Survey of Cns Expression of the Amylin Receptor in Health And

Home , Histamine H1 receptor, Histamine receptor, RAMP1, RAMP3

SURVEY OF CNS EXPRESSION OF THE AMYLIN RECEPTOR IN HEALTH AND

METABOLIC DISEASE: POTENTIAL RELEVANCE TO ALZHEIMER’S DISEASE

A Thesis submitted to

Kent State University in partial

Fulfillment of the requirements for the

Degree of a Master of Science

Spencer J Servizi

August 2019

©Copyright

Except for previously published materials

Thesis written by

Spencer J Servizi

B.S., Washington State University, 2015

M.S., Kent State University, 2019

Approved by

____Gemma Casadesus______, Advisor

____Ernest Freeman______, Director, School of Biomedical Sciences

____James L. Blank______, Dean, College of Arts and Sciences

TABLE OF CONTENTS

TABLE OF CONTENTS………………………………………………………………………...iii

LIST OF FIGURES……………………………………………………………………………….v

ACKNOWLEDGEMENTS………………………………………………………………………vi

CHAPTERS:

1. Introduction...... ………………..……………………………………..1

1.1 - Alzheimer’s Disease...... ………………….…………………..1

1.2 - Relationship Between AD & T2D...... ………………….…………….3

1.3 - Amylin Function...... ………………….………………………………5

1.4 - Amylin & its Relationship to AD……………………………………………7

1.5 - Amylin Receptor...... ………………….……………………………..10

2. Methods...... ………………….…………...... ………………….………..14

2.1 - Animals...... ………………….………………………………………14

2.2 - Tissue Preparation & Blood Collection...... …….……..……………………14

2.3 - Insulin ELISAs………………………………………………………….…..15

2.4 - Cell Culture...... ………………….……………………………....…..15

2.5 - Lentiviral Transduction...... ………………….………………………15

2.6 - Cell Sorting…………………………………………………………………17

2.7 - qPCR & Western Blot Analysis...... ………………….………………17

2.8 - ERK Phosphorylation Measurements...... ………………….…………19

2.9 - Statistical Analysis ...... ………………….…………………..………20

3. Results...... ………………….…………...... ………………….…………22

3.1 - RAMP1 expression...... ……………… …….………………………..22

iii

3.2 - RAMP3 Expression...... …………...... ………………….………...27

3.3 - CalcR Expression ...... ……………………………………………….31

3.4 - TRPV4 Expression…….……………………………………………………33

3.5 - Metabolic Measurements & Correlations to mRNA Expression……………36

3.6 - Lentiviral Transduction Drives Genetic Overexpression……………………37

3.7 - Lentiviral Transduction Drives Overexpression of RAMP3……………….41

3.8 - ERK Phosphorylation Measurements………………………………………43

4. Discussion...... ………………….………………………………………………45

4.1 – Regional Expression Changes in Amylin Receptor Transcription………...45

4.2 – Diet Induced Changes in Amylin Receptor mRNA Expression…………...49

4.3 - Cell Line Overexpression and Function…………………………………….53

4.4 – Concluding Remarks……………………………………………………….56

REFERENCES...... ………………….………… ...... ………………….………….57

LIST OF FIGURES

Figure 1: Changes in Cortical and Hypothalamic RAMP1 Expression.……………………...…24

Figure 2: Changes in RAMP1 Expression Due to Region…………………………………...….26

Figure 3: Changes in Hippocampal RAMP3 Expression………………………………………..29

Figure 4: Changes in RAMP3 Expression Due to Region…………………………………...….30

Figure 5: Changes in Hypothalamic TRPV4 Expression ……………………………………….35

Figure 6: Genetic Overexpression in Lentiviral Transduced Cells…………………..……….....39

Figure 7: RAMP3 & CalcR Protein Upregulation in AMY3 Transduced Cells…………….…..42

Figure 8: ERK Phosphorylation Measurements in Transduced Cells…………………………...44

ACKNOWLEDGEMENTS

I would like to thank everyone who has helped me to reach this point of my career. I would first like to thank my friends and family back home for their unwavering support as I chase my dreams thousands of miles away from home. In particular, I would like to thank my mom and dad,

Marci and Marc, for their emotional support and encouragement through all the peaks and valleys encountered since leaving home.

I would also like to thank my PI and mentor, Dr. Gemma Casadesus for her guidance, her constant drive to educate and her support when the going got tough. I would like to thank Gemma for helping me to take a step back, keep things in perspective, and look at the bigger picture in life.

I would also like to thank my committee members, Dr. Denise Inman and Dr. Jennifer

McDonough, for their support and guidance not only through scientific techniques and strategies but via career and life advice as well.

I would also like to thank my lab mates and friends, John Grizzanti, Rachel Corrigan,

Megan Mey, Sabina Bhatta and Jeff Blair for their guidance, support and friendship through thick and thin over the past three years. Life in the lab would be much less interesting without this group of aspiring scientists. I would also like to thank John for helping me with some of the western blots and ELISAs used in this thesis.

Lastly, I would like to acknowledge my uncle Paul, who’s untimely death due to complications associated with a traumatic brain injury sparked my interest in the workings of the brain and fueled my drive to search for effective treatments of the different ailments and diseases of the brain. Rest in peace Uncle Paul.

Chapter 1: Introduction

1.1 - Alzheimer’s Disease

As the life expectancy of United States citizens and people around the world continues to increase with advances in science and medicine, so too does the prevalence of age-related disorders. Alzheimer’s Disease (AD) is the leading cause of dementia and the sixth leading cause of death in the United States that primarily impacts the elderly population, with the majority of impacted individuals being above the age of 65. After 65, the risk of AD development doubles every five years, and reaches nearly 1/3 by the age of 851. While the leading cause of death; heart disease, decreased 11% from 2000 to 2015, AD increased 123% over the same time period 1. The estimated 5.7 million Americans living with AD in 2018 is projected to increase to 13.8 million by 2050 2.

AD is a progressive neurodegenerative disease that impairs memory, problem solving, language and other cognitive abilities1. The initial symptoms of AD typically involve episodic memory loss, which eventually progresses to the inability to perform simple tasks. AD patients also undergo a number of behavioral changes, which can include depression, psychosis, executive dysfunction, irritability, sleep disorders and even personality changes3. The average duration of the illness is 8-10 years, but the preclinical and prodromal stages that precede the clinical symptomatic stages typically extend over 20 years4.

