This Thesis Has Been Approved by the Honors Tutorial College and Department of Biological Sciences

Home , Bovine somatotropin

This thesis has been approved by

The Honors Tutorial College and Department of Biological Sciences

______

Dr. Darlene Berryman

Professor, School of Applied Health Sciences and Wellness

College of Health Sciences and Professions

Thesis Adviser

______

Dr. Soichi Tanda

Director of Studies, Honors Tutorial College

Biological Sciences

______

Jeremy Webster

Dean, Honors Tutorial College

THE EFFECT OF GROWTH HORMONE ON THE MACROPHAGE CONTENT

OF DIFFERENT ADIPOSE TISSUE DEPOTS

A Thesis

Presented to

The Honors Tutorial College

Ohio University

______

In Partial Fulfillment

Of the Requirements for Graduation

From the Honors Tutorial College

With the Degree of

Bachelor of Science in Biological Sciences

______

Rachel D Munn

June 2011

Table of Contents

Acknowledgements…………………………………………………3 Abstract……………………………………………………………...4 Introduction…………………………………………………………6 Adipose Tissue………………………………………………6 Adipose Tissue Depots……………………………………...7 Obesity………………………………………………………11 Inflammation………………………………………………..12 Macrophages………………………………………………..14 Physiological Function……………………………...14 Adipose Tissue Macrophages……………………….15 Growth Hormone……………………………………………18 Function……………………………………………..19 Growth Hormone and Macrophages………………..23 Growth Hormone and Adipose……………………...24 Transgenic Mouse Models…………………………………..26 Significance of Research…………………………………….29 Materials and Methods…………………………………………….30 Results……………………………………………………………….36 Discussion……………………………………………………………46 References……………………………………………………………55

Acknowledgements

This work was supported in part by the State of Ohio‟s Eminent Scholar

Program that includes a gift from Milton and Lawrence Goll, by the AMVETS, by the

Diabetes Research Initiative at Ohio University, by the Provost‟s Undergraduate

Research Fund, and by NIH grants DK075436, AG019899, AG031736. Additionally I would like to personally thank Dr. Darlene Berryman, Dr. John Kopchick, and everyone working in Dr. Kopchick‟s lab at Edison Biotechnology Institute for their continued assistance and support in completing this project. I cannot imagine a better group of people with whom to work. I would also like to thank Dr. Soichi Tanda for his support throughout the entirety of my undergraduate career and for his belief in my abilities as a student. Finally, I would like my family and friends for providing such a support network. I am forever grateful.

Abstract

The prominence of obesity has drastically increased during the last decades and is now approaching epidemic proportions. Obesity is highly associated with deleterious health conditions such as type 2 diabetes and atherosclerosis. The greatly increased amount of adipose tissue present in obese individuals exhibits a chronic, low-grade form of inflammation. This inflammation is hypothesized to be the underlying cause of the aforementioned obesity associated comorbidities. The source of this inflammation is thought to be a specific phenotype of macrophages, M1 macrophages, which infiltrate obese adipose tissue and secrete inflammatory cytokines as well as macrophage chemoattractants. Growth hormone drastically decreases the amount of fat mass by inducing lipolysis and prohibiting lipogenesis. Growth hormone also acts on macrophages; however, current research has yet to define the true effect.

The purpose of this study is to elucidate the effect of growth hormone on macrophages within adipose tissue.

This study uses three transgenic mouse models with varying levels of growth hormone signaling: bGH (bovine growth hormone), GHA (growth hormone antagonist), and GHR-/- (growth hormone receptor knockout). Two adipose tissue depots were dissected from mice of all three genotypes as well as wild type controls. mRNA expression analysis was performed on whole adipose tissue, via PCR Super

Arrays. The expression of several macrophage markers was measured to determine the macrophage content and phenotype within adipose tissue.

The results obtained in this study showed no significant effect of growth hormone on the macrophage content of either adipose tissue depot studied. However, a differential content of macrophages between adipose tissue depots was seen, coinciding with previous research demonstrating the functional and metabolic differences between adipose tissue depots.

Introduction

I. Adipose Tissue

Adipose tissue is one of the many types of connective tissue. It is largely composed of adipocytes, or fat cells, but contains other cell types as well, including fibroblasts, macrophages, and endothelial cells. All of these cell types appear to be critical to the function of the tissue and may be responsible for certain molecules secreted by the tissue. Previously, it was thought that the only significant role of adipose tissue was to act as an energy reservoir via the storage of fat. Indeed, adipose functions as a dynamic reservoir to store or release energy depending on the needs of the body. If food and energy are plentiful, the body can deposit the excess energy in adipose tissue in the form of triglycerides (Sethi et al. 2007). During times of starvation or low energy, the body can access this energy by breaking down triglycerides into glycerol and free fatty acids, which are readily transported throughout the body (Sethi et al. 2007).

More recently, research has shown that adipose tissue has an additional function as an important endocrine organ secreting hormones such as adiponectin and leptin, as well as many others. Leptin functions as a metabolic signal of energy sufficiency, and as obesity is a state of over-nutrition, high circulating leptin levels are associated with obesity (Kershaw et al. 2004). On the other hand, high levels of adiponectin are associated with lean states and increased insulin sensitivity (Yamauchi et al. 2009). Thus, the endocrine function of adipose tissue varies according to the

6 metabolic state of the tissue. Like all hormones, adipose tissue derived hormones not only affect the tissue itself, but many other tissues and organs as well. For example, leptin has far reaching effects and can dramatically alter energy balance by increasing appetite and decreasing energy expenditure when circulating leptin levels are too low

(Kershaw et al. 2004). Equally, the dysfunction of adipose tissue, as in an obese or emaciated state, has far reaching effects on the body. For example, certain antiretroviral medicines used in the treatment of HIV can cause severe lipodystrophy, which is a deficiency in adipose tissue and is associated with metabolic dysfunction

(Kershaw et al. 2004). The effects of obesity are discussed in detail below.

II. Adipose Tissue Depots

There are two distinct types of adipose tissue known as brown and white adipose, which differ in anatomical location, morphology, and function (Casteilla et al.

2001). White adipose tissue is present far more abundantly than brown adipose; however, brown adipose tissue contains more vasculature than white adipose tissue, and brown adipocytes contain more mitochondria and possess the unique ability to produce heat (Casteilla et al. 2001). Brown adipose is most prominent in newborn mice, as well as other mammals (Cinti et al. 2007). However, it has recently been shown that adult humans also have brown fat and that the amount of brown fat present is inversely correlated with body mass index (BMI) (Cypess et al. 2009). This suggests a role for brown fat in adult metabolism, and thus there is much current interest in elucidating the specific function of brown fat in adults. The largest brown adipose depots are located in the interscapular and perirenal areas. Because this study only

7 focuses on white adipose tissue, the remaining review of literature will focus on exclusively white adipose tissue.

The white adipose depots can be simply classified as subcutaneous or visceral

(Casteilla et al. 2001). There is some inconsistency with regards to the use of the term

„visceral.‟ Some authors use visceral only to describe adipose tissue depots which drain into the portal vein, while others include all intra-abdominal depots in the visceral category. The view which categorizes intra-abdominal depots as visceral leads to an overly simplistic view of adipose tissue depots, as the true visceral and intra- abdominal depots have very distinct properties.

Adipose tissue is distributed regionally throughout the body. The subcutaneous depot is located superficially beneath the skin in both the anterior and posterior regions (Cinti 2007). The visceral depots are located in the abdominal cavity and, in mice, include the perigonadal, retroperitoneal, and mesenteric depots (Cinti 2007).

Using the strict definition of visceral, however, only the mesenteric depot is classified as visceral, while perigonadal and retroperitoneal are intra-abdominal depots. The perigonadal depot is connected to the ovaries in females and the epididymus in males.

