Growth Hormone (GH) and the Cardiovascular System: Studies in Bovine GH

Transgenic and Inducible, Cardiac-Specific GH Receptor Gene Disrupted Mice

A dissertation presented to

the faculty of

the College of Arts and Sciences of Ohio University

In partial fulfillment

of the requirements for the degree

Doctor of Philosophy

Adam Jara

May 2014

This dissertation titled

Growth Hormone (GH) and the Cardiovascular System: Studies in Bovine GH

Transgenic and Inducible, Cardiac-Specific GH Receptor Gene Disrupted Mice

ADAM JARA

has been approved for

the Department of Biological Sciences

and the College of Arts and Sciences by

John J. Kopchick

Distinguished Professor of Molecular Biology and Goll-Ohio Eminent Scholar

Robert Frank

Dean, College of Arts and Sciences 3

ABSTRACT

JARA, ADAM, Ph.D., May 2014, Biological Sciences

Growth Hormone (GH) and the Cardiovascular System: Studies in Bovine GH

Transgenic and Inducible, Cardiac-Specific GH Receptor Gene Disrupted Mice

Director of Dissertation: John J. Kopchick

Growth hormone (GH) and insulin-like growth factor I (IGF-I) are thought to play key roles in the development and maintenance of the heart. Evidence of the profound effect GH has on the heart can be found in patients with diseases that disrupt GH action.

In pathological states of acromegaly (caused by oversecretion of GH), GH deficiency, and Laron Syndrome (a disease caused by mutations in the GH receptor resulting in systemic lack of GH induced action), patients exhibit unique cardiovascular phenotypes of altered structure and function. Despite these observations, the exact role of GH in the cardiovascular system is not well characterized. To better understand the effects that GH action has on the cardiovascular system, we studied the well-established bovine GH

(bGH) transgenic mouse and developed a novel tamoxifen-inducible, cardiac-specific GH receptor (GHR) gene disrupted mouse (iC-GHRKO). We find that the bGH mice exhibit an age-dependent elevation of systolic blood pressure that is correlated with changes in both the brain natriuretic peptide and renin angiotensin systems. Our initial characterization of the iC-GHRKO mice surprisingly reveals that cardiac GH signaling is not necessary for maintainance of baseline cardiac function, but does appear to be required for normal glucose homeostasis in older mice. These studies take us a step closer 4 to understanding the role of GH in the cardiovascular system and imply complex hormonal regulation of both cardiovascular function and whole body metabolism. 5

DEDICATION

This work is dedicated to all of the aspiring young scientists who face significant

socioeconomic challenges on their way to achieving their dreams.

It is possible. 6

PREFACE

The work described in this dissertation has been organized in manuscript format.

Chapters 1, 3, 4, and 5 represent standalone bodies of work. Chapter 2 explains the

Specific Aims of our studies. Chapter 6 is a summary of the work presented in the

preceeding chapters and focuses on plans for future experimental studies. Please note that

“Chapter 3: Elevated Systolic Blood Pressure in male GH transgenic mice is age-

dependent” was previously published in the monthly periodical Endocrinology.

Permission for reproducing this chapter can be found in Appendix A. Appendix B

contains a copy of the slides used in the Oral Dissertation Presentation on Tuesday,

March 11, 2014. Appendices C and D contain supplemental materials for Chapters 3 and

4, respectively. Appendix E contains a complete immunoblot procedure guide with recepies and protocols. Appendix F contains information on a side-project regarding automated statistics in the R programming environment. 7

ACKNOWLEDGMENTS

I would like to thank the senior members of our laboratory group (John Kopchick,

Darelene Berryman, Nick Okada, Ed List, and Bruce Kelder) at Edison Biotechnology

Institute for being great mentors through this experience. I would like to thank John for

taking me under his wing as a graduate student and teaching me endocrinology. The shift

from working in the computational chemistry field was drastic, but well worth the effort.

The environment in John’s laboratory is one of productivity, collaboration, and partying.

It is unique and is something I will miss after I graduate. I would like to thank Darlene for demonstrating to me that it is entirely possible to balance life, work, and play. Even during the most stressful of times she somehow manages to keep a smile and an upbeat attitude. Going forward I hope I can emulate this in my own career. I want to Thank

Bruce for his help in setting up cell culture experiments and teaching me the “old ways” of science. I want to thank Nick for all of the discussions concerning computers and electronics—they are always welcomed respites from my lab work. Indeed it has been

great having someone who can appreciate the increased hashing power of CUDA! I want

to thank Ed for being a great listener and his encouragement. I can’t recall how many

times we had discussions in his office about half-witted science projects and life.

I am also thankful for the experimental and planning support of professors outside

of Ohio Univeristy: Richard Klabunde, Shawn Bender, and Jason Kim. I am grateful to the graduate students (Elahu Gosney, Juan Ding, and Lucila Sackmann-Sala) and post- docs (Diana Cruz-Topete and Riia Junnila) who trained me as a beginning graduate 8

student. Many of the techniques and general laboratory “know-how” presented in this document are a result of their teaching.

I am grateful to the staff at the Edison Biotechnology Institute: Missey Standley and Lori Abdella for their daily efforts to ensure our labs are stocked, funded, and

inhabitable; Kevin Funk and Lara Householder for their help in collecting data and

designing experiments; and Ed, Darla, and Tammy for their daily efforts to ensure our

animals are well maintained.

One of the most challenging, yet most satisfying parts of completing this dissertation was the opportunity to mentor students. I want to thank Chance Benner for

sharing his enthusiasm for life and health—it is addicting and has helped keep me excited

about science even when our experiments didn’t work for weeks on end. I would like to

thank Don Sim for taking on several research projects beyond the requirements of his

degree program and always providing timely and honest feedback. I would like to thank

Xingbo Liu for always asking questions and ensuring that I am up to date with my

science knowledge. I would also like to thank her for her PCR and pipetting skills which

were indispensable in finishing these projects.

I would also like to thank my mother Trudi, my sister Emily, my brother Alex,

and my late step father Rob for supporting me through such an arduous process and

always encouraging me to go the extra mile.

Finally I would like to thank my partner Lauren Volpe for her continued

companionship, her impeccable editing skills, and her uncanny ability to keep me 9 grounded. Her love, encouragement, and support have made, and will continue to make, my life meaningful. 10

TABLE OF CONTENTS

Page

Abstract ...... 3 Dedication ...... 5 Preface ...... 6 Acknowledgments...... 7 List of tables ...... 12 List of figures ...... 13 Chapter 1: Alterations in growth hormone’s action and its effect on the cardiovascular system: A focus on mouse models ...... 14 Abstract ...... 14 Physiology of growth hormone ...... 14 GH receptor induced signaling ...... 22 GH-related diseases and the human heart ...... 23 Mouse models of GH action and the cardiovascular system ...... 31 Future perspectives ...... 43 Acknowledgements ...... 43 Chapter 2: Specific aims ...... 45 Chapter 3: Elevated systolic blood pressure in male GH transgenic mice is age-dependent ...... 48 Abstract ...... 48 Introduction ...... 49 Materials and methods ...... 52 Results ...... 56 Discussion ...... 65 Acknowledgements ...... 74 Chapter 4: Cardiac growth hormone receptor induced signaling is necessary for maintaining glucose homeostasis in adult male mice ...... 76 Abstract ...... 76 Introduction ...... 77 Materials and methods ...... 80 11

Results ...... 86 Discussion ...... 97 Acknowledgements ...... 105 Chapter 5: Differential gene expression in 12-month-old bovine GH transgenic mouse heart...... 106 Abstract ...... 106 Introduction ...... 106 Materials and methods ...... 107 Results ...... 110 Discussion ...... 115 Chapter 6: Concluding remarks and future studies ...... 118 Elevated systolic blood pressure in male GH transgenic mice is age-dependent ...... 118 Cardiac GHR signaling is necessary for maintaining glucose homeostasis in adult male mice ...... 119 References ...... 128 Appendix A: Endocrine society license for reproduction of chapter 3...... 149 Appendix B: Oral defense presentation slides ...... 156 Appendix C: Chapter 3 supplemental materials and methods ...... 186 Appendix D: Chapter 4 supplemental material ...... 193 Appendix E: Immunoblot protocol ...... 194 Appendix F: R script for high throughput ANOVA based statistics of mouse circulating parameters ...... 205

LIST OF TABLES Page

Table 1.1: Double-blinded, placebo-controlled studies of GH treatment in CHF ...... 30

Table 4.1: M-mode echocardiography measurements ...... 96

Table 5.1: Top 10 up- and downregulated genes in 12 month old bGH heart ...... 112

Table 5.2: IPA top disrupted cellular pathways ...... 113

Supplemental Table 3.1: RTqPCR primers ...... 192

Supplemental Table 4.1: PCR primers ...... 193

LIST OF FIGURES

Page

Figure 1.1: Control of GH secretion and main tissues of action ...... 15

Figure 1.2: Main cardiovascular findings in acromegaly ...... 26

Figure 3.1: Body composition, length, tissue mass ...... 57

Figure 3.2: Heart and kidney histology ...... 59

Figure 3.3: Systolic blood pressure, BNP, and heart calcium channels ...... 61

Figure 3.4: Glucose homeostasis ...... 63

Figure 3.5: Circulating inflammatory cytokines ...... 65

Figure 3.6: Expression of ACE, ACE2, and eNOS in kidney ...... 65

Figure 4.1: Verification of inducible GHR gene disruption ...... 87

Figure 4.2: Body composition analysis, length, and dissected tissue weights ...... 89

Figure 4.3: Insulin and glucose tolerance testing ...... 90

Figure 4.4: Insulin stimulated Akt and MAPK phosphorylation ...... 92

Figure 4.5: Circulating metabolic peptides ...... 93

Figure 4.6: Cardiac calcium channel RNA levels ...... 94

Figure 5.1: Venn diagram of differential gene expression in heart ...... 111

Figure 5.2: Diagram of mitochondrial electron transport chain ...... 114

Figure 6.1: Possible crosstalk between cardiac GHR signaling and insulin receptor signaling ...... 124

Supplemental Figure 4.1: Systolic blood pressure ...... 193

CHAPTER 1: ALTERATIONS IN GROWTH HORMONE’S ACTION AND ITS

EFFECT ON THE CARDIOVASCULAR SYSTEM: A FOCUS ON MOUSE

MODELS1

Abstract

Human diseases resulting in alterations of the GH/IGF-I axis result in unique

cardiovascular phenotypes. Likewise, animal models of altered GH or IGF-I levels show

distinct effects on cardiac, vessel, and renal structure and function. Here we review the literature with a focus on what animal models have taught us about the role of both IGF-I

and GH on the structure and function of the cardiovascular system. Where appropriate we

also briefly review human disease states related to the GH/IGF-I axis and their resulting

cardiovascular phenotypes. Finally, we propose new avenues for research in this area.

Physiology of growth hormone

Growth hormone (GH) is a 191 amino acid protein produced in somatotrophs of

the anterior pituitary. GH circulates in the blood as two biologically active forms of

22kDa and 20kDa, with the 22kDa being the major form (1). GH exerts its action via binding to the GH receptor (GHR), which has been identified in almost every tissue type

including brain, muscle, adipose, bone, heart, and glandular tissue (2). The main

regulators of GH release are GH releasing hormone (GHRH) and somatostatin (SST)

secreted from different populations of hypothalamic neurons (Figure 1.1). While GHRH

induces release of GH, SST inhibits its release. GH secretion is also stimulated by

1 Worked presented in this chapter represents a manuscript in preparation. The contributing authors are: Adam Jara, Chance M Benner, Don Sim, and John J Kopchick.

Figure 1.1: Control of GH secretion and main tissues of action. See text for more details for tissues shown. GH is released from the anterior pituitary in response to GHRH, stress, sleep, exercise, and the stomach-derived peptide ghrelin. GH is inhibited by somatostatin and circulating IGF-I. GH is secreted in a pulsatile fashion throughout the day with the largest pulses during sleep. Abbreviations: GHRH - growth hormone releasing hormone; SST- somatostatin; GH- growth hormone; IGF-I- insulin-like growth factor 1. Adapted and updated from Kopchick et al. (3).

ghrelin, an endogenous GH secretagogue (GHS) produced primarily in the stomach,

which binds to GHS receptors in the anterior pituitary (4). Three main feedback systems

regulate GH secretion. GH secretion is regulated via a “long-loop” feedback by which

circulating insulin-like growth factor 1 (IGF-I) acts either directly upon the pituitary or

via the hypothalamus to induce SST release. A “short-loop” feedback system exists by

which GH inhibits its own release via hypothalamic stimulation of SST release (5). And

lastly, an “ultra-short loop” feedback system exists by which GH attenuates its own

release via direct somatotroph inhibition (5).

GH has systemic effects on metabolism, growth, and development. GH promotes

linear bone growth before puberty, allowing for attainment of normal height. After

puberty, GH stimulates periosteal bone apposition that serves to thicken and strengthen

cortical bone, a process that becomes pathologic when GH is secreted or administered in

supraphysiologic doses, as seen in acromegalic patients and cases of recombinant GH

(rGH) doping (6). GH also affects carbohydrate and lipid metabolism by inducing lipolysis through activation of hormone sensitive lipase possibly via stimulation of protein kinase C and extracellular related kinase pathways (7); stimulating skeletal muscle triglyceride uptake via lipoprotein lipase activation and promoting an overall

anabolic effect on muscle (8). This is crucial during a famine state where GH acts as the

major anabolic hormone acting to supplant glucose and protein metabolism with lipid

metabolism (9). In skeletal muscle, GH is important for promoting local IGF-I

production, which has been shown to work in an autocrine manner to promote muscle 17

myoblast fusion through upregulation of the nuclear factor of activated T-cells /

interleukin 4 (NFATc2/IL-4) pathway (10).

GH also impairs both peripheral and hepatic insulin sensitivity. The anti-insulin

effects of GH were realized in the early 1930s (11) when GH levels were shown to inversely correlate with serum glucose levels. Later, in the 1960s anti-insulin effects were observed in humans (12) injected concomitantly with insulin and GH. Explanations for the anti-insulin effects of GH include GH-induced lipolysis (9) leading to an influx of systemic free fatty acid and, at the molecular level, stimulated expression of suppressor of cytokine signaling (SOCS) 1 and 3 and p85, the regulator subunit of PI3K (13)—all which negatively feed back on the insulin signaling pathway (14). However, the exact mechanism by which GH inhibits insulin action is likely more complicated. Confounding the exact interplay of GH and insulin (15) is the recent finding in ghrelin O- acyltransferase -/- mice, which lack the ability to form active acylated-ghrelin, that GH

secretion, via ghrelin stimulation, is necessary to maintain blood glucose during calorie restriction. Finally, GH exerts an antinatriuretic effect resulting in expansion of extracellular volume—a change that may, in part, be mediated via activation of the renin- angiotensin-aldosterone (RAAS) system (16). Insulin, however, is also known to exert an

anti-natriuretic effect (17) and, as stated previously, GH can have anti-insulin effects which can lead to a state of insulin resistance.

GH and IGF-I in growth

It is widely accepted that many of the anabolic effects of GH are the result of GH- induced hepatic IGF-I expression—known as the dual-effector theory (18) or the 18

somatomedin hypothesis (19, 20). Hepatic Igf1 transcript levels are almost completely

dependent on proper GH signaling as demonstrated by a 98% decrease in GH receptor

null (GHR-/-) mice relative to control littermates (21). Igf1 transcript levels in the heart,

lung, testis and uterus, however, do not depend as much on intact GH signaling, as

reflected by a 0.5%, 12.2%, 7.4%, and 22.4% respective decrease in GHR-/- mice relative to control littermates (21). Furthermore, loss of Igf1 transcript production in hepatocytes has been directly correlated to a loss of plasma IGF-I levels (21). Mice with a liver- specific Igf1 deletion exhibited a 75% decrease in circulating IGF-I levels, but do not significantly differ from wild type littermates with respect to body weight or length (22,

23), suggesting that circulating IGF-I may not be necessary for postnatal growth and

development. More recently, however, this conclusion was challenged in a study (20)

using bi-transgenic mice with an Igf1 null background and a Cre-LoxP mediated hepatocyte-specific Igf1 knock-in. Results showed that hepatic derived IGF-I is responsible for approximately 30% of adult body size and greater than 50% of circulating

IGF-I.

While many actions of GH are an indirect result of IGF-I regulation, independent effects of GH and IGF-I in postnatal growth have been clearly demonstrated in a comparison of growth charts of hepatic Igf1 null, GHR-/-, and double hepatic Igf1/Ghr null mice from 0 to 100 days after birth (21). Results show Igf1 null and Igf1/Ghr null mice had decreased birth weights compared to GHR-/- and wild-type control mice (21).

Additionally, the weight of GHR-/- mice does not deviate from wild-type until ten days after birth, indicating a delayed effect of GH mediated growth (21). Total growth of the 19

double Igf1/Ghr null mouse represents growth due to IGF-I and GH independent mechanisms and constitutes approximately 17% of total weight relative to wild-type mice

(21). When growth charts of GHR-/- and Igf1 null mice are normalized for the IGF-I/GH independent processes, GH independent, IGF-I independent, and combined IGF-I/GH effects are calculated to be 14%, 35%, and 34%, respectively (21). These results are not surprising as IGF-I is known to act as both a GH-dependent endocrine hormone and a

GH-independent local growth factor in the skeletal system (6). Furthermore, GH can independently stimulate the production of osteoprotegerin causing subsequent antagonism of the RANK-L receptor and a decrease of osteoclast activation and bone

reabsorption (6). The discovery of these independent actions underscores the need to

understand the physiology of GH and IGF-I on a tissue by tissue basis.

GH and IGF-I in the heart and kidney

The GH/IGF-I axis has been implicated in several pathways regulating growth,

metabolism, and intrinsic contractility of cardiomyocytes. In particular, IGF-I promotes

cardiac hypertrophy by increasing collagen synthesis and GH, specifically, has been

shown to increase the rate of collagen deposition in the heart of rats (24). IGF-I has also

been shown to be cardioprotective if injected into mice prior to ischemia (25), leading to

a decrease in the number of infiltrating neutrophils. Rats with GH secreting tumors have

been shown to have prolonged ventricular action potentials due to a decreased outward

K+ transient (26) and IGF-I, independent of GH, has been reported to augment the

sensitivity of the dihydropyridine-sensitive sarcolemmal Ca2+ channel (27). Further, GH

is known to cause a conversion from the V1 isoform of myosin to the relatively low 20

ATPase activity V3 isoform (28), which is initially regarded as a compensatory mechanism to allow the heart to operate at lower energy cost but is also a pathologic

marker if it is the prevailing isoform. Recently, GH has been shown to impair acute

cardiac insulin stimulation indicating unique adapatations in the acromegalic heart to

changing energy demands (29).

Outside of the heart, the GH/IGF-I axis is also known to play important roles in

renal function. Evidence for these effects can be found in studies of patients with

acromegaly, a condition caused by increased GH production secondary to a pituitary

adenoma. Patients with acromegaly (30, 31) or those receiving GH injections (32, 33)

often present with elevated fluid retention. Upregulation of a kidney-specific endothelial

sodium channel (ENaC) and NKCC2, a nephron specific sodium-potassium-chloride co-

transporter, is observed in acromegaly (31, 34) and acute GH administration to normal

patients (35), respectively. Patients with acromegaly display enhanced kidney size, but

kidney damage is difficult to assess and no scarring of the glomerulus has been detected

(36)—likely due to reduced longevity and/or pharmacological intervention.

The renin angiotensin aldosterone system (RAAS) is a hormonal system involved

in maintaining cardiovascular homeostasis. Angiotensin II (AngII), the primary effector

hormone of the RAAS, is formed through a multi-stepped, enzyme-regulated cascade.

When bound to its receptor, the angiotensin 1 (AT1) receptor, AngII directly affects the

heart, kidney, and blood vessels— promoting hypertrophy and fibrosis. Through vessel

constriction, sodium retention, and aldosterone release, AngII positively influences blood

pressure. Within the last two decades, a new arm of the RAAS, the ACE2/Ang-(1-7)/ 21

Mas receptor axis was discovered. Upon binding to the Mas receptor, Ang-(1-7) opposes

AngII through vasodilatory, natriuretic, anti-hypertrophy, and anti-fibrosis effects (37).

Due to the water retention and hypertensive effects of GH, the RAAS has been heavily investigated in GH disease states. In healthy humans, GH treatment alone has been shown to increase both renin and aldosterone levels while also increasing distal renal tubule reabsorption of sodium and water (38). Interestingly, when renin and aldosterone elevations are corrected with subsequent ibuprofen administration, the increased distal tubule reabsorption of sodium and water remained. Taken together, these results show that while the RAAS plays a role in GH mediated water retention, GH likely affects the nephron either directly or perhaps through autocrine IGF-I production (38).

The effects of GH on the activation of the RAAS have been debated in the literature. Several GH injection studies in dwarf rats (39), aged rats (40), GHD adults (32,

33, 41, 42), and healthy humans (38, 43) show elevated renin or angiotensin II levels, a common indicator of RAAS activation, while others show no activation (33, 44).

Activation of the RAAS in GH injection studies may be the result of supraphysiological

GH dosing (33). Also, differences in RAAS component levels may in part be due to sampling time as kidney IGF-I levels, in humans, do not reach peak levels until several hours after GH injection (45). A subset of patients with hypertensive acromegaly show a gene polymorphism (CYP11B2-344T/C) for aldosterone synthase compared to normotensive patients (46). After treatment, patients with acromegaly experience a significant drop in circulating aldosterone levels with no change in renin levels (47).

However, others have found that patients with acromegaly have no change in either renin 22

(48) or aldosterone levels (49). Therefore, more studies will be required to solidy the role of GH in activation of the RAAS, but there does appear to be a positive correlation between RAAS activation and GH level.

GH receptor induced signaling

At the molecular level GH exerts its action via binding to GHR which is made of two monomeric subunits consisting of 638 amino acids formed into two domains: an ectodomain that binds GH and can be liberated to produce a serum GH binding protein, and an intracellular tyrosine kinase associated domain (2). The two domains are connected via a membrane-spanning region. Early studies proposed that GH bound to a single GHR molecule, induced dimerization of receptors, and resulted in signal transduction; however, it has been confirmed through several more recent studies that

GHR found on the cell surface is expressed mainly as a preformed dimer (50, 51). These findings are in line with what is known about other members of the cytokine receptor superfamily (ie. prolactin and erythropoeitin), of which GHR is a member (52). The extracellular ligand binding domain of GHR is composed of two 110 residue beta sandwich domains (53). Binding of GH to specific sites on the extracellular domain causes a physical rotation in the receptor that is transduced across the membrane. This leads to rotation and apposition of the intracellular regions and subsequent phosphorylation and activation of associated Janus kinase 2 (JAK2) domains (52).

Phosphorylation of the intracellular domains allows for docking and activation of several

cellular mediators such as suppressor of cytokine signaling (SOCS)1 and 3, Src

homology 2 domain containing (SHC), Src homology region 2 domain-containing 23

phosphatase 2 (SHP2), and signal transducer and activator of transcription 5 (STAT5)

(54). SOCS and SHP-2 activation are thought to serve as negative regulators of GHR activation (55).

The JAK2-STAT interaction is regarded as the canonical GH signaling pathway.

Activated JAK2 phosphorylates transcription factor STAT5 (56) monomers leading to

STAT5 homodimerization and subsequent translocation to the nucleus (54). Active GHR, however, can directly activate mitogen-activated protein kinase 1 and 3 (ERK2 and 1, respectively) leading to systemic proliferative and growth effects (52) and highlighting how GH can have IGF-I independent effects. While the focus of this review is not JAK2 signaling, it is interesting to note that in a review by Kurdi et al. (57), JAK2, principally through STAT3, is reported to play several roles in cardiac growth and protection from injury. In general, it appears that activation of JAK2 is protective in the heart. For example, activation of JAK signaling through IL-6 improves response to ischemia in cultured rat ventricular cardiomyocytes (58). Further, attenuation of JAK2 signaling results in loss of the protective effects of ischemic preconditioning (59), a phenomenon by which short bursts of ischemia can protect downstream cells from prolonged ischemia

(60).

GH-related diseases and the human heart

Obesity

Human diseases that result in decreased GH action (either by decreased GH production or resistance to GH itself) provide evidence for GH’s role in cardiac 24 maintenance and function. Obesity is one of the most interesting diseases relating GH action and the heart. Over 30 years ago, it was observed that obese patients have decreased GH release in response to GHRH administration, an effect that is partially reversed when the patients lose weight (61). Later studies revealed that both GH secretion and GH clearance rates are negatively correlated with the degree of obesity (62). Obesity has even been shown to blunt the stimulatory effects of aerobic exercise on GH secretion

(63). Recently, obese individuals were shown to exhibit a state of GH resistance in which

Ghr expression is downregulated in adipose tissue (64, 65). When viewed in light of the subclinical decrease in systolic function and altered lipid profiles common in obesity, GH signaling, and perhaps cardiac GH signaling, may play a central role in the complex pathophysiology of obesity.

