and endotoxemia to the
programmed phenotype in SL-HFD mice, polymyxin B (an antibiotic that also
neutralizes LPS (10)) will be used to reduce endotoxemia. NL, SL, and SL-
antibiotic mice will all be fed a HFD for 12 weeks, followed by a comprehensive
evaluation of WAT inflammation and metabolic phenotyping, as described above.
3. Pre- and probiotic supplements may be a simple and desirable intervention
strategy for reversing perinatal programming. The prebiotic oligofructose has
been shown to mitigate WAT inflammation and glucose intolerance induced by
HFD (11), therefore experiment 2 above will be repeated, but oligofructose will be
given rather than the antibiotic. Treatment can be given during the pre-weaning
period in one series of experiments and the post-weaning period in another
series to determine whether the pre-weaning period would also be a critical
period for intervention.
Interpretation:
1. The first experiment will identify the natural evolution of the gut microbiome
during the pre-weaning period and whether SL rearing alters this process. This
experiment will also identify whether SL rearing causes persistent changes in the
85
gut flora composition (NL-Chow vs. SL-Chow) or whether perinatal overnutrition
alters the HFD-induced changes in microflora (NL-HFD vs. SL-HFD)
2. By comparing the levels of WAT inflammation and insulin resistance between NL,
SL, and SL-antibiotic mice, the second experiment will allow us to determine
whether gut-derived endotoxemia is causally contributing to the programmed
phenotype in SL-HFD mice.
3. Finally, the third experiment would provide proof of principle that a relatively
simple intervention could alleviate the inflammatory and metabolic burden
induced by early postnatal overnutrition. Oligofructose may be difficult or
impossible to give to the suckling pups, therefore probiotic treatment with
bifidiobacterium spp. (a previously identified beneficial species) may provide a
way to prevent the early changes in gut microbiome that may be altered by SL
rearing.
Conclusion
Obesity-induced inflammation is an important cause of insulin resistance and risk
for developing T2D. Most animal and clinical research in this field has focused on
inflammation in adults, and little is known about adipose tissue inflammation at earlier
points in the lifespan. This dissertation first and foremost demonstrates age can have a
profound and differential effect on inflammation.
Using an animal model of early postnatal overnutrition, we showed the rapid
weight gain in pups prior to weaning does not induce adipose tissue macrophage
recruitment, and in the absence of this inflammation, these pups maintain normal
glucose and insulin levels. In addition, our longitudinal analysis in obese adolescents
showed that only MCP-1 and IL-6 were related to reduced insulin sensitivity, which was
only present during puberty, and none of the cytokines predicted decreased β-cell
function. Together, and along with the literature in adults, these data are consistent the
hypothesis that non-inflammatory mechanisms primarily contribute to insulin resistance
during early life, but that inflammation progressively contributes more to the
pathogenesis of insulin resistance and T2D as individuals reach adulthood (Fig 4-2).
86
Previous studies support this hypothesis. For example, insulin resistance is observed in
obese neonates and adolescents, but inflammatory markers do not predict insulin
resistance after controlling for adiposity, whereas circulating inflammatory markers do
independently predict insulin resistance in adults (12-14). It is possible that inflammation
could be detected in young obese patients, but that it is not actively contributing to the
metabolic dysfunction in this population. Identifying non-inflammatory therapeutic
targets may be more beneficial for pediatric patients.
Figure 4-2: Proposed relationship between age and the pathophysiological importance
of inflammation to diabetes risk
Weight loss would be the most desirable treatment of obese children. However,
weight loss can be difficult to obtain regardless of age, therefore additional therapeutic
approaches may be warranted. If inflammation does contribute relatively little to insulin
resistance in obese adolescents, targeting non-inflammatory mechanisms would be
more desirable. Such therapies could include reductions in fructose intake or
supplementation with omega-3 fatty acids in order to reduce liver fat (15-17), or exercise
interventions designed to improve skeletal muscle insulin sensitivity (18, 19). Further
work will be required to conclusively determine whether adipose tissue inflammation is
less important during adolescence, and if so, what are the primary mechanisms linking
obesity to diabetes risk in these patients, particularly decreased β-cell function.
However, very early obesity can greatly influence the adult metabolic phenotype.