There are two classifications of AD – sporadic and familial. Early onset familial AD occurs in younger subjects, with a mean age of 45, due to an inherited genetic mutation, but accounts for less than 1% of all AD cases4. While many genetic mutations have been linked with familial AD,

1 the majority of cases stem from APP, PSEN1 or PSEN2 mutations5,6. These mutations lead to alterations in amyloid precursor protein (APP) processing and increased production and aggregation of the amyloid beta peptide (Aß), the hallmark pathological feature of AD7. The overwhelming majority of AD cases are sporadic, with a late onset over the age of 65. The cause of late onset AD is not known, and the pathogenesis involves multiple environmental and genetic factors1.

AD is characterized by neurodegeneration, oxidative stress (OS), neuroinflammation, decreased brain metabolism, impaired synaptic transmission and neuronal cell death, as well as two hallmark lesions; extracellular amyloid plaques composed of Aß and intracellular neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau4,8-12. Tau is a microtubule- associated protein that becomes hyperphosphorylated and self-aggregates in AD brains, levels of which correlate with cognitive impairment and cell death8,13-15. Aß is a 37-43 amino acid peptide that is the cleavage product of APP, orchestrated by ß-secretase (BACE1) and subsequent γ- secretase cleavage8,16.

While 90% of basal Aß production is Aß40, Aß42 levels are elevated in AD patient brains17-19. Mutations to γ-secretase catalytic subunits presenilin 1 & 2 (PSEN1 & PSEN2), as well as APP mutations, lead to the overproduction of Aß4219-23. Aß42 is more prone to aggregation and is believed to be the building block for the toxic Aß oligomers which affect memory and cell survival24. While there is much debate as to whether Aß oligomers or amyloid plaques are the more toxic species of Aß, it is clear that there is a positive feedback loop established between Aß, oxidative stress, neuroinflammation and cell death, contributing to the pathological cascade observed in AD24-27. This feed-forward mechanism between toxic oligomers and plaques with

2 oxidative stress, neuroinflammation and cell death is not restricted to AD alone but involves other diseases as well; namely Type 2 Diabetes Mellitus (T2D).

1.2 - Relationship between AD & T2D

As previously mentioned, the more prominent form of AD, sporadic AD, is the result of numerous genetic and environmental factors28. Lifestyle choices such as diet and exercise that can lead to obesity, metabolic syndrome and the development of T2D are associated with sporadic AD development29-31. T2D is one of the strongest risk factors for the development of sporadic AD1 and having T2D for more than five years significantly increases the risk for AD development32. AD has even been referred to as ‘Type 3 Diabetes’ by some, indicating the strikingly similar pathological features between Diabetes and AD27,31,33.

Diabetes is the seventh leading cause of death in the United States, just behind AD.

According to the CDC, in 2015, 30.3 million people; 9.4% of the US population, had diabetes and a staggering 84.1 million had prediabetes; 33.9% of the US population. The prevalence of T2D is expected to increase to almost 600 million cases worldwide by the year. While men develop T2D more frequently than women, women develop T2D-associated cognitive decline more commonly than men34. Women are also more prone to develop dementia and AD1.

T2D is a metabolic disease derived from chronic hyperglycemia, typically due to poor diet and a sedentary lifestyle35, which leads to chronic hyperinsulinemia and hyperamylinemia as the body tries to regulate blood glucose levels36. This leads to insulin resistance, impaired insulin signaling in the brain, impaired glucose utilization, and the eventual decrease in insulin and amylin production with pancreatic ß-cell loss37.

AD & T2D share many pathological characteristics, which include impaired insulin signaling, decreased brain metabolism, metabolic hormone resistance, inflammation, mitochondrial dysfunction, OS, amyloid pathology and cognitive decline33,38,39. Overproduction of insulin causes the down regulation of insulin receptors, impaired transport of insulin across the blood brain barrier (BBB) and reduced insulin signaling in the brain11,40-42. As insulin’s primary function is to modulate blood glucose levels43, this leads to impaired cerebral glucose uptake and utilization, which is one of the first signs of cognitive impairment that continues to worsen with cognitive decline11,44,45. Impaired cerebral glucose utilization leads to neuronal starvation, impaired energy production, mitochondrial dysfunction, OS, DNA damage and increased cell death, all of which drive pro-apoptotic, pro-inflammatory and pro-Aß cascades46,47.

Insulin receptors are widely distributed throughout the brain and are highly expressed in the hippocampus and cerebral cortex, downregulation of which correlates with deficits in synaptic transmission and impaired learning43,48. This is likely due to the various cascades associated with neuronal plasticity, learning and memory, that insulin and insulin-like growth factor (IGF) signaling activate; dysregulation of which contributes to cognitive decline33,49,50. This is supported by the finding that acute insulin administration was shown to improve performance on memory and cognition tests51. Conversely, chronic hyperinsulinemia induced the opposite effect52, likely due to the development of insulin resistance and impaired insulin signaling.

Impaired insulin signaling also induces increased tau hyperphosphorylation. Dysregulated insulin signaling impairs downstream PI3K-Akt signaling and subsequent dephosphorylation and activation of glycogen synthase kinase 3ß (GSK3ß), which is normally responsible for binding tau to microtubules53. Inability to properly inhibit GSK3ß activity leads to the hyperphosphorylation and subsequent aggregation of tau. Insulin receptor dysfunction has also been shown to impair Aß

4 clearance and contribute to Aß aggregation54. This seems to establish a positive feedback loop as

Aß has been shown to impair insulin signaling and induce insulin resistance55,56. Dysregulated insulin signaling also leads to impaired Aß clearance via changes in insulin degrading enzyme

(IDE), as IDE degrades not only insulin, but Aß as well57-59. Furthermore, IDE activity decreases in both T2D and AD brains, which may also lead to amylin aggregation60.

1.3 - Amylin Function

Islet amyloid polypeptide, or amylin, is a 37 amino-acid peptide hormone produced by the pancreatic ß-cells and co-secreted with insulin after eating61. In health, amylin signals primarily as an acute satiety hormone and works in synchrony with insulin to decrease blood glucose by way of reducing food intake, inhibiting glucagon secretion and slowing gastric and intestinal emptying during meals62. Amylin also has an important role in long-term metabolic regulation with insulin and leptin. All three hormones are secreted in proportion to body adiposity, as the body attempts to regulate adiposity, increase long-term satiety and decrease food intake. Because of this, all three are overproduced as a response to high fat diet and chronically high levels of glucose36,63.