Growth hormone deficiency

On one end of the GH action spectrum is GH deficiency (GHD), resulting from either genetic dysfunctions of the GH gene, radiation therapy for brain tumors, or traumatic brain injury (66, 67). Due to the lack of GH induced intracellular signaling,

GHD symptoms broadly include increased adiposity with centralized deposition (due to loss of the lipolytic effects of GH), hypoglycemia, and decreased quality of life (67).

However, patients with GHD often have many concomitant disorders such as deficiency of other pituitary hormones and insulin resistance due to increased amounts of adipose tissue (68, 69). GHD patients also have increased low density lipoprotein (LDL) levels

(68), a finding that highlights the role GH plays in mediating lipid balance. Additionally,

GHD patients also exhibit increased intima thickness of coronary vasculature, which is a 25 hallmark feature of early atherosclerosis (68). Compounding the poor lipid profile is an altered cardiac morphology characterized by decreased left ventricular wall and interventricular septal thickness (68)—findings that, in part, explain the altered exercise ability and decreased quality of life so common in GHD patients (70).

Laron syndrome

Laron syndrome (primary GH insensitivity or resistance) is usually caused by mutations in the GHR, which results in little or no GH signaling. Patients with Laron syndrome are dwarf and obese with high serum GH levels but low IGF-I levels (71).

These patients show decreased cardiac size with thin ventricular walls and decreased cardiac output (72), and have drastically reduced VO2max during exercise (73). When

IGF-I replacement is initiated in children with Laron Syndrome, loss of ventricular function and mass is attenuated (74). This indicates that IGF-I action is required for proper maintenance of cardiac growth during childhood. Recently, it has been shown that these patients are relatively resistant to the development of Type 2 diabetes and cancer, underscoring the effects of GH on insulin signaling and growth (75).

Acromegaly

At the other end of the GH action spectrum are patients with acromegaly, a disease characterized by hypersecretion of GH from the anterior pituitary. Acromegaly is most often secondary to the formation of a pituitary adenoma. These patients develop a unique cardiomyopathy characterized by concentric hypertrophy, hypertension, and a predisposition to atherosclerosis (76, 77). Figure 1.2 summarizes the main cardiovascular deficits in acromegaly. Three clinical stages of acromegalic cardiomyopathy are 26

recognized (78). Initially, there is an asymptomatic cardiac hypertrophy and left

ventricular function is often increased. This early phase is described as cardiac

hyperkinesia or ‘hyperkinetic syndrome’ (79). This phase is followed by concentric

hypertrophy of both ventricles, which results in stiffening of the ventricles and filling

abnormalities. Given that most patients with acromegaly are diagnosed later in life, most

will present during this phase of impaired ventricular filling. If the disease is allowed to

progress, the continued exposure to high GH results in further hypertrophy with

compensatory dilation of the ventricles and eventual cardiac failure (80). Thus, in human

diseases of disrupted GH production (either more or less) or GH resistance, there are

unique cardiac phenotypes.

Figure 1.2: Main cardiovascular findings in acromegaly. LV: left ventricle, LVH: left ventricular hypertrophy, IMT: intima media thickness. Adapted from a review by Colao (78).

Chronic heart failure (CHF)

Due to their size and well established methods of manipulating the in vivo and ex vivo heart, rats are popular choices for pre-clinical trials. The initial use of recombinant human (rh)GH as a therapy in heart failure of humans was preceded by several experiments showing beneficial effects of both GH and IGF-I treatment in experimentally induced heart failure in rats. In 1992, Castagnino and colleagues demonstrated that treatment of post-infarction rats with rhGH helped to maintain the collagenous matrix around ventricular cardiomyocytes and resulted in a significant reduction in the rate of ventricular aneurysm formation (81). Just a year later, male Wistar rats were injected with doxorubicin to induce cardiomyopathy and were subsequently placed on osmotic pumps with either IGF-I or saline treatment for three weeks (82). The rats treated with

IGF-I had improved cardiac output and, while not statistically significant, a tendency to have improved survival (82). Two weeks of GH treatment in post-infarction rats was shown to improve cardiomyocyte shortening and increase peak intracellular calcium levels (83). This increase in peak calcium was related to an increase in ventricular

SERCA2 protein level (83). Further, it has been demonstrated that the cardiac specific effects of GH and IGF-I synergize with captopril treatment (an angiotensin converting enzyme inhibitor, which is standard treatment for chronic heart failure). Rats placed on both captopril and GH/IGF-I combination treatment after left coronary artery ligation exhibit increased cardiac and stroke volume index compared to captopril treatment alone

(84). This indicates the ability of GH/IGF-I to directly affect myocardial contractility and afterload (84). Subsequent studies have demonstrated that GH treatment in post- 28

infarction rats actually improves survival rate, 68% in GH versus 48% in control animals

(85). The GH treatment is not associated with any change in SERCA2 mRNA expression, but it was associated with a decrease in the amount of pathologic fibrosis (85).

During this experimentation with GH treatment in animal models of heart failure,

patients with GHD receiving GH replacement therapy were showing favorable outcomes.

In one double-blinded, placebo-controlled, cross-over study, 10 patients with GHD were

placed on GH (0.5U/kg/week) or placebo for 6 months before crossing treatments for

another 6 months. Echocardiographic analysis demonstrated an increase in left

ventricular mass, cardiac output, and heart rate with a decrease in peripheral vascular

resistance and diastolic blood pressure. These improved cardiac parameters were

mirrored with an increased glomerular filtration rate and decreased serum creatinine level

in the patients receiving GH replacement (86). Another double-blind, cross-over study

examined long-term follow-up of GH replacement in GHD males compared to similar

aged males. The GHD male initially began on a 6-month treatment, a one-year washout,

and a 42 month treatment. At the follow-up exam, the GHD patients had increased

exercise capacity, had regained their initially reduced stroke volume, and showed no

signs of heart disease during an exercise stress test (87).

The effects of GH treatment in chronic heart failure have been contested in the

literature over the past 25 years. The general trend has been for case reports to

demonstrate a positive effect of GH therapy on cardiac structure and function with mixed

results for the larger double-blind, placebo-controlled studies. For example, from 1998 to

present (Table 1.1) there have been four double-blind, placebo-controlled studies 29 examining GH therapy in CHF patients (88-91). The study from Isgaard et al. (88) included patients with mixed etiologies of heart failure and used a dose of 0.1U/kg GH for 1 week and 0.25U/kg GH for 11 weeks. The 22 patients in the study showed no change in any functional cardiac parameters, exercise capacity, or New York Heart

Association (NYHA) functional class (88). A study the same year from Osterziel and colleagues (89) randomized 50 patients to placebo or 2U GH daily for 12 weeks. The only significant finding was an increase in left ventricular mass that correlated positively with IGF-I status (89). Additionally, a double-blind, placebo-controlled study (91), which examined low dose (0.21U/kg/week) GH therapy in patients with heart failure due to cardiomyopathy secondary to muscular dystrophy, demonstrated positive outcomes in heart failure. Of the 10 patients treated in this study, there was a significant increase in ventricular mass with a corresponding decrease in wall stress, a decrease in vascular resistance, and a decrease in circulating BNP levels (91). Finally, the most recent study was conducted by Fazio et al. (90) and demonstrated that three months of GH therapy

(4U every other day) improved NYHA functional class and exercise capacity in terms of peak oxygen consumption and power output.

Interestingly, a recent cross-sectional study by Cittadini et al. examined 158 patients with chronic heart failure and showed that 40% of study individuals met diagnostic criteria for GHD (92). This result indicates that GH may play a central role in the pathophysiology of heart disease independent of genetic defects of the GH gene or pathology of the pituitary. Patients in the study were separated into a control and GH replacement therapy group. After six months of therapy, the patients on GH 30

Table 1.1: Double-blinded, placebo-controlled studies of GH treatment in CHF

U: international unit, LV: left ventricle, NT-proBNP: N-terminal portional of brain natriuretic peptide.

replacement therapy showed increased left ventricular wall thickness, interventricular septal thickness, and ejection fraction (92). Thus, GH replacement can significantly improve heart morphology, heart performance, and quality of life in GHD patients.

Recently Cittadini and colleagues followed up with these patients four years after the initial therapy to reevaluate cardiovascular function (93). Of the 31 patients who returned for evaluation, the 17 rhGH treated patients had improved left ventricular ejection fraction and decreased end-systolic volume, indicating a long-term beneficial effect of

GH replacement in heart failure patients concomitantly presenting with GHD (93).

The results of these clinical trials allude to a possible beneficial effect of GH treatment and, in the case of GHD patients, GH replacement in chronic heart failure.

Much of the discordance between studies likely has to do with the different doses of GH used, the number of individuals examined, and the possibility of concurrent development of resistance to GH and IGF-I. Indeed, it is well known that the development of cachexia in the later stages of CHF is correlated with a developed resistance to GH and IGF-I (94). 31

Therefore, it will be important for future studies investigating the effects of GH treatment

on CHF to: 1) screen patients for GHD and customize replacement doses to the patient

and 2) screen patients for conditions which might predispose them to GH resistance.

Mouse models of GH action and the cardiovascular system

Ames dwarf mice

The Ames mouse has multiple pituitary hypoplasia due to a mutation in Prophet

of Pit-1 (Prop-1) transcription factor which results in loss of development of the

somatotrophs, lactotrophs, and thyrotrophs of the anterior pituitary (95). The result is

decreased circulating GH and IGF-I. In terms of the cardiovascular impact of the Prop-1

mutation only a handful of studies have been conducted. The Ames dwarf mice were

found to have decreased cardiomyocyte size and decreased collagen content at both

young (5-7 months) and old (24-28 months) age (96). It has been proposed that Ames

dwarf mice have increased vascular oxidative stress. Endothelial production of reactive

oxygen species has been reported to be elevated in aorta, and real-time PCR analysis has

demonstrated decreased aortic expression of superoxide dismutase and endothelial nitric

oxide synthase (97). Proper ventricular cardiomyocytes contraction has also been shown

to be affected in Ames dwarf mice. When isolated cardiomyocytes were electrically stimulated, those from the Ames dwarf mouse took a longer time to shorten (98). This increase in shortening time was related to decreased intracellular calcium during peak

contraction and increased clearing time of intracellular calcium during relaxation (98).

These studies indicate that lack of a functional GH/IGF-I axis in the Ames dwarf mice 32

may be responsible for impaired endothelial function, decreased heart size, and decreased cardiomyocyte contractility.

Bovine growth hormone transgenic mice

Transgenic mice provide a powerful model for investigating the biological effects of hormones. A transgenic mouse model that mimics the hypersecretion of GH by overexpression of the bovine growth hormone (bGH) gene (99) represents a suitable model for studying the cardiac phenotype of acromegaly. A large number of studies have investigated many aspects of the cardiovascular system in bGH mice. The following discussion will focus specifically on those studies examining cardiac structure and function, endothelial function, blood pressure homeostasis, and renal performance.

The bGH mouse grows much larger than wild type littermates, has significantly larger organ mass, and experiences a shorter lifespan (99). Microscopic studies of cardiomyocyte fibers from six month old have shown that bGH mice have hypertrophic myofibers compared to wild type controls (100). While acute hypertrophy can be physiologically adaptive, too much hypertrophy can lead to ineffective heart function.

Indeed, myelin structures are found intermittingly in six-month-old bGH cardiac tissue and may point to pathological changes in cardiac innervation due to GH hypersecretion

(100). Supporting this claim, six-month-old bGH mice also demonstrate a downregulation in the number of parasympathetic muscarinic receptors in the heart, pointing to a loss of vagal tone and a possible increase in sympathetic tone (100). These findings agree with the initial increase in cardiac function, or hyperkinetic syndrome, which is observed in the acute phase of acromegaly cardiomyopathy—both the 33

hypertrophy and increased sympathetic tone can lead to increased contractility and

positive chronotropy.

Direct cardiac function in bGH mice has been assessed in at least two studies.

Echocardiographic analysis of 8-month-old bGH mice reveals massively enlarged hearts, decreased systolic function, and decreased fractional shortening (101). Along with these

functional changes, there is a decrease in high-energy phosphocreatine to ATP ratios, and

the presence of dysmorphic mitochondria in the heart of bGH mice (101). Nearly a

decade later, Izzard et al. used ventricular cannulation and isoprenaline challenge to show

that there is no difference in ventricular developed pressure of bGH mice versus controls

(102). However, the age of these mice was not noted in the publication.

Blood pressure analysis has also been conducted in bGH mice with conflicting results. Direct comparison between the studies is difficult due to various promoter/enhancer elements used to drive the transgene expression and the age of the mice during analysis. However, three studies have reported increased systolic blood pressure in bGH mice (102-104), while three other studies have reported no change in systolic blood pressure (101, 105, 106). We recently demonstrated that young male bGH mice less than 6 months of age have normal systolic blood pressure, but after 6 months of age they develop increased systolic blood pressure that remains elevated at least through the first year of life when the study concluded (104). Thus, age differences may explain the variation observed in these studies.

The cause of changes in blood pressure in bGH mice are of interest due to the increased prevalence of hypertension in patients with acromegaly (107). In 1989, despite 34

their measurement of normal systolic blood pressure, Dilley and Schwartz observed

significant increases in vascular wall mass and an increased wall-to-lumen ratio in the mesenteric vessels, which are normally indicators of hypertension (105). They attributed these findings to an unknown genetic mechanism that permanently fixed the mesenteric vascular networking pattern. In addition to reporting increased mean arterial blood pressure in bGH mice, Bohlooly et al. also investigated hemodynamic properties by recording differences in hindquarter perfusion rates and the response to both acetylcholine (Ach)-mediated vasodilation and endothelium-independent vasodilator sodium-nitroprusside (SNP) in mesenteric vessels (103). Results establish that an increase in baseline perfusion flow to the hindquarters is necessary for female bGH mice to obtain the same perfusion pressure as their WT counterparts, pointing to increased hindquarter vascular resistance that can be explained by a narrower average lumen diameter in the vascular bed measured (103). However, there was no difference in the vasodilator response to Ach between the bGH and control mice, leading to the conclusion that the observed peripheral resistance was due to structural narrowing of the resistance vessels and not endothelial dysfunction or vascular reactivity.

Endothelial dysfunction, commonly characterized by a shift in the endothelium to a reduced vasodilatory and proinflammatory state (108) has been shown to precede

adverse cardiac events and parallel other comorbid conditions such as diabetes mellitus

and renal disease (109). In contrast to the study by Bohlooly et al., Andersson and

colleagues took a more comprehensive approach in investigating the role of excess GH

on endothelial and vascular function (110). They report that both young (9-11 weeks) and 35

aged (22-24 weeks) bGH mice had significantly impaired maximal relaxation in response

to Ach in the carotid arteries compared to the control mice. However, administration of

Mn(III)tetrakis(4-benzoic acid) porphyrin chloride (MnTBAP), a superoxide dismutase

(SOD) mimetic, eliminates this difference only in the young bGH mice (110). On the other hand, only aged bGH mice were reported to have an impaired maximal relaxation response to Ach in the aorta compared to their counterparts. Furthermore, young bGH mice show significantly higher aortic extracellular SOD (EC-SOD) and eNOS mRNA expression compared to the control mice whereas no differences are found in the aged mice (110). A commonly known mechanism responsible for endothelial dysfunction often leading to hypertension is the role of oxidative excess, due to an increase in the generation of reactive oxygen species, in diminishing the bioavailability of endothelial nitric oxide (NO) (108, 110). Though there is no substantial evidence associating excess

GH with increased production of ROS, the effect of MnTBAP in endothelial function and response to Ach in this study make it reasonable to believe that initiation of endothelial dysfunction in bGH transgenic mice is caused by oxidative excess. These results suggest that there is a time- and vessel- specific deterioration of endothelial function, again underscoring the importance of recognizing acute and chronic effects of GH stimulation.

As observed in acromegaly, the bovine growth hormone transgenic mouse displays elevated fluid accumulation compared to wild type control mice. This is likely due to GH mediated kidney changes as the bGH mice develop enhanced kidney weight compared to WT (104, 111). In addition, the glomerulus in bGH mice progressively increases in size that is disproportionate to kidney or body weight (112). Doi et al. 36

confirmed that the bGH mice had detectible mesangial proliferation, asymptomatic

enlargement of the somatic kidney cells representing the first stages of

glomerulosclerosis, at 4 weeks of age that progressively developed into diffuse

glomerulosclerosis (113). At 6 months of age peak sclerosis is observed (113).

Interestingly, this mimics the time point in which the bGH mice have been shown to

develop hypertension relative to controls (104). In addition to the structural morphology,

albuminuria is reported to be positively correlated with the glomerulosclerosis

development (112). These sclerotic changes develop independent of body weight (112),

kidney weight (112), hyperglycemia (113) and IGF-I levels (114). Interestingly, scarring

of the glomerulus is regulated by a different portion of the GH molecule than is body or

kidney growth (114).

Glomerulosclerosis in bGH mice presents as an abundance of extracellular matrix

and a reduction in glomerular cells, a process similar to that of diabetic nephropathy

(115). In hyperglycemic states, like diabetes mellitus, GH tends to be elevated (116,

117). However, unlike patients with poorly controlled diabetes, kidney damage observed

in the bGH mouse is independent of hyperglycemia (113). Chen et al. have shown that

when bGH mice, bGH mice expressing a GH anatgonist, and littermate controls are

administered streptozotocin to induce hyperglycemia, the bGH antagonist group are

protected from glomerulosclerosis development, both in the presence and absence of

hyperglycemia (118, 119). Additionaly, Flyberg et al. have shown that treatment of

streptozotocin-induced diabetic mice with a GHR anatgonic (G120K) normalized

glomerular expansion and decreased kidney weight and urinary albumin levels (120). 37

Further, mice with transgenic expression of a GH receptor antagonist (121) as well as

mice with a genetic knock out of both the GH receptor and GH receptor binding protein

genes showed resistance to streptozotocin induced diabetic nephropathy despite having

high circulating GH (122). Together, these data indicate that GH plays a key role in

glomerular expansion and is a likely target for treatment of diabetic nephropathy.

It is well established that GH promotes lipolysis and fatty acid oxidation.

Therefore, the bGH mice display high circulating levels of cholesterol and triglycerides

compared to control mice (123). In a pro-inflammatory state, as observed in bGH mice

(104), abnormal lipoprotein metabolism can lead to atherosclerotic plaque formation.

Interestingly, when crossed with an apolipoprotein E deficient (ApoE-/-) mice, a mouse

model known to develop arterial plaque at an accelerated rate, the bGH mice displayed plaque formation greater than ApoE-/- mice alone (124). This suggests a pro- atherosclerotic phenotype for the bGH. The hypertension present in the aged bGH mice likely accelerates blood vessel damage and small capillary beds, like the glomerulus, are especially prone to atherosclerosis. The bGH mice develop glomerular lipid deposits and have increased macrophage scavenger receptor expression. Both of these factors play a role in plaque formation (123) and suggest a lipid-centered development of glomerulosclerosis.

Activation of RAAS components is a recognized feature of bGH mice. Bielohuby et al. discovered the bGH mice display elevated aldosterone levels despite no increase in circulating renin or adrenal aldosterone synthase protein levels (47). Interestingly, when the bGH mice co-express IGF binding protein 2, which sequesters IGF-I, there is no 38 change in aldosterone compared to mice expressing only bGH (47). Thus, aldosterone induced fluid retention may be due to direct action of GH, independent of IGF-I, renin, or aldosterone synthase. When the bGH mice are subjected to angiotensin converting enzyme (ACE) inhibition, they develop glomerulosclerosis and kidney hypertrophy

(125). Thus, despite increased blood pressure, kidney damage is likely independent of increased hemodynamics. We have shown that at 12 months of age bGH mice have a high ACE/ACE2 ratio relative to controls suggesting a shift towards the ACE/AngII/AT1 receptor axis of the RAAS (104). This shift correlates with the kidney hypertrophy, mesangial proliferation, and cardiac fibrosis (104). Taken together, these data indicate that the effects of chronic GH stimulation of the kidney may be a precipitating factor in the development of elevated blood pressure in bGH mice.

In addition to the many changes noted in the RAAS with bGH mice, alterations in the natriuretic peptide system have also been observed. At 6 and 12 months of age, the bGH mice exhibit elevated levels of BNP mRNA compared to WT (104). However, they display reduced circulating BNP protein levels at 5 and 7 months compared to WT (104).

These data indicate that the bGH heart is stressed and that an unknown mechanism is responsible for the lack of BNP protein formation. Dirsch et al. also report ANP levels in older bGH mice (126). Twenty-seven-week-old bGH mice show elevated ANP mRNA transcript levels in heart tissue from the bGH mouse relative to the younger mice

(7 weeks) and age-matched controls (126). Despite the increased transcript levels, the older mice had significantly lower circulating ANP protein levels compared to WT.

Alternatively, the young mice exhibited increased levels of ANP protein and low levels 39 of pro-ANP compared to WT controls. This interesting similarity between ANP and

BNP studies in the bGH mice indicates that GH is likely altering the natriuretic peptide system of the bGH mice. Possible explanations include suppressed natriuretic peptide cleavage rates, suppressed formation rates, or enhanced clearance by the natriuretic peptide clearance receptor (NPRC).

Growth hormone receptor null mice (GHR-/-)

The GHR null (GHR-/-) mouse, produced in 1997, is often used as a model for human Laron Syndrome (LS), an autosomal recessive disorder resulting in dwarfism and described by insensitivity to growth hormone due to a genetic mutation in its receptor

(127). Key similarities between affected patients and the “Laron mouse” include growth retardation, delayed sexual maturation, severely suppressed IGF-I levels, reduced cardiac dimensions and increased longevity (127-129). While LS patients tend to be hypoglycemic and appear to be insulin resistant as observed by high levels of plasma insulin and prevalence of obesity, GHR-/- mice are obese but show a substantial reduction in blood insulin levels (128, 130).

Given the disruption in GH signaling, one may expect GHR-/- mice to have an increased risk of metabolic or cardiovascular mortality as seen in GHD patients; however, the GHR-/- mouse is the longest lived mouse (129, 131). Echocardiographic studies of the GHR-/- mouse have shown that systolic blood pressure is reduced by 25% compared to wild-type controls (132). Furthermore, findings also point to systolic dysfunction, with GHR-/- mice showing decreased left ventricular end diastolic diameter and decreased posterior wall thickness compared to wild type controls (132). 40

Surprisingly, the cardiac output of the GHR-/- mouse, when normalized to body weight, is

not significantly altered from wild-type controls (132). These results point to impaired

parameters that would normally characterize cardiac dysfunction, but in the case of the

small body size of the GHR-/- mice, the impaired heart is able to provide enough output to

meet the demands of the body. These results of cardiac function developing in line with

body size in the GHR-/- mice are mirrored in a later study by Izzard et al. (102). Neither

of these studies, however, investigated exercise tolerance of the GHR-/- mouse, which

may accentuate the differences found in cardiac structure.

In terms of endothelial function, GHR-/- mice show a 146% increase in aortic

eNOS mRNA expression, which is consistent with an increased sensitivity to Ach-

mediated dilation and reduced aortic media thickness (29%) compared to WT mice (132).

Decreased systolic blood pressure may be a direct result from an overall reduction of

global systolic function as observed by a 43% reduction in cardiac output (CO), which is

comparable to the 43% reduction in GHR-/- body weight. These findings suggest GHR-/- mice most likely maintain normal endothelial function via increased systemic production of NO despite altered cardiac structure. This is in contrast to what is observed in growth hormone deficient (GHD) patients, who display endothelial dysfunction likely from a decrease in NO production either due to oxidative excess or reduced antioxidant defense.

Hence, it is not unreasonable to suggest that normal endothelial function paralleled with increased sensitivity to Ach-mediated vasodilation, increased insulin sensitivity, and reduced body weight seen in GHR-/- mice contribute to increased longevity (127-129,

132). 41

Also unlike the bGH mice, the lack of GH signaling in GHR-/- mice is associated

with an opposite effect on the kidney and the RAAS. Reduced growth hormone action

(due to GH antagonist or GH receptor deletion) has been shown to result in protection

from partial nephrectomy induced kidney damage (133), development of hypertension

(132), and glomerulosclerosis (121). Plasma renin concentrations are reported to be 40%

lower in GHR-KO mice, though no differences in aldosterone levels are observed (132).

At young age (2 to 3 months) GHR-/- show a low ACE/ACE2 ratio compared to WT,

indicating a shift towards the cardio and renal protective ACE/Ang-(1-7) Mas receptor

axis (125). The RAAS differences between the bGH and GHR-/- mice, two models of

opposing GH action, likely play a role in cardiovascular health and longevity difference

between the two. Future investigation of RAAS components across lifespan is necessary

to further characterize the relationship between GH and the RAAS.