The retroperitoneal depot is located behind each kidney, while the mesenteric depot connects the intestines. These depots, as well as other depots not analyzed in this study, can be viewed in Figure 1. As can be seen here, adipose is a very anatomically heterogeneous tissue.

Figure 1. Representative adipose tissue depots (Sackmann Sala, 2010). The names of the individual depots are as follows: A: deep cervical, B: anterior subcutaneous (interscapular, subscapular, axillo-toracic, superficial cervical), C: visceral mediastinic, D: visceral mesenteric, E: visceral retroperitoneal, F: visceral perirenal, periovaric, parametrial (females), perigonadal (males), and perivescical, G: posterior subcutaneous (corso-lumbar, inguinal, and gluteal). This figure is categorized using the broad categorization of visceral. Areas of brown and white fat are indicated via the respective colors in the schematic representation located on the right.

Adipose tissue is also functionally heterogeneous, as these different depots, particularly the subcutaneous and visceral depots, are known to be metabolically distinct (Wajchenberg et al. 2002). Visceral adipose is less responsive to the hormone insulin and more responsive to catecholamines and thus undergoes higher fatty acid turnover and lipolysis (Wajchenberg et al. 2002, Linder et al. 2003). Because visceral depots drain into the portal system, the increased fatty acids released directly affect the

9 liver, and thus have a more profound effect on the body. In addition, visceral adipose shows a larger increase in adipocyte size relative to subcutaneous adipose in obese mice (Gollisch et al. 2009), which is hypothesized to contribute to the insulin resistance within visceral adipose tissue. Visceral adipose depots are also known to produce more interleukin 6 (Il-6), an inflammatory molecule, and less leptin and adiponectin than subcutaneous adipose tissue (Wajchenberg et al. 2002). A study in obese humans shows that expression of phospholipid transfer protein (PLTP), a protein which functions in lipid redistribution, is higher in visceral adipose (Linder et al. 2003). Another human study found that levels of chemokine (c-c motif) receptor 2

(CCR2) and macrophage migration inhibitory factor (MIF) are both higher in visceral than in subcutaneous adipose (Alvehus et al. 2010). In addition, two macrophage markers (CD14 and CD163) show increased visceral expression. As a whole, increased adiposity within the visceral depots are more highly associated with adverse health conditions such as type 2 diabetes and atherosclerosis (Wajchenberg et al.

2002). However, subcutaneous adipose has been shown to contain significantly more adipogenic progenitor cells (Joe et al. 2009). The proliferation of these cells increases significantly in response to high fat in the subcutaneous region, but not visceral adipose tissue (Joe et al. 2009). In humans, subcutaneous adipose tissue was found to contain higher levels of adipsin, a protein involved in lipid turnover, relative to visceral adipose (Linder et al. 2003). Increased subcutaneous adipose has not been correlated with insulin resistance (Alvehus et al. 2010). Overall, it is important to

10 appreciate that adipose depots differ more than just by anatomical location; depots from various anatomical sites are also metabolically distinct.

III. Obesity

According to Karalis et al. (2009), obesity is the epidemic of our century.

Obesity is defined as an excess accumulation of body fat. Under obese conditions, adipose tissue is forced to store a large surplus of lipids. The tissue accomplishes this by undergoing cellular hypertrophy, the increase of cell volume, and by hyperplasia, the increase in cell number. Excess fat can be stored in the two main adipose tissue depots mentioned above, brown and white adipose.

Obesity is characterized by a state of chronic, low-grade inflammation, indicating a dysfunction in the molecular pathways that regulate inflammation as well as those regulating metabolism. The expression profile of adipose tissue during obesity is altered to a pro-inflammatory state, meaning the tissue secretes molecules that promote an inflammatory response. The relationship between obesity and chronic inflammation has been shown to be not only correlative but causative (Xu et al. 2003).

This condition is associated with an increased development of health problems including atherosclerosis, insulin resistance, and some types of cancers (Heilbronn et al. 2008). According to the Center for Disease Control and Prevention, obesity and the many associated metabolic abnormalities affect approximately 27% of the adult population in the United States; thus, research into these pathologies is critical to help treat this growing epidemic. Additional information regarding the underlying

11 physiology and molecular mechanisms responsible for the obesity induced inflammatory response is given in the following section entitled “Inflammation.”

IV. Inflammation

The inflammatory response is a non-specific immune response and can be induced by many physiological events, the most common being acute injury or infection. In the case of injuries, the inflammatory response assists in the healing process by including vasodilation, which increases blood flow and allows white blood cells to accumulate at the site of injury and fight any pathogens that may have entered the wound (Ferrero-Miliani et al. 2006).The inflammatory molecules of this response are released by cells resident to the particular tissue, such as macrophages, as well as immune cells which migrate to the site of injury in response to the initial inflammatory reaction.

The inflammatory response is normally self-limiting. However, the inflammation associated with obesity is chronic, low-grade, and functions in the disease pathologies mentioned above rather than the healing process. Because inflammatory molecules have short-lived effects, the chronic inflammation associated with obesity requires a constant secretion of inflammatory molecules. Interestingly, this inflammation is thought to be restricted to the adipose tissue itself (Goossens et al.

2008). In addition to their role in the acute inflammatory response to injury or infection, macrophages also reside within, and in some cases infiltrate, adipose tissue.

The distinct phenotypes of resident and infiltrating adipose tissue macrophages

(ATMs) will be discussed later in the section entitled “Adipose Tissue Macrophages.”

These infiltrating ATMs are considered to be key cells in the chronic inflammation associated with obesity, as they respond to inflammatory cytokines as well as secrete them (Ferrero-Miliani et al. 2006). The upregulation of inflammatory molecule expression in obesity include the cytokines tumor necrosis factor α (TNF-α), interleukin 6 (Il-6), and leptin (Goossens et al. 2008) as well as interleukin 1β (Il-1β) and macrophage chemoattractant protein 1 (MCP-1) (Zeyda et al. 2007). These inflammatory cytokines not only contribute to adipose inflammation but also inhibit insulin action in adipocytes, thus providing a possible mechanism for the insulin resistance commonly associated with obesity and inflammation (Zeyda et al. 2007).

The inflammatory state of adipose tissue is much increased in visceral adipose tissue as compared to subcutaneous adipose tissue, with visceral adipose showing increased expression of inflammatory molecules such as TNF-α, Il-6, and MCP-1

(Bourlier et al. 2009). In addition, macrophages have been shown to preferentially infiltrate visceral adipose tissue, which may provide a mechanism behind the observed increased inflammatory profile and thus the increased co-morbidities associated with increased visceral adiposity. (Bourlier et al. 2009). Specifically, the inflammation of visceral adipose has been shown to increase atherosclerosis in mice (Ohman et al.

2008) as well as type 2 diabetes and cardiovascular disease in humans (Alvehus et al.

2010).

In addition to macrophages and non-specific immune cells, adipose tissue is also home to T-cells, which function in cell mediated immunity. The resident

13 population of T-cells increases with obesity and is also thought to play a role in the observed chronic inflammation. T-cells located specifically in obese, visceral adipose have been shown to produce excessive amounts of pro-inflammatory molecules, such as those mentioned above (Ohman et al. 2008). Thus T-cells function alongside macrophages to increase adipose tissue inflammation, preferentially in visceral adipose tissue.

V. Macrophages a. Physiological Function

Macrophages are immune cells derived from the monocyte class of white blood cells. Monocytes differentiate into macrophages once they have traveled through the bloodstream and enter into a tissue. Macrophages are phagocytic cells that function in both innate and adaptive immunity. Innate immunity is a non-specific defense reaction against any foreign molecule, while adaptive immunity is a specified response to defend the body against a known pathogen. In addition to the phagocytosis of foreign particles, macrophages also secrete molecules that stimulate other immune cells, such as leukocytes. The variety of macrophage functions can be seen in Figure 3.