Importantly, leptin and insulin resistance; key aspects of T2D, are both a consequence of chronically upregulated levels64.

Amylin meal signaling that results in satiety and decreased eating occurs in the area postrema (AP), as indicated by strong amylin binding and neuronal activation following amylin administration65,66. The satiety effect of amylin-derived signaling has been consistently shown to decrease food intake and body weight when administered both peripherally and centrally65,67,68.

This effect is mediated through the AP due to the abolishment of amylin’s anorectic effect in response to AP lesion, and attenuation of amylin’s effect in response to amylin receptor inhibition

5 via AC187 administration directly into the AP67-69. Several other brain regions are activated by amylin signaling, but several of them are dependent upon AP activation, as indicated by a lack of cFOS activation following lesion to the AP66,70.

The long-term metabolic effects of amylin results primarily from its interaction with leptin through the ventromedial hypothalamus (VMH), where the two have been shown to act synergistically69,71,72 via the H1 histamine receptor. To this end, amylin sensitizes hypothalamic leptin signaling in the ventromedial nucleus (VMN) by way of stimulating interleukin-6 release from microglial cells, which then binds to its neuronal receptor, GP130, enhancing leptin receptor

(LepRb)-dependent STAT3 phosphorylation and activation69,71,73. This effect is mediated in part through the H1 receptor74,75, which is upregulated by co-administration of leptin and amylin76, and its knockdown attenuates amylin’s anorectic effect, and completely eliminates leptin’s anorectic effect77.

Importantly, leptin receptors have also been implicated with memory function78,79. In this regard, leptin receptors are highly expressed in the hippocampus and leptin signaling has been shown to enhance long-term potentiation (LTP), a form of synaptic plasticity commonly used as a cellular model of memory80, in hippocampal slices. Low leptin levels and central leptin resistance have both been suggested to be involved in AD development, and leptin treatment has been shown to improve function in mouse models of AD81-83. Thus, while it is apparent that dysregulated amylin and leptin signaling play a role in T2D through their effect on satiety and body weight, these results indicate that amylin and leptin may also play a role in cognition, through their interaction in memory-related areas such as the hippocampus.

1.4 - Amylin & its Relationship to AD

In normal conditions amylin exists as a soluble monomer, but undergoes conformational and biochemical changes in T2D, leading to aggregation and fibril formation84. These amylin fibrils, which are found in the brain and pancreas of over 90% of T2D patients, are closely linked with pancreatic ß-cell death, and the consequential decrease in amylin and insulin production characteristic of T2D37,63,85.

Amylin not only aggregates in the pancreas and causes ß-cell death, but it also readily crosses the BBB and aggregates in the brain, leading to cognitive impairment86-88. To this end, Aß and amylin have been found in AD brains, and fibrillar amylin has been suggested to seed Aß aggregation and plaque formation, while monomeric amylin may inhibit Aß aggregation89-92.

Whether amylin in itself is a toxic insult, or whether its functional loss via aggregation and ß-cell loss in T2D participates in AD development is still a topic of debate. This is highlighted by several conflicting articles supporting benefits of both amylin receptor agonists and antagonists (reviewed in Grizzanti, 201938).

Drug development for AD treatment has proven to be a challenge, with no new treatment approvals since 2003, and the six drugs approved by the FDA for AD and dementia treatment being only symptomatic93,94. Recent evidence, however, has shown promise in the use of pramlintide acetate (PRAM) for AD treatment. PRAM, a synthetic analogue of amylin, was synthesized to mimic non-aggregating rat amylin (rAmy), which differs from human amylin

(hAmy) by three proline substitutions at positions 25, 28 and 29, the area responsible for amyloid formation95. PRAM was approved by the FDA in 2005 for treatment of T1D and T2D as an adjunct therapy to insulin due to its improval of glycemic control and reduction in body weight96. Studies have also indicated PRAM’s ability to slow hAmy aggregation in vitro97. The fact that PRAM

7 exerts therapeutic effects against diabetes supports the theory that loss of amylin signaling is the root of dysfunction in T2D. This theory is further supported by findings indicating a positive association between levels of plasma amylin and cognition in healthy elderly subjects, T2D patients and AD patients98-100.

The results of numerous animal studies also support the theory of therapeutic amylin replacement therapy. Our lab and others have indicated the benefits of centrally and peripherally administered PRAM on memory and cognition in various animal models of AD. Subcutaneously

PRAM treated senescence-accelerated prone (SAMP8) mice performed significantly better at the novel object recognition task than saline treated mice100. This was in conjunction with increases in both synapsin I and CDK5, two proteins implicated in synapse growth and formation. PRAM also exhibited antioxidant and anti-inflammatory effects as PRAM treated mice showed a significant decrease in the oxidative stress marker HO-1, and the inflammation marker, COX-2100.

Intraperitoneal (IP) and intracerebroventricular (ICV) treatment of PRAM and hAmy improved Y maze and Morris water maze performance, reduced pathology and increased Aß42 in the CSF of 5XFAD AD model mice; suggesting that amylin may shuttle Aß out of the brain101. IP injections of hAmy were also shown to reduce tau pathology in 3xTg AD mice and neuroinflammation markers Iba-1 and CD68, while simultaneously improving cognition102.

Importantly, IP injection of the AmyR inhibitor, AC253, attenuated the beneficial effects observed on cognition and pathology, indicating the importance of amylin interaction with its cognate receptor to mediate these therapeutic effects.

Another study replicated the benefits of IP hAmy treatment, in additional to a reversal of the expression of hundreds of genes that are altered in AD related to neuroinflammation, transcription regulation and mitochondrial function103. To this end, hAmy treatment significantly

8 decreased in the inflammatory marker, CD68. This downregulation was also replicated in vitro in

BV-2 microglial cells and was abolished by RAMP3 downregulation, indicating a vital role for

AMY3 in mediating amylin’s effect on neuroinflammation103.

Other studies, however, have indicated the therapeutic potential of amylin receptor inhibition in vivo and in vitro. Treatment of TgCRND8 mice with AC253 and a cyclic form of

AC253, cAC253, decreased plaque burden and neuroinflammation while improving cognition104.

The same study indicated that both AC253 and cAC253 attenuated cell death induced by hAmy and Aß42 in HEK cells overexpressing AMY3104. In vitro, both hAmy and Aß exerted dose- dependent neurotoxic effects when administered to primary hippocampal, cortical and forebrain cholinergic neurons105,106. Similar studies also indicated impaired cell and neuronal viability107,108, as well as increases in apoptotic markers caspases 3, 6, 9, BID and XIAP, by both Aß and hAmy109.