Cardiac IGF-I transgenic and IGF-I receptor null mice

While the focus of this review is not IGF-I, we would like to highlight a few recent studies that have solidified a role for GH and IGF-I in cardiovascular function.

Global IGF-I null mice experience severe growth retardation and greatly increased

mortality (134). Therefore, much of the data concerning IGF-I effects on the

cardiovascular system come from studies of cardiac specific IGF-I receptor null mice or

transgenic IGF-I mice.

Overexpression of local IGF-I in mice using the α-actin promoter results in high

levels of IGF-I in muscle and heart without a concomitant increase in circulating IGF-I.

These mice develop physiologic concentric ventricular hypertrophy before 10 weeks of 42

age with no decline in cardiac function. After 10 weeks, however, the chronic effects of

high IGF-I manifest as ventricular stiffening, loss of ventricular compliance, decreased

cardiac function, and fibrotic changes on ventricular histological examination (135).

Cardiac specific deletion of IGF-IR (CIGF1RKO) in mice has been reported to result in

normal cardiac development but an attenuated response to exercise induced hypertrophy

(136). This may be due, in part, to an upregulation of AMP kinase (AMPK) signaling, which is known to inhibit Akt signaling (a principal pathway responsible for cardiac growth and hypertrophy) (136). Interestingly, when the CIGF1RKO mice are crossed with cardiac-specific insulin receptor null mice (CIRKO), dilated cardiomyopathy develops in young mice and results in heart failure (137). CIRKO mice alone are known to exhibit small hearts, increased fetal myosin expression, and a change in cardiac

metabolism to favor glucose over fatty acid metabolism (138).

Recently, a tamoxifen-inducible, cardiac-specific IGF-I receptor gene disrupted

mouse (iCM-IGF-IRKO) was described. Surprisingly, induction of IGF-IR disruption in

three-month-old mice does not lead to any functional changes measured by in vivo

pressure measurement or MRI at 6 months of age (3 months post induction) (139).

When disruption is induced at 11 months of age, however, there is an approximate 25%

decrease in ventricular developed pressure with no changes in wall thickness, left

ventricular volume, or cardiac fibrosis (139). In the presence of streptozotocin treatment,

the iCM-IGF-IRKO have similar cardiac function to controls, effectively ruling out a

compensatory effect of insulin (139). This study highlights that IGF-I signaling is

important for sustaining cardiac function in old age. 43

Future perspectives

Clinical studies of patients with GHD, Laron Syndrome, and acromegaly and

experimental studies with animal models of disrupted and enhanced GH signaling allude

to a principal role of GH in cardiac function and structure. Given this evidence, it is

surprising that, to date, no group has developed a cardiac-specific GHR gene disrupted mouse. Studies in CIGF1RKO (136, 137) and iCM-IGF-IRKO (139) mice have shown

that loss of IGF-I signaling does not alter cardiac development and baseline function;

therefore, GH signaling may be a more important factor. Two areas that deserve more

attention in terms of the already established models of GH action are cardiac energy

metabolism and cardiac hypertrophic response to exercise. IGF-I has been reported to

play key roles in both of these processes, and it is therefore likely that GH also plays a

role. As previous discussed, recent studies indicate a subset of CHF patients with GHD

respond favorably to GH therapy (92, 93). As these types of studies become more

widespread, it will be even more important to understand specifically what effects GH are

having not only in the heart, but also the vasculature, and the renal system.

Acknowledgements

We would like to acknowledge Lauren Volpe, M.Ed (Patton College of

Education, Ohio University) for her careful editing of the manuscript.

Funding

This work was supported in part by the Gates Millennium Scholars (GMS)

Graduate Fellowship program; the State of Ohio's Eminent Scholar Program that includes a gift from Milton and Lawrence Goll; National Institutes of Health (NIH) Grants

P01AG031736; the Provost Undergraduate Research Fund, and the Diabetes Institute at

Ohio University. 45

CHAPTER 2: SPECIFIC AIMS

As reviewed in Chapter 1, the GH/IGF-I axis is believed to play an important role in both the development and maintenance of cardiac structure and function. The following studies seek to add to our knowledge of GH action by examining the bovine

GH transgenic mouse (which chronically expresses high levels of bovine GH) and developing a new mouse line that will allow us to temporally disrupt cardiac GH signaling.

We were specifically interested in examining blood pressure in the bGH mice due to conflicting results in the literature concerning systolic blood pressure. The wide array of mouse ages and technical methods previously used to measure blood pressure are likely one reason for the discordant findings. In addition to blood pressure, we sought to examine extra-cardiac pathways that may be contributors to blood pressure change in bGH mice. Specifically, we focused on examining insulin resistance, brain natriuretic peptide, and components of the ACE2/Ang(1-7)/Mas pathway.

Therefore the specific aims for our studies in bGH mice were the following: bGH Aim #1: Establish a longitudinal profile of systolic blood pressure in bGH mice using a non-invasive technique. Hypothesis: Blood pressure in bGH mice is age dependent and likely correlates with the significant shift in body composition that occurs around 5-7 months of age.

bGH Aim #2: Examine contributory pathways known to impact blood pressure including 1) development of insulin resistance, 2) production of brain natriuretic 46

peptide, and 3) shifts in the ACE2/Ang(1-7)/Mas pathway. Hypothesis: The

development of dysfunctional blood pressure in bGH mice is related to the development

of insulin resistance, inappropriate brain natriuretic peptide response, and shifts in the

ACE2/Ang(1-7)/Mas pathway.

Our desire to produce a temporally controllable cardiac-specific GHR gene

disrupted mouse line is more exploratory. Clinical evidence from acromegalic, GHD, and

Laron syndrome patients allude to a significant impact of GH action on the heart (see

Chapter 1). However, there are are at least two outstanding questions: 1) What is the role

of GH induced intracellular signaling in maintaining the structure and function of the

adult heart? 2) Could defects in cardiac GH signaling explain the increased mortality

associated with GH dysfunction? A distinct advantage of our choice to produce a

temporally controllable GHR-/- mouse line is that it allows us to observe any functional and molecular changes that may occur in a mouse that otherwise developed in the presence of intact GH signaling.

Specifically our aims for the production of an inducible, cardiac-specific GHR gene disrupted mouse (iC-GHRKO) are: iC-GHRKO Aim #1: Produce and validate inducible, heart-specific GHR

disruption. Hypothesis: Crossing of a cardiac-specific, tamoxifen inducible Cre

recombinase expressing mouse line with our mouse line expressing LoxP sites around

exon 4 of the GHR gene will allow us to selectively disrupt the GHR gene in

cardiomyocytes.

47 iC-GHRKO Aim #2: Investigate the physiological consequences of acute, heart specific, GHR gene disruption. Hypothesis: Acute loss of the GHR (and thus GH induced intracellular signaling) within cardiomyocytes will alter the functional capacity of the heart.

iC-GHRKO Aim #3: Explore the effects of heart specific, GHR gene disruption on the expression of the principal cardiac calcium channels. Hypothesis: If disruption of cardiac GH signaling results in decreased cardiac performance, then one of the mechanisms will be through perturbation of the calcium channel gene expression.

iC-GHRKO Aim #4: Characterize the metabolic and anthropomorphic phenotype of mice with disrupted cardiac GHR gene. Hypothesis: GH is a master regulator of growth and metabolism, however, cardiac specific GHR disruption will not perturb perturb systemic metabolism.

CHAPTER 3: ELEVATED SYSTOLIC BLOOD PRESSURE IN MALE GH

TRANSGENIC MICE IS AGE-DEPENDENT2

Abstract

Acromegaly is associated with an increased incidence of cardiovascular disease.

Transgenic mice expressing bovine growth hormone (bGH) gene have previously been used to examine the effects of chronic GH stimulation on cardiovascular function.

Results concerning systolic blood pressure (SBP) in bGH mice are conflicting. We hypothesized that these discrepancies may be the result of the various ages of the mice used in previous studies. In the current study, SBP was assessed monthly in male bGH mice from 3 to 12 months of age. Factors known to alter blood pressure were assessed during this time and included: levels of brain natriuretic peptide (BNP) and glucose homeostasis markers, and renal levels of angiotensin converting enzyme 2 (ACE2) and endothelial nitric oxide synthase (eNOS). Beginning at six months of age bGH had increased SBP compared to wild-type (WT) controls, which remained elevated through

12 months of age. Despite having increased blood pressure and cardiac BNP mRNA, bGH mice had decreased circulating levels of BNP. Additionally, bGH mice had an age- dependent decline in insulin levels. For example, they were hyperinsulinemic at 3 months, but by 11 months of age were hypoinsulinemic relative to WT controls. This decrease in insulin was accompanied by improved glucose tolerance at 11 months.

Finally, both ACE2 and eNOS expression were severely depressed in kidney of 11-

2 The work presented in this chapted was previous published in Endocrinology (2014) 155(3): 975-86. The contributing authors are: Adam Jara, Chance M Benner, Don Sim, Xingbo Liu, Edward O List, Lara A Householder, Darlene E Berryman, and John J Kopchick.

49 month-old bGH mice. These results indicate that elevated systolic blood pressure in bGH mice is dependent on age, independent of insulin resistance, and related to alterations in both the natriuretic peptide and renin-angiotensin systems.

Introduction

Acromegaly is a disease caused by increased GH secretion often secondary to a pituitary adenoma and results in profound metabolic and cardiovascular complications.

The development of the clinically recognized disease is slow and most patients are not diagnosed until the fourth decade of life (30). Metabolically, patients with acromegaly have altered body composition, with increased lean mass and decreased fat mass and often develop insulin resistance and subsequent diabetes mellitus (30). In the cardiovascular system, acromegaly leads to left ventricular hypertrophy with subsequent cardiomyopathy, and a predisposition to developing hypertension and atherosclerosis

(140, 141). Left untreated, the chronic exposure to high GH levels causes the development of a unique cardiomyopathy characterized by concentric hypertrophy of both ventricles and eventual congestive failure (78, 142). The evolution of cardiovascular disease in patients with acromegaly is unclear. The overarching question has been: are the resulting cardiovascular deficits due to direct actions of GH/IGF-I on cardiomyocytes or are they secondary to the chronic changes in the vasculature and renal systems?

Bovine GH (bGH) transgenic mice are commonly used as an animal model of acromegaly because they exhibit gigantism, with increased body length and mass, and have elevated serum levels of GH and IGF-I (143-145). bGH mice also exhibit altered 50 body composition with increased lean mass, decreased fat mass, increased fluid mass

(111, 130), altered metabolism including the development of insulin resistance (146), endothelial dysfunction (110), altered blood pressure (101-103, 105, 106), and decreased life span (147). Previous studies concerning the cardiovascular function of bGH mice have been mixed. Reports concerning blood pressure in bGH mice have shown both normal (101, 105, 106) and elevated blood pressure (102, 103). Salt challenge does not affect blood pressure in bGH mice, which suggests a structural or hormonal deficit underlying the change in blood pressure (103). There is evidence from studies of bGH mice that chronic GH may lead to endothelial dysfunction and structural changes of mesenteric vasculature (103, 110). Hearts of bGH mice are enlarged, show deteriorating function, and exhibit increased hypertrophy and fibrosis (101, 105). In contrast, isolated bGH cardiomyocytes show no change in function and demonstrate an increased sensitivity to calcium (148) and an inability to respond to acute insulin stimulation (148), implicating a multi-system mechanism for the cardiovascular dysfunction found in bGH mice that may be linked to insulin resistance.

In addition to the heart, the kidneys of bGH mice exhibit glomerular hypertrophy with severe mesangial sclerosis, which correlate with an increasing albumin to creatinine ratio (149). Counterintuitively, this renal phenotype has been associated with an increased glomerular filtration rate (103). Despite this report of increased kidney function, increased GH action has been implicated with alterations in the renin- angiotensin system (RAS). Indeed, circulating aldosterone levels are known to be increased in both patients with acromegaly and bGH mice; however, the increased levels 51

appear to be dependent on GH and independent of renin and IGF-I (47). Interestingly,

long-lived GHR-/- mice (which lack GH signaling) show a shift in the RAS system away

from the angiotensin converting enzyme (ACE)/Angiotensin II arm to the favor the

ACE2/angiotensin 1-7 (Ang(1-7))/Mas pathway (125). The ACE2/Ang(1-7)/Mas

pathway is thought to be protective and antagonizes the development of renal sclerosis

and cardiac fibrosis (150). Unfortunately, no studies have been conducted that examine

this alternate pathway in bGH mice.

Despite several previous studies describing the nature of cardiovascular

complications in bGH mice, there are discrepancies that may be due to various ages of the mice examined. Given the shortened life span of bGH mice, the time course of the

development of cardiovascular complications is important in understanding the

progression of acromegaly and the chronic effects of GH. Here we present data

describing an age dependent elevation in systolic blood pressure which develops

independent of bodyweight. Further, we challenge the traditional belief that bGH mice

are insulin resistant throughout life and show that older bGH mice are more glucose

tolerant and have lower circulating insulin levels than controls. Finally, we examine

several factors which may influence blood pressure in bGH mice with a focus on brain

natriuretic peptide (BNP) and renal expression of the ACE2/Ang(1-7)/Mas pathway.

Materials and methods

Animals

Male bGH transgenic mice, generated as previously described (130), and wild-

type (WT) littermate controls were used for this study. Mice were housed at a maximum

density of four mice per cage in the temperature controlled (23°C) vivarium and exposed to 14h/10h light/dark cycle. All mice were allowed ab libitum access to water and food

(ProLab RMH 3000, PMI Nutrition International, Brentwood, MO.). All procedures performed with the mice were approved by the Institutional Animal Care and Use

Committee (IACUC) at Ohio University and are in accordance with all standards set forth

by federal, state, and local authorities.

Body composition measurements

Body composition was measured in bGH (n=9) and WT littermates (n=7) monthly

from 3-12 months of age. Measurements were collected using a desktop NMR Bruker

LF50 Minispec as previously described (145).

Non-invasive blood pressure measurement

Systolic blood pressure (SBP) was measured monthly from 3-12 months of age in

bGH (n=9) and WT littermates (n=7). SBP measurements were made using a non-

invasive blood pressure tail-cuff system (#IN125/M, ADInstruments) connected to a

PowerLab system (#PL3508, ADInstruments). For each measurement, mice were placed

in a mouse restrainer and maintained at approximately 37 ºC using a heating pad

throughout all training periods and measurements. To ensure acclimation to the

procedure, each mouse underwent four days of mock measurements prior to data 53

collection. Each training day consisted of five SBP measurements. For SBP readings, at

least five technical replicates were performed for each time point on each mouse. The

first measurement was always discarded to avoid variation from stress due to handling.

As suggested by the manufacturer, we identified SBP as the cuff pressure at which the

tail pulse first re-appeared after occlusion. All data were analyzed using Lab Chart v7.4

(ADInstruments).

Histological preparation and measurements

Whole hearts and kidneys were dissected from 3, 6, and 12 month bGH and WT littermates (N=2) and fixed in 15% (v:v) neutral buffered formalin for 24 hours. Samples were then transferred to 70% ethanol and shipped to AML Laboratories for paraffin embedding and processing. Longitudinal sections (5µm) of whole heart were stained with

Masson Trichrome to highlight collagen deposits. Longitudinal sections (5µm) of whole kidney were stained with periodic acid schiff (PAS) stain without diastase digestion to highlight areas of increased matrix expansion. All micrographs were collected using

Nikon Elements imaging software. All images were processed using ImageJ (151) software. Kidney glomerular area was collected in 10 non-overlapping fields (400x) from each mouse. Heart collagen content was determined by collecting 20 non-overlapping fields (200x) from each mouse. An automated threshold procedure was used to separate collagen from other cellular components (see Supplemental Materials and Methods for description).

Real-time quantitative PCR (RTqPCR)

Two step RTqPCR was performed using total RNA isolated from heart ventricular samples of bGH (N=5) and WT (N=9) mice. Reverse transcription was performed using the Maxima First Strand cDNA Synthesis Kit (#K1642, Thermo

Scientific). RTqPCR was performed in a BioRad iCycler machine using the Maxima

SYBR Green/Fluorescein qPCR kit (#K0242, Thermo Scientific). All data were analyzed using qBase Plus v2.4 (Biogazelle) and are in compliance with MIQE (152) standards.

Details can be found in the Supplemental Materials and Methods. Primer sequences are listed in Supplemental Table 3.1 (Appendix C).

Plasma measurements

Whole blood was collected from the tail tips of bGH and WT littermates after a

12 hour overnight fast by clipping ~1mm of the tail tip and collecting ~250µL of blood using heparinized capillary tubes. Plasma was collected after centrifugation for 10 minutes at 7000g, 4°C. Circulating levels of BNP were determined using the Mouse BNP

EIA (#EIA-BNP-1, RayBiotech) following the manufacturer’s directions. Levels of insulin, c-peptide, MCP-1, and IL-6 were measured using a Milliplex Mouse Metabolic

Panel (#MMHMAG-44K, Millipore) according to the manufacturer’s instructions.

Fasting blood glucose levels were collected every three months from tail vein bleeding using OneTouch Ultra test strips and glucometers (Lifescan).

Intraperitoneal insulin/glucose tolerance testing (ITT/GTT)

For the GTT, bGH (n=8) and WT littermates (n=14) were fasted for 12 hour prior to measurements. Each mouse received an intraperitoneal injection of 10% glucose at 55

0.01 ml/g body weight. For the ITT, bGH (n=8) and WT littermates (n=14) were non-

fasted. Each mouse received an intraperitoneal injection of 1U/kg bodyweight insulin

(Humilin R, Lilly). For both GTT and ITT, blood glucose measurements were collected

using OneTouch Ultra test strips and glucometers before glucose or insulin injection and at 15, 30, 45, 60, 90, 120, and 150 minutes after injection.

Immunoblots

Protein was isolated from homogenized sections of flash frozen kidney tissue

(~30mg) from bGH (N=4) and WT (N=3). Protein samples (20µg) were separated on

10% SDS-polyacrylamide gels before being transferred to PVDF membranes

(#RPN2020LFP, GE Healthcare). Subsequently, membranes were blocked and probed with primary antibodies: ACE (#SC-20791, 1:200), ACE2 (#SC-20998, 1:200), eNOS

(#SC-654, 1:200), (Santa Cruz Biotechnology); GAPDH (#2118, 1:1000), (Cell

Signaling). Finally, membranes were incubated with Cy5 conjugated secondary antibody

(1:2500) (#PA45011, GE Healthcare) and scanned using a Pharos FX laser scanner

(Biorad). Full details can be found in the Supplemental Materials and Methods

(Appendix C).

Statistics

All values are reported as mean ± standard error of the mean (SEM). Statistics

were performed using SPSS v 17.0 (IBM). All time-dependent analysis was performed

using two-way ANOVA with repeated measures, age and genotype as factors. Maulchy’s

test of sphericity was performed on all repeated measures data. The Green-House Geisser

correction was applied if Maulchy’s test was found to be significant. For single time 56

point measurements, equality of variance was tested using Levene’s test and group means

were then compared using an independent student’s t test or a Welch’s t test for unequal variances. For all tests, statistical significance was determined when p<0.05.

Results

Body weight and body composition

There was a significant interaction between genotype and age for body weight, fat, lean, and fluid mass (p<0.05) (Figure 3.1A-D). At every time point from 3-12 months of age, bGH mice have significantly increased body weight (p>0.05) (Figure 3.1A). bGH mice showed a trend of failure to gain fat mass beginning at 4 months of age that became

significant at 6 months of age (p<0.05) (Figure 3.1B). This failure to gain fat mass was

accompanied by an increase in lean mass percentage (Figure 3.1C), which also became

significant at 6 months of age (p<0.05). Fluid mass showed a similar trend, with

increased fluid mass in bGH mice from 6-8 months of age and from 10-12 months of age

(p<0.05).

Body length and tissue mass

Concomitant with increased body weight, bGH mice demonstrated an increased

body length at dissection (Figure 3.1E) with a mean length of 110.2 ± 1.3 mm versus 95.1

± 0.6 mm in controls (p<0.05). Additionally, 12-month-old tissue masses were

significantly different in bGH versus control mice (p<0.05). bGH mice had significant decreases in relative weights of white adipose tissue (WAT) depot mass (72-87%), interscapular brown adipose tissue (BAT) mass (19%), and in whole brain size (14%) 57

Figure 3.1: Body composition, length, and tissue masses. (A) Body weight in grams, (B) % fat mass, (C) % lean mass, and (D) % fluid mass from 3-12 months of age in bGH (dot-dash line) and WT littermates (solid line). (E) 12 month length in mm from tip of nose to anus and (F) tissue mass normalized to body weight and then to WT of 10 dissected tissues. All values are presented as the average within genotype ± SEM. * Significant difference between genotype (p<0.05), ǂ significant difference with age (p<0.05), †significant interaction between age and genotype (p<0.05). bGH: bovine growth hormone transgenic mice, WT: wild-type littermate mice.

58 compared to controls. Tissues significantly increased in bGH mice included liver

(112%), kidney (43%), heart (60%), and lung (25%). In terms of absolute mass, the hearts of 12-month-old bGH mice were 0.248±0.011g versus 0.122±0.003g in WT. The mass of the kidneys of 12-month-old bGH were 0.604±0.019g versus 0.334±0.010g in

WT.

Cardiac histology and fibrosis

In order to determine the effects of chronic GH on cardiac fibrosis, cardiac tissue from 3-, 6-, and 12-month-old bGH and control mice were evaluated for the level of collagen deposition. Figure 3.2A shows representative sections from bGH mice and WT littermates at each time point with the light blue staining representing collagen against the purple and red muscle fibers. The bGH mice had significant increases in percent collagen area at 3 (WT: 7.1±0.6%, bGH: 9.2±0.4%) and 12 (WT: 11.6±0.4%, bGH: 15.9±1.1%) months of age (p<0.05). No difference between bGH and control mice was observed at

6 months of age.

Glomerular histology

Kidneys were examined from 3-, 6-, and 12-month-old bGH and littermate controls to assess glomerular size and structure (Figure 3.2C-D). There was a significant interaction between age and genotype in glomerular tuft size in bGH mice from 3-12 months of age (p<0.05). Visible membrane thickening and mesangial sclerosis were also apparent in kidneys of bGH mice (Figure 3.2C).

Figure 3.2: Heart and kidney histology. (A) Sections of heart stained with Masson’s Trichrome from 3-, 6- and 12-month-old bGH and WT littermates (N=2). (B) Collagen content calculated from 10-20 non-overlapping sections of left ventricular cardiac tissue at each time point. Single arrowhead denotes bright blue collagen deposition. (C) Sections of glomeruli stained with Periodic Acid Schiff stain from 3-, 6-, and 12-month- old bGH and WT littermates (N=2). Single arrowhead denotes glomerular basement membrane thickening, double arrow head denotes mesangial proflieration and matrix expansion. (D) Glomerular tuft area calculated from at least 10 glomeruli from at least 5 non-overlapping sections at each time point. All values are presented as average ± SEM. Scale bars in A are 50µm and in C are 20µm. * Significant difference between genotype (p<0.05), ǂ significant difference with age (p<0.05), †significant interaction between age and genotype (p<0.05). bGH: bovine growth hormone transgenic mice, WT: wild-type littermate mice.

Systolic blood pressure (SBP)

In order to establish longitudinal SBP, measurements were taken each month from

3-12 months of age. Changes in SBP demonstrated a significant interaction between age and genotype (p<0.05). Specifically, from 3-5 months of age, bGH and littermate controls had similar SBP ranging between 102-107 mmHg (Figure 3.3A). At 6 months of age, however, bGH mice had significantly elevated SBP relative to controls (113.6±1.2 mmHg versus WT: 107.5±0.9 mmHg, p<0.05). From 7-12 months of age, bGH mice continued to exhibit higher SBP than controls. The bGH mice had a peak SBP of

119.6±0.7 mmHg (10 months) and the controls had a peak SBP of 111.5±0.6 mmHg (12 months).