Many tissues have a fixed population of macrophages „stationed‟ there by the body to help prevent infection as well as perform the specific paracrine functions of that tissue.

These macrophages exist in addition to the circulating monocytes, which remain ready to fight infection at any time. This general information related to macrophages is provided by the following citation (Janeway et al. 2001).

14 b. Adipose Tissue Macrophages

Adipose tissue is one such tissue containing a fixed population of macrophages. The fixed, or resident, population of macrophages contributes to the heterogeneous nature of adipose tissue. Under normal physiological conditions, the macrophages residing in adipose tissue exhibit a specific phenotype, designated as

M2, and perform functions such as tissue remodeling (Pamir et al. 2009) and the uptake of particles such as apoptotic cells and other cellular debris. (Zeyda et al.

2007). These macrophages have an anti-inflammatory expression profile which is characteristically induced by Il-4 and Il-13 (Zeyda et al. 2007). Specifically within adipose tissue, resident and infiltrating macrophages are known to localize around apoptotic adipocytes to form what are termed „crown-like‟ structures and function to phagocytize lipids and pieces of the dead cell (Zeyda et al. 2007).

There is also a second macrophage phenotype that does not normally reside in adipose tissue. This new, infiltrating population of macrophages is recruited to adipose tissue and exhibits an entirely different phenotype, designated as M1. The M1 subtype of macrophages is responsible for secretion of the inflammatory molecules seen in obesity. In fact, the M1 phenotype macrophages have been identified as the primary source of a number of circulating pro-inflammatory molecules present in obesity

(Heilbronn et al. 2008). Thus, the macrophage content of adipose tissue and not the amount of adipose tissue may be the critical factor that links obesity to chronic inflammation. Numerous secretion products of M1 macrophages, such as TNF- α, are known to decrease insulin sensitivity in adipose tissue and thus directly affect the

15 dysfunction of adipose tissue. The M1 and M2 macrophage phenotypes can be distinguished based on expression profiles. The expression profiles of both M1 and

M2 macrophages have been well characterized and are summarized in Table 1.

Table 1. Summary of macrophage subtype gene expression profiles..Macrophage

Subtype

M1 M2 (infiltrating macrophages) (resident macrophages)

TNF-α (Weisberg et al. 2003) Ym-1 (Heilbronn et al. 2008) Tumor necrosis factor α induces apoptotic cell Chitinase 3-like-3 (known as Ym-1) has no death, inflammation, and inhibits tumorigenesis. currently known function, but it is secreted by alternatively activated macrophages.

MCP-1 (Menghini et al. 2007) Arg-1 (Mosser 2003) Monocyte chemotactic protein -1 recruits Arginase functions as an enzyme to remove monocytes, memory T cells, and dendritic cells to nitrogen and excrete it in the form of urea. sites of tissue injury, infection, and inflammation.

Il-1,6 (Menghini et al. 2007) Fizz-1 (Martinez et al. 2009) Interleukins 1 and 6 function as part of the Resistin (known as Fizz-1) functions in adipocyte inflammatory response to injury or infection. differentiation.

IFN- γ (Zeyda et al. 2007) Il-10 (Mosser 2003) Interferon-λ functions in both innate and adaptive Interleukin 10 is an anti-inflammatory cytokine immunity and has been indicated in a number of that also functions to enhance B cell survival, autoimmune diseases. proliferation, and antibody production. iNOS (Weisberg et al. 2003) Il-4,13 (Martinez et al. 2009) Nitric oxide synthase functions to produce nitric Interleukin 4 and 13 function to induce oxide and dilate blood vessels. differentiation of naïve T-cells.

It is well known that the number of macrophages in adipose increases during obesity in association with the development of the characteristic inflammation

(Weisberg et al. 2003), but why? Since the resident macrophages do not

16 characteristically secrete inflammatory cytokines (Weisberg et al. 2003), the number of M1 macrophages are likely responsible for the increase. Several cytokines have been indicated as being responsible for this increase in M1 macrophages (Weisberg et al. 2003). Macrophages are stimulated to adopt the M1 phenotype by the pro- inflammatory molecule IFN-γ (Zeyda et al. 2007). M1 macrophages are also activated by MCP-1, which is a pro-inflammatory, macrophage recruiting factor that has shown an increase in expression in earlier stages of obesity than other macrophage recruiting factors (Menghini et al. 2007). Interestingly, MCP-1 is secreted by both adipose tissue and macrophages, thus the recruitment and activation of macrophages are self- perpetuating processes. This suggests that elevation of MCP-1 expression may be an initial event in the recruitment and infiltration of M1 macrophages into obese adipose tissue. As shown in Figure 4, many other factors contribute to the infiltration of macrophages into obese adipose tissue including: hypertrophy, or increased cell size, hyperplasia, or increased cell number (Cinti et al. 2007), hypoxic conditions

(Heilbronn et al. 2008), and hormones such as leptin (Bourlier et al. 2009).

Figure 4. Proposed mechanisms of macrophage infiltration and insulin resistance in adipose tissue (Heilbronn et al. 2008).

VI. Growth Hormone

Growth hormone (GH) is a protein hormone with many complex functions including cellular growth and reproduction. It is produced by somatotrophs in the anterior pituitary gland and acts directly via a specific receptor on the cell surface and indirectly via stimulating the expression of a molecule called insulin-like growth factor 1 (IGF-1) (Mitchell et al. 2009). GH is a 191 amino acid, 22kDa protein hormone and is organized into four alpha helices. These alpha helices are important for binding to the GH receptor (GHR) (Baumann 2009). GH was first discovered in the 1950s as a treatment for children with growth hormone deficiency (GHD). GHD manifests itself in the short stature of affected individuals. When present in excess,

GH has the opposite affect and causes acromegaly (Clemmons et al. 2003). GH has also been used to improve athletic performance, as it increases lean muscle mass and decreases fat mass. This practice is strictly prohibited, but until recently a reliable test for its abuse was not available (Mitchell et al. 2009). a. Function

As stated previously, GH has independent effects. These effects are manifested via GH binding to its receptor and the subsequent signaling pathways. GH first binds to one molecule of the GHR, which subsequently induces receptor dimerization and activation of the signaling molecule, Janus kinase 2 (JAK2) (Wells et al. 1996). JAK2 is capable of activating a number of subsequent signaling molecules, however, the signal transducer and activator of transcription (STAT) 1, 3, and 5 are the most common. These signaling molecules travel into the nucleus in order to alter the expression of specific genes, as can be seen in Figure 6. However, some GH action is mediated by another endocrine molecule known as insulin-like growth factor 1

(IGF-1).

Figure 6. The GH signaling pathway (SABiosciences.com). Abbreviations: STAT-5: signal transducer and activator of transcription 5, SOCS-3: suppressor of cytokine signaling 3, GHR: growth hormone receptor, IGF-1: insulin-like growth factor 1, IGF-1R: insulin-like growth factor 1 receptor, IGFBP-3: insulin-like growth factor binding protein 3, ALS: acid-labile subunit. JAK2: janus kinase 2 (Walters & Griffiths 2009).

IGF-1 is a 70 amino acid protein and possesses a structure similar to insulin. It has significant endocrine functions as well as both autocrine and paracrine actions

(Laviola et al. 2007). Most IGF-1 in circulation is secreted by the liver in response to

GH and regulates cellular growth (Laviola et al. 2007). IGF-1 acts on many tissues including muscle, but in an autocrine manner, to stimulate proper proliferation and differentiation of the muscle cells (Laviola et al. 2007). IGF-1 binds to a specific receptor which is also capable of binding to insulin. In addition, the IGF-1 and insulin signaling pathways share many intracellular mediators giving IGF-1 insulin-like properties (Laviola et al. 2007). IGF-1 also shares many signaling pathways with GH which combined account for as much as 34% of post natal growth in mice (Lupu et al.