Soluble Aß42 oligomers and hAmy also induced impairments in LTP in hippocampal slices of

TgCRND8 AD mice. These effects were blocked by AC253, but interestingly, by PRAM as well110,111. Given that PRAM did not exert an effect on LTP when administered alone, the authors postulated that PRAM exerts its therapeutic effects by way of blocking the toxic actions of amylin and Aß110. Together, the studies summarized above seem to highlight a discrepancy between the results of in vivo and ex vivo/in vitro studies and potentially in the nature of how different agonists and antagonists bind and signal through the amylin receptor.

1.5 - Amylin Receptor

As indicated above, Aß has been suggested to signal through the same receptor as amylin.

The amylin receptor (AmyR) is composed of the calcitonin receptor (CalcR) complexed to a receptor activity modifying protein (RAMP). While the CalcR does respond to amylin on its own,

9 its affinity for amylin greatly increases when complexed to a RAMP112-114. There are two splice variants of the CalcR; CalcRα and CalcRß, and three RAMP isoforms; RAMP1, RAMP2 and

115 RAMP3, resulting in six possible AmyRs . However, CalcRα is more highly expressed than

CalcRß in the brain, and RAMP2 is not highly expressed in the CNS, nor does it exhibit high

66,115-117 affinity for amylin, when compared to its counterparts . Therefore, CalcRß and RAMP2 will not be discussed any further, and the CalcRα/RAMP1 & CalcRα/RAMP3 combinations will be referred to as AMY1 and AMY3, respectively.

Morfis et al conducted an in-depth analysis of signaling pathways activated by amylin.

HEK cells and COS7 cells were transfected with the CalcRα and either RAMP1, RAMP2 or

RAMP3 and subsequently treated with rAmy, and the cellular response compared to that of human calcitonin. They observed a 20 – 40-fold increase in cAMP signaling, a 2 – 5-fold increase in ERK phosphorylation and a 2 – 4-fold increase in intracellular calcium depending upon the RAMP isoform and cell type117. With the exception of the cAMP response in COS7 cells, which showed a more potent response in cells transfected with RAMP1, all dose response assays indicated a more potent response in cells transfected with RAMP3117.

Based on the results of the experiments conducted by Morfis et. al indicating a prominent role for AMY3, Fu et. al conducted a study looking further into the signaling cascades mediated by that particular receptor. HEK cells transfected with AMY3 displayed an increase in cytosolic cAMP and calcium, as well as an increase in Akt, ERK and PKA activity; as indicated by phosphorylation, upon receptor activation108. The role of AMY3 was confirmed when AC253 was shown to block the increase in intracellular calcium, as well as activation of PKA, Akt and ERK.

The importance of AMY3 in mediating amylin (and Aß) effects was supported by findings

10 indicating that knockdown of the CalcR and RAMP3 rendered human fetal neurons more resistant to hAmy and Aß induced cell death107.

Several studies have indicated that amylin and Aß signal through the same receptor. Studies mentioned above indicated that specific AmyR inhibition attenuated increased cell death104,106-108, decreased levels of pro-apoptotic mediators109, and rescued impaired LTP110,111 induced by both hAmy and Aß. Aß42 was also shown to induce increases in intracellular cAMP and calcium as well as activation of Akt, ERK and PKA in AMY3 expressing HEK cells, similar to hAmy108. Co- application of hAmy and Aß42 did not increase the neuronal toxicity105 or the rise of cytosolic calcium108 observed when compared to incubation of a single peptide, indicating a common receptor and/or signaling pathway. Gingell et al, however, indicated that Aß42 was unable to evoke a cAMP response through HEK and COS7 cells overexpressing the AMY1 or AMY3 receptors at a wide variety of concentrations, when hAmy, rAmy and PRAM all induced a significant increase of cytosolic cAMP through both receptor subtypes118. As the same receptor subtype, cellular background and Aß isoform were used for both studies, the cause of the discrepancy of results regarding the ability of Aß to stimulate cAMP production is unclear108,118.

A separate study indicated that oligomeric hAmy mediates its toxic effects via calcium signaling directly through the AmyR, and indirectly through the nonselective cation TRPV4 channel119. Low concentrations of hAmy, rAmy and PRAM were all able to induce a small calcium response in hippocampal neurons mediated through the AmyR; in agreement with the findings of

Morfis, et. al previously described. At higher concentrations of hAmy, however, the more pronounced calcium response was found to also be mediated through the TRPV4 receptor, and subsequently through voltage gated calcium channels119.

Excitotoxicity; the result of excessive glutamate release, and subsequent NMDA and

AMPA receptor activation increases intracellular calcium levels. While low doses of calcium govern a wide array of cellular processes, too much calcium can overwhelm calcium regulatory mechanisms and eventually cause cell death120. Aberrant calcium influx plays a role in neuronal dysfunction, inflammation, mitochondrial dysfunction, OS and apoptosis, all of which are closely associated with AD and T2D121-123. As hAmy and Aß have also been shown to play a role in each of the pathological features mentioned above, it is possible that their toxicity is mediated through the TRPV4 receptor via aberrant calcium influx and excitotoxicity. This theory is supported by the detection of hAmy oligomers and plaques in the high hAmy dose solution; but not the low hAmy dose solution, suggesting that the AmyR and TRPV4 receptors mediate some of the cellular dysfunction and AD-like pathological development driven by toxic amyloid signaling. It is likely that Aß may activate a similar calcium signaling cascade, but these experiments have not been done.

These findings are supported by a prior study, indicating amylin’s ability to increase calcium levels in pancreatic ß-cells124. Importantly, amylin’s ability to increase intracellular calcium levels and trigger cell death was attenuated by TRP channel inhibitors as well as siRNA used to knockdown the TRPV4 receptor124. Extracellular amylin aggregates were detected adjacent to irregular invaginated regions on the plasma membrane, inspiring the writers to suggest the ability of the TRPV4 receptor to sense changes on the cell membrane induced by amylin aggregates. Whether the TRPV4 receptor activates due to cell membrane changes induced by amylin aggregates, and the signaling cascade that may connect the AmyR and TRPV4 receptors, have not yet been investigated and warrant further study.