Brain natriuretic peptide (BNP) levels in serum and cardiac tissue

Circulating levels of BNP were measured at 5 and 7 months of age to assess levels of natriuretic peptides around the age of increased SBP in bGH mice. Level of circulating BNP tended to be decreased at 5 months of age; however, levels did not reach statistical significance (59.7±2.1 pg/mL versus WT: 108.3±27.2 pg/mL, Figure 3.3 D-E, p=0.12). At 7 months of age, bGH mice had a significant and more substantial decrease in circulating BNP levels (29.0±6.2 pg/mL versus 116.7±25.5 pg/mL, p<0.05). In cardiac tissue, BNP mRNA levels showed a nearly significant (p=0.054) increase at 6 months of age and were significantly increased by more than three-fold at 12 months of age (Figure

3.3 B-C, p<0.05).

Figure 3.3: Systolic blood pressure, BNP, and heart calcium channels. (A) SBP measured in un-anaesthetized male mice (N=7-9) from 3-12 months of age. Cardiac left ventricular BNP RNA levels were measured at 6 (B) and 12 (C) months of age (N=5-9). Circulating BNP levels were measured by ELISA at 5 (D) and 7 (E) months of age (N=7- 9). RNA levels of the major calcium channels in heart were measured at 6 months (F) and 12 months (G) of age. All values are presented as average ± SEM. *Significant difference between genotype (p<0.05), ǂsignificant difference with age (p<0.05), †significant interaction between age and genotype (p<0.05). bGH: bovine growth hormone transgenic mice, WT: wild-type littermate mice, SBP: systolic blood pressure, BNP: brain natriuretic peptide, SERCA2: sarcoplasmic endoreticulum calcium exchanger 2, LTCC: L-type calcium channel, NCX1: dodium calcium exchanger 1, RYR2: ryanodine receptor 2.

Cardiac calcium channel gene expression

Results from both 6- and 12-month-old bGH and WT littermates (Figure 3.3 F-G)

showed that there was no difference in mRNA expression of any of the four cardiac

calcium channels at either age between genotypes.

Glucose homeostasis and insulin levels

Both FPG and plasma insulin levels showed a significant interaction between age and genotype (p<0.05). FPG levels (Figure 3.4A) at 3 months of age in bGH and

WTwere similar (WT: 112.3±6.8 mg/dL versus bGH: 111.8±9.6 mg/dL, p=0.968). By 6 months of age, bGH mice tended (p=0.07) to have decreased FPG (WT: 163.9±14.2 mg/dL vs bGH: 132.2±3.9 mg/dL). At 9 and 12 months of age, bGH mice had significantly (p<0.05) decreased FPG levels relative to littermate controls (9 months WT:

166.2±10.4 mg/dL vs bGH: 125.0±4.3 mg/dL; 12 months WT: 170.6±11.8 mg/dL vs bGH: 92.7±3.8 mg/dL).

Plasma insulin levels (Figure 3.4B) showed a significant interaction between age and genotype (p<0.05). At 3 months of age bGH mice were hyperinsulinemic relative to controls (WT: 707±124 pg/mL vs bGH: 1352±166 pg/mL, p<0.05). Insulin levels were similar at 6 months of age, but by 12 months of age bGH mice were hypoinsulinemic compared to controls (WT: 1192±144 pg/mL vs bGH: 765±76 pg/mL). C-peptide levels were also measured at 3, 9, and 11 months of age but did not reach statistical significance

(Figure 3.4C). The trend of C-peptide levels did match that of plasma insulin.

Insulin (ITT) and glucose tolerance tests (GTT) were conducted using 11-month- old bGH and WT controls. bGH mice showed no difference at any time point in response 63

Figure 3.4: Glucose homeostasis. Fasting blood glucose (A), fasting plasma insulin (B), and fasting plasma c-peptide (C) levels at 3, 9, and 11 months of age (N=7-10). (D) Intraperitoneal insulin tolerance testing was performed in 11-month-old non-fasted mice by injecting mice (N=8-10) with 1U/kg bodyweight insulin and subsequent sampling of blood glucose. (E) Intraperitoneal glucose tolerance testing was performed in 11-month- old mice (N=8-10) following a 12 hour fast by injecting mice with a 10% glucose solution at 0.01ml/g bodyweight and sampling glucose before injection at 15, 30, 45, 60, 90, 120, and 150 minutes after injection. (F) Area under the curve (AUC) of the glucose tolerance test was calculated for both groups of mice. *Significant difference between genotype (p<0.05), ǂsignificant difference with age (p<0.05), †significant interaction between age and genotype (p<0.05). bGH: bovine growth hormone transgenic mice, WT: wild-type littermate mice.

to the ITT (Figure 3.4D). In contrast, the GTT (Figure 3.4E-F) demonstrated that bGH

mice had significantly improved glucose clearance with a calculated area under the curve

(AUC) of 29,378±1,549 mg/dL*min-1 versus 42,399±5,499 mg/dL*min-1 (p<0.05) in

littermate controls.

Circulating inflammatory cytokines

Levels of circulating MCP-1 and IL-6 were measured in 2-, 8-, and 11-month-old bGH and WT controls. IL-6 levels showed an increase throughout age regardless of genotype while both IL-6 and MCP-1 levels showed an interaction with age and genotype. In young 2-month-old mice, bGH had similar levels of IL-6, but increased levels of MCP-1. By 8 months of age, bGH had significantly eleveated circulating levels of both IL-6 and MCP-1. By 11 months of age, levels of both cytokines were significantly elevated in bGH mice with IL-6 levels nearly triple (WT: 46.3±8.6 pg/mL,

bGH: 117.3±33.2 pg/mL, Figure 3.5A) and MCP-1 levels almost double (WT: 98.4±25.1

pg/mL, bGH: 171.6±22.9 pg/mL, Figure 3.5B) that of littermate controls (p<0.05).

ACE, ACE2, and eNOS expression in 12-month-old bGH kidney

Renal levels of ACE, ACE2, and eNOS protein were measured in 12-month-old

mice. Expression of ACE (Figure 3.6A) tended to be higher in bGH mice versus controls

(P=0.08) and the levels of ACE2 (Figure 3.6B) and eNOS (Figure 3.6C) were severely

and significantly depressed (p<0.05) in bGH mice by ~82% and ~75%, respectively.

Figure 3.5: Circulating inflammatory cytokines. Plasma levels of interleukin-6 (IL-6) (A) and monocyte chemotactic protein 1 (MCP-1) (B) at 2, 8, and 11 months of age (N=7-10). *Significant difference between genotype (p<0.05), ǂsignificant difference with age (p<0.05), †significant interaction between age and genotype (p<0.05). bGH: bovine growth hormone transgenic mice, WT: wild-type littermate mice.

Figure 3.6: Expression of ACE, ACE2, and eNOS in kidney. Immunoblot analysis of 12-month-old ACE (A), ACE2 (B), and eNOS (C) levels normalized to GAPDH in kidney (N=3-4). * Significant difference between genotype (p<0.05), bGH: bovine growth hormone transgenic mice, WT: wild-type littermate mice.

Discussion

The goal of our study was to follow the development of elevated systolic blood pressure (SBP) in bGH mice and simultaneously consider several contributory factors. 66

The key findings from our study were that bGH mice developed elevated SBP throughout

the first year of life, and the time period between 5 and 7 months of age marked a

significant change in both body composition and blood pressure. Our longitudinal

histological examination of kidney and heart indicated that renal changes preceded the

development of cardiac fibrosis, suggesting that changes in the kidney may precipitate

elevated blood pressure in bGH mice. However, the maintenance of the elevated blood

pressure is likely due to derangements in multiple organs. The bGH mice showed a

dramatic increase in renal ACE/ACE2 ratio indicating a shift in the RAS towards the pro- inflammatory, pro-fibrotic AngII pathway and away from the cardioprotective Ang(1-7) pathway. In the heart of bGH mice, BNP mRNA expression was expectedly increased but

the circulating levels of active BNP were severely depressed, indicating the inability to

produce an adequate natriuretic peptide response. Finally, the initial hyperinsulinemia in

bGH mice was not sustained as the bGH mice became hypoinsulinemic by 11 months of

age. This hypoinsulinemia was accompanied by improved glucose tolerance and

improved fasting blood glucose levels. Overall, elevated SBP in bGH mice is age

dependent and associated with hormonal changes in kidney and heart, but not related to

insulin resistance or hyperinsulinemia in old age.

To date, five studies have assessed blood pressure in bGH mice. Our results of

normal SBP in early life between 3-5 months and increased SBP from 6-12 months of age in bGH mice are in agreement with most of these studies (102, 103, 106) but are inconsistent with two studies (101, 105). Early studies of bGH mice at 3 (106), 7 (105), and 8 months (101) of age describe no difference in SBP versus WT controls. More 67

recent studies, however, find that 5- (103) and 9- (102) month-old bGH mice have

elevated SBP relative to WT controls. Both Bollano et al. (101) and Dilley and Schwartz

(105) report extremely low pressures for WT mice of 84.0±4 mmHg at 7 months of age

and 88.0±3.7 mmHg at 8 months of age, respectively. These pressures are well below

what we and others (102, 103) measure for WT mice. This difference may reflect an

environmental or methodological variable that was not accounted for in the earlier

studies.

Insulin resistance is thought to be a contributory factor to hypertension (153).

Indeed, a 2004 analysis of more than 1000 mixed ethnicity people found that insulin

resistance, but not circulating insulin levels, is positively correlated with blood pressure

(154). Chronic GH action is commonly accepted to exert an overall anti-insulin effect—

an effect underscored by the increased incidence of hyperinsulinemia and diabetes in

acromegalic individuals (30). In our current study, bGH mice had hyperinsulinemia in early life but improved glucose homeostasis and hypoinsulinemia in later life. Our data argue against insulin resistance being a significant factor in the chronic maintenance of elevated SBP in bGH mice. Nevertheless, we cannot rule out the possibility that early hyperinsulinemia (before 9 months of age) played a role in the establishment increased

SBP. Our laboratory has previously reported this trend in insulin levels in bGH mice

(155). The drastic decline in insulin levels throughout life may point to a defect in

pancreatic beta cells. Although young, 3-month-old bGH mice, are reported to have

increased islet cell mass (156), to date there has not been a study addressing the function

or structure of the pancreas in bGH mice throughout age. 68

To our knowledge, only one prior study has commented on the disconnect between the presence of improved glucose homeostasis in the face of the chronic GH stimulation in bGH mice (157). In that study, bGH mice have improved glucose tolerance at 3, 6, and 9 months of age regardless of sex. Together with the improved glucose tolerance, the bGH mice also have improved glucose stimulated insulin secretion but a decreased response to pyruvate tolerance testing indicating a deficit in gluconeogenesis

(157). While the exact mechanism causing this disconnect is not known, bGH have elevated IGF-I (143-145), which may play a role. IGF-I is known to decrease gluconeogenesis through inhibition of hepatic PEPCK (158, 159) and has been shown to stimulate glucose uptake in the absence of functional insulin receptor (158). Another intriguing possibility may be that bGH mice demonstrate tissue specific insulin resistance that may not be reflected in the results of ITT and GTTs. It was recently demonstrated that bGH mice hearts are resistant to acute insulin stimulation, but at baseline actually exhibit an increase in insulin signaling activation (29).

Glomerulosclerosis is a well-documented age-dependent feature in bGH mice

(112, 113, 123, 160). The mesangial sclerosis is thought to be a direct result of increased

GH action and not IGF-I (112). Our histological analysis of the kidney supports previous studies (113), showing a disproportionate increase in mesangial scarring and glomerular capsule thickening throughout age in bGH mice versus WT controls. Further, our findings showed that renal histological changes occurred early in the life of the bGH mouse, by 3 months, and before the onset of increased SBP at 6 months with progressive enlargement and mesangial scarring throughout age. Given these renal histological 69 alterations, it would be expected that function is compromised. In one study examining glomerular filtration rate (GFR) in 5- to 7-month-old bGH mice, GFR is not altered when normalized to body weight (103). However, in a more recent study, bGH mice have an increased albumin to creatinine ratio at both 5 and 12 weeks of age (149). The role of GH in renal function is supported by clinical studies of acromegalic patients showing a positive correlation between GH, hypercalciuria, nephrolithiasis, microalbuminuria, and decreased sodium secretion (161). While the exact mechanism underlying this pathology is not known, a partial explanation may be that, in vitro, GH can induce the production of

ROS and promote reorganization of the actin cytoskeleton in glomerular podocytes (162).

The precipitating event may be an increase in lipid accumulation within the mesangium

(123).

The kidney plays a critical role in blood pressure homeostasis through ion balance and through the production of vasoactive substances such as renin, angiotensin II (AngII), and angiotensin (1-7) (Ang(1-7)). The canonical renin-angiotensin system (RAS) relies on an enzymatic cascade resulting in the formation of the principle mediator AngII through action of the angiotensin converting enzyme (ACE). The discovery of another arm of the RAS by which AngI and AngII can be converted into Ang(1-7) via the action of ACE2, expressed primarily in kidney, heart, and testis (163), has added complexity to the system. As opposed to AngII, Ang(1-7) counteracts, through interaction with its receptor Mas, the classical actions of the RAS exerting an eNOS mediated vasodilatory and anti-proliferative effect (150). The ACE to ACE2 ratio, therefore, gives insight into which arm of the pathway is most activated. Recently, long-lived GHR knockout mice 70

(GHRKO) were shown to have decreased ACE/ACE2 ratios in both heart and kidney

with a concurrent rise in eNOS expression in both tissues (125). Our results showed that

unlike GHRKO mice, bGH mice have a drastically increased ACE/ACE2 ratio and

decreased eNOS expression in kidney at 12 months of age versus WT. This implies that

local levels of AngII may be elevated in the kidney of bGH mice and may contribute to

the observed glomerulosclerosis which in turn contributes to the elevated SBP. The

cardiac fibrosis we observed in the bGH mice may also be a consequence of the

imbalance in ACE/ACE2 expression.

The leading cause of death in acromegalic individuals is cardiovascular disease

(164). Untreated these patients develop a unique form of cardiomyopathy characterized

initially by a hyperkinetic syndrome with improved cardiac contractility and output. This

evolves to concentric left ventricular hypertrophy, diastolic dysfunction due to a stiffened

ventricle, and eventual systolic failure (78). bGH mice have been used in several studies

to consider cardiac function with varying results. Using echocardiography in 8-month-old

bGH mice, Bollano et al. showed a dramatic decrease in systolic ejection fraction and

fractional shortening (101). A report from the same lab a year later, however, showed no change in cardiac contractility using direct ventricular cannulation (103). In vitro work using isolated ventricular myocytes from bGH mice showed that the isolated cells have increased cell shortening, increased maximal shortening and re-lengthening velocities, and increased peak calcium transients, supporting an overall enhanced contractile ability

(148). Our measurement of the four main cardiac calcium channel mRNAs revealed no difference between bGH and WT. Therefore, factors such as cardiac fibrosis or altered 71

blood volume may play a more prominent role in the pathophysiology of chronic GH

excess. Indeed, our results demonstrated that cardiac fibrosis was a distinguishing feature

in old bGH mice—a finding that agrees with previous studies (101)–but was not

prominent until 12 months of age.

Upon being stretched, cells of the atrium and ventricle release natriuretic peptides

(NP). These proteins are cardioprotective and work to counteract the effects of the RAAS

by promoting vasorelaxation and urinary sodium excretion (165). The two main natriuretic peptides are atrial NP (ANP) and brain NP (BNP) and are released primarily from the heart atrium and ventricle, respectively (166). The NPs act primarily through the

G-coupled NP receptor A and are cleared through the NP receptor C or via proteolysis

(167). Disruption in the action of these hormones can have a direct effect on systemic fluid homeostasis. Our results showed disconnect between levels of BNP transcript in the heart and circulating BNP, indicating that GH may be inhibiting BNP post- transcriptionally at the level of translation, release, or by accelerating clearance. An inhibitory effect of GH on ANP (49), BNP (168), and N-terminal pro BNP (which is released in 1:1 quantities after cleavage of BNP) (169) has been described in humans with GH disturbances. A study conducted using bGH mice demonstrated that circulating levels of active ANP were increased at 7 but not 27 weeks of age (126). This decrease in

circulating active ANP mirrored an increase in the pro-hormone at 27 weeks in the bGH mice, pointing to an inability to properly cleave ANP to its active form (126). Our measurements of BNP are in line with these observations concerning ANP. 72

Attenuation of the GH/IGF-I axis is associated with a decrease in inflammatory

markers and an improvement in aging (170). Thus, the opposite may be true in chronic

GH excess, which may promote a deleterious pro-inflammatory environment.

Inflammation in bGH kidney (171) and adipose tissue (172) is thought to contribute to

the overall dysregulated physiology of the bGH mouse. It was recently shown that

adipocytes cultured from patients with acromegaly show an increased production of

monocyte chemotactic protein 1 (MCP-1) and several other proinflammtory cytokines

(173). Our data demonstrated that the level of circulating MCP-1 was higher throughout age in bGH mice while the level of interleukin 6 (IL-6) increased from 2 to 8 months and remained elevated at 11 months of age. MCP-1 is a potent macrophage chemoattractant

that, via its receptor CCR2, is thought to play an important role in early macrophage

infiltration during the pathogenesis of atherosclerosis (174). Further, CCR2-/- mice are

known to develop less kidney damage in models of AngII induced hypertension (175).

IL-6 is an important mediator of the acute phase inflammatory response and is necessary for the survival and proliferation of T and B cell populations (176). Human studies associate increased IL-6 levels with an increased risk of all-cause mortality (177, 178).

Despite this relationship, IL-6 is a major driver of cardiac development and hypertrophy

(179) with IL-6-/- mice demonstrating severe ventricular dilation and fibrosis (180).

Interestingly, AngII can increase expression of IL-6 in vascular smooth muscle of rats

(181). Thus the increased MCP-1 levels we observed may be promoting damage in the

kidneys, while the increased IL-6 may be a compensatory mechanism driving cardiac

hypertrophy to deal with the increased blood pressure in bGH mice. 73

There are several limitations to our study. The first is that we only used male

mice. We know that female bGH mice have differences in body composition (145) and

that estrogen is known to directly inhibit GH signaling (182); thus, it is likely there are

sex differences in blood pressure. Secondly, bGH mice have been reported to have

increased spontaneous locomotor activity in response to new environments (183, 184).

This may play a role in the measurement of our early SBP, as mice acclimate to the

procedure. Thirdly, the tail-cuff system we used for SBP measurement does not permit

measuring diastolic blood pressure, which may show earlier changes than SBP (107).

Finally, the increased SBP in bGH mice may be the result of altered levels of vasoactive

substances or may be related to vasculature dysfunction, which was not explored in this

study but has been previously evaluated in other studies (103, 105, 110). Previous

studies using bGH mice show that the small resistance vasculature (such as mesenteric

vessels) has a decreased average diameter (103) and an increased wall-to-lumen ratio

(105). There is also evidence that increased oxidative stress plays a role in the vascular

function of 2- to 3-month-old bGH mice (110). In humans, acromegalic patients exhibit

vascular abnormalities with increased intima medial thickness and decreased flow-

mediated dilatation (78). Based on these data, GH likely plays a role in both endothelial

function and vessel structure.

In conclusion, bGH mice developed elevated SBP with advancing age. This change was accompanied by increased cardiac fibrosis, glomerular hypertrophy, and mesangial sclerosis. A disconnect was observed between increased cardiac BNP mRNA and decreased circulating BNP levels. In the kidney, bGH mice showed a dramatic 74 decrease in both ACE2 and eNOS protein expression levels, which may indicate loss of the ability to form antiproliferative and cardioprotective Ang(1-7). Finally, systemic insulin resistance and hyperinsulinemia were not contributing factors to the maintenance of higher SBP in older bGH mice. Our current study identified several contributory pathways, which may play a role in cardiovascular function of bGH mice. In the future it will be important to 1) examine the effects of GH on BNP with a focus on BNP production, release, and cleavage in the presence of acute and chronic GH stimulation, 2) further investigate the status of the ACE2/Ang(1-7)/Mas pathway in animal models of

GH disruption including measurements of circulating and tissue specific AngII and

Ang(1-7), and 3) solidify our understanding of the interaction between chronic GH action and insulin signaling by examining both systemic and tissue level insulin sensitivity and performing an in-depth evaluation of pancreatic structure and function throughout age in bGH mice.

Acknowledgements

We would like to acknowledge Diana Cruz-Topete, Ph.D. (NIH/NIHES) for her help in performing the Milliplex MAP experiment and Lauren Volpe, M.Ed. (Ohio

University Patton College of Education) for her careful editing of the manuscript.

Funding

This work was supported in part by the Gates Millennium Scholars (GMS)

Graduate Fellowship program; the State of Ohio's Eminent Scholar Program that includes 75 a gift from Milton and Lawrence Goll; National Institutes of Health (NIH) Grants

P01AG031736; the Provost Undergraduate Research Fund, and the Diabetes Institute at

Ohio University. 76

CHAPTER 4: CARDIAC GROWTH HORMONE RECEPTOR INDUCED

SIGNALING IS NECESSARY FOR MAINTAINING GLUCOSE HOMEOSTASIS IN

ADULT MALE MICE3

Abstract

Growth hormone (GH) is considered to be necessary for the proper development and maintenance of several tissues, including the heart. In disease states of GH action such as acromegaly (caused by overproduction of GH), GH deficiency, and Laron

Syndrome (caused by mutations in the GH receptor), patients exhibit unique cardiac phenotypes of altered structure and function. In all of these clinical syndromes, IGF-I is concomitantly affected and therefore little is known about the specific effect of GH on the heart. To better understand the effects that GH action has on cardiac tissue, we developed a tamoxifen-inducible, cardiac-specific GHR disrupted (iC-GHRKO) mouse.

In order to examine the effects of cardiac GHR signaling in the adult mouse in the absence of any developmental effects due to disruption in neonatal mice, four-month-old mice were injected with tamoxifen (80mg/kg) to induce disruption of the GHR gene specifically in cardiac tissue (iC-GHRKO). The mice were then subjected to longitudinal body composition and systolic blood pressure measurement (n=8) from 4-12 months of age, dobutamine stress test echocardiography at 12 months of age (n=8), and insulin and glucose tolerance testing (6 and 12 months of age) (n=10). Surprisingly, iC-GHRKO mice showed no difference versus controls in baseline or post-dobutamine stress test

3, Worked presented in this chapter represents a manuscript in preparation. The contributing authors are: Adam Jara, Xingbo Liu, Don Sim, Chance M Benner, Edward O List, Darlene E Berryman, and John J Kopchick.

77 echocardiography measurements at 12 months of age, nor did iC-GHRKO mice show any difference in longitudinal systolic blood pressure measurements. Interestingly, iC-

GHRKO mice were significantly more insulin sensitive at 6 months of age and had less fat mass versus controls. By 12 months of age, however, iC-GHRKO mice were significantly glucose intolerant and moderately insulin resistant versus controls.

Subsequent immunoblot analysis of insulin signaling in heart, liver, and epididymal white adipose tissue demonstrated that iC-GHRKO mice had significantly decreased insulin stimulated Akt phosphorylation specifically in heart and liver, but not epididymal white adipose tissue. These data indicate that disruption of cardiomyocyte GH signaling in adult mice does not affect cardiac function or structure but does influence whole body metabolism, suggesting that cardiac GH action is important in mediating tissue crosstalk.

Introduction

Growth hormone (GH) is a principal mediator of growth, development, and metabolism. Traditionally, GH is thought to exert the majority of its metabolic effects on liver and adipose tissue and its growth effects on bone and muscle; however, several studies have demonstrated that the cardiovascular system is also a target of GH action.

That is, GH and its downstream mediator insulin-like growth factor 1 (IGF-I) have been shown to cause molecular changes in the heart including promotion of hypertrophy (24), and regulation of contractility through ion channel regulation and myosin isoform switching (26-28). 78

In humans with GH related pathologies, unique cardiovascular phenotypes are associated with too much or too little GH signaling. Acromegaly, a disease caused by hypersecretion of GH secondary to a pituitary adenoma, results in several cardiovascular derangements including cardiomyopathy, hypertension, dyslipidemia, and vascular dysfunction (76). The main cause of death in untreated acromegaly is cardiac failure (80) due to biventricular hypertrophy with resulting filling dysfunction and eventual systolic failure. On the opposite end of the spectrum is GH deficiency (GHD), which results from a lack of GH production due to a genetic or physical cause such as traumatic brain injury.

Patients with GHD often exhibit decreased heart dimensions with thinned ventricular walls, increased systolic wall stress, and decreased exercise tolerance (68). Likewise, patients with Laron Syndrome, a disease resulting from mutations in the GH receptor

(GHR) gene, exhibit decreased heart size and decreased cardiac function (72, 73). In all of these clinical scenarios, IGF-I is concomitantly affected due to GH status, being high in acromegaly, and low in GHD and Laron syndrome. Therefore, separating the aspects of the cardiovascular changes caused specifically by GH is difficult as many of the observed changes may be the result of too much or too little IGF-I action.

Based on this previous work it has been hypothesized that GH treatment of chronic heart failure (CHF) patients may lead to improved outcomes. Small observational studies have indeed shown that GHD is often present in CHF patients and GH replacement therapy not only improves New York Heart Association (NYHA) score, but also leads to improved cardiac dimensions, function, and lower pro-brain natriuretic peptide (BNP) levels (92, 93). Larger randomized, double-blinded, placebo-controlled 79 clinical studies, however, have not observed a positive effect of GH therapy (88, 185).