2001).

The combined actions of GH and IGF-1 are known as the “dual effector theory,” which was first coined by Green et al. in 1985. Prior to the development of this theory, it was thought that all GH action was mediated via IGF-1. Morikawa et al.

(1982) discovered that GH alone could stimulate the differentiation of pre-adipocytes into adipocytes, thus necessitating the development of a new theory. It has been shown that daily doses of GH or IGF-1 can act to improve protein synthesis in humans, however the best results are obtained when GH and IGF-1 are administered together

(Jenkins et al. 1996), thus exemplifying the combined actions of GH and IGF-1.

Although GH and IGF-1 have many combined actions, they do not always have the same effect. One of the most fundamental differences between GH and IGF-1 is that

GH has virtually no role in prenatal growth and development, while IGF-1 is

21 absolutely required for fetal development (Baker et al. 1993). Also, relevant to this thesis and as implied above, GH and IGF-1 have been shown to have differing effects on adipose tissue. GH increases lipolysis in adipose tissue, while IGF-1 may even reduce lipolysis in adipose tissue (Simpson et al. 2004). IGF-1 has also been shown to induce differentiation of preadipocytes into mature adipocytes (Louveau et al. 2004).

A simplified view of the interactions between GH, IGF-1 and the tissues they affect can be seen in Figure 7.

Figure 7. Actions of GH and IGF-1 on sensitive tissues. (Kopchick & Andry, 2000).

22 b. GH and Macrophages

GH has been shown to have macrophage activating properties (Edwards et al.

1992) and acts via the growth hormone receptor (GHR) present on macrophages. GH is a positive regulator of the pro-inflammatory molecule MCP-1, which is secreted by both adipose tissue and macrophages and highly associated with macrophage infiltration into adipose tissue (Fasshauer et al. 2004). However, these results are contradicted by research which shows that patients with growth hormone deficiency have higher basal levels of the inflammatory molecules TNF- α and IL-6. These levels are returned to normal after growth hormone replacement therapy (Serri et al. 1999).

In this case, growth hormone decreases inflammation by decreasing the amount of pro-inflammatory molecules secreted by M1 macrophages.

Although prior research remained inconclusive, a new study, conducted by Lu et al. (2010), finally provided a more clear view of the effect of GH on macrophages.

This study demonstrated that GH increases the proliferation and alters the morphology of macrophages in cell culture. Specifically, these macrophages showed an increase in uptake and degradation of low-density lipoprotein in a dose dependent manner following GH treatment. GH treated macrophages showed an altered expression profile including a decrease in the pro-inflammatory molecule Il-1β and a decrease in phosphorylated NF-kB. NF-kB is a transcription factor that regulates the expression of several pro-inflammatory cytokines including Il-1β, Il-2, TNF-α, and Il-12 (Lu et al.

2010). These GH induced alterations in macrophage expression profile could have significant effects on adipose tissue, such as increasing adipogenesis and decreasing

23 inflammation. In addition to possessing the GHR, macrophages can also synthesize

GH (Weigent et al. 1991 and Hattori 2009). Macrophage-synthesized GH acts primarily in an autocrine/paracrine manner on macrophages and adipose tissue(Lu et al. 2010). Macrophage-synthesized GH can act in an endocrine manner, but contributes very little to the pituitary-synthesized GH. Due to macrophages being present in adipose tissue, GH can act on adipose tissue indirectly through the change in the macrophage expression profile. GH can also act directly on adipose tissue via the GHR present on adipocytes and macrophages. c. Growth Hormone and Adipose Tissue

Growth hormone has a profound effect on the body as it has the capability to decrease the amount of fat mass and increase the amount of lean mass in mice

(Berryman et al. 2004). Similar effects have been observed when obese humans are treated with recombinant human growth hormone (rhGH). Subjects show a decrease in fat mass, and in particular visceral adiposity, as well as an increase in lean body mass

(Mekala et al. 2009). Obese humans have been characterized as having decreased GH expression (Scacchi et al. 1999).

GH asserts this effect on adipose tissue via enhancing lipolytic activity and reducing triglyceride accumulation (Johannsson et al. 1997), and can act directly on the adipocytes as they express the GHR. GH increases lipolysis, particularly in visceral adipose tissue, by increasing hormone sensitive lipase (HSL) activity as well as decreases glucose uptake into adipose tissue, most likely by down-regulating

24 expression of the glucose transporter-1 (GLUT-1) (Tai et al. 1990). HSL functions to hydrolyze fatty acids from stored triglycerides. Lipoprotein lipase (LPL) activity in adipose tissue is also reduced in response to GH (Richelsen et al. 2000). LPL activity is known to be increased due to obesity, and may play a role in increasing adiposity

(Richelsen et al. 2000). GH has also been shown to induce the differentiation of preadipocytes into mature adipocytes via increasing expression of peroxisome proliferator-activated receptors (PPARγ) (Kawai et al. 2007). This causes an increase in adipocyte number, but a decrease in adipocyte volume. This is an interesting point, as adipocyte hypertrophy has been shown to be associated with increased adipose tissue inflammation. Thus, GH may indeed function to reduce inflammation in adipose tissue.

In addition to adipose-specific effects, GH exerts an effect on circulating levels of adipokines such as adiponectin and leptin; however, the results have remained inconclusive as to the precise effect (Berryman et al. 2004, Nilsson et al.

2005). Some studies have shown that in humans GH causes increased adiponectin and decreased leptin (Silha et al. 2003); while others have shown that GH represses adiponectin expression in mice (Berryman et al. 2004).

These effects are directly visible in individuals with GH excess or deficiency.

GH deficiency is marked by an obese phenotype with abnormally large adipocytes.

GH replacement therapy has been shown to decrease fat mass and adipocyte size in these patients (Rosenbaum et al. 1992). However, chronic exposure to excess GH induces insulin resistance in adipose tissue in part by suppressing insulin induced

25 glucose transport via the GLUT1 and GLUT4 transporters (Goodman et al. 1990). GH also increases circulating free fatty acids (FFA), which impair insulin action

(Vijayakumar et al. 2009) and increases expression of resistin. High circulating resistin levels have been shown to correlate with insulin resistance (Delhanty et al.

2002).

VII. Transgenic Mouse Models

There are many mouse models with varying levels of growth hormone signaling which have been key in elucidating the multitude of functions performed by

GH. Three of these models will be used in this project: bGH, GHA, and GHR-/-, whose phenotypes can be seen in Table 2 and Figure 8. bGH, or bovine growth hormone, mice are transgenic mice expressing the gene for bovine growth hormone and thus have elevated levels of growth hormone. These mice are larger than wild type mice, with a greater proportion of lean mass to fat mass. They exhibit increased insulin resistance, resistance to diet induced obesity, decreased levels of IGF-1, and a shortened lifespan (Palmer et al. 2009). GHA, or growth hormone antagonist, mice express an antagonistic protein that acts to reduce growth hormone signaling

(Coschigano et al. 2003). They have a very similar phenotype to GHR-/-, or growth hormone receptor knock-out mice, which inhibits growth hormone signaling via disrupting the gene coding for GHR (Coschigano et al. 2003). GHA and GHR-/- mice are smaller than wild type mice, obese, sensitive to insulin, exhibit reduced IGF-1 levels, and have an extended lifespan (Coschigano et al. 2003, Berryman et al. 2004).

However, GHR-/- and GHA mice differ in their relative glucose and insulin levels.

GHR-/- mice show mildly reduce glucose levels and markedly reduced insulin levels.

GHA mice also show mildly reduced glucose levels, but show no decrease in insulin levels (Coschigano et al. 2003). In addition, GHA mice exhibit increased concentrations of GH, GHR, and growth hormone binding protein (GHBP), while

GHR-/- mice exhibit only an increase in GH and an absence of GHR and GHBP

(Berryman et al. 2004).