Amylin replacement therapy has shown effectiveness in its ability to treat T2D and has shown promise in its ability to treat AD and cognitive decline. Whether this benefit is mediated directly through restoration of lost amylin signaling, or indirectly by way of inhibiting Aß signaling or enhancing leptin or insulin signaling is unclear. Before these questions can be addressed, this study sought to tease apart amylin signaling mechanisms, the specific roles mediated by each receptor component and their role in T2D and cognitive decline by way of surveying AmyR expression in healthy vs diabetic mice in regions relevant to metabolism and cognition, along with the generation of cell lines overexpressing various components of the amylin receptor.

Chapter 2: Methods

2.1 - Animals

C57Bl6/J mice were be purchased from Jackson Laboratories (Bar Harbor, ME) and housed in accordance with the Kent State University Institutional Animal Care and Use

Committee. Mice were housed 2-4 mice per cage under a 12-hour light-dark cycle with the lights turning on at 7:00am or 8:00am, depending upon daylight savings time. At 3 months of age, mice were separated into two groups and half were put on western high fat diet (Custom Diet TD.88137,

Envigo Teklad Diets, NJ) while the other half were fed standard rodent chow. 14 animals fed a high fat diet (7M/7F) and 14 animals fed a standard rodent chow (7M/7F) were used in this study.

Food and water were available ad libitum. These animals were part of a larger study that involved surgical implantation of a cannula to deliver drug, but all of the animals in this study were in the control group and received only CSF.

2.2 - Tissue Preparation & Blood Collection

Animals were fasted for four hours prior to sacrifice. Just prior to sacrifice, blood glucose was measured using the Contour next ONE glucose meter (Bayer, Germany). Animals were anesthetized with isoflurane and their blood collected via cardiac draw. Mice were decapitated, and brains were carefully extracted from the skull and dissected by specific brain region from the side contralateral to the probe (when applicable). Blood was centrifuged at 2000g for 10 minutes, and the serum extracted. Serum was stored at -20OC until further ELISA processing. Brain tissue was flash frozen and stored at -80OC until further qPCR processing.

2.3 - Insulin ELISAs

Serum collected from the terminal cardiac draw was used to measure serum insulin levels, with the use of the Mouse Ultrasensitive Insulin ELISA kit (ALPCO, NH) following the manufacturer’s protocol. Briefly, duplicate wells with 5uL serum sample were incubated with

75uL conjugated mouse ultrasensitive insulin antibody for 2 hours at room temperature while mixing at 9000rpm on a linear rotator (Corning, NY). Wells were washed with 1X wash buffer 6 times and mixed on the linear shaker with 100uL TMB substrate at room temperature for 30 minutes. 100uL stop buffer was added to each well and the plate was read at 450nM. Insulin values of each sample were determined with the use of a 5-parameter standard curve. Any readings out of range were excluded from analysis.

2.4 - Cell Culture

SH-SY5Y human neuroblastomas (ATCC CRL-2266, VA) were purchased and grown in reduced serum Opti-MEM supplemented with HEPES, 2.4 g/L sodium bicarbonate and L- glutamine (Gibco, MA), 5% heat-inactivated fetal bovine serum (FBS) (Mediatech Inc, VA) and

O 1% penicillin/streptomycin (Fisher, MA) at 37 C with 5% CO2. Confluent monolayers were routinely passaged in T-75 flasks (Worldwide, PA) via trypsinization (0.1% trypsin, 0.02% EDTA in HBSS, pH 7.2).

2.5 - Lentiviral Transduction

Four lentiviral stocks were purchased from VectorBuilder (IL) with genetic plasmids prepackaged into the virus. The first virus was packaged with a vector designed to overexpress human RAMP1 and the CalcR, as well as the enhanced green fluorescent protein (EGFP)

15 fluorescent marker, and the neomycin resistance gene. The second virus was packaged with a vector designed to overexpress human RAMP3 and the CalcR, as well as the mCherry fluorescent marker and the puromycin resistance gene. The third virus was packaged with a vector designed to overexpress the human TRPV4 receptor, the EGFP fluorescent marker, and the hygromycin resistance gene. A fourth virus was used as the negative control virus; packaged with a vector designed to overexpress the EGFP and mCherry fluorescent markers as well as the puromycin resistance gene.

On passage 4 - 6, 1x106 cells were plated in a T25. The following day, 5x106 viral particles were added to the plated cells, based on the optimal multiplicity of infection (MOI) for SH-SY5Ys suggested by Origene Technologies, in 2.5mL fresh media. Viral particles were allowed to infect the cells overnight at 37OC. The following day, virus-containing medium was removed, replaced with fresh medium and allowed to incubate overnight. The following day, antibiotics were administered in fresh medium to begin the selection process. 600ug/mL geneticin was administered to the RAMP1 cells, 200ug/mL hygromycin was administered to the TRPV4 cells and 1ug/mL puromycin was administered to the RAMP3 cells and cells infected with the negative control virus. One flask of cells that were not infected with virus were used as a negative control for each antibiotic to ensure total cell death of non-infected cells. Media was changed every 2-3 days to remove dead cells. Viral infection was confirmed via EGFP or mCherry fluorescence under the microscope. Three separate viral infections were conducted for each virus; 3 flasks were infected with the AMY1 virus, 3 flasks were infected with the AMY3 virus, and so on.

2.6 – Cell Sorting

Following antibiotic selection, cells from one viral infection per virus were sorted at the

FlowCore flow cytometry core at the Lerner Research Institute in Cleveland, Ohio. Cells were grown to roughly 1x107 in a T75 flask, detached with accutase (MilliporeSigma, MA) and resuspended in phosphate buffered saline (PBS) with live/dead dye (Fisher, MA). Cells were incubated on ice for 30 minutes, rinsed with PBS and resuspended in PBS with 1mM EDTA

(Fisher, MA), 25mM Hepes (Life Technologies, CA) and 1% FBS (Mediatech Inc, VA). Cells were transferred to the Lerner Institute on ice. The cells were sorted with the FACS AriaII SORP

(BD Biosciences, NJ) and the data analyzed with the Aria II BD FACSDiva (Becton Dickinson,

NJ). Cells that expressed the fluorescent protein of their respective viral vectors were collected and grown again to establish pure cell lines. Once a confluent monolayer was reached in a T75, cells were frozen in an 80% FBS, 10%media, 10% DMSO solution and stored at -80OC for future use. Cells were maintained in media with their respective antibiotics at concentrations half that used in the selection process to ensure pure cell lines through subsequent passages.