One major shortcoming in the larger studies, however, was the exclusion of cachexia as a contraindication to treatment. Cachexia, or muscle wasting, is a finding in many chronic diseases including heart failure and is associated with GH resistance (94, 186). Therefore,

CHF patients exhibiting cachexia would be unlikely to benefit from GH replacement therapy.

Studies conducted using bovine GH (bGH) transgenic mice and global growth hormone receptor knockout (GHRKO) mice, which are viewed as models for acromegaly and Laron syndrome, respectively, have shown a distinct effect of GH status on cardiovascular function. Studies of the short-lived (147) bGH transgenic mice show both normal and increased systolic blood pressure, and we recently demonstrated that the elevation of systolic blood pressure (SBP) in bGH mice depends on age (104).

Functionally, bGH mice have been shown to have decreased (101) to normal cardiac function (102) and increased fractional shortening in isolated cardiomyocytes (148).

However, cardiac hypertrophy and fibrosis are prominent features in bGH mice (101,

104, 105). GHRKO mice, on the other hand, are long-lived (187) and while they have demonstrated decreased baseline cardiac function, when the results are normalized to body size they have normal function (132). Similar to the aforementioned clinical studies, these animal studies in both bGH and GHRKO mice are not able to differentiate the effects of circulating IGF-I action, which high and low in these two models, respectively.

In order to study the role of GH on the myocardium without the contributory effects of changes in circulating IGF-I or developmental deficiencies due to lack of GH 80 action in early life, we produced an inducible, cardiac-specific GH receptor gene disrupted mouse line. We report for the first time that loss of GHR signaling specifically in cardiomyocytes does not play a prominent role in the cardiac function of adult male mice throughout the first year of life. While loss of cardiac GHR signaling did not affect heart weight, function, or dimensions, body composition, systemic insulin sensitivity and insulin and glucose tolerance testing were altered. Interestingly, insulin stimulated Akt phosphorylation was decreased in liver and heart, but not in epididymal white adipose tissue. Our results indicate that in adult mice, cardiac GHR signaling is involved in mediating tissue crosstalk to regulate systemic glucose homeostasis.

Materials and methods

Animals

Mice, hemizygous for the myosin heavy chain 6 (Myh6) driven MerCreMer gene, were purchased from Jackson Laboratories (#005657). The MerCreMer fusion gene gives rise to a Cre recombinase flanked by mutated estrogen receptors (Mer) that are insensitive to endogenous estrogens but sensitive to tamoxifen due to a single point mutation at G525R (188). When tamoxifen is present the Mers release Cre, which translocates to the nucleus and acts on Lox-P sites. In the absence of tamoxifen the Cre remains inactive in the cytoplasm bound to the Mers. The Myh6-MerCreMer+/- mice were crossed with growth hormone receptor (GHR) floxed mice (GHRfl/fl) to produce Myh6-

MerCreMer+/-/GHR+/fl offspring. These offspring were crossed to produce the experimental mouse line Myh6-MerCreMer+/-/GHRfl/fl, which were maintained through 81

matings which yielded one-half Myh6-MerCreMer+/-/GHRfl/fl and one-half GHRfl/fl mice.

We refer to tamoxifen injected Myh6-MerCreMer+/-/GHRfl/fl mice as iC-GHRKO mice

(inducible, cardiac-specific, GHR knockout). Unless otherwise noted, due to no

differences between control groups, the control mice in all experiments are the combined

results from Myh6-MerCreMer+/-/GHRfl/fl mice injected with oil (vehicle) and GHRfl/fl

mice injected with either tamoxifen or oil. All mice were housed at a maximum density

of four mice per cage in a temperature controlled (23°C) vivarium and exposed to

14h/10h light/dark cycle. All mice were allowed ab libitum access to water and food

(ProLab RMH 3000, PMI Nutrition International, Brentwood, MO.). All procedures performed with the mice were approved by the Institutional Animal Care and Use

Committee (IACUC) at Ohio University and are in accordance with all standards set forth

by federal, state, and local authorities.

Tamoxifen induction of Cre recombinase

Tamoxifen (Sigma) was prepared as previously described (189). Briefly, 100mg tamoxifen free base was dissolved in 500uL absolute ethanol and then diluted to 10mL with peanut oil (Fisher). The solution was then sonicated for 30 minutes and subsequently filter sterilized using a Millipore vacuum filter (<0.5micron). Aliquots were stored at -

20°C for up to 1 month. All tamoxifen injections began at 16 weeks of age. Tamoxifen injected mice received a total dose of 80mg/kg body weight, administered as 2 intraperitoneal injections, one per day for two days.

Echocardiography and dobutamine stress test

Mice were shipped to University of Massachusetts Mouse Phenotyping Core

where M-mode echocardiography was performed on 12-month-old iC-GHRKO (n=8)

and peanut oil injected Myh6-MerCreMer+/-/GHRfl/fl control littermates (n=8) using a

VisualSonics Vevo2100 Imaging System and a 40Mhz linear transducer collecting data at

a rate of 279 frames/sec. Mice were placed on a heating pad to avoid hypothermia and

put under light anesthesia, maintained with a minimal amount of isoflourane (1-2%),

while keeping heart rate greater than 400bpm. The parasternal short axis view at the level

of the papillary muscles was used to obtain measurements. Three sets of replicate

measurements were performed on each mouse and average values were used to calculate ejection fraction, fractional shortening, and left ventricular mass. A dobutamine stress test

was subsequently performed by collecting baseline M-mode measurements, injecting

each mouse with dobutamine (1.5ug/g body weight, i.p.), waiting 5 minutes, and

collecting post-administration M-mode measurements.

Body composition measurements

Body composition was measured in iC-GHRKO (n=8) and control littermates

(n=24) monthly from 3-12 months of age. Measurements were collected using a desktop

NMR Bruker LF50 Minispec as previously described (145).

Non-invasive blood pressure measurement

Systolic blood pressure (SBP) was measured monthly from 4-12 months of age in

iC-GHRKO (n=8) and control littermates (n=24). SBP measurements were made using a

non-invasive blood pressure tail-cuff system (#IN125/M, ADInstruments) connected to a 83

PowerLab system (#PL3508, ADInstruments). Training and acclimation procedures were

followed as previously described (104). All data were analyzed using Lab Chart v7.4

(ADInstruments).

Real-time quantitative PCR (RTqPCR)

Two step RTqPCR was performed using total RNA isolated from heart

ventricular samples of iC-GHRKO (N=5) and control (N=15) mice as previously described (104). All data were analyzed using qBase Plus v2.4 (Biogazelle) using Rpl38,

Eif3f, and Hprt as reference genes. Please see Supplemental Materials and Methods for primer sequences (Supplemental Table 4.1, Appendix D).

Plasma measurements

Whole blood was collected from the tail tips of iC-GHRKO and littermate controls after a 12-hour overnight fast by clipping ~1mm of the tail tip and collecting

~250µL of blood using heparinized capillary tubes. Plasma was collected after centrifugation for 10 minutes at 7000g, 4°C. Circulating levels of insulin were determined using the Mouse Insulin Elisa (#80-INSMS-E01, ALPCO) following the manufacturer’s directions. Levels of circulating IGF-I were measured using the Mouse

IGF-I ELISA (#22-IG1MS-E01, ALPCO) following the manufacturer’s directions. C-

peptide, leptin, resistin, MCP-1, and IL-6 were measured in samples from 12-month-old

mice using a Milliplex Mouse Metabolic Panel (#MMHMAG-44K, Millipore) according

to the manufacturer’s instructions.

Intraperitoneal insulin/glucose tolerance testing (ITT/GTT)

For the GTT, iC-GHRKO (n=8) and littermate controls (n=24) were fasted for 12

hours prior to measurements. Each mouse received an intraperitoneal injection of 10%

glucose at 0.01ml/g body weight. For the ITT, iC-GHRKO (n=8) and control littermates

(n=24) were non-fasted. Each mouse received an intraperitoneal injection of 1U/kg bodyweight insulin (Humilin R, Lilly). For both GTT and ITT, blood glucose measurements were collected using OneTouch Ultra test strips and glucometers before glucose or insulin injection (0 minutes) and at 20, 40, 60, 90 minutes (GTT) or 15, 30, 45,

60, 90 minutes (ITT) after injection.

Immunoblots

For the insulin signaling immunoblots, iC-GHRKO (n=3) and oil injected Myh6-

MerCreMer+/-/GHRfl/fl (control) littermates (n=3) were injected with 1U/kg bodyweight

insulin (Humalin R, Lilly). Mice were sacrificed 15 minutes after insulin injection.

Protein was isolated from homogenized sections of flash frozen heart (~30mg) from iC-

GHRKO and littermate controls. Protein concentration was determined using a Bradford

assay (BioRad) following the manufacturers’ directions. Protein samples (20µg) were

separated on 10% SDS-polyacrylamide gels before being transferred to PVDF

membranes (#RPN2020LFP, GE Healthcare). Subsequently, membranes were blocked in

5% fat free dry milk (Carnation) in 0.5% TBS/Tween-20 and probed with primary

antibodies: pan Akt (#4685, 1:1000), p-Akt (Ser473) (#4058, 1:1000), p42/44 MAPK

(#4695, 1:1000), and p-p42/44 MAPK (#4377, 1:1000) (Cell Signaling). Membranes

were incubated with goat-anti rabbit HPR conjugated secondary antibody (1:50,000) (GE 85

Healthcare) in 5% fat free dry milk / 0.5% TBS/Tween-20 for 1 hour at room temperature before being subsequently washed in TBS and covered with ECL Prime reagent (GE

Healthcare) for 60 seconds. Finally, membranes were exposed to CLExposure X-ray Film

(Thermo) and developed using an automatic film developer. Densitometry analysis was performed using ImageJ software (151).

For the STAT5 phosphorylation immunoblots, iC-GHRKO and control mice

(n=2) were injected with bovine GH (5µg/g bodyweight) and dissected 15 minutes later.

Hearts and livers were flash frozen and protein was subsequently extracted and processed for immunoblot analysis following the procedure described above for the insulin signaling immunoblots. The following primary antibodies were used for STAT5 (#SC-

835, 1:200, Santa Cruz Biotechnology) and p-STAT5 (#9351, 1:1000, Cell Signaling).

Statistics

All values are reported as mean ± standard error of the mean (SEM). Statistics were performed using SPSS v 17.0 (IBM). All time-dependent analysis was performed using two-way ANOVA with repeated measures; genotype as the main factor. Maulchy’s test of sphericity was performed on all repeated measures data. The Green-House Geisser correction was applied if Maulchy’s test was found to be significant. For single time point measurements between two groups, equality of variance was tested using Levene’s test and group means were then compared using an independent student’s t test or a

Welch’s t test for unequal variances. For single time point measurements between more than two groups, the values were analyzed using ANOVA with orthogonal contrasts for 86 tamoxifen treatment and genotype. For all tests, statistical significance was determined when P<0.05.

Results

Validation of GHR gene disruption

Disruption of GHR gene in cardiac tissue was accomplished using the inducible

MerCreMer-LoxP system (Figure 4.1A). An assay of genomic DNA from eight tissues revealed that recombination around exon 4 of the GHR gene was present only in cardiac tissue (Figure 4.1B). Since the recombination did not appear to be complete at the level of DNA, we performed RTqPCR to quantify GHR transcript levels in cardiac tissue. Our tamoxifen treatment protocol yielded an approximate 80% decrease in GHR transcript levels in the heart (Figure 4.1C). There did, however, appear to be a minor (~10-20%) change in GHR transcript levels in the liver, which occurred in a tamoxifen dependent manner. To ensure that GHR signaling was being disrupted, iC-GHRKO and control mice were injected with bovine GH and protein homogenates from heart and liver (iC-

GHRKO) were assayed for STAT5 phosphorylation. Figure 4.1D demonstrates that only mice injected with tamoxifen and co-expressing both the floxed GHR locus and the

MCM transgene (iC-GHRKO mice) failed to show bGH induced STAT5 phosphorylation in cardiac tissue. In the liver, however, iC-GHRKO mice responded to the injection of bGH with robust STAT5 phosphorylation.

Figure 4.1: Verification of inducible GHR gene disruption (A) Diagram showing exon 4 of GHR flanked by LoxP sites before and after recombination when in the presence of both MerCreMer expression and tamoxifen. Arrows denote primer positions used to distinguish floxed locus from recombined locus. (B) PCR results of the floxed GHR exon 4 locus using genomic DNA isolated from eight different tissues (heart, gastrocnemius, liver, kidney, brain, lung, epididymal white adipose tissue, and brown adipose tissue) in GHRfl/fl mice without or without MerCreMer expression and with or without tamoxifen injection. (C) Real time quantitative PCR analysis of GHR in heart, liver, kidney, and whole brain at 4.5 months of age and in heart at 12.5 months of age. (D) Bovine GH stimulated STAT5 phosphorylation in heart from GHRfl/fl mice without or without MerCreMer expression and with or without tamoxifen injection and in liver from Myh6- MerCreMer+/-/GHRfl/fl (iC-GHRKO) mice. Different letters denote a difference between groups of mice (P<0.05). EX4: exon 4 of growth hormone receptor, TAM: tamoxifen, GHR: growth hormone receptor, bGH: bovine growth hormone, WAT: white adipose tissue, BAT: brown adipose tissue.

Body composition analysis and tissue weights

There was a significant effect of age on bodyweight, fat, lean, and fluid percentage in both iC-GHRKO and control mice (P<0.05) (Figure 4.2A-D). The iC-

GHRKO and control mice both had similar body weights at every time point tested

(Figure 4.2A). Body composition analysis revealed that the iC-GHRKO mice gained less fat mass from 4-8 months of age (Figure 4.2B, P<0.05). This failure to gain fat mass was accompanied by an increase in lean body mass from 4-8 months of age (Figure 4.2C,

P<0.05). There was also a slight increase in % fluid mass at 4.5 months of age in the iC-

GHRKO vs control mice (Figure 4.2D, P<0.05).

Along with no change in body weight, the iC-GHRKO and control mice showed similar nose to anus lengths at dissection (Figure 4. 2E). Dissected tissue masses did not vary much between iC-GHRKO and control mice. Tissue weights at dissection indicate that iC-GHRKO mice have similar sized hearts compared to control littermates (Figure

4.2F). In terms of absolute tissue mass, the heart of iC-GHRKO mice was 163 ± 12 mg while the heart of control mice was 155 ± 4 mg (P=0.279). There was, however, an approximate 26% decrease in epididymal WAT mass between iC-GHRKO and control mice (P=0.014). There was also a tendency for the retroperitoneal WAT mass to be lower in iC-GHRKO mice, although not statistically significant (P=0.082).

ITT/GTT

Intraperitoneal glucose and insulin tolerance tests were performed at both 6.5 and

12.5 months of age in iC-GHRKO and control littermates. At 6.5 months of age, there 89

Figure 4.2: Body composition analysis, length, and dissected tissue weights (A) Body weight in grams, (B) percent fat mass, (C) percent lean mass, and (D) percent fluid mass in iC-GHRKO (N=8) mice and littermate controls (N=24) from 3-12.5 months of age. The black arrow denotes the injection of tamoxifen at 16 weeks of age. (E) Length in millimeters of iC-GHRKO (N=8) and control mice (N=24) at dissection (12.5 months of age). (F) Tissue mass normalized to body mass and graphed relative to controls (N=24) in iC-GHRKO mice (N=8) at dissection (12.5 months of age). * significant difference between genotypes (P<0.05), † significant difference with age (P<0.05). iC-GHRKO: inducible, cardiac-specific GHR gene disrupted mouse, SubQ: subcutaneous (inguinal), Epi: epididymal, Retro: retroperitoneal, Mes: mesenteric, WAT: white adipose tissue, BAT: brown adipose tissue, Quad: quadricep muscle.

90 was no difference in GTT (Figure 4.3A); however, there was a slight increase in insulin sensitivity in iC-GHRKO mice at 30 minutes (Figure 4.3B, P<0.05).Unexpectedly, at

12.5 months of age the iC-GHRKO mice were significantly more glucose intolerant than control mice having an area under the curve of 29575 ± 723 mg/dL*min-1 versus 23962

± 578 mg/dL*min-1 in control mice (Figure 4.3C, P<0.05). In line with this observation, iC-GHRKO mice were significantly more insulin resistant than control littermates based on ITT results at 30 minutes (Figure 4.3D, P<0.05).

Figure 4.3: Insulin and glucose tolerance testing. Intraperitoneal glucose tolerance testing performed in 6.5 month old (A) and 12.5 month old (C) iC-GHRKO (N=8) and control littermates (N=24) following a 12 hour fast and an injection of 10 µL/g bodyweight of a 10% glucose solution. Area under the curve of the glucose tolerance testing was calculated for both groups. Intraperitoneal insulin tolerance testing was performed in 6.5 month old (B) and 12.5 month old (D) non-fasted iC-GHRKO (N=8) and control littermates (N=24) following an injection of 1U/kg bodyweight insulin. * significant difference between genotypes (P<0.05). iC-GHRKO: inducible, cardiac- specific GHR gene disrupted mouse, AUC: area under curve.

Immunoblots for insulin responsiveness

In order to determine if the observed insulin resistance was tissue specific at 12.5 months of age, both iC-GHRKO and peanut oil injected MerCreMer+/-/GHRfl/fl control mice were stimulated with 1U/kg intraperitoneal insulin and dissected 15 minutes later.

As shown in Figure 4.4A, the ratio of phosphorylated Akt to total Akt was decreased by approximately 44% in heart of iC-GHRKO mice versus control littermates (P=0.045).

Likewise, in liver (Figure 4.4B), the ratio of phosphorylated Akt to total Akt was decreased by approximately 53% versus control littermates (P=0.022). The ratio of phosphorylated MAPK to total MAPK was not different between the two groups of mice in either heart or liver. Interestingly, there was also no difference between groups of mice in either ratio of phosphorylated Akt or MAPK in epididymal white adipose tissue

(Figure 4.4C).

Plasma parameters

To help explain the increase in glucose intolerance and insulin resistance with age, we examined several metabolically related circulating factors. Circulating insulin levels in iC-GHRKO were similar to controls at 4, 8, and 12 months of age (Figure 4.5A).

Circulating levels of IGF-I were similar in both iC-GHRKO and control littermates at 4 and 8 months of age, but were significantly decreased at 12.5 months of age, with iC-

GHRKO mice having 220.2 ± 20.5 ng/mL and controls having 285.9 ± 21.8 ng/mL,

(Figure 4.5D, P=0.039). Levels of circulating IL-6 (iCGHRKO: 50.5 ± 14.6 pg/mL vs

Control: 101.3 ± 12.4 pg/mL, Figure 4.5F, P=0.038) and resistin (iCGHRKO: 9921 ±

Figure 4.4: Insulin stimulated Akt and MAPK phosphorylation. Immunoblot quantification of insulin stimulated phosphorylation of Akt (Ser473) and p42/44 MAPK from dissected (A) heart, (B) liver, and (C) epididymal WAT tissue 15 minutes post 1U/kg intraperitoneal injection of insulin in iC-GHRKO (N=3) and peanut oil injected MerCreMer+/-/GHRfl/fl (control) littermates (N=3). * significant difference between genotypes (P<0.05). iC-GHRKO: inducible, cardiac-specific GHR gene disrupted mouse, WAT: white adipose tissue. 92

2131 pg/mL vs Control: 13524 ± 676 pg/mL, Figure 4.5G, P=0.041) in 12.5 month old iC-GHRKO mice were significantly lower than control littermates. While not statistically significant (P=0.066), the level of plasma leptin tended to be lower in iC-GHRKO mice than in controls. There was no difference between C-peptide or MCP-1 levels between iC-GHRKO and control mice.

Figure 4.5: Circulating metabolic peptides Circulating levels of (A) insulin and (D) IGF-I at 4, 8, and 12-months of age in iC-GHRKO (N=8) and control (N=24) littermates. Circulating levels of (B) C-peptide, (C) leptin, (E) MCP-1, (F) IL-6, and (G) resistin in 12.5 month old iC-GHRKO (N=8) and control (N=24) littermates. * significant difference between genotypes (P<0.05). iC-GHRKO: inducible, cardiac-specific GHR gene disrupted mouse, IGF-I: insulin-like growth factor I, MCP-1: monocyte chemoattractant protein 1, IL-6: interleukin 6.

Cardiac calcium channel RNA expression

Levels of RNA for the four major cardiac channels were assessed at two weeks and 12 months post GHR gene disruption, 4.5 months (Figure 4.6A) and 12.5 months

(Figure 4.6B) of age, respectively. Interestingly, just after GHR gene disruption (4.5 months), there was a decrease (~28%) in SERCA2 (Figure 4.6A) and an increase (~30%) in NCX1 (Figure 4.6A) expression with no change in RYR2 or LTCC expression in iC-

GHRKO mice versus controls (P<0.05). However, by 12.5 months of age the decrease in

SERCA2 expression (Figure 4.6B) in iC-GHRKO mice had slightly recovered with only

~11% decrease in expression (P<0.05). The level of NCX1 expression returned to that of controls at 12.5 months of age.

Figure 4.6: Cardiac calcium channel RNA levels. Expression of the major cardiac calcium SERCA2, NCX1, LTCC, and RYR2 in 4.5 month old (A) and 12.5 month old (B) iC-GHRKO (N=5) and control (N=15) littermates. * Significant difference between genotypes (P<0.05). iC-GHRKO: inducible, cardiac-specific GHR gene disrupted mouse, SERCA2: sarcoplasmic endoreticulum calcium exchanger 2, LTCC: L-type calcium channel, NCX1: sodium calcium exchanger 1, RYR2: ryanodine receptor 2.

Echocardiography and Systolic Blood Pressure

In order to examine cardiac functional changes, baseline and post-dobutamine injection M-mode echocardiography was performed. At baseline, iC-GHRKO mice had similar cardiac dimensions compared to oil injected control mice (Table 4.1, top).

However, there was a trend for the iC-GHRKO mice to have decreased left ventricular interal diameter during systole (LVID;s) (P=0.08), posterior wall thickness during diastole (LVPW;d) (P=0.08), and systole (LVPW;s) (P=0.06) than controls. Relative wall thickness was significantly (P=0.04) decreased in iC-GHRKO mice (0.36 ± 0.01) versus control mice (0.42 ± 0.02) at baseline. However, there was no change in left ventricular mass, ejection fraction, fractional shortening, or cardiac output. After stressing the mice with the β1-adrenergic agonist dobutamine, iC-GHRKO showed no differences when compared to vehicle injected control mice in dimensions or calculated functional parameters.

Systolic blood pressure showed a significant increase throughout age in both iC-

GHRKO and control mice (P<0.05). However, there were no differences in blood pressure at any time point between the two groups (Supplemental Figure 4.1, Appendix

D).

Table 4.1: M-mode echocardiography measurements

IVS: interventricular septum, LVID: left ventricular internal diameter, LVPW: left ventricular posterior wall, EF: ejection fraction, FS: fractional shortening, SV: stroke volume, CO: cardiac output, RWT: relative wall thickness, d: diastole, s: systole. 96

Discussion

The results of this study reveal several interesting insights into the role of GH signaling in adult cardiomyocytes. First, intact GH signaling through its receptor does not appear to be necessary to maintain cardiac mass nor does it appear to be necessary for maintenance of baseline or dobutamine-stressed cardiac function. Evaluation of SBP over age also revealed no effect of cardiac GHR gene disruption. Interestingly, there was an initial decrease in SERC2A expression and an increase in NCX1 expression at the RNA level; however, these changes were attenuated in older iC-GHRKO mice. Surprisingly, cardiac GHR gene disruption was associated with an age-dependent decline in glucose tolerance and insulin sensitivity. Immunoblot analysis demonstrated that the iC-GHRKO mice had lower levels of insulin stimulated Akt phosphorylation in heart and liver, but not epididymal white adipose tissue—indicating that the decrease in insulin sensitivity was tissue specific. Along with the decrease in insulin sensitivity, the iC-GHRKO mice had slightly lower circulating IGF-I levels at 12 months of age, but not earlier in life.

There was no change in circulating insulin at any of the three age points examined.

Finally, the iC-GHRKO mice experienced a shift in body composition with a tendency to have lower fat mass and increased lean mass, which was most prominent from 4.5-8.5 months of age, but without a change in body weight throughout life. Together, these data indicate adult cardiac GHR signaling in mice plays a prominent metabolic role in later life and suggests intriguing tissue crosstalk.

Animal studies of transgenic GH and GHR knockout mice have established possible roles for GH action in the development, maintenance, and function of cardiac

98 tissue. Studies of transgenic mice overexpressing bovine GH (bGH) have shown disparate results with regard to cardiovascular function. Echocardiographic study of 8- month-old female bGH mice showed that ejection fraction and fractional shortening was decreased in bGH versus wild-type controls (101). These changes were related to a decreased phospho-creatine to ATP ratio and enlarged, disorganized cardiac mitochondria (101). A later study, however, using direct ventricular cannulation and isoprenaline stimulation reported no difference in left ventricular function (102). Reports of blood pressure in bGH mice are also mixed, with some studies reporting no difference

(101, 105, 106) and others reporting increased blood pressure (102-104). Indeed, our laboratory recently showed that bGH transgenic mice develop increased SBP and cardiac fibrosis as a function of age and that this change is associated with an increase in circulating inflammatory cytokines throughout life (104).