These mice also exhibit distinct adipose tissue profiles. Overall, GHR-/- mice have a greater percentage of body fat than WT mice (Berryman et al. 2009). GHA mice also exhibit a greater percentage of body fat than WT and even GHR-/- mice

(Berryman et al. 2004). Both GHR-/- and GHA mice exhibited a significant increase in adipocyte size relative to controls (Li 2006). Interestingly, in both the GHR-/- and

GHA mouse models, the subcutaneous adipose tissue depots were preferentially enlarged in comparison to intra-abdominal and visceral adipose tissue depots, suggesting a unique effect of GH on the distinct depots (Berryman et al. 2004). In contrast, both subcutaneous and visceral adipose tissue depots in bGH mice are significantly smaller than in WT mice (Palmer et al. 2009), giving bGH mice a lower percentage of body fat (Berryman et al. 2004). In congruence, bGH mice also have significantly smaller adipocytes than WT mice (Li 2006). Due to their varying levels of GH signaling, these mouse models have, and will continue to, allow researchers to uncover the effects of GH on various physiological processes.

Table 2. Comparison of growth hormone altered mouse models.

Phenotypes of the Transgenic Mice

GH IGF-1 Body Insulin Lifespan Body Signaling Levels Composition Resistance Size

bGH Increased Increased Lean Resistant Decreased Large

GHA Decreased Decreased Obese Sensitive Increased Small

GHR-/- Absent Decreased Obese Sensitive Increased Very Small

Figure 8. Mouse models used in this thesis. From left to right: bGH, WT,

GHA, GHR-/-.

Significance of Research

The aim of this study is to determine the effect of GH on the macrophage content of different adipose tissue depots. As detailed in the above introduction, macrophages within adipose tissue are thought to be the source of the obesity associated inflammation, which in turn is thought to be the underlying cause of obesity associated deleterious health conditions, namely type 2 diabetes and atherosclerosis.

As GH has previously been shown to affect macrophage morphology and activation as well as adipose tissue, uncovering the specific effects of GH on macrophages within adipose tissue may expose or deny GH as a possible therapeutic agent in terms of obesity associated inflammation.

Materials and Methods

Tissues

This study examines the inguinal (subcutaneous) and epididymal (intra- abdominal) adipose tissue of mice of three genotypes: bGH, GHR-/-, and GHA, as well as their littermate controls. Tissues utilized were obtained from three previously completed studies (Palmer et al. 2009, Berryman et al. 2009, Magon 2009). This study analyzes the adipose tissue of 6 male mice of each genotype as well as their littermate controls; however, the studies referenced contained a greater number of mice of both male and female genders. Due to the varying life expectancies of these mouse models, the mice of each group were of different ages upon sacrifice. The short-lived bGH mice and their corresponding littermates were 14 months old while the longer lived

GHA mice were 20 months of age, and the GHR-/- mice were 24 months old at the time of dissection. Immediately prior to dissection, each mouse was sacrificed via cervical dislocation. During dissection, many tissues were removed; however, only inguinal and epididymal adipose tissue are analyzed in this study. All tissues were weighed and flash-frozen in liquid nitrogen and subsequently stored at -80°C until processing.

Body Weight and Composition

As reported previously, the total body weight of all mice was measured at multiple time points throughout their lifespan (Palmer et al. 2009, Berryman et al.

2009, Magon 2009). The body composition of all mice was also measured throughout

30 their lifespan by NMR using a Bruker Minispec (The Woodlands, TX). The measurements taken to determine body composition were: lean mass, fat mass, and fluid mass. Tissue weights are reported as normalized to whole body weight.

RNA isolation

RNA was isolated from 200mg of whole adipose tissue from the subcutaneous and epididymal depots using a phenol/chloroform extraction method using RNA Stat-

60 (Tel-Test Inc, Friendswood, TX) as described previously (Chomczynski et al.,

1987). A ratio of 1mL of RNA Stat-60 to 0.1mg of adipose tissue was used. The samples were mechanically homogenized in RNA Stat-60 prior to completion of the chloroform extraction. Following isolation, the samples were treated with the RNeasy

Mini Kit and the RNase-Free DNase Set (Qiagen, Valencia, CA) to further purify and increase the RNA quality. After completing the isolation protocol, the RNA was stored in RNase free H2O (Qiagen, Valencia, CA ) at -80°C. RNA concentration and quality were then analyzed using a NanoDrop Spectrophotometer (NanoDrop

Products, Wilmington, DE) followed by the Agilent 2100 Bioanalyzer (Agilent

Technologies, Foster City, CA). RNA quality was assessed by the RNA integrity number (RIN), which is a measure of RNA degradation. According to SABiosciences protocol, RNA with a RIN of greater than 7.0 is of high quality and suitable for subsequent use in cDNA synthesis and PCR. Only RNA meeting this standard was used to synthesize cDNA with the RT First Strand Kit (SABiosciences, Frederick,

MD) as described by Kerber et al. (2008).

PCR Array

Custom PCR arrays from SABiosciences (Frederick, MD) were used to determine RNA expression levels of 12 genes, according to the company protocol.

The cDNA generated from isolated RNA is utilized by these arrays to measure gene expression. The custom PCR arrays are manufactured with a primer for one of the 12 chosen genes inside each well. The plate design allowed for 8 samples to be analyzed per plate and can be seen below in Table 3.

Included on the custom designed plates are: three housekeeping genes (hprt1 - hypoxanthine phosphoribosyltransferase 1, Tfb2m - transcription factor B2, mitochondrial, gapdh - Glyceraldehyde 3-phosphate dehydrogenase), one general macrophage marker (emr1 - EGF-like module-containing mucin-like hormone receptor-like 1), four pro-inflammatory markers (Tnf – tumor necrosis factor, Il6 – interleukin 6, Il1b – interleukin 1-beta, Ccl2 – chemokine (C-C motif) ligand 2, the receptor for MCP-1 - monocyte chemoattractant protein-1), and four anti- inflammatory markers (Arg1 – arginase 1, Il10 – interleukin 10, Retnla – resistin-like alpha, Chi313 – chitinase 3-like-3).

Table 3. Plate setup for each custom PCR Array.

A Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 B Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 C Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 D Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 E Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 F Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 G Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 H Tfb2m Ccl2 Tnf Il6 Il1b Arg1 Il10 Retnla Chi3l3 Emr1 Hprt1 Gapdh 1 2 3 4 5 6 7 8 9 10 11 12 Abbreviations: Tfb2m: transcription factor B2, mitochondrial; Ccl2: Tnf: tumor necrosis factor; Il6: interleukin 6; Il1b: interleukin 1 beta; Arg1: arginase 1; Il10: interleukin 10; Retnla: resistin-like alpha Chi3l3: chitinase 3-like-3; Emr1: EGF- like module-containing mucin-like hormone receptor-like 1, also known as F4/80; Hprt1: hypoxanthine phosphoribosyltransferase 1; Gapdh: Glyceraldehyde 3- phosphate dehydrogenase.

These plates were analyzed using qRT-PCR using the Bio-Rad iCycler iQ Real

Time PCR Detection System (Bio-Rad, Hercules, CA) in conjunction with SYBR

Green master mix (SABiosciences, Frederick, MD). SYBR Green master mix contains the necessary enzymes for PCR to take place, as well as a dye that allows the machine to visualize the amplified DNA. The collected data are in the form of Ct values, which are a logarithmic measure of expression and must be converted to a linear form in order to allow comparisons to be made. To accomplish this, data were normalized to the chosen housekeeping genes and analyzed using the delta-delta Ct method (Livak et al. 2001). The delta-delta Ct method uses the following equations:

(1) Target Gene Ct – Housekeeping Gene Ct = Delta Ct

(2) Delta Ct – Max(all Delta Ct values) = Delta-delta Ct

(3) 2^(-Delta-delta Ct) = Relative Expression

Housekeeping genes (HKGs) are genes known to be consistently expressed in a given tissue. Thus, the relative expression of the genes of interest can be determined by comparing their expression to that of the HKGs. The relative expression levels determined for each genotype, bGH, GHA, and GHR-/-, were compared to the relative expression levels in their wild type counterparts, thus allowing us to determine the effect of varying levels of growth hormone on expression of the chosen target genes.