2.7 - qPCR & Western Blot Analysis

For in vivo studies, RNA was extracted from the hippocampus, cortex, and hypothalamus using the RNeasy mini kit (Qiagen, Germany) following the manufacturer’s instructions. The amount of RNA extracted was measured via Nanodrop. 1ug of cDNA was made using the High

Capacity cDNA Reverse Transcriptase Kit (Fisher, MA) in a 20uL volume. Quantitative PCR was conducted using 10ng cDNA per reaction with the use of Agilent Mastermix and mouse RAMP1

(Mm00489796_m1), RAMP3 (Mm00840142_m1), CalcR (Mm00432282_m1), TPRV4

(Mm00499025_m1) and the 18S control (Mm03928990_g1) Taqman primers (Life Technologies,

CA). Each sample was run in triplicate to ensure lack of variation.

For in vitro studies, 6x105 cells were plated in T25 flasks. 24 hours after plating, cells were treated with 10uM retinoic acid (MilliporeSigma, MA) to induce differentiation prior to collection.

When cells were fully differentiated five days later, cells allocated for qPCR were collected in

Trizol (Invitrogen, CA), and RNA was extracted following the manufacturer’s protocol. Extracted

RNA was then washed and subjected to ethanol precipitation following the referenced protocol

(Harvard Protocol) to ensure a pure RNA sample. cDNA was produced, and qPCR conducted as described above, using the human RAMP1 (Hs00195288_m1), RAMP3 (Hs00389131_m1),

CalcR (Hs01016882_m1), TPRV4 (Hs01099348_m1) and 18S (Mm03928990_g1) Taqman primers (Life Technologies, CA). Each sample was run in duplicate to ensure lack of variation, and cell samples were subjected to two rounds of qPCR at different time points to ensure sustained overexpression through subsequent passages and to ensure there was no cross-contamination across cell lines. Both the mouse CalcR primers used for the in vivo studies, and the human CalcR primers used for the in vitro studies, recognize a sequence conserved between both splice variants of the CalcR. cDNA amplification was measured using the Stratagene Mx3005P qPCR system

(Agilent Technologies, CA).

Cells allocated for western blot analysis were collected in PBS and subsequently lysed in

1X cell lysis (Cell Signaling, MA) supplemented with DTT, PMSF, protease inhibitor cocktail and phosphatase inhibitor. Two flasks of cells were collected for each cell line under investigation.

Lysed cell samples were sonicated using the Fisherbrand Model 120 sonic dismembrator (Fisher,

MA) at 3x1second intervals at 37% amplitude. Protein concentrations were analyzed with the

Pierce BCA Protein Assay Kit (Thermo Scientific, IL). Tris-acrylamide resolving gels were made

18 at 12% and the stacking gels at 4%. 15ug protein was separated using the SDS-PAGE Bio-Rad mini system (Bio-Rad, CA). Blots were blocked with 10% milk in TBST for 1 hour at room temperature. Primary antibodies [Ramp1 (Rabbit, 1:1000, Abcam, United Kingdom), Ramp3

(Rabbit, 1:300, Abcam, United Kingdom), Calcitonin Receptor (Rabbit, 1:1000, Thermo Fisher,

MA) and Actin (Mouse, 1:50,000, Millipore, MA) were incubated overnight at 4OC in 5mL TBST.

Similar to the CalcR primer, the antibody is designed to recognize both the and α and ß forms of the CalcR. Anti-rabbit and anti-mouse IgG HRP-conjugated secondary antibodies (1:1000, Cell

Signaling, MA) were incubated for 1 hour at room temperature in 5mL TBST. Protein-bound antibodies were visualized using ECL (Millipore, MA) and the Pxi 6 Touch chemiluminescent developer (Syngene, India). Images were quantified using Image J software. Once it was determined that sonication was essential for sufficient receptor detection, duplicate blots were conducted to confirm overexpression of the proteins of interest.

2.8 - ERK Phosphorylation Measurements

To begin to verify functionality of the AMY3 overexpressing cell line, ERK phosphorylation was assessed based previously reported data108,117. AMY3 overexpressing cells and cells infected with the negative control virus were plated in a 6-well plate with 4x105 cells and

2mL media per well. Two plates were included in the experiment so that each well could be run in duplicate. The following day, cells were differentiated with 10uM retinoic acid. After full differentiation five days later, cells were treated with 20uL of 0nM, 10nM or 250nM Pramlintide

Acetate (Anaspec, CA) dissolved in water. After a 15-minute incubation at 37OC, media was removed, and cells collected in 1X lysis buffer (Cell Signaling, MA) supplemented with DTT,

PMSF, protease inhibitor cocktail and phosphatase inhibitor. Cells were sonicated, and protein

19 concentrations determined as described above. 10% tris-acrylamide resolving gels, 4% stacking gels, and the SDS-PAGE Bio-Rad system (Bio-Rad, CA), were used to separate 10ug of protein.

Blots were blocked with 5% BSA & TBST for one hour at room temperature. Primary antibodies

[ERK-phospho-p44/42 MAPK (Mouse, 1:1000, Cell Signaling, MA), ERK 2 (C14) (Rabbit,

1:1000, Santa Cruz, TX) and GAPDH (1:25,000, Mouse, Sigma-Aldrich, MO) were incubated overnight at 4OC in 5mL TBST. Anti-rabbit and anti-mouse IgG HRP-conjugated secondary antibodies (1:1000, Cell Signaling, MA) were incubated for 1 hour at room temperature in 5mL

TBST. Protein-bound antibodies were visualized and quantified as described above. Blots were quantified based on the relative density of pERK to tERK, after they were both normalized to their respective GAPDH controls. Previously collected AMY3 expressing cells and cells infected with the negative control virus were included to ensure no basal differences when comparing to the

0nM PRAM treated cell groups. Two ERK phosphorylation assays were conducted, and samples from each assay were subjected to two replicate western blots.

2.9 – Statistical Analysis

All in vivo qPCR and blood data were analyzed via two-way ANOVA. Sex vs diet two- way ANOVAs were conducted to determine if there were significant differences due to sex, diet, or an interaction between the two, in each separate brain region. Sex vs region two-way ANOVAs were also conducted in rodent chow fed animals to examine any differences in expression due to brain region at a basal level. Body weights, serum insulin levels and fasting blood glucose were subjected to two-way ANOVAs to examine metabolic changes induced by diet, sex or an interaction between the two. When the data set failed the Levene’s equality of error variances test,

Kruskal-Wallis tests; the non-parametric equivalent of a one-way ANOVA, was conducted to look

20 for statistical differences between groups. Insulin levels and fasting blood glucose reads were subjected to Pearson’s correlations with qPCR data to determine if metabolic dysregulation correlated with amylin receptor expression. Significant outliers, as determined with the use of the

Grubbs GraphPad QuickCalcs website, were removed from data sets prior to parametric statistical analyses. In vitro experiments were analyzed with a one-way ANOVA and Bonferroni post-hoc tests. Western blots were subjected to Independent Samples T-tests to examine differences in band density, separately; for each protein of interest. The results of the ERK phosphorylation measurement were analyzed via Independent Samples T-tests when analyzing differences between control virus cells and AMY3 cells within each treatment, and via one-way ANOVA when analyzing changes across treatment groups.