Further confounding the cardiovascular phenotype of bGH mice is that in vivo experiments have reported improved contractility in isolated ventricular myocytes from bGH mice (148), indicating a possible positive effect of GH stimulation directly on the myocardium calcium handling. However, IGF-I likely plays a role by sensitizing the contractile apparatus to calcium (27). Our RNA analysis of four of the cardiac calcium channels does allude to an acute change in cardiac calcium channel expression with a decrease in SERCA2 and an increase in NCX1 expression—a pattern often observed in heart failure (190). SERCA2 is responsible for a large efflux of calcium from the sarcoplasmic endoreticulum into the cytoplasm of the cardiomyocyte. This allows for increased myosin-actin cross bridge formation and increased force generation for

99 contraction (190). Increased levels of NCX1 can compete with SERCA2 by leaking calcium out of the cell, resulting in decreased contractile force (190). This pattern of decreased SERCA2 and increased NCX1, however, is attenuated in the older iC-GHRKO mice which likely means there is a compensatory mechanism at play in maintaining proper cardiac calcium channel expression.

Unlike the mixed reports of bGH mice, GHRKO mice (127), which systemically lack GH signaling and have decreased circulating IGF-I levels, have been shown to have cardiac function that develops in line with their small body size and remains normal at 9 months of age (102). Egecioglu and colleagues showed that GHRKO mice had decreased systolic function using echocardiography, but cardiac output was sufficient to meet the metabolic demands of the smaller sized mouse (132). Opposite of what is described in bGH mice, GHRKO mice are reported to have lower systolic blood pressure and enhanced vessel response to norepinephrine and nitric oxide (132). It has also been shown that there is increased insulin stimulated Akt phosphorylation in the heart of

GHRKO mice, which may provide an enhanced cardioprotective effect (191). This is contrary to what we observed in the heart of the iC-GHRKO mice, which had decreased insulin stimulated Akt phosphorylation. However, a direct comparison with the GHRKO mouse and our iC-GHRKO mouse is difficult due to the fact that GHRKO mice develop throughout life in the absence of GH signaling.

In both bGH and GHRKO mice, the gain or loss of GH signaling is present throughout development and downstream IGF-I is concomitantly affected. Therefore, it is difficult to separate the specific effects of GH from IGF-I in these mouse lines. Studies

100 using cardiac specific IGF-I receptor (IGF-IR) knockout have shown that loss of IGF-IR signaling does not change cardiac growth but does blunt exercise induced hypertrophy, perhaps through an AMPK driven mechanism (136). Adult disruption of cardiac-specific

IGF-IR using the same inducible, Myh6-driven MerCreMer transgene used in our current study resulted in different phenotypes depending on when the induction took place (139).

Specifically, when IGF-IR gene disruption was induced in adult (11-month-old) mice there was a decrease in diastolic cardiac function indicating that cardiac IGF-IR signaling is important in maintaining cardiac function late in life (139). In light of our results showing no change in baseline or dobutamine-stressed cardiac function when cardiac

GHR is disrupted at 4 months of age, it appears that GHR and IGF-IR signaling is not required for proper cardiac structure and function at young ages. Unfortunately

Moellendorf et al. did not report cardiac function results for the 3 month old cardiac- specifi IGF-IR disrupted mice greater than 6 months of age (139).

Along with GH and IGF-I signaling, insulin signaling plays a role in cardiac development and function. Constitutive cardiac specific insulin receptor knockout

(CIRKO) mice are reported to have a small heart phenotype (138), impaired substrate utilization, switched myosin expression to the fetal β form (138), and increased cardiac mitochondrial uncoupling and oxidative stress (192). In the diabetic state, the CIRKO mice show decreased cardiac efficiency (193). Double cardiac-specific knockout of both insulin receptor (IR) and IGF-IR results in dramatic 100% mortality by the 4th week of life due to heart failure from dilated cardiomyopathy (137). Death in these mice is preceded by down regulation of genes involved in the mitochondrial electron transport

101 and beta oxidation of fatty acid, and distinct structural changes to cardiomyocytes including increased mitochondria and disrupted sarcomere organization (137). Given the molecular crosstalk inherent in GH, IGF-I and insulin signaling, which includes p42/44

MAPK and Akt signaling, it may be that when signaling pathway is lost, the others respond to compensate for the deficit and therefore only when several of the pathways are disrupted (137) is an overt phenotype observed.

Our results indicate a role of cardiac GH action, in mediating complex tissue crosstalk resulting in altered glucose metabolism through tissue specific mediation of insulin action. Indeed, we showed that iC-GHRKO mice had normal GTT and slightly improved ITT results at 6.5 months but by 12.5 months experienced decreased glucose tolerance and decreased insulin sensitivity. This decrease in insulin sensitivity was supported by immunoblot demonstrating that iC-GHRKO mice had decreased insulin stimulated Akt phosphorylation in heart and liver, but not in epididymal WAT. One intriguing possibility is that a ‘cardiokine’ is being released from the cardiomyocytes lacking GHR leading to systemic alterations in insulin signaling. The emerging role of the heart as a metabolic mediator was demonstrated in 2012 when Greuter and colleagues discovered another protein, cardiac MED13, which can control systemic energy homeostasis (194). Ablation of cardiac MED13 results in increased obesity and metabolic syndrome when mice are challenged with a high-fat diet. Overexpression of MED13 results in increased insulin sensitivity and decreased fat mass (194). Further, the role of the heart as an endocrine organ has been recognized since 1981 with the discovery that heart extracts cause a sustained natriuretic effect in rats—this would later be called atrial

102 natriuretic factor or peptide (ANP) (195). Since then, atrial natriuretic peptide and brain natriuretic peptide have been recognized as key mediators of cardiovascular function through their concerted effects on the endothelium function and renal water balance. A recent review of ‘cardiokines’ describes more than 10 secreted factors that are recognized to be released from the heart, supporting the idea of the heart being viewed as an endocrine organ (196).

While our current study is the first to report disruption of cardiac GHR,

Vijayakumar et al. have previously reported constitutive disruption of cardiac and skeletal muscle GHR (mGHRKO) using the creatine kinase promoter (197). Interestingly, the mGHRKO have lower absolute fat mass, but similar percent adiposity compared to controls, and show increased insulin sensitivity when challenged with a high fat diet around 5 months of age (197). Additionally, the high fat fed mGHRKO mice show an increased respiratory exchange ratio indicating an improved metabolic efficiency (197).

Our results of decreased adiposity and increased insulin sensitivity in 6.5 month old iC-

GHRKO mice agree with the findings from the mGHRKO mice. Unfortunately, data from aged mGHRKO mice are not presented, and therefore, we cannot compare the study with our observation of impaired insulin sensitivity at 12.5 months of age. The improved metabolic efficiency may partly explain the decreased adiposity in the mGHRKO mice.

While we do not believe an altered metabolic efficiency is responsible for the decrease in adiposity observed in the iC-GHRKO mice because there was no change in body weight, we will need to conduct future studies on the topic to rule out this possibility.

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GH is traditionally thought to exert an anti-insulin effect through a molecular mechanism involving inhibition of P13K through upregulation of the regulatory p85 subunit (13, 14). Supporting an anti-insulin effect of GH, GHRKO mice are more insulin sensitive throughout life (187) and bGH mice are hyperinsulinemic (at least at young ages, 3-5 months) (146) with impaired insulin stimulated Akt phosphorylation in heart

(29). However, recent studies in bGH mice have brought to light the fact that as the mice age they become insulin sensitive and glucose tolerant with decreasing circulating insulin levels despite high circulating GH levels (157). This seemingly counterintuitive profile may be the result of impaired gluconeogenesis (158, 159) or the result of chronic adaptation to increased GH and related changes in the pancreas. Future studies will require us to take an in-depth look at the iC-GHRKO cardiac proteome as a function of age as one way of identifying possible changes in secreted factors.

Clinical studies have examined the use of GH supplementation in the treatment of chronic heart failure (CHF) with mixed results. Small open trials have shown beneficial effects of improved exercise capacity and hemodynamic indices (198). Of the double- blinded, placebo-controlled studies that have examined rhGH treatment in CHF patients, two have showed no beneficial effect on cardiac function (88, 185): one study using patients with Duchenn’s muscular dystrophy induced CHF demonstrated a reduction in

NT-proBNP (91), and one study demonstrated increase exercise capacity with increased

VO2max (90). Recently, Cittadini and colleagues identified a subset of chronic heart failure patients who also presented undiagnosed growth hormone deficiency (92). Their single-blinded, controlled study reported that replacement GH therapy for 3 months

104 resulted in improved cardiovascular scoring, increased exercise capacity, decreased NT- proBNP levels, and improved ejection fraction (92). On a four year follow-up these beneficial effects remained (93). The authors posit that dosage of rhGH and identification of existing GHD are paramount to observing positive outcomes of GH replacement therapy (93). Together with our current finding of no change in cardiac function of iC-

GHRKO mice, perhaps the principal effects of GH action in the adult cardiovascular system are outside of the cardiomyocyte or only become important in states of heart failure.

We should note that our study has several limitations. We examined only a single time point for GHR gene disruption. Studies with the iCM-IGF1RKO mice have shown changes depending on the age of gene disruption (139). Therefore, a future study would be to induce disruption at several time points to give a more complete picture of the role of cardiac GH signaling in cardiac development. Further, we only examined male mice due to the possible confounding effects of tamoxifen, high endogenous estrogen levels, and GH signaling in female mice. Finally, induction of the Cre recombinase in cardiomyocytes has been shown to acutely alter cardiac gene expression (199) with changes that resolve within one month of induction. The design of our mouse breedings did not allow us to explore Cre specific effects.

In conclusion, we report on the first cardiomyocyte specific GHR gene disrupted mouse line. Our data allude to tissue crosstalk with adult cardiac GH signaling being important in the regulation of systemic metabolic homeostasis—iC-GHRKO developed insulin resistance and glucose intolerance and had significantly lower fat mass from 4.5

105 to 8.5 months of age. Surprisingly, our results do not support a necessary role of adult cardiac GH signaling in the maintenance of cardiac function in male mice with no differences in echocardiographic measurements at baseline or after dobutamine challenge. In the future, it would be worthwhile to use the iC-GHRKO mice to provide answers to several interesting questions: What is the nature of the cardiac secretome, and how is it altered by cardiac GH action? Is cardiac GH signaling important in postinfarction recovery? Does cardiac GH action play a role in exercise-induced hypertrophy? Do the iC-GHRKO mice respond differently to dietary challenges such as high-fat feeding or caloric restriction?

Acknowledgements

We would like to acknowledge Kevin Funk, M.S. (Ohio University Edison

Biotechnology Insitute) for his assistance in designing a PCR based genotyping assay and

Lauren Volpe, M.Ed. (Ohio University Patton College of Education) for her careful editing of the manuscript.

Funding

This work was supported in part by the Gates Millennium Scholars (GMS)

Graduate Fellowship program; the State of Ohio's Eminent Scholar Program that includes a gift from Milton and Lawrence Goll; National Institutes of Health (NIH) Grant

P01AG031736; the Scholarly Enhancement Award, the Provost Undergraduate Research

Fund, and the Diabetes Institute at Ohio University.

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CHAPTER 5: DIFFERENTIAL GENE EXPRESSION IN 12-MONTH-OLD BOVINE

GH TRANSGENIC MOUSE HEART4

Abstract

Bovine growth hormone (bGH) transgenic mice have chronic high levels of GH

and downstream IGF-I and are used as models of human acromegaly. We have

previously shown that throughout age bGH mice develop elevated systolic blood pressure and exaggerated cardiac fibrosis (Chapter 3). To date, little is known about the dysregulation of gene networks in bGH heart that may help explain the chronic effect of

GH on the myocardium. Herein, we describe transcriptome analysis of 12 month old male bGH heart using RNA sequencing technology. Ingenuity Pathway Analysis revealed that the most dysregulated cellular pathways concern mitochondrial dysfunction.

In particular, several genes involved in expression of the mitochondrial electron transport chain Complex I were overexpressed in bGH heart versus littermate controls. Coupled with findings of decreased phosphofructokinase-1 (Pfkfb1), a key mediator of glycolytic flux, these data suggest a shift in mitochondrial substrate utilization in bGH heart. Future mitochondrial function assays will be necessary to validate these claims.

Introduction

The cardiovascular complications of acromegaly are well described with an increased incidence of hypertension, dyslipidemia, and development of cardiomyopathy

(140-142). The bovine growth hormone (bGH) transgenic mice overexpress bovine GH

4 Worked presented in this chapter represents a manuscript in preparation. The contributing authors are: Adam Jara, Vijay Nadella, Edward O List, and John J. Kopchick.

107 and as a result are often used as a rodent model of acromegaly (145, 147). Studies have shown that bGH mice exhibit elevated blood pressure (102-104), cardiac fibrosis (101,

104, 105), endothelial dysfunction (103, 110), and decreased cardiac performance (102).

Interestingly, no studies have examined the changes in the cardiac transcriptome in bGH mice. Therefore, the goal of this study was to examine differential gene expression in 12- month-old bGH mouse heart versus littermate controls. These results give insight into the complex genetic alterations of chronic GH stimulation and point to a role of GH in regulating cardiac mitochrondrial substrate metabolism.

Materials and methods

RNA-Sequencing

Total RNA was isolated from 50mg of ventricular tissue from bGH transgenic

(N=7) and NT littermate controls (N=8) following the aforementioned procedure described for RTqPCR. RNA quality was assessed using a Bioanalyzer 2100 (Agilent), and all samples had a RIN ≥ 9.0. Total RNA samples were then pooled such that we had three bGH samples (pool 1: 2 samples, pool 2: 2 samples, and pool 3: 3 samples) and two WT control samples (pool 1: 4 samples, pool 2: 4 samples). Poly-adenylated RNA was then isolated from total RNA pools using an Oligotex mRNA mini kit (Cat# 70002,

Qiagen). mRNA samples were then quantified using a Qubit RNA assay (Q32852, Life

Technologies) following the manufacturer’s directions. Whole transcriptome libraries were constructed using 200ng of mRNA template and a 1:100 ERCC spike-in controls

(Illumina). Transcriptome libraries were constructed and their quality checked using the

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Ion Total RNA-Seq Kit v2 (Life Technologies) following the manufacturer’s instructions.

Libraries were then sequenced using an Ion 318 (LifeTechnologies) semiconductor chip

analyzed on an Ion Personal Genome Machine (Life Technologies). Raw sequences were

exported in FastQ format and uploaded to the Galaxy cloud servers (200-202) for analysis.

Processing and Quality Checking of Ion Torrent Raw Reads

Raw sequence files using Sanger quality Phred scores were saved in FASTQ format and analyzed using FastQC. Sequences were then trimmed using Flexbar (203) based on the following criteria: 1) adapter sequences used during library preparation were

trimmed, 2) the first 15 bases at the 5’ end were trimmed and 3) the 3’ end was trimmed

using a sliding window of 3 and a minimum average Phred score of 20. The average read

length in each of the samples was 150-250bp.

Mapping RNA-seq Reads

Trimmed read files were uploaded to the Pittsburgh Galaxy Servers, and Tophat

v1.4.0 (204) was used to align the reads to the UCSC mm10 Mus Musculus reference

genome using an annotation file of known genes extracted from the UCSC genome

tables. Alignment was then performed using default parameters. Tophat is based on the

Bowtie short read aligner algorithm and breaks reads into 25bp fragment before mapping them back to the genome. When provided a reference gene annotation file, Tophat first maps reads to those locations before searching for other matches. Mapped reads form

clusters of expression which are interpreted as putative exons.

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Transcript Assembly, Gene Annotation, and Differential Expression

Sequence alignment files were used to assemble transcripts and determine transcript abundance using Cufflinks v2.1.1 (205). Cufflinks clusters the set of alignments into a minimum set of transcripts that best describe the alignment data and then calculates the abundance of these transcripts. If provided a gene annotation file,

Cufflinks will attempt to fit data to known transcripts. However, since we were also interested in the possibility of discovering novel transcripts we ran Cufflinks without providing a gene annotation file. A set of transcripts were assembled independently for each sample and each sample was bias corrected against the reference genome and corrected for multiple reads.

Cuffmerge is an algorithm included in the Cufflinks program and is used to compare each assembled transcript set to the reference annotation and create a single file describing known and novel transcripts in the set of data. Each set of transcripts produced by running Cufflinks on each sample were read into Cuffmerge to form an annotation file that described transcripts present in all samples.

Cuffdiff is also an algorithm included in the Cufflinks program which allows for calculation of differential expression between transcripts. The resulting Cuffmerge annotation file, along with the TopHat alignment files for each sample, were supplied to

Cuffdiff to compare differential gene expression between WT and bGH groups.

Differential expression (DE) is based on the measurement of fragments per kilobase of exon per million fragments mapped (FPKM) and significant DE was determined when the false discovery rate corrected p-value (q) is <0.05. The false discovery rate was set to

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5%. All Cufflinks, Cuffmerge, and Cuffdiff analyses were performed on a 2.8 Ghz quad core desktop computer with 16GB of RAM running Ubuntu 12.04 LTS.

Results

To gain perspective on the chronic changes GH makes to heart gene expression,

RNA-seq was used to determine transcriptome changes in 12-month old bGH heart compared to WT littermate controls. Out of the 31172 annotated transcripts, compiled using both the UCSC mm10 genome and the sequence data from this experiment, 961 transcripts showed significantly decreased expression (q<0.05) and 20 transcripts showed significantly increased expression (q<0.05) (Figure 5.1). Table 5.1 shows the top 10 up and down regulated genes. Due to the large number of differentially expressed genes,

Ingenuity Pathway Analysis (IPA) was used to assess the biological pathways that were perturbed in bGH heart. Table 5.2 lists the most significantly regulated pathways showing that the mitochondrial biosynthetic pathways are disturbed in the bGH heart as well as the

NRF2 mediated oxidative stress pathway. Figure 5.2 shows the mapping of the genes related to mitochondria dysfunction to encoded proteins in the electron transport chain.

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Figure 5.1: Venn diagram of differential gene expression in heart. Venn diagram showing transcripts which were significantly down-regulated (light gray) or up-regulated (dark gray) in 12-month old bGH heart relative to wild-type littermates. The overlap shows the number of transcripts that were not changed.

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Table 5.1: Top 10 up- and downregulated genes

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Table 5.2: IPA Top Disrupted Cellular Pathway

Figure 5.2: Diagram of mitochondrial electron transport chain. Overlaid in color are the genes which are significantly regulated in bGH heart. Shades of orange to red indicate higher levels of expression compared to wildtype. Dark shades of green indicate lower levels of expression compared to wildtype. 114

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Discussion

In the absence of experiements assessing function of the bGH heart mitochondria, gene analysis can be difficult to interpret. Based on our findings from Ingenuity Pathway

Analysis (IPA) and looking at the top 10 up and downregulated genes we can infer what functionally may be occuring in the aged bGH mouse heart. IPA of the resulting differentially expressed genes point to a majority of mitochondrial related genes being up-regulated in the bGH heart. When mapped to mitochondrial proteins, these genes

cluster in complex I of the electron transport chain (Figure 2). Complex I is responsible

for the oxidation of NADH, produced from glycolysis and the citric acid cycle, to NAD+.

Interestingly, phosphofructokinase/fructose-2,6-bisphosphatase (Pfkfb1) was one

of the top 10 down regulated genes in bGH heart (1.8 log2 fold decrease) (Table 5.1,

bottom). Pfkfb1 encodes a multi-functional enzyme, which through the formation of

fructose-2,6-bisphosphate, controls glycolytic flux. High levels of F-2,6-P2 increase

glycolytic flux while low levels decrease glycolytic flux. The inability to increase F-2,6-

P2 levels in the heart were recently associated with increased reactive oxidative stress

and maladaptation to pressure overload (206) The importance of increased cardiac

glycolysis during stress is underscored by a study that shows increased cardiac glucose

uptake and glycolysis, resulting from transgenic expression of cardiac-specific GLUT1,

protects mice from heart failure induced by aortic constriction (207). The decrease in

Pfkfb1 expression taken together with the upregulation of several components of

Complex I might suggest that glycolytic flux is decreased in the bGH heart, but the need

to produce NAD+ is increased. An increase in fatty acid oxidation may explain this shift.

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It has been reported that in young bGH mice, fatty acid metabolism is increased heart, but

as the bGH mice age, fatty acid metabolism actually decreases in the heart (208). It has

been proposed that the hypertrophied heart experiences a decreased energy reserve,

which causes a subsequent increase in AMPK activity, increased F-2,6-P2 production,

and increased glycolytic flux (209). Therefore, if this pathway is altered in the bGH mice,

it may explain, in part, the massive fibrotic cardiac remodeling we observed in old bGH

mice (Chapter 3, Figure 3.3A-B).

A future study that would allow us to examine both fatty acid oxidation and

stability of the complex I of the electron transport chain in bGH heart mitochondria

would be especially interesting. One possibility is to use a platform such as the Seahorse

Flux Analyzer, which allows for simultaneous collection of data from 24 wells, to

examine oxygen consumption rate in the presence of fatty acids such as palmitate. With

the addition of an inhibitor of carnitine palmitoryl transferase 1 (CPT-1), we can begin to

examine how efficient bGH myocardial cells utilize fatty acids for energy production.

Simultaneously, we could also examine the preference of the bGH myocardial cells for

glucose versus fatty acid by injecting each during the experiment and calculating the

change in rate of oxygen consumption (210). Isolated mitochondria from bGH heart

could then be used to perform an electron flow analysis where we could, in a step-wise manner, inhibit the different complexes of the electron transport chain, comparing

oxygen consumption between bGH and wild-type at each step (211).

In conclusion, gene expression analysis reveals that genes related to mitochondria function are the most differentially regulated genes in the aged bGH heart. Our analyses

117 indicate that mitochondria substrate balance may be altered with bGH mice having decreased glycolytic flux in the heart. Future studies analyzing mitochondria function will be required in order to test this theory.

Funding

This work was supported in part by the Gates Millennium Scholars (GMS)

Graduate Fellowship program; the State of Ohio's Eminent Scholar Program that includes a gift from Milton and Lawrence Goll; National Institutes of Health (NIH) Grant

P01AG031736; the Scholarly Enhancement Award, the Provost Undergraduate Research

Fund, the Diabetes Institute, and the Genomics Facility at Ohio University.

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CHAPTER 6: CONCLUDING REMARKS AND FUTURE STUDIES

Detailed discussions regarding data in the context of the related literature are

included at the end of Chapter 3 for studies involving bGH transgenic mice and Chapter 4

for studies involving the iC-GHRKO mice. Here we will summarize the salient points

from each of the previous chapters and propose ideas for future projects.

Elevated systolic blood pressure in male GH transgenic mice is age-dependent

Key Findings: The effects of chronic GH stimulation on systolic blood pressure (SBP)

vary with age. Under the age of 6 months, bGH mice displayed normal SBP and after 6

months had elevated SBP. Along with this increase in SBP with age, bGH mice exhibited

exaggerated cardiac fibrosis and glomerular enlargement with mesangial proliferation at

older age. These changes correlated with decreased circulating levels of brain natriuretic

peptide (BNP) levels from 5 to 7 months of age and with a dramatically increased renal

ACE/ACE2 ratio in older bGH mice. Therefore, both the ACE2 and BNP represent

pathways that should be exploited for a potential role in reversing elevated SBP in bGH mice.

In terms of our specific aims for this study (outlined at the end of Chapter 1), our hypothesis that systolic blood pressure was dependent on age was correct. Further our hypothesis that there were alterations in the natriuretic peptide and ACE2/Ang(1-

7)/MasR pathway was also correct. However, our hypothesis that insulin resistance was important was not supported, as our data showed that 10-month-old bGH mice were significantly more insulin sensitive than control mice.

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Cardiac GHR signaling is necessary for maintaining glucose homeostasis in adult male mice

Key Findings: Intact cardiac GH signaling in adult mouse heart is required for long-term maintenance of systemic glucose homeostasis, but not for maintenance of cardiac mass or function. Disruption of GHR gene specifically in cardiomyocytes resulted in an age- dependent decline in glucose tolerance and insulin sensitivity. There also appeared to be a tissue specific attenuation of insulin stimulated Akt phosphorylation. Surprisingly, cardiac mass and function (at baseline and under dobutamine stress) were unaffected by the gene disruption. These results indicate that 1) the heart may be a major player in whole-body metabolism and 2) perturbation of cardiac GH signaling results in whole body metabolic changes. It is exciting to posit that a circulating factor from the myocardium is responsible for these metabolic changes.