Before expression data can be normalized to the housekeeping gene expression, the expression stability of the HKGs must be determined. BestKeeper©

Software was used to analyze each of the three HKGs, gapdh, tfb2m, and hprt1.

BestKeeper© Software uses repeated pair-wise regression analysis to determine if the

HKGs are indeed stably expressed across the control and experimental treatments.

BestKeeper© Software determined that gapdh was the most stable HKG across all three genotypes of mice (bGH, GHA, and GHR-/-), and thus gapdh was solely used for the normalization of our target gene expression data.

Statistical Analysis

Each genotype of mice, bGH, GHA, and GHR-/- were analyzed only with respect to their WT controls. No comparisons were made between groups as the mice in each group were of different ages at the time of sacrifice. Statistical analysis was

34 performed using SPSS 14.0 (Somers, NY). Student‟s T-Tests were performed on the body weight and body composition data to determine significance. In this analysis, the body weight and composition data for each genotype was compared solely to their respective WT controls to determine a significant effect of genotype. Two-way

ANOVA tests were performed on the tissue weight and expression data using the dependent variables of genotype (transgenic vs. wild type) and adipose tissue depot

(epididymal vs. subcutaneous). In these analyses, comparisons were also made solely between each genotype and their respective WT controls; however, an effect of depot was also analyzed in addition to an effect of genotype. For the gene expression data, data points with Ct values over 35 were excluded from analysis, as Ct values this high represent a very low level of expression and contain a higher degree of error.

Expression data are reported as relative expression values ± SEM, with the WT epididymal depot set as 1. Setting the WT epididymal depot for all transgenic mouse groups creates a reference point to help visualize the effects of GH signaling on the subcutaneous depots relative to the epididymal depots.For all presented values, the standard error of the mean (SEM) was calculated using Microsoft Excel. Results were considered significant when p < 0.05. Body composition and tissue weight data are reported ± SEM.

Results

Body Weight and Composition

The body weights and composition of each genotype, bGH, GHA, and GHR-/-, was measured across the entire lifespan of each group (Palmer et al. 2009, Berryman et al. 2009, Magon 2009). Only the final measurements taken prior to sacrifice for the select mice analyzed in this thesis are reported here in Figures 9 and 10. bGH mice have a significantly increased body weight and significantly decreased percent body fat relative to WT controls. GHA mice do not have a significant difference in body weight, but do have a significant increase in percent body fat relative to WT controls.

GHR-/- mice have a significantly decreased body weight, while still having a significantly increased percent body fat relative to WT mice.

Figure 9. Body weight. Body weight of (A) bGH, (B) GHA, and (C) GHR-/- mice. Shown are means ± SEM. N=6 for all groups. A significant difference was seen for (A) bGH and (C) GHR-/-, p<0.0, but not for (B) GHA.

Figure 10. Percent Body Fat. Percent body fat of (A) bGH, (B) GHA, and (C) GHR-/- mice. Percent body fat is calculated as total fat mass relative to total body weight (g fat mass/g body weight). Shown are means ± SEM. N=6 for all groups. A significant difference between the transgenic mice and wild type mice was seen for all three genotypes p<0.05.

Adipose Tissue Depots Weight

The weights of subcutaneous (inguinal) and epididymal adipose tissue depots are reported here both in absolute tissue weight and tissue weight normalized to body weight, Figure 11, and the respective P-values can be seen in Table 4 and Table 5. bGH mice have significantly decreased amounts of adipose tissue both in absolute weight and relative to body weight in both subcutaneous and epididymal adipose tissue depots as compared to WT mice. In contrast, GHA mice show a significant increase in both absolute and relative weight of the subcutaneous adipose tissue depot, but no significant change in the epididymal depot. GHR-/- mice show a similar trend; however, the significant increase in subcutaneous adipose tissue was only observed relative to body weight and not in absolute weight.

Figure 11. Adipose Tissue Depot Weights. Subcutaneous (SubQ) and epididymal (Epi) adipose tissue depot absolute weights for (A) bGH, (C) GHA, and (E) GHR-/- mice with WT controls. Adipose tissue depot weights normalized to body weight (g tissue/g body weight) for (B) bGH, (D) GHA, (F) GHR-/- mice with WT controls. Shown are means ± SEM. N=6 for all groups.

Table 4. Results of Two-Way ANOVA for the absolute tissue weights. Values in bold are significant.

Interaction of Mouse Model Genotype Depot Genotype X Depot bGH F(1,12)=13.684 F(1,12)=8.510 F(1,12)=0.006 P=0.001 P=0.009 P=0.937 GHA F(1,12)=11.936 F(1,12)=0.530 F(1,12)=14.535 P=0.003 P=0.475 P=0.001 GHR-/- F(1,12)=0.00 F(1,12)=0.066 F(1,12)=5.090 P=0.984 P=0.800 P=0.037

Table 5. Results of Two-Way ANOVA for the normalized tissue weights. Values in bold are significant.

Genotype Depot Interaction of Mouse Model Genotype X Depot bGH F(1,12)=24.961 F(1,12)=10.774 F(1,12)=0.186 P=0.000 P=0.004 P=0.671 GHA F(1,12)= 10.041 F(1,12)= 0.669 F(1,12)= 6.552 P=0.05 P=0.414 P=0.020 GHR-/- F(1,12)=8.270 F(1,12)=1.444 F(1,12)=8.270 P=0.01 P=0.245 P=0.021

Expression data; bGH mice

A two-way factorial ANOVA showed no significant differences for the main effect of genotype or depot, or the interaction genotype x depot (p>0.05). The relative expression data can be seen in Figure 12, and the individual p-values can be seen in

Table 6.

Figure 12. Macrophage marker expression data for bGH mice. (A) F4/80, a general macrophage marker and M1 markers epididymal depot. (B) M2 markers, epididymal depot. (C) F4/80 , a general macrophage marker and M1 markers, subcutaneous depot. (D) M2 markers, subcutaneous depot. No significant results.

Table 6. Results of Two-way ANOVA for the expression data of bGH mice. Values in bold are significant. bGH Interaction of Gene Genotype Depot Genotpye X Depot F4/80 F(1,12)=1.019 F(1,12)=0.911 F(1,12)=0.871 P=0.325 P=0.351 P=0.362 Ccl2 F(1,12)=1.150 F(1,12)=0.858 F(1,12)=0.843 P=0.296 P=0.365 P=0.370 Tnf F(1,12)=0.544 F(1,12)=0.916 F(1,12)=0.545 P=0.471 P=0.352 P=0.470 Il1-β F(1,12)=0.850 F(1,12)=1.069 F(1,12)=0.690 P=0.370 P=0.316 P=0.418 Arg1 F(1,12)=2.095 F(1,12)=2.186 F(1,12)=1.834 P=0.167 P=0.159 P=0.194 Il10 F(1,12)=0.475 F(1,12)=2.861 F(1,12)=0.632 P=0.500 P=0.109 P=0.437 Retnla F(1,12)=1.083 F(1,12)=0.996 F(1,12)=1.135 P=0.310 P=0.330 P=0.299 Chi3l3 F(1,12)=1.386 F(1,12)=1.417 F(1,12)=1.423 P=0.257 P=0.252 P=0.251

Expression Data; GHA mice

A two-way factorial ANOVA revealed significant differences in macrophage marker expression between depots for the following genes: F4/80 and Retnla (p<0.05);

Tnf, Il1-β, Arg1, and Il-10 (p<0.01). No significant differences were observed for main effects of genotype or the interaction between genotype and depot. The relative expression data can be seen in Figure 13, and the individual p-values can be seen in

Table 7.