Chapter 3: Results

mRNA expression levels of different components of the amylin receptor were measured in brain regions known to be associated with metabolism and cognition. Taqman primer manufacturing scientists suggest using CTs less than 38, however, anything greater than 37 was excluded as a conservative measure. This is because these values were found to correlate with expression levels too low for reliable amplification of the specific gene of interest, or levels too low to represent any biological significance.

The difference in expression of the gene of interest and the control housekeeping gene, 18S

(Delta CT), was obtained for each sample and quantified using the 2^-Delta CT method to derive a linear comparison between groups. Statistical analyses were conducted on the resulting data set.

Data were then normalized to the average of all the samples in the comparison and the relative quantity (RQ) of each sample obtained, to allow for a simpler graphical representation of the results.

3.1 – RAMP1 expression

qPCR was used to analyze levels of RAMP1 expression in the hippocampus, cortex, and hypothalamus of male and female mice fed standard rodent chow or a high fat diet. RAMP1 expression was analyzed in each region independently via two-way ANOVA. No significant differences in hippocampal RAMP1 expression were observed due to sex (F(1,23) = 0.000, p =

0.985) or diet (F(1,23) = 0.001, p = 0.97). There was also no observed interaction between sex and

22 diet (F(1,23) = 0.741, p = 0.398) (data not shown). Cortical RAMP1 expression was also analyzed via two-way ANOVA, which indicated a significant difference due to diet (F(1,24) = 5.237, p =

0.031), but not due to sex (F(1,24) = 0.077, p = 0.783). There was also no observed interaction between the two (F(1,24) = 1.663, p = 0.21) (Figure 1A). Two-way ANOVA analysis indicated a significant increase in hypothalamic RAMP1 expression due to sex (F(1,24) = 15.966, p = 0.001), but not due to diet (F(1,24) = 2.201, p = 0.151). There was also no observed interaction between sex and diet (F(1,24) = 0.276, p = 0.604) (Figure 1B).

Figure 1. Changes in Cortical and Hypothalamic RAMP1 Expression. RAMP1 expression in the cortex (A) & hypothalamus (B) for n = 14/group (7M & 7F). Two-way ANOVA indicated statistical significance for diet irrespective of sex in the cortex (A) and for sex irrespective of diet in the hypothalamus (B) as denoted by * where p < 0.05. No statistical differences were observed in the hippocampus (data not shown). The results are depicted as mean ± standard error of the mean.

To address whether there were any basal differences in expression of RAMP1 and/or whether levels were different across sex, a separate two-way ANOVA was conducted with brain region and sex as independent factors in animals fed a normal diet. The data analysis demonstrated no statistically significant differences in RAMP1 levels across regions (F(2,36) =

0.191, p = 0.827) or sex (F(1,36) = 0.969, p = 0.332). However, a significant interaction between the two was observed (F(2,36) = 7.078, p = 0.003) (Figure 2).

Figure 2: Changes in RAMP1 Expression Due to Region. RAMP1 expression in the hippocampus, cortex and hypothalamus for n=14/group (7M &7F) rodent chow fed animals. Two- way ANOVA analysis indicated a significant interaction between region and sex as denoted by * where p < 0.05. No statistical differences were observed due to region or sex individually. The results are depicted as mean ± standard error of the mean.

3.2 – RAMP3 Expression

The same animals and regions as those examined for levels of RAMP1 were also analyzed for RAMP3 expression via two-way ANOVA. There was a significant difference in hippocampal

RAMP3 expression observed due to diet (F(1,21) = 10.332, p = 0.004). There were no significant differences observed due to sex(F(1,21) = 0.091, p = 0.766) or an interaction between sex and diet

(F(1,21) = 0.039, p = 0.846) (Figure 3). There were no significant differences observed in cortical

RAMP3 expression due to diet (F(1,24) = 0.59, p = 0.45), sex (F(1,24) = 0.041, p = 0.842) or an interaction between the two (F(1,24) = 0.858, p = 0.364) (data not shown). No significant differences were observed in hypothalamic RAMP3 expression due to diet (F(1,23) = 0.359, p =

0.555), sex (F(1,23) = 0.044, p = 0.835) or an interaction (F(1,23) = 0.007, p = 0.932) (data not shown).

RAMP3 expression was also compared across brain regions in rodent chow fed animals.

As the data failed Levene’s equal variance test, Kruskal-Wallis analyses were conducted to examine differences. Significant differences due to region were found in males (χ2 (2) = 17.462, p

< 0.001) with mean rank expression scores of 10.86 for the hippocampus, 18 for the cortex and

4.14 for the hypothalamus and in females (χ2 (2) = 11.072, p = 0.004) with mean rank expression scores of 9.86 for the hippocampus, 17 for the cortex and 6.14 for the hypothalamus (Figure 4).

As Kruskal-Wallis analyses don’t include post-hoc tests, subsequent Independent Samples T-tests were conducted to examine the differences among groups. Significant differences were detected with comparing cortical RAMP3 levels to both hippocampal levels and hypothalamic levels in both males and females (all comparisons p < 0.001). Statistically significant differences were also observed in males (p < 0.001) and females (p = 0.005) when comparing hippocampal levels and hypothalamic levels (Figure 4).

When comparing RAMP3 expression in males and females fed a standard rodent chow,

Kruskal-Wallis analyses did not indicate any differences in hippocampal expression (χ2 (1) =

0.184, p = 0.668) with mean rank expression scores of 6.57 for males and 7.5 for females. There were also no differences observed in cortical levels (χ2 (1) = 0.037, p = 0.848) with mean rank expression scores of 7.71 for males and 7.29 for females or hypothalamic levels (χ2 (1) = 0.184, p

= 0.668) with mean rank expression scores of 6.57 for males and 7.5 for females (Figure 4).