In terms of our aims for this study we were successfully able to disrupt cardiac

GHR gene in a tamoxifen dependent manner; however, our hypothesis that GH signaling would alter cardiac function was not supported. In fact, iC-GHRKO demonstrated no change in function at 12 months of age versus control mice. Further our hypothesis that

GH signaling would alter cardiac calcium channel expression was only partially supported. By 12.5 months of age (8 months post-induction), the iC-GHRKO mice had only a minor decrease in SERCA2 expression. Finally, our hypothesis that cardiac GHR disruption would not alter systemic metabolism was also not supported. The most striking feature of the iC-GHRKO mice was the development of insulin resistance and glucose intolerance with age.

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Future Directions in Bovine GH Transgenic Mice

Our study described in Chapter 3 demonstrates that cardiac fibrosis is a

characteristic of chronic GH stimulation in bGH mice. Likewise, cardiac fibrosis with exaggerated collagen deposition is common in humans with acromegaly (212). The extra collagen likely promotes improper ventricular filling and contributes to the development

of cardiomyopathy, as described in Chapter 1. Outside the heart, a positive relationship

between GH action and collagen deposition has been observed in several other tissues. In

the kidney, bGH transgenic mice exhibit glomerulosclerosis with increased type IV

collagen around the glomerular basement membrane and mesangial interstitium (115).

Our results (Chapter 3) showing increased mesangial sclerosis as a function of age in

bGH mice support this finding. In skeletal muscle of acromegaly patients versus GHD

patients, expression of IGF-I, collagen I, and collagen III mRNA is elevated and related

to a marginal increase in rate of protein synthesis (213). In GHR-/- mice, expression of collagen I and III mRNA in calf and Achilles tendon is decreased and associated with a decrease in collagen fibril diameter compared to littermate controls (214). On the other hand, bGH mice have increased collagen I and III mRNA in calf muscle and Achilles tendon, but also show a decrease in collagen fibril diameter (214). In the liver of rats with chemically induced cirrhosis, administration of human GH causes increased production of both collagens I and IV (215). Taken together, these studies suggest that GH promotes collagen deposition in many tissues and is not specific to any one subtype of collagen.

Collagen, mainly types I and III, constitute a principle component of cardiac structure (216). Interestingly, cardiac collagen I fibrils demonstrate increased elasticity,

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decreased plasticity, and increased resistance to stretch versus cardiac collagen III fibrils

(216). Therefore, the relative distribution of type I and III collagen fibers in the heart may

represent an adaptive response to changing hemodynamics. For example, a relative

increase in type I collagen may allow the heart to resist dilation and allow for increased

force generation (216). Given these insights, it would be interesting to explore the

relative distribution of collagen subtypes in the bGH mouse heart as a function of age.

Since the bGH mice develop elevated systolic blood pressure around 6 months of age, it

may be that this is also the timepoint when the chronic effects of GH cause a shift in the

collagen subtypes within the heart. Another interesting study would be to cross the bGH

mouse with inducible, cardiac-specific collagen I and collagen III gene disrupted mouse

lines. The resulting cross would allow for targeted disruption of the main cardiac collagen

subtypes in the adult bGH mouse. By inducing collagen disruption at different

timepoints throughout life and examining cardiac function and histology, it would be

possible to determine: 1) which collagen subtype is preferentially affected by GH action,

and 2) how cardiac function is affected by the presence or absence of a particular collagen subtype.

Moving away from collagen, our finding that BNP transcript levels increased with age, but BNP circulating levels decreased with age in bGH mice indicates that chronic

GH stimulation may inhibit formation of active BNP. Our experiments did not allow us

to understand at what level GH regulates BNP. It could be secretion of proBNP from the

myocardium, cleavage of proBNP to BNP, or enhanced degradation of BNP in the

periphery. As we mentioned in the discussion in Chapter 2, bGH mice were previously

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shown to have decreased levels of a related peptide, atrial natriuretic peptide (ANP)

(126). Inhibition of the natriuretic peptide system, which is paramount to maintaining

proper blood pressure, may help to explain the increased prevalence of hypertension in

patients with acromegaly (107). In 2010, two convertases, furin and corin, were reported

to be responsible for processing of proBNP to active BNP (217). It would be interesting

to assay the levels of these two enzymes in bGH heart as a function of age.

A final study we would like to propose for the bGH mice is to further examining

the role of the ACE2/Ang(1-7)/MasR pathway in the development of cardiac fibrosis and elevated blood pressure. Our results demonstrated that in kidneys of old aged (12 months) bGH mice, there is an elevated level of ACE versus ACE2 protein (Chapter 3, Figure 6).

We also found that eNOS, which we assayed as an indirect measurement of Mas receptor activity, was dramatically attenuated in bGH kidney. These data imply that production of the pro-fibrotic, vasoconstrictive angiotensin II prevails over the vasodilatory, antiproliferative angiotensin (1-7) (150) in the kidney of old bGH mice. A future study examining ACE, ACE2, eNOS, MasR, AngII, and Ang(1-7) levels as a function of age in

both heart and kidney would give a clearer picture of how these arms of the RAAS are

affected by short-term and long-term GH stimulation.

Future Directions in iC-GHRKO Mice

The studies we conducted with the new iC-GHRKO mouse line are only the beginning of what these mice can be used to explore. We established baseline cardiac function and metabolic measurements due to gene disruption at a single age. Given that our disruption was successful, we are now positioned to ask several interesting questions.

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The altered metabolic profile in the iC-GHRKO mice alludes to an underlying role of the cardiac GH action in regulating systemic glucose homeostasis. At the molecular level, GH action is thought to antagonize insulin signaling through upregulation of the p85 subunit of PI3K, leading to inhition of PI3K activation (Figure

6.1A) (13, 14). In the older iC-GHRKO mouse heart, however, this relationship appears to reverse. One possibility is that GHR signaling modulates other molecular pathways involved in mediating insulin stimulated AKT phosphorylation. Loss of GHR control of these pathways could simultaneously impact the effect of insulin on AKT (Figure 6.1B).

However, this does not explain how GHR disruption in the heart can affect systemic glucose tolerance and insulin stimulated AKT phosphorylation in liver. One possible explanation is that cardiac GHR signaling controls the production of a secreted factor, which is altered when GHR is disrupted. Changes in the level of this unknown secreted factor could affect insulin signaling in distant organs (Figure 6.1C).

We currently have work ongoing to examine the effect of blood plasma isolated from iC-GHRKO and control mice on the insulin sensitivity of 3T3L1 fibroblasts and

HepG2 hepatocytes. Given that we observed a tissue specific effect in the iC-GHRKO with decreased insulin stimulated Akt phosphorylation in heart and liver, but not in epididymal WAT, the use of both 3T3L1 fibroblasts (which are pre-adipocytes) and

HepG2 hepatocytes should give us a system to test different cell types. Due to us having a limited amount of plasma from the 12-month-old iC-GHRKO and control mice, we plan to do the following: 1) assay p-Akt/Akt in 3T3L1 fibroblasts and HepG2hepatocytes

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Figure 6.1: Possible crosstalk between cardiac GHR signaling and insulin receptor signaling. A) Currently accepted role of GHR inhibition of insulin stimulated P13K activation, B) Loss of cardiac GHR signaling decreases insulin stimulated AKT activation possibly through a co-regulated pathway, C) Cardiac GHR signaling may regulate production of a secreted factor from the heart that can control insulin signaling in distant organs. IR: insulin receptor, GHR: growth hormone receptor, PI3K: phosphoinositide 3-kinase, AKT: Ak thymoma, also known as protein kinase B.

treated with increasing amounts of insulin (300nM, 100nM, 30nM, 10nM, 3nM, 1nM,

0nM), and 2) assay p-Akt/Akt in both cell types cultured in 10% iC-GHRKO or control mouse plasma from 12-month-old mice and subsequently treated with the aforementioned series of insulin concentrations. P-Akt and Akt levels will be assayed using immunoblot as explain in Chapter 2 and 3 (see Appendix B for a tutorial on immunoblotting). The result will be a dose response curve with insulin concentration on the x-axis and p-

Akt/Akt ratio on the y-axis. This experiment will be able to show any inhibition of Akt

125

phosphorylation that results from pretreatment with iC-GHRKO as a downward shift in

the insulin response curve.

Given that we observed no change in baseline or dobutamine stressed cardiac function, the logical next step would be to examine how the iC-GHRKO mice respond to chronic cardiac stress and hypertrophy. Broadly, cardiac hypertrophy can be regarded as physiologic or pathological. Pathologic hypertrophy is enlargement of the heart that is associated with fibrosis, disorganized cellular organization, and decreased cardiac function, while physiologic hypertrophy is enlargement of the heart with an ordered cellular structure and no development of fibrosis (218). It is generally accepted that physiologic hypertrophy develops through activation of the PI3K/Akt pathway while

pathological hypertrophy develops though activation of G-coupled protein receptors and

downstream activation of MAPK and NFAT (218). Given that inducible loss of cardiac

IGF-IR in both young and aged mice was reported to not change the hypertrophic

response to isoproterenol induced hypertrophy (139), and cardiac IGF-IR null mice have attenuated cardiac hypertrophic response to swim training which is not mediated through

Akt signaling (136), it would be interesting to assess the iC-GHRKO mice. GH signaling may be the major player linking exercise and downstream Akt signaling in physiologic hypertrophy.

Finally, a larger study examining the influence of age on cardiac structure and function and recovery from cardiac infarction in iC-GHRKO mice could be especially

revealing. As described in the section entitled Chronic heart failure in Chapter 1, many

of the early studies linking GH action to cardiac function were performed by injecting

126

GH into rats after experimentally induced cardiac infarction (most often by coronary

artery ligation). Further, it was recently reported that inducible excision of cardiac IGF-

IR gene in aged, but not young, mice resulted in decreased diastolic cardiac function

(139). This report indicates that the hormonal regulation of the myocardium may change

throughout age. Therefore, we propose a study in which we induce GHR gene excision at

4 different time points: prenatal, postnatal before weaning, six months of age, and one year of age. Mice from these four time points would be split into three experimental groups: group 1) serial histological analysis of heart every 3 months, group 2) serial

echocardiographic baseline and dobutamine stress measurements every 3 months, and

group 3) coronary artery ligation to induce infarction with follow-up echocardiography to

assess recovery.

As a final note in performing future studies, we should point out that it may be beneficial to change the breeding scheme we used for our initial evaluation. Currently, the iC-GHRKO mice are maintained in a breeding line between Myh6-MerCreMer+/-

/GHRfl/fl and GHRfl/fl which only yields one-half Myh6-MerCreMer+/-/GHRfl/fl mice, half of which must be injected with vehicle as a control. This is compounded by one-half

again if you use a single sex, meaning that in our studies we only had 1/8 of the mice being used in the iC-GHRKO group. Breeding the MerCreMer to homozygosity would allow for half of the mice to be potential iC-GHRKO, allowing for a theoretic four-fold

reduction in mouse cage costs.

In conclusion, our study assessing blood pressure in bGH transgenic mice has

emphasized the need to consider the changing effects of GH in an acute and chronic

127 stage. The study has opened up new avenues for understanding the role of GH in the cardiovascular system, including a possible role in regulating the natriuretic peptide system and the ACE2/Ang(1-7)/MasR pathway. Our study involving the production and characterization of the iC-GHRKO mouse line suggests that while cardiac GH signaling is not important for cardiac function, it does appear to regulate systemic glucose homeostasis. Future studies in both of these mouse lines will help us to solidify our understanding of GH in the cardiovascular system and likely demonstrate an integrated molecular network through which GH regulates growth and development.

128

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APPENDIX B: ORAL DEFENSE PRESENTATION SLIDES

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APPENDIX C: CHAPTER 3 SUPPLEMENTAL MATERIALS AND METHODS

Real time quantitative PCR (RTqPCR) primer design

All RTqPCR primer pairs were designed using Primer Blast (219) to 1) span exon-exon junctions, 2) give amplicons between 80 and 200 bp, and 3) have melting points between 59-61°C. All amplicons were quality checked in silico using mFold (220) to determine if hair pin structures would form at the 3’ or 5’ ends. Primer efficiency curves were determined for each primer pair using a serial dilution of cDNA template spanning 4 orders of magnitude. All primer pairs exhibited efficiencies between 98-

102%. The primer sequences used for each gene are listed in Supplemental Table 1.1.

RTqPCR

Small sections of heart ventricle isolated from whole heart samples were dissected from bGH (N=5) and WT (N=9) mice, rinsed with PBS, and immediately flash frozen in liquid nitrogen. Small sections (~35mg) of heart ventricle were cut and placed on dry ice and total RNA was isolated using the RNeasy Mini Kit (#74104, Qiagen) following the manufacturer’s directions. A Precellys 24 Dual ceramic bead homogenizer (Bertin) connected to a dry ice chilled Cryolys (Bertin) cooler maintained at < 10 °C chamber temperature was used for sample homogenization (5000rpm, 2x20 second cycle, mixed

2.8mm large and 1.4mm small and ceramic beads). RNA quality was assessed using a

BioAnalyzer 2100 (Agilent). Only samples with a RIN > 7.0 were used for further analysis. Reverse transcription was performed using the Maxima First Strand cDNA

Synthesis Kit (#K1642, Thermo Scientific). RTqPCR was performed in a BioRad iCycler machine using Maxima SYBR Green/Fluorescein qPCR kit (#K0242, Fermentas/Thermo

187

Scientific). Each PCR reaction contained 25ng of cDNA template and forward and

reverse primers at a final concentration of 0.2uM. For each sample a reverse transcription

negative (NoRT) control was included, and for each gene on every plate a no template

control was run. The PCR amplification protocol was as follows: 10min at 95°C (dwell time and well factor collection), 10 min at 95°C (initial denaturation), followed by 40

cycles of 15 seconds at 95°C, 30 seconds at 60°C, and 30 seconds at 72°C. Following

amplification, a melting curve analysis was performed from 55-85 °C in 0.5°C steps to

determine specificity of amplification and to check for primer dimer formation.

Subsequently, one sample from each triplicate was separated on a 1.5% agarose gel to

check for a single PCR product band. Three reference genes (Rpl38, Hprt, Eif3f) picked

from a panel of eight candidate genes based on a combined GeNorm M value < 0.15 were

used for normalization.

Immunoblots

Protein was isolated from homogenized sections of flash frozen kidney (~30mg).

Tissue sections were placed in 600µL 1x RIPA buffer (#9806, Cell Signaling) spiked

with 1mM phenylmethylsufonyl fluoride and placed on ice for 5 minutes. Samples were

subsequently homogenized using a Precellys 24 Dual ceramic bead homogenizer (small

1.4mm ceramic beads, 2 cycles of 20 seconds at 5000rpm). Homogenates were

centrifuged at 14000g for 10 min at 4°C and supernatants were collected. Protein

concentration was determined using a Bradford Assay (BioRad). Protein samples (20ug)

were separated on 10% SDS-acrylamide gels and then transferred to Amersham Hybond-

LFP membranes (#RPN2020LFP, GE Healthcare). After rinsing in Tris Buffered Saline /

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0.05% Tween 20 (TBS/T) and one hour of blocking in 5% non-fat dry milk in TBS/T, membranes were rinsed six times using TBS/T and exposed to overnight incubations with primary antibodies at optimal dilutions in 5% bovine serum albumin in TBS/T: ACE

(#SC-20791, 1:200), ACE2 (#SC-20998, 1:200), eNOS (#SC-654, 1:200), (Santa Cruz

Biotechnology); GAPDH (#2118, 1:1000), (Cell Signaling). Membranes were then washed three times in TBS/T and incubated for 1 hour with Cy5 conjugated secondary antibody (1:2500) (#PA45011, GE Healthcare) in TBS/T. Membranes were scanned using a Molecular Imager PharosFX Plus laser scanner (Biorad) using the following scanning parameters: 635nm EX, 695nm BP, 50µm resolution. Densitometry measurements were performed using 8-bit membrane scans in ImageJ software (151). All protein densities were first normalized to GAPDH density levels.

Automation of ImageJ cardiac collagen calculation

The following script written for use in the ImageJ software (151) allows the user to select the input directory containing the images they wish to process and an output directory which will contain the processed images with flattened overlays showing the area used in the % collagen determination and an Excel spreadsheet containing the image name and % collagen. Each image is loaded into ImageJ as an 8-bit RGB stack and the green channel is chosen because it demonstrates a stark contrast between the bright blue stained collagenous fibers and all other cellular components. The image is then set against a black background to invert threshold levels. To adjust for differences in white levels between images, we empirically determined the brightest image within a group from the same mouse and calculated a minimum and maximum “threshold coefficient”

189 as: MinOffset Coefficient = minimum manual threshold / automatic minimum threshold,

MaxOffset Coefficient= maximum manual threshold / automatic maximum threshold.

These coefficients are supplied to the script and used to adjust the minimum and maximum thresholds determined automatically in ImageJ. This results in each micrograph being independently adjusted for white level. The selected area is then assessed as a percentage of the total area of the slide. We suggest that when using large groups of images (30+) in tiff format that the user have > 2GB RAM free and assign this to the Java VM running ImageJ.

function getOptions() {

Dialog.create("Set Options");

Dialog.addMessage("Enter the minimum and maximum threshold offsets.\nUse values obtained from the brightest image\nin the set that you intended to analyse.\nMin offset = Manual Min/Auto Min\nMax offset = Manual Max/Auto

Max");"

Dialog.addNumber("Minimum offset:",1.000,3,4,"");

Dialog.addNumber("Maximum offset:",1.000,3,4,"");

Dialog.addMessage("Leave offset as 1.000 if you desire no correction.");

slices = newArray("Red", "Green", "Blue");

Dialog.addChoice("Set slice to: ", slices, "Green");

formats = newArray("TIFF", "JPEG", "PNG", "BMP");

Dialog.addChoice("Convert to: ", formats, "JPEG");

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Dialog.show();

minoff = Dialog.getNumber();

maxoff = Dialog.getNumber();

sliceset = Dialog.getChoice();

picformat = Dialog.getChoice();

if (sliceset == "Red")

sliceset = 1;

else if (sliceset == "Green")

sliceset = 2;

else if (sliceset == "Blue")

sliceset = 3;

options = newArray(minoff, maxoff, sliceset, picformat);

return options;

} run("Memory & Threads...", "maximum=2304 parallel=2 run"); dir1 = getDirectory("Choose source directory "); dir2 = getDirectory("Choose Destination Directory "); optionslist = getOptions(); list = getFileList(dir1); setBatchMode(true); for (i=0; i

showProgress(i+1, list.length);

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open(dir1+list[i]);

run("RGB Stack");

setSlice(optionslist[2]);

run("Set Scale...", "distance=584 known=100 pixel=1 unit=um");

setAutoThreshold("Default dark");

getThreshold(min, max);

setThreshold(min*optionslist[0], max*optionslist[1]);

run("Set Measurements...", "area area_fraction limit display redirect=None

decimal=3");

run("Measure");

run("Create Selection");

run("RGB Color");

run("Overlay Options...", "stroke=red width=0 fill=#ffff0000 set");

run("Add Selection...");

run("Flatten");

saveAs(optionslist[3], dir2+list[i]);

close();

} selectWindow("Results"); saveAs("Results", dir2+"Results.xls"); if (isOpen("Results")) {

selectWindow("Results");

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run("Close");

} call("java.lang.System.gc"); showMessage("All done."+" "+i+" images were processed!");

Supplemental Table 3.1: RTqPCR primers

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APPENDIX D: CHAPTER 4 SUPPLEMENTAL MATERIAL

Supplemental Table 4.1: PCR primers

Supplemental Figure 4.1. Systolic blood pressure. Non-invasive tail-cuff systolic blood pressure was measured from 4.5 – 12.5 months of age in iC-GHRKO (N=8) and Control (N=24) littermates. * significant difference between genotypes (P<0.05), † significant difference with age (P<0.05). iC-GHRKO: inducible, cardiac-specific GHR gene disrupted mouse, SBP: systolic blood pressure.

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APPENDIX E: IMMUNOBLOT PROTOCOL

**All solution recipes follow the protocol

Step 1) Protein Isolation and Quantification (Time: 2-3 hours)

**If you are going to run gels today, pour them now!**

Cell Culture (60-80% confluent cells starved overnight in serum free media)

-Treat cells according to your experimental protocol. -Wash cells with sterile PBS (~1mL if plated, ~5mL if in small flask) -Add 1x RIPA w/ PMSF (1:100) [400uL/well (6-well plate) or 1mL/small flask] -Incubate on ice for 5 minutes -Scrape cells and collect suspension in a microcentrifuge tube. -Sonicate in ice water for 5 min. -Centrifuge at 14,000g for 10min at 4C. -Decant supernatant to a new microcentrifuge tube.

Tissue

-Cut 25-30mg of snap frozen tissue. -Add 600uL 1x RIPA w/ PMSF (1:100) to each sample -Incubate on ice for 5 minutes -Homogenize in Precellys using conditions outlined in Appendix (PRECELLYS HOMOGENIZATION SETTINGS). -Centrifuge at 14,000g for 10min at 4C. -Decant supernatant to a new microcentrifuge tube.

Quantification (Using Bradford Assay, performed in 96well plate)

-Prepare Bradford reagent 1x stock. Bio-Rad Bradford Reagent is supplied as 5x. Dilute to 1x with ddH2O (1:4). -Make BSA standards in same buffer used for samples (or if you are diluting samples with H2O you can make BSA standards with H2O). a. Stock 1ug/uL b. 0.50ug/uL c. 0.25ug/uL d. 0.125ug/uL e. 0.0625ug/uL f. 0.03125ug/uL g. Blank (Buffer or H2O)

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-If you have no idea about the range of the concentration of your sample, make 1:10, 1:50, and 1:100 dilutions. -Add 10uL of sample dilution or standard (in triplicate) to 200uL 1x Bradford Reagent, gently mix. -Incubate for 5min at RT (no longer than 1hr). Read plate at 595nm Absorbance.

Step 2) Running SDS-PAGE (Time: 1.5-2 hours)

-Decide on the percentage of resolving gel necessary to put your protein of interest around the middle of the gel. See Appendix PROTEIN GELS. *Remember to position gels into running cassette such that the small plates are facing inward* -Calculate ul of each sample needed to load between 20-30ug. Typically 15-20uL per sample is good.

Ex) I want to load 20ug of sample 1 in 20uL of buffer.

Sample 1 [4ug/uL] Sample 10uL ddH2O 10uL Laemmli 20uL_____ TOT 40uL

-Boil diluted samples in Laemmli Buffer for 5 min (use heating block or PCR machine) -Load gel, including protein ladder. -Run @ 35 mAmp/gel for ~45min – 1.5 hr (depends on gel%, higher % means longer running time). *Run until dye front reaches the bottom* -Remove stacking gel and any remaining dye front before continuing to transfer. -Cut the top left corner from the resolving gel so that you can keep the gel oriented throughout the experiment.

Step 3) Protein Transfer (Time: 1.5-2 hours)

-Prepare 1L of 1x transfer buffer -Soak gels in cold transfer buffer for 20 minutes (the gels will change size due to the MeOH in the buffer). -Cut membrane and filter paper (2 filters per gel) to 9.5cm wide x 5.5cm tall (assuming mini gels). -Submerge PDVF membranes in ice cold 100% methanol for 2 minutes. -Rinse in ddH2O for 2 minutes -Equilibrate in transfer buffer for 5 minutes

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-Submerge sponges and filter papers in transfer buffer just prior to assembling the transfer sandwich. -To minimize the chance of introducing air bubbles between the membrane and gel, assemble the sandwich under transfer buffer. -Do this by placing the black side of the cassette (- end) in the buffer, apply one sponge on top and gently push air bubbles out of the sponge, lay one filter paper on the center of the sponge, then lay the gel (noting the orientation) on top of the filter paper, next place the membrane on top of the gel, use a serological pipette to roll any air bubbles out of the membrane-gel interface, next place the remaining filter paper on top of the membrane, then place the remaining sponge to complete the sandwich. Slide the latch to secure the transfer sandwich. *The order of your transfer sandwich should be: Black (- end) Sponge Filter paper Gel Membrane Filter paper Sponge Clear (+ end) -Place the sandwich in the transfer apparatus ensuring that the latch is on the top and the black end is oriented towards the black end of the apparatus. -Insert a small stirring rod and the ice pack into the running tank. -Fill the running tank with transfer buffer. -Run at 100V for 1hr, under gentle stirring at room temperature. *Note, a longer transfer can be performed if this does not work*. *20V overnight, under gentle stirring at 4C*. -Gauge the level of protein transfer by the amount of rainbow protein ladder that has been transferred to the membrane. -Transfer membrane immediately to 10mL TBS used for rinsing in next step.