Figure 13. Macrophage marker expression data for GHA mice. (A) F4/80, a general macrophage marker and M1 markers, epididymal depot. (B) M2 markers, epididymal depot. (C) F4/80, a general macrophage marker and M1 markers, subcutaneous depot. (D) M2 markers, subcutaneous depot. Significant differences were seen between Epi and SubQ depots, but not genotype. P<0.05 for Retnla and F4/80. P<0.01 for Rnf, Il1-β, Arg1, and Il10.

Table 7. Results of Two-way ANOVA for the expression data of GHA mice. Reported as P values. GHA Gene Interaction of Genotype Depot Genotype X Depot F4/80 F(1,12)=2.373 F(1,12)=6.214 F(1,12)=1.206 P=0.141 P=0.023 P=0.287 Ccl2 F(1,12)=1.776 F(1,12)=0.877 F(1,12)=0.001 P=0.199 P=0.361 P=0.978 Tnf F(1,12)=4.222 F(1,12)=27.586 F(1,12)=1.357 P=0.074 P=0.001 P=0.278 Il1-β F(1,12)=0.103 F(1,12)=14.266 F(1,12)=0.161 P=0.757 P=0.007 P=0.700 Arg1 F(1,12)=2.057 F(1,12)=19.926 F(1,12)=2.217 P=0.177 P=0.001 P=0.162 Il10 F(1,12)=2.385 F(1,12)=23.683 F(1,12)=2.470 P=0.146 P=0.000 P=0.140 Retnla F(1,12)=0.392 F(1,12)=6.073 F(1,12)=0.480 P=0.539 P=0.024 P=0.497 Chi3l3 F(1,12)=0.002 F(1,12)=5.078 F(1,12)= - P=0.969 P=0.059 P= -

Expression data; GHR-/- mice

A two-way factorial ANOVA showed no significant differences for the main effect of genotype, depot, or the interaction of genotype x depot (p>0.05). The relative expression data can be seen in Figure 14, and the individual p-values can be seen in

Table 8.

Figure 14. Macrophage marker expression data for GHR-/- mice. (A) F4/80, a general macrophage marker and M1 markers, epididymal depot. (B) M2 markers, epididymal depot. (C) F4/80, a general macrophage marker and M1 markers, subcutaneous depot. (D) M2 markers, subcutaneous depot. No significant results.

Table 8. Results of Two-way ANOVA for the expression data of GHR-/- mice. Values in bold are significant. GHR-/- Interaction of Gene Genotype Depot Genotype X Depot F4/80 F(1,12)= F(1,12)= F(1,12)= P=0.446 P=0.612 P=0.462 Ccl2 F(1,12)=1.773 F(1,12)=0.383 F(1,12)=0.706 P=0.200 P=0.544 P=0.412 Tnf F(1,12)=0.449 F(1,12)=1.483 F(1,12)=0.553 P=0.511 P=0.239 P=0.467 Il1-β F(1,12)=0.987 F(1,12)=0.011 F(1,12)=0.089 P=0.336 P=0.918 P=0.769 Arg1 F(1,12)=1.462 F(1,12)=0.097 F(1,12)=0.044 P=0.247 P=0.760 P=0.836 Il10 F(1,12)=4.063 F(1,12)=3.774 F(1,12)=3.831 P=0.072 P=0.081 P=0.079 Retnla F(1,12)=1.987 F(1,12)=0.020 F(1,12)=0.000 P=0.174 P=0.889 P=0.988 Chi3l3 F(1,12)=0.016 F(1,12)=0.214 F(1,12)=1.456 P=0.899 P=0.649 P=0.242

Discussion

The purpose of this study was to elucidate the effect of growth hormone on the macrophage content within adipose tissue. Additionally, this study sought to identify the phenotype of the macrophages, either M1 or M2, within adipose tissue in response to GH. The methods used employed the measurement of mRNA levels of several known macrophage markers in mice with differing levels of GH signaling. As adipose tissue is quite heterogeneous, two different adipose tissue depots were examined.

Effect of GH

The extreme effect of growth hormone on adipose tissue is well known. GH levels have consistently been shown to be inversely correlated with adiposity. Mice with excess GH signaling, such as the bGH mice used in this study, are known to have significantly decreased fat mass (Frick et al. 2001, Berryman et al. 2004, Olsson et al.

2005, Palmer et al. 2009) than do wild type mice; whereas mice with decreased GH signaling, such as the GHA and GHR-/- mice used in this study are known to have indreased fat mass (Knapp et al. 1994, Berryman et al. 2004, Berryman et al. 2009,

Magon 2009, Egecioglu et al. 2006, Bonkowski et al. 2006). The results obtained in this thesis support this data, as the body composition analysis showed that the bGH group exhibited significantly decreased fat mass while the GHA and GHR-/- exhibited significantly increased fat mass relative to WT controls. These results also show that

GH excess, as seen in the bGH mice, similarly affects both subcutaneous and intra- abdominal (epididymal) adipose tissue, which contradicts prior findings demonstrating that GH has a more prominent effect on intra-abdominal adipose (Flint et al. 1993,

Bengtsson et al. 1993). The apparent descrepancy could be due to species differences since the results obtained by Flint et al. are from rats, while the results obtained by

Bengtsson et al. are from humans. On the other hand, the results of this thesis support data obtained by List et al. (2009) showing that all adipose tissue depots analyzed

(subcutaneous, epididymal, retroperitoneal, and mesenteric) were dramatically, but similarly affected by GH excess induced by GH injection. GH injection studies provide means for examining GH excess that is different than the transgenic bGH mice used in this study. bGH mice represent a model for endogenous excess GH, which is more representative of pathological conditions, such as acromegaly. GH injection studies represent a model for exogenous excess GH, which is more directly applicable to developing possible therapeutic treatments.

On the contrary, decreased GH signaling was only shown to have a significant effect on subcutaneous adipose tissue and not epididymal. These results support data obtained in previous studies examining both GHA mice (Berryman et al. 2004) and

GHR-/- mice (Liu et al. 2004, Berryman et al. 2004, 2006, 2009) which also showed that the subcutaneous depot was most affected by decreased GH signaling in both mouse models. Two recent theses conducted at Ohio University (Magon 2009, Yang

2010) studying the GHA mouse model also showed a preferential accumulation of fat in the subcutaneous depot. However, a study conducted by Pomp et al. (1995) showed that the withdrawal of excess GH, using a controllable transgene, caused an equal increase in both subcutaneous and epididymal obesity. It is interesting to note that

47 excess and decreased GH signaling do not have equal, opposing effects on adipose tissue depots.

Separately, GH has previously been shown to have distinct effects on macrophages. It has been suggested that GH may influence the infiltration of macrophages into adipose tissue by positively regulating the expression of the macrophage chemoattractant MCP-1 in adipocytes (Fasshauer et al. 2004, Bruun et al.

2005, Kanda et al. 2006). This thesis examined MCP-1 expression in all three transgenic mouse models, but did not see a significant difference in expression as a result of differential GH signaling, thus lending no support to the GH/MCP-1 based theory of macrophage infiltration into adipose tissue. However, a previous thesis conducted at Ohio University (Wright-Piekarski 2010) studying the effect of GH injection on macrophage infiltration into adipose tissue showed no significant effect of

GH on the macrophage content of the epididymal or subcutaneous (inguinal) depots.