87
Despite a limited contemporaneous relationship between obesity and
inflammation during development, a major finding of the work presented in this
dissertation is that perinatal overnutrition is a major determinant of adipose tissue in
later life. The phenomenon of metabolic imprinting has been known for decades, and
our study extends previous work by implicating inflammation as a principle effector of
the programmed phenotype in adulthood. We found that perinatal overnutrition critically
altered the inflammatory response in obesity, on the order of 4- to 5-fold greater
macrophage recruitment and expression of inflammatory cytokines, demonstrating that
altered development can fundamentally regulate the inflammatory response in
adulthood (Fig. 4-3). Given the magnitude of the effect, these findings have practical
implications for basic scientists studying metabolic inflammation: litter size must be
controlled in the same manner as diet quality, time-of-day, and genetic background in
order to prevent unnecessary variation and potential bias in results. Given the number
of studies that employ the same mouse strain and diet used in this dissertation work,
these findings have broad generalizability to the design of experiments in mice. And
most importantly, these findings have major potential implications for public health.
Figure 4-3: Proposed relationship between perinatal obesity and inflammation and
diabetes risk
88
As mentioned above, obesity is a major risk factor for insulin resistance in
humans, yet there is growing evidence that many obese patients remain insulin
sensitive and this distinction may be due to differences in adipose tissue inflammation
(4, 7). The prevalence of obesity in adults is exceedingly high and begins from a very
early age (20, 21). This means that there is already a high population exposure to
current and developmental obesity. Therefore, it is essential to confirm the relevance of
this phenomenon in humans, and if such confirmation is attained, perinatal nutrition will
be a critical period for intervention. Without more mechanistic data available, prudent
recommendations for public health officials would be to emphasize the importance of
normal pre- and gravid weight gain, in addition to monitoring early postnatal growth of
the offspring. Future work in this animal model will help to identify potential targeted
interventions such as probiotics and other therapeutics that could supplement
behavioral interventions. And while the deterministic quality of the perinatal environment
may be somewhat discouraging, successful interventions may be equally deterministic
for improving the duration and quality of life for millions of patients.
89
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Abstract (if available)
Abstract
The prevalence of overweight and obesity has increased in all ages, including neonates and adolescents. Childhood obesity is complicated by insulin resistance, and understanding the pathophysiology of this link may help alleviate the increased diabetes risk in this population. Chronic low‐grade inflammation is an important cause of insulin resistance, and may be driving obesity‐associated insulin resistance in children. Adipose tissue is central to the inflammatory phenotype, where adipocytes and recruited macrophages produce inflammatory cytokines that directly impair insulin signaling. The purpose of this dissertation is to examine the relationships between obesity, inflammation, and diabetes risk during periods of development. ❧ Previous studies have shown that obese children have increased inflammatory biomarkers, but it is unclear if inflammation itself is associated with metabolic outcomes in these individuals. In this dissertation, we report that most circulating cytokines actually decreased during the adolescent period. Some of these cytokines were associated with a greater fall in insulin sensitivity during puberty. There were no associations with β-cell function. Changes during very early development may have a more profound impact on inflammation. ❧ Perinatal nutrition is known to have a lasting impact on adult metabolism and disease risk, including sensitization to obesity‐induced insulin resistance. Using an animal model of early postnatal over nutrition, we report that rapid early weight gain did not cause adipose tissue inflammation in weanling pups. However, perinatal over nutrition greatly exacerbated obesity‐induced adipose tissue inflammation, ectopic fat deposition, and insulin resistance in adulthood. ❧ This dissertation concludes by summarizing the data presented within and proposing several prospective experiments, and discusses the hypothesis that obesity‐induced inflammation contributes relatively little to insulin resistance at younger ages, but that its contribution gradually increases in adulthood. In addition, while the contemporaneous relationships between obesity, inflammation, and insulin resistance during childhood may be weak, very early life obesity appears to critically determine the inflammatory, and therefore metabolic, phenotype of adult obesity.
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Asset Metadata
Creator
Kayser, Brandon David
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Core Title
Metabolic consequences of obesity-associated inflammation during puberty and perinatal development
School
College of Letters, Arts and Sciences
Degree
Doctor of Philosophy
Degree Program
Integrative and Evolutionary Biology
Publication Date
07/07/2014
Defense Date
05/06/2014
Publisher
University of Southern California
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Tag
Inflammation,OAI-PMH Harvest,obesity,perinatal programming
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Donovan, Casey D. (
committee chair
), Bouret, Sebastien (
committee member
), Goran, Michael (
committee member
), Watts, Alan G. (
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bkayser@usc.edu,brandonkayser@gmail.com
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