Step 3a) Optional Staining of membrane and gel to verify transfer

Membrane Stain with Ponceau Red (Time: 10 min) -If the membrane is dry, wet it in 100% methanol for 2min prior to staining. -Cover membrane with Ponceau red, and agitate for 1 minute -Rinse membrane with H2O until contrast is achieved. -Wash membrane with 0.1N NaOH to remove stain.

Gel Stain with Commassie Blue (Time: 1.5 hours) -Fix gel in 40%EtOH/10%AcOH for 20 minutes. -Stain gel for 1 hours using 0.1% colloidal Coomassie G-250 in 35%MeOH / 2.5% phosphoric acid / 10% ammonium sulfate.

197

Step 4) Membrane Blocking and Primary Antibody (1 hour then o/n)

-Wash membrane in 10mL TBS for 2 minutes under gentle agitation. -Block membrane in 10mL of Blocking Buffer for 1 hr. -Wash membrane in 10mL TBS/T for 5 minutes under gentle agitation. -Add primary antibody at optimal dilution in 5%BSA/TBS-T. *Typically this is 1:1000 for Cell Signaling, but check manufacturer. -Incubate overnight at 4C, sealed with parafilm with gentle agitation.

Step 5) Secondary Antibody (1.33 hours)

-Rinse membrane once in an excess of TBS/T. -Wash membrane six times in an excess of TBS/T for 5 minutes under gentle agitation. -Add secondary antibody at optimal dilution in TBS/T.*SEE NOTES BELOW* -Incubate for 1 hour at room temperature. If using a fluorescent secondary make sure the container is protected from light. If using a fluorescent secondary antibody (next 2 steps apply): -Rinse membrane once in an excess of TBS/T. -Wash membrane 3 times in an excess of TBS/T for 5 minutes under gentle agitation. -Rinse membrane in 5mLTBS. -Keep membrane in 10mL TBS (unless drying, see next step). If using a non-fluorescent secondary: -Rinse membrane once in an excess of TBS/T. -Wash membrane six times in an excess of TBS/T for 5 minutes under gentle agitation. -Keep membrane in 10mL TBS/T.

*Secondary antibodies (CyDye Antibodies) are light sensitive so keep everything wrapped in aluminum foil. For Cy5/Cy3 GE Antibodies the optimal dilution is 1:2500. *If using ECL reagent: 1) Dilute secondary antibody in 5% milk (or protein used for blocking) in TBS/T. 2) A good starting dilution for secondary is 1:50000. Due to the sensitivity of ECL more dilution may be necessary.

Step 6a) Fluorescent Imaging (15 minutes)

-If no further probing/stripping is planned, then dry the membrane prior to imaging. -Dry by placing on blotting paper and incubating at 37C for 1 hour. -Scan using the PharosFX Plus

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-Ensure that external laser is turned on. -Set channel to proper fluorophore (Cy5 or Cy3). -Place membranes on screen using a small drop of water to ensure no air is introduced between membrane and screen. *Place membrane with proteins facing up, the machine scans from above. -Capture a low resolution scan (200um) to ensure correct membrane orientation. -Capture high resolution (50um) final scans. -Be sure to export jpeg files at 100% quality and store both the scan and jpegs on an external drive.

Step 6b) ECL Imaging (30 minutes)

-Mix the ECL reagent following the manufacturer’s instructions. -Typically this involves mixing a luminol solution 1:1 with a peroxide solution. -If using RPN2232 GE Amersham ECL Prime Reagent you will need approximately 3mL of ECL reagent for a single membrane. -Prepare this by mixing 1.5mL Solution A (Luminol) with 1.5mL Solution B (Peroxide solution) and briefly vortex. - Gently remove the membrane from the TBS/T and allow excess TBS/T to run off the membrane. *Work quickly to ensure your membrane doesn’t dry out. -Pipette the ECL reagent onto the membrane and gently rotate to ensure membrane coverage. -Incubate at room temperature for approximately 30-45 sec. *Note that the manufacturer protocol suggests 5 min, we have found this to produce severe background signal. -Gently pick up the membrane to allow the ECL reagent to run off and blot the edge on a Kim wipe. -Place the membrane between two pieces of plastic (paper protectors work great!) and smooth to get rid of any air bubbles. -In the dark room (lights off, red light on) 1) Place the sheet of x-ray film in the corner of the developing cassette. 2) With the protein side facing down, expose your membrane to the x-ray film. *For exposure times <10-15sec you can hold the membrane in place. For longer exposure times it is easier to close the cassette. 3) Try a few different exposure lengths. 4) Develop your film.

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Western Blot Solution Recipes

1. PMSF Stock 100mM (100x) 1mL

17.42mg PMSF Dissolve in 1mL isopropanol

2. Laemmli Buffer (2x) 10mL

4mL 10% (w/v) SDS* 2mL Glycerol 0.5mL 0.1% (w/v) Bromophenol Blue 2.5mL 0.5M Tris-HCl, pH6.8 * Dilute to 10mL ddH2O

**Prior to use add betamercaptoethanol (B-ME) 1:20 (9.5mL Laemmli 2x + 500uL B-ME)

*10% SDS: 10g SDS diluted to 100mL with ddH2O, may need heating *0.5M Tris-HCl: 39.4g Tris-HCl diluted to 500mL with ddH20, adjust pH 6.8.

3. RIPA Buffer (1x)

Thaw 10X RIPA mix (Cell Signaling #9806) Dilute 1:10 with ddH2O Prior to use add PMSF 1:100

4. TBS (10x) 1L

24.2g Tris Base 80g NaCl To 1L ddH2O

Adjust pH to 7.6 Dilute 1:10 for working solution.

4b. TBS (10x) 2L

48.4g Tris Base 80g NaCl To 2L ddH2O

200

Adjust pH to 7.6 Dilute 1:10 for working solution

5. TBS/T 100mL

10mL 10x TBS 90mL ddH2O 0.1mL Tween-20

6. Stock Transfer Buffer (10x) 2L

288g Glycine 60.4g Tris Base To 2L ddH2O

7. Working Transfer Buffer (1x) 1L

100mL Methanol 100mL 10x Stock Transfer Buffer To 1L ddH2O

**For proteins > 80kDa, you may need to include 0.1% SDS for better transfer.

8. Blocking Buffer 150mL

15mL 10x TBS 7.5g Nonfat Dry Milk 0.15mL Tween-20 To 150mL ddH2O

**Filter this solution for best results. **If doing phospho protein western blots, it is best to use BSA instead of nonfat dry milk. Caseins in the milk are phosphoproteins and may cause a high background reaction.

9. Primary Antibody Dilution Buffer

Dilute antibody to recommend range using TBS/T.

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If you are not experiencing high background, include 0.5% BSA in dilution buffer. This will produce a stronger signal.

10. Seconday Antibody Dilution Buffer

Dilute secondary antibody in TBS/T.

If you are experiencing high background, use blocking buffer as a diluent instead. This, however, may lead to a less specific signal.

11. Electrophoresis Running Buffer (5x)

72g Glycine 15g Tris Base 5g SDS To 1L ddH2O

Dilute 1:5 for working solution.

12. Upper Stacking Gel Tris (0.5M) 1L

60.6g Tris Base 1g SDS To 1L ddH2O

Adjust pH to 6.8.

13. Lower Resolving Gel Tris (1.5M) 1L

181.8g Tris Base 1g SDS To 1L ddH2O

Adjust pH to 8.8.

14. Mild Stripping Buffer

15g Glycine 1g SDS 10mL Tween-20 To 1L ddH2O

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Adjust pH to 2.2.

15. Harsh Stripping Buffer

20mL 10% SDS 12.5mL 0.5M Tris-HCl, pH 6.8 800uL B-mercaptoethanol To 100mL ddH2O

*Prepare under a hood.

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Protein Gel Recipes

10% Acryl-Bis Resolving Gel (10mL/gel) [15-100kDa]

3 gels 5 gels 7 gels 9 gels 40% Acrylamide:Bis 5mL 10mL 15mL 20mL Lower Tris (pH 8.8, SDS) 5mL 10mL 15mL 20mL ddH2O 10mL 20mL 30mL 40mL 10% APS* 143uL 286uL 429uL 572uL TEMED** 28.5uL 57uL 85.5uL 114uL

12% Acryl-Bis Resolving Gel (10mL/gel) [12-85kDa]

3 gels 5 gels 7 gels 9 gels 40% Acrylamide:Bis 6mL 12mL 18mL 24mL Lower Tris (pH 8.8, SDS) 5mL 10mL 15mL 20mL ddH2O 9mL 18mL 27mL 36mL 10% APS* 143uL 286uL 429uL 572uL TEMED** 28.5uL 57uL 85.5uL 114uL

4% Acryl-Bis Stacking Gel (1mL/gel)

3 gels 4 gels 5 gels 6 gels 40% Acrylamide:Bis 0.625mL 0.83mL 1.04mL 1.25mL Upper Tris (pH 6.8, SDS) 1mL 1.34mL 1.67mL 2mL ddH2O 4.25mL 5.66mL 7.08mL 8.5mL 10% APS* 50uL 66.6uL 83.3uL 100uL TEMED** 10uL 13.34uL 16.67uL 20uL

***Prepare all gel solutions on ice***

Always prepare enough mixture for 2 gels more than what you plan to run.

*APS is a powder, prepare fresh (10mg/100uL ddH2O, 10%) just before using.

**ADD APS AND TEMED JUST PRIOR TO POURING GELS. These initiate the polymerization.

Cover gels with isopropanol after pouring to level the top.

Keep excess mixture in a conical tube as a guide to polymerization

Once polymerized, keep gels covered with water.

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Precellys Homogenization Settings

**Try to use tissue weights between 20-30mg. All should be run at 5000rpm** **Tubes should all be of equal weight. Try not to exceed total weight of tube+cap+beads=2.25grams** **Mixed tubes have 3-5 large beads. Choose an amount and keep it constant**

Tissue Precellys Conditions (Bead size, # of cycles x time) Liver Small, 2x10s Brain Small, 1x20s Kidney Small, 1x20s Skeletal Muscle Mixed, 2x20s Heart Mixed, 2x20s Testis Mixed, 1x15s Lung Small, 2x10s Pancreas Small, 2x10s WAT Small, 1x20s Stomach Small, 1x15s Spleen Mixed, 2x10s

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APPENDIX F: R SCRIPT FOR HIGH THROUGHPUT ANOVA BASED STATISTICS

OF MOUSE CIRCULATING PARAMETERS

The following script is for use with R Statistics software which is available free of charge at www.r-project.org. The script references functions available in two other R

packages: “stringr” and “multcompView”. These must first be installed before using the

script. The script can be loaded into R using the source(“script_name”) command. The

user can then follow the text prompts to enter number of files, file names, and plot option.

The code is good for any number of parameters given the user has enough available

RAM to load the source data table. We have successfully used this script to automate the

statistical analysis and graphing of up to 50 variables across 60 mice (4 groups of 15

mice). The output from the program can take the form of three separate types of files:

1) A TukeyHSD.csv spreadsheet listing p values for pairwise comparisons separated

by columns for each parameter and by row for each pair.

2) An ANOVA.csv spreadsheet listing ANOVA omnibus p values for each

parameter.

3) A barchart for each parameter, the format of which is determined by what value

the user enters for Plot Option during script start-up.

Truncated Example Output:

TukeyHSD.csv CPeptide IL6 Insulin FFxx- FFCx 0.901096 0.123999 0.692014 xxCx- FFCx 0.900283 0.999746 0.62699

206 xxxx- FFCx 0.963163 0.733916 0.85636 xxCx- FFxx 0.999999 0.111057 0.999321 xxxx- FFxx 0.655709 0.642891 0.249782 xxxx- xxCx 0.658865 0.691522 0.212197

ANOVA.csv ANOVA_p CPeptide 0.5942 IL6 0.082091 Insulin 0.163428

Barcharts for each parameter

Usage Notes: Unless you otherwise specify in the pathname, the script will use your current working directory as the source directory for data tables. The graphing component of the script does not place designators of significance (ie. a * for P<0.05); you will need to place these designators manually. Note that your data tables must be in

.csv format and must be of the following format:

Line MiceID Sex Genotype Mouse Parm-1 Parm-2 Parm-N Fat F1245 Female FFCx 1245 967.2768 38.55939 393.5682

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The column headings “Line”, “MiceID”, “Sex”, “Genotype”, and “Mouse” must be the first five columns in each data file and must remain in that order. Column headings

“Parm-1” to “Parm-N” can take any alphanumeric name and be in any order. The script

expects “Male” or “Female” for sex and “FFCx”, “FFxx”, “Fxxx”, or “xxxx” for

genotype. Values for “Line” and “MiceID” are treated in a case sensitive manner so

“F1245” is different from “f1245” under “MiceID”.

{BEGIN} SCRIPT SOURCE CODE {BEGIN}

## BEGIN FUNCTION DEFINITIONS

## Main starting program start.prog<-function() { suppressWarnings(library(stringr)); suppressWarnings(library(multcompView)); file_number<-file_num(); if (file_number < 1) { cat("You must enter a positive integer value.\nType 'start.prog()' to run again."); break; } input_names<-input_name(file_number); Plot_Option<-Plot_Option(); for (i in 1:length(input_names)) { Data <- read.csv(toString(input_names[i]), header = TRUE);##Reads in data table and assigns it to Data. old.dir<-paste(getwd()); ##Saves the old working directory. new.dir<- paste(getwd(),"/",levels(Data$Line),".",get.line.name(Data),sep=""); ##Gets the name of the new directory based on the input file contents. dir.create(paste(new.dir)); ##Creates a new directory based on the input file contents. setwd(paste(new.dir,sep="")); ## Changes working directory to newly created directory. switch (Plot_Option, {general.graph(Data,Plot_Option);plot.legend(Plot_Option)}, ##If Plot_Option = 1, Two Geno-One Sex, do these

{general.graph(Data,Plot_Option);plot.legend(Plot_Option);calculateaov( Data); calculateHSD(Data)}, ##If Plot_Option = 2, Four Geno-One Sex, do these

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{general.graph(Data,Plot_Option);plot.legend(Plot_Option); calc.twoway(Data)}, ##If Plot_Option = 3, Two Geno-Two Sex, do these {general.graph(Data,Plot_Option);plot.legend(Plot_Option); calc.twoway(Data)}) ##If Plot_Option = 4, Four Geno-Two Sex, do these setwd(paste(old.dir)); } cat("Files saved in: ",new.dir); cat("\nType 'start.prog()' to run program again."); }

##Ask for user input. How many data files and their names file_num<-function () { file_num<-as.numeric(readline("Enter number of data files: ")); file_num } input_name<-function (file_number) { name_list<-list(); for(i in 1:file_number) { name_list[i]<-readline(paste("Enter name ", i , ":")) }; name_list }

Plot_Option<-function () { Option<-as.numeric(readline(cat("Type of Plot?\n1 = Two Geno-One Sex\n2 = Four Geno-One Sex\n3 = Two Geno-Two Sex\n4 = Four Geno-Two Sex"))); Option }

##Plot the legend on a new plot by itself plot.legend<-function (Plot_Option) { if (Plot_Option == 1) { jpeg(filename=paste("LEGEND_2Geno.OneSex.jpg"), width=4, height=5, units="in", quality=100,res=300); plot.new(); legend(0.5,0.5, legend=c("FFxx", "FFCx"), fill=c("white","black")); } else if (Plot_Option == 2) { jpeg(filename=paste("LEGEND_4Geno.OneSex.jpg"), width=4, height=5, units="in", quality=100,res=300); plot.new(); legend(0.5,0.5, legend=c("FFxx", "FFCx", "xxxx", "xxCx"), fill=c("white","black","gray","dark gray"));

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} else if (Plot_Option == 3) { jpeg(filename=paste("LEGEND_2Geno.MF.jpg"), width=4, height=5, units="in", quality=100,res=300); plot.new(); legend(0.5,0.5, legend=c("FFxx", "FFCx"), fill=c("white","black")); } else if (Plot_Option == 4) { jpeg(filename=paste("LEGEND_4Geno.MF.jpg"), width=4, height=5, units="in", quality=100,res=300); plot.new(); legend(0.5,0.5, legend=c("FFxx", "FFCx", "xxxx", "xxCx"), fill=c("white","black","gray","dark gray")); } graphics.off() }

##More general function to graph any of the 5 options. general.graph<-function (Data, Plot_Option) { for (i in 6:ncol(Data)) { find.name<-levels(Data$Sex); if (Plot_Option == 1) { var.mean<-tapply(Data[[i]], list(Data$Genotype,Data$Sex),mean,na.rm=T); var.sem<-tapply(Data[[i]], list(Data$Genotype, Data$Sex),FUN=function (x) sqrt(var(x,na.rm=TRUE)/length(na.omit(x)))); if (find.name == "Female" || find.name == "female") { var.mean<-var.mean[c("FFxx","FFCx","xxxx","xxCx"),c("Female")]; var.sem<-var.sem[c("FFxx","FFCx","xxxx","xxCx"),c("Female")]; } else if (find.name == "Male" || find.name == "male") { var.mean<-var.mean[c("FFxx","FFCx","xxxx","xxCx"),c("Male")]; var.sem<-var.sem[c("FFxx","FFCx","xxxx","xxCx"),c("Male")]; } dropped <- c("xxxx","xxCx"); ## Defines the rows we wish to drop from the data frames. var.mean<-var.mean[!(rownames(var.mean) %in% dropped),]; ## Redefines the Averages dataframe without the 'dropped' columns. var.sem<-var.sem[!(rownames(var.sem) %in% dropped),]; jpeg(filename=paste(names(Data[i]),"_2Geno.OneSex.jpg",sep=""), width=4, height=5, units="in", quality=100,res=300); par(mar=c(7,6,6,4),mgp=c(4,1,0)); plot<-barplot(var.mean, beside = T, col=c("white","black"), main= paste(names(Data[i])), ylab = paste(names(Data[i])), ylim=c(0,1.4*max(var.mean, na.rm=T)),las=1,cex.axis=1.4,cex=1.5); abline(0,0); }

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else if (Plot_Option == 2) { var.mean<-tapply(Data[[i]], list(Data$Genotype,Data$Sex),mean,na.rm=T); var.sem<-tapply(Data[[i]], list(Data$Genotype, Data$Sex),FUN=function (x) sqrt(var(x,na.rm=TRUE)/length(na.omit(x)))); if (find.name == "Female" || find.name == "female") { var.mean<-var.mean[c("FFxx","FFCx","xxxx","xxCx"),c("Female")]; var.sem<-var.sem[c("FFxx","FFCx","xxxx","xxCx"),c("Female")]; } else if (find.name == "Male" || find.name == "male") { var.mean<-var.mean[c("FFxx","FFCx","xxxx","xxCx"),c("Male")]; var.sem<-var.sem[c("FFxx","FFCx","xxxx","xxCx"),c("Male")]; } dropped <- c("xxxx","xxCx"); ## Defines the rows we wish to drop from the data frames. var.mean<-var.mean[!(rownames(var.mean) %in% dropped),]; ## Redefines the Averages dataframe without the 'dropped' columns. var.sem<-var.sem[!(rownames(var.sem) %in% dropped),]; jpeg(filename=paste(names(Data[i]),"_2Geno.OneSex.jpg",sep=""), width=4, height=5, units="in", quality=100,res=300); par(mar=c(7,6,6,4),mgp=c(4,1,0)); plot<-barplot(var.mean, beside = T, col=c("white","black"), main = paste(names(Data[i])), ylab = paste(names(Data[i])), ylim=c(0,1.4*max(var.mean,na.rm=T)),las=1,cex.axis=1.4,cex=1.5); abline(0,0); } else if (Plot_Option == 3) { var.mean<-tapply(Data[[i]], list(Data$Genotype, Data$Sex),mean,na.rm=T); var.sem<-tapply(Data[[i]], list(Data$Genotype, Data$Sex),FUN=function (x) sqrt(var(x,na.rm=TRUE)/length(na.omit(x)))); var.mean<- var.mean[c("FFxx","FFCx","xxxx","xxCx"),c("Male","Female")]; var.sem<- var.sem[c("FFxx","FFCx","xxxx","xxCx"),c("Male","Female")]; dropped <- c("xxxx","xxCx"); ## Defines the rows we wish to drop from the data frames. var.mean<-var.mean[!(rownames(var.mean) %in% dropped),]; ## Redefines the Averages dataframe without the 'dropped' columns. var.sem<-var.sem[!(rownames(var.sem) %in% dropped),]; jpeg(filename=paste(names(Data[i]),"_2Geno.MF.jpg",sep=""), width=4, height=5, units="in", quality=100,res=300); par(mar=c(7,6,6,4),mgp=c(4,1,0)); plot<-barplot(var.mean, beside = T, col=c("white","black"), main = paste(names(Data[i])), ylab = paste(names(Data[i])), ylim=c(0,1.4*max(var.mean, na.rm=T)),las=1,cex.axis=1.4,cex=1.5); abline(0,0); } else if (Plot_Option == 4) {

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var.mean<-tapply(Data[[i]], list(Data$Genotype, Data$Sex),mean,na.rm=T); var.sem<-tapply(Data[[i]], list(Data$Genotype, Data$Sex),FUN=function (x) sqrt(var(x,na.rm=TRUE)/length(na.omit(x)))); var.mean<- var.mean[c("FFxx","FFCx","xxxx","xxCx"),c("Male","Female")]; var.sem<- var.sem[c("FFxx","FFCx","xxxx","xxCx"),c("Male","Female")]; jpeg(filename=paste(names(Data[i]),"_4Geno.MF.jpg",sep=""), width=4, height=5, units="in", quality=100,res=300); par(mar=c(7,6,6,4),mgp=c(4,1,0)); plot<-barplot(var.mean, beside = T, col=c("white","black","gray","dark gray"), main = paste(names(Data[i])), ylab = paste(names(Data[i])), ylim=c(0,1.4*max(var.mean, na.rm=T)),las=1,cex.axis=1.4,cex=1.5); abline(0,0); } arrows(plot,var.mean+var.sem,plot,var.mean,code=1,angle=90,length=.05); ## Plots only the positive error bar abline(0,0); graphics.off() } }

##Two-way ANOVA Calculation (Variable ~ Genotype * Sex) and output to file. calc.twoway<-function (Data) { line.name<-paste(levels(Data$Line)); for (i in 6:ncol(Data)) { Test<-anova(lm(Data[[i]]~Genotype*Sex, Data)); capture.output(cat("\n","Variable: ", names(Data[i]),"\n","______","\n","\n"),Test,file=paste( line.name,".Two-way.Geno-Sex.ANOVA.doc",sep=""),append=TRUE); } }

## Will output a single row spread sheet from one-way ANOVA calculateaov<- function (Data) { pvalues<-list(); frame1<-data.frame(matrix(NA,ncol=1, nrow=(ncol(Data)-5))); for(i in 6:ncol(Data)) { f<-as.formula(paste(names(Data[i]),"~Genotype")); frame1[(i-5),1]<- summary(aov(f,data=Data))[[1]][["Pr(>F)"]][1]; }; colnames(frame1)<-c("ANOVA_p"); row.names(frame1)<-names(Data)[6:ncol(Data)];

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write.table(frame1,paste(get.line.name(Data),".ANOVA.csv",sep="" ), sep=",",row.names=TRUE,col.names=NA); ## Prints a .csv table containing ANOVA p values for all variables. }

##TukeyHSD Test From rawdata. Must load multcompView library first to get functionality to extract p values. calculateHSD<- function (Data) ## If there are variables with unequal number of groups the program will repeat p values (ie. if most variables have 4 groups and 1 variable has 2 groups the p value for the 2 group comparison will be repeated for all 6 comparisons in the 4 group scenario). { group.num<-nrow(table(Data$Genotype)); frame1<-data.frame(matrix(NA, ncol=ncol(Data)- 5,nrow=((group.num*(group.num-1))/2))); p<-list(); for(i in 6:ncol(Data)) { f<-as.formula(paste(names(Data[i]),"~Genotype")); p<- extract_p(TukeyHSD(exp_aov<-aov(f, data=Data))); frame1[,(i-5)]<-as.data.frame(do.call(cbind,p)) }; row.names(frame1)<- rownames(TukeyHSD(aov(as.formula(paste(names(Data[6]),"~Genotype")), data=Data))$Genotype); colnames(frame1)<-names(Data)[6:ncol(Data)]; write.table(frame1,paste(get.line.name(Data),".HSD.csv",sep=""), sep=",",row.names=TRUE,col.names=NA); }

## Returns the sex(s) of the input data file. get.line.name<-function (Data) { if (nlevels(Data$Sex) == 1) { line.name<-paste(levels(Data$Sex)); } else if (nlevels(Data$Sex) == 2) { line.name<- paste(levels(Data$Sex)[1],".",levels(Data$Sex)[2],sep=""); } line.name; }

##Program Execution ## MAIN start.prog();

{END} SCRIPT SOURCE CODE {END}

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