As previously mentioned, GH injection as a model for GH excess differs from GH transgenic mice, as it does not entirely mimic the pulsatile secretion of GH normally accomplished by the pituitary. That being said, similar results have been obtained using both models in terms of GH‟s effect on adipose tissue (List et al. 2009,

Berryman et al. 2004) and thus comparing results of the two models is reasonable in terms of GH‟s effect on macrophages. This thesis supports the finding that GH injection did not affect the macrophage content of adipose tissue, as neither excess nor decreased GH signaling were shown to have a significant effect on the macrophage content of subcutaneous or epididymal adipose tissue.

Effect of Adipose Tissue Depot

Adipose tissue is spread throughout the body in different, distinct depots.

These depots can be simply classified as subcutaneous, visceral, or intra-abdominal and exhibit metabolic and functional differences (Wajchenberg et al. 2002). Thus, it is important to analyze more than only one adipose tissue depot to gain a full understanding of the effect of growth hormone on the macrophages within distinct depots. Our study chose the inguinal depot, a subcutaneous depot, and the epididymal depot, an intra-abdominal depot, as representative depots for analysis. The selection of these depots was two fold. First, these depots are the two largest, meaning we had sufficient tissue. Second, previous studies in our lab (Berryman et al., 2004, 2006,

2010) have demonstrated these depots are at the extreme ends of the spectrum in terms of their response to GH action. In other words, inguinal tends to be the most radically altered, whereas epididiymal seems to be least responsive to GH action.

A significant difference in several macrophage markers between depots was seen in the GHA group, but not in the bGH or GHR-/- groups. A significant difference was obeserved in the GHA group of the general macrophage marker F4/80, as well as the M1 markers Tnf and Il1-β, and the M2 markers Retnla, Il-10, and Arg1. These data suggest a significant increase in macrophage accumulation in the subcutaneous depot relative to the epididymal depot. This contradicts previous literature showing that, in humans, visceral adipose tissue has a higher degree of macrophage infiltration than does subcutaneous adipose tissue (O‟Rourke et al. 2009). Current literature also shows that visceral adipose tissue exhibits a higher degree of inflammation than does

49 subcutaneous adipose tissue (O‟Rourke et al. 2009), which supports the theory that macrophages are the main source of inflammation within adipose tissue (Heilbronn et al. 2008). However, O‟Rourke et al. (2009) did not detail the specific adipose tissue depots sampled in their study nor do they provide the specific definition of visceral adipose tissue. Thus, it is impossible to know if this study sampled a true visceral depot. Although the epididymal depot examined in this study is not a true visceral depot, it is an intra-abdominal depot, which show more similarities to visceral adipose than do subcutaneous depots. As a significant difference with respect to genotype and depot was not observed in this thesis, the higher macrophage content of subcutaneous adipose tissue is not related to the decrease in GH signaling seen in GHA mice.

Additionally, macrophage markers associated with both the M1 and M2 phenotypes were increased, suggesting that subcutaneous adipose tissue houses a larger population of both phenotypes of macrophages. A possible theory explaining the increased macrophage infiltration seen in the subcutaneous adipose tissue of the GHA mice is their naturally obese phenotype. As detailed throughout this thesis, obesity is highly associated with an accumulation of macrophages. It is well documented that GHA mice exhibit extreme subcutaneous obesity, which may be the underlying cause for the significant, subcutaneous macrophage infiltration.

Limitations and Future Prospects

The methods used in this thesis involve the analysis of whole adipose tissue.

While, in the context of this subject, analyzing whole tissue provides a more comprehensive view of the interaction between GH, adipose tissue, and macrophages,

50 it does come with limitations. The proportion of macrophages to adipocytes and other cell types may be very small, and thus we may be attempting to amplify the mRNA expression products of only a fraction of the tissue sample. However, other researchers have successfully employed these methods. A possible limitation specific to this thesis is the concentration of mRNA isolated from the whole tissue. Although the concentrations used were within the guidelines of the PCR Super Arrays, it is possible that the specific expression products being amplified were low enough in concentration that an especially high concentration of total mRNA would be necessary to detect their presence with certainty. Additionally, this study did not use technical replicates when conducting the PCR Super Arrays, thus if by happenstance the PCR reaction in a single well failed to complete, a data point was lost, decreasing the N for that sample group. Each group within my experiment began with an N of 6. Some experimental groups ended with an N of 0 or 1 for certain macrophage markers, meaning that all, or all but 1 of the Ct values gathered for that marker within that experimental group were eliminated from analysis.However, many groups were able to retain all 6 data points and many more were able to retain an average of 4 data points. When dealing with expression products that are naturally low in concentration, detection by RT-PCR can be difficult. Due to the time constraints of this thesis, additional samples could not be processed to raise the N values, however future studies may do so.

Current literature suggests a large effect of GH on visceral adipose tissue

(O‟Rourke et al. 2009), however no visceral adipose tissue depots were analyzed in

51 this study. Instead, an intra-abdominal depot, the epididymal depot, was used due to difficulties isolating the proper concentrations of RNA from the true visceral depot dissected, the mesenteric depot. Optimization of the RNA isolation protocol may allow for the analysis of true visceral depots, which may show an effect of GH on macrophage content.

There are also confounding factors among our sample groups, which may influencethe observed results. All of the mice used in this study were near the end of their lifespan when tissue collection was performed and thus the old age of the mice may be a factor in the macrophage content of their adipose tissue. Body composition analysis throughout the lifespan showed that in both bGH and GHR-/- mice, percent fat mass increased to a certain point, and then began decreasing near the end of their lifespan (Berryman et al. 2009, Palmer et al. 2009). This decrease in fat mass may alter the macrophage content and phenotype within the adipose tissue. Although this study aimed to elucidate the effect of GH on macrophages, as stated previously, GH has an extreme effect on the phenotype of the mouse models used. In addition to causing a lean or obese phenotype, GH also plays a role in insulin sensitivity, glucose levels, and IGF-1 levels. bGH mice are known to be insulin resistant (Chen et al.

1991), while GHA and GHR-/- mice are known to be insulin sensitive and have low levels of IGF-1 (Coschigano et al. 2003). Thus, it could be that the phenotypic differences exhibited by mice with differing levels of GH signaling exert an effect on the macrophage content of adipose tissue, separate from the sole effect of

GH.However, when working with animal models, confounding factors are often unavoidable.

As the data obtained in this study show a great deal of error and in some cases are contradictory to published literature, further studies using the same or alternative methods should be conducted in order to validate these results.

Alternative methods for studying the effect of GH on adipose tissue macrophages include immunohistochemistry (Cinti et al. 2005), fluorescence-activated cell sorting (FACS) (Weisberg et al. 2003), or cell culture (Lu et al. 2010). See associated references for example studies using these techniques.

Immunohistochemistry is valuable in that it allows for the direct visualization of the macrophages within adipose tissue and even for the determination of the M1 or M2 phenotype. FACS allows for the isolation of the SVF (stromal vascular fraction) cells from adipose tissue, and thus the analysis of a more specific cell population. Surface antibodies can be used to separate macrophages from other cell types within the tissue.

This type of analysis is valuable in that it still uses macrophages isolated directly from adipose tissue, but does not include adipocytes, which may mask the true macrophage expression profile. Cell culture experiments allow for the most controlled environment, but are the least similar to the in vivo situation.

Conclusions

This thesis aimed to uncover how GH affects the macrophage content of two separate adipose tissue depots using three transgenic mouse models with altered GH

53 signaling. Across all three models, no effect of GH on the macrophage content of either studied depot was seen. However, it was observed that, in the GHA mice specifically, the subcutaneous adipose tissue depot contained more macrophages than did the epididymal depot. Due to the complications and limitations discussed above, the results of this study should be validated either by repeating a similar experiment, or by using a different methodoology. Continued research in this area is of great importance, as previous literature strongly suggests a correlation between obesity, inflammation, and macrophages, and GH may yet be a possible therapeutic agent to help control the deleterious health conditions associated with obesity.

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