Figure 3: Changes in Hippocampal RAMP3 Expression. RAMP3 expression in the hippocampus for n = 13/group (7M & 6F). Two-way ANOVA indicated statistical significance for diet irrespective of sex in the hippocampus as denoted by * where p<0.05. No statistical differences were observed in the cortex or the hypothalamus (data not shown). The results are depicted as mean ± standard error of the mean.

Figure 4: Changes in RAMP3 Expression Due to Region. RAMP3 expression in the hippocampus, cortex and hypothalamus of rodent chow fed animals for n = 14/group (7M & 7F).

Kruskal-Wallis analyses indicated statistical significance due to region irrespective of sex.

Significant differences in expression were observed across all regions for both males and females, as denoted by * where p<0.05.

3.3 - CalcR Expression

CalcR expression levels were also compared across diets and sexes in all the study group animals. There was determined to be no CalcR expression in the cortex as the average raw CT value of the CalcR observed in this region for both male and female mice fed both rodent chow and a high fat diet was above 37 (hippocampus = 34.79, cortex = 37.23, hypothalamus = 26.73).

Based on this, CalcR expression in the cortex was deemed too low and excluded from further analysis.

Data for hippocampal CalcR expression failed the Levene’s equal variance test, thus non- parametric testing using the Kruskal-Wallis tests was performed to examine differences in expression due to diet in males and females separately. Similar analyses were performed to assess differences in expression due to sex in rodent chow and high fat diet fed mice separately. Kruskal-

Wallis analyses indicated no significant difference due to diet in males (χ2 (1) = 1.636, p = 0.201) with mean rank expression scores of 4.5 for high fat diet and 7.0 for rodent chow mice, or in females (χ2 (1) = 0.3, p = 0.584) with mean rank expression scores of 5.5 for high fat diet and 6.6 for rodent chow mice (data not shown). Kruskal-Wallis analyses also indicated no significant difference due to sex in high fat diet fed mice (χ2 (1) = 2.564, p = 0.109) with mean rank expression scores of 4.83 for males and 8.17 for females, or in rodent chow fed mice (χ2 (1) = 2.16, p = 0.142) with mean rank expression scores of 3.5 for males and 6.2 for females (data not shown). A two- way ANOVA for hypothalamic CalcR expression revealed no differences due to diet (F(1,24) =

0.005, p = 0.944), sex (F(1,24) = 0.03, p = 0.865) or an interaction between the two (F(1,24) =

1.28, p = 0.269) (data not shown).

Kruskal-Wallis analyses were also conducted to examine differences in CalcR expression in rodent chow fed mice across brain regions, as the data failed Levene’s equal variance test. No

31 significant difference due to region was detected in males (χ2 (1) = 1.75, p = 0.186) with mean rank expression scores of 4.25 for the hippocampus and 7.0 for the hypothalamus, or in females

(χ2 (1) = 2.908, p = 0.088) with mean rank expression scores of 8.6 for the hippocampus and 5.0 for the hypothalamus (data not shown). Kruskal-Wallis analyses also indicated no significant difference due to sex in the hippocampus (χ2 (1) = 2.16, p = 0.142) with mean rank expression scores of 3.5 for males and 6.2 for females, or in the hypothalamus (χ2 (1) = 0.69, p = 0.406) with mean rank expression scores of 8.43 for males and 6.57 for females (data not shown).

3.4 - TRPV4 Expression

TRPV4 hippocampal expression values obtained from qPCR were subjected to Kruskal-

Wallis analysis as the data failed the Levene’s test. No significant difference was observed due to diet in males (χ2 (1) = 2.469, p = 0.116) with mean rank expression scores of 5.43 for high fat diet and 8.83 for rodent chow mice, or in females (χ2 (1) = 0.331, p = 0.565) with mean rank expression scores of 6.86 for high fat diet and 8.14 for rodent chow mice. Kruskal-Wallis analyses also indicated no significant difference due to sex in high fat diet fed mice (χ2 (1) = 0.037, p = 0.848) with mean rank expression scores of 7.29 for males and 7.71 for females, or in rodent chow fed mice (χ2 (1) = 0.184, p = 0.668) with mean rank expression scores of 7.5 for males and 6.57 for females. Although not significant, results indicated higher basal TRPV4 expression in the male hippocampus when compared to females, which was reversed when animals were fed a high fat diet (data not shown).

Kruskal-Wallis analyses were also conducted on the cortical TRPV4 expression data set.

No significant difference was observed due to diet in males (χ2 (1) = 0.51, p = 0.475) with mean rank expression scores of 7.71 for high fat diet and 6.17 for rodent chow mice, or in females (χ2

(1) = 0.103, p = 0.749) with mean rank expression scores of 6.83 for high fat diet and 6.17 for rodent chow mice. Kruskal-Wallis analyses also indicated no significant difference due to sex in high fat diet fed mice (χ2 (1) = 0.184, p = 0.668) with mean rank expression scores of 6.57 for males and 7.5 for females, or in rodent chow fed mice (χ2 (1) = 0.641, p = 0.423) with mean rank expression scores of 5.67 for males and 7.33 for females (data not shown). Two-way ANOVA analysis of hypothalamic TRPV4 expression indicated no significant differences due to diet

(F(1,24) = 2.995, p = 0.096), however there was a significant difference due to sex (F(1,24) =

6.747, p = 0.016). No significant interaction was observed between sex and diet (F(1,24) = 0.22, p = 0.643) (Figure 5).

Kruskal-Wallis analyses were also conducted to examine changes in TRPV4 expression across brain regions in rodent chow fed animals as the data set did not exhibit equal variance across groups. No significant differences due to region were found in males (χ2 (2) = 4.939, p = 0.085) with mean rank expression scores of 13.67 for the hippocampus, 10.17 for the cortex and 6.71 for the hypothalamus or in females (χ2 (2) = 1.384, p = 0.5) with mean rank expression scores of 9.86 for the hippocampus, 12.83 for the cortex and 9.14 for the hypothalamus (data not shown).

Kruskal-Wallis analyses also did not indicate any differences in hippocampal expression (χ2 (1) =

0.184, p = 0.668) with mean rank expression scores of 7.5 for males and 6.57 for females, in cortical levels (χ2 (1) = 0.641, p = 0.423) with mean rank expression scores of 5.67 for males and

7.33 for females, or in hypothalamic levels (χ2 (1) = 3.433, p = 0.064) with mean rank expression scores of 5.43 for males and 9.57 for females (data not shown).

Figure 5: Changes in Hypothalamic TRPV4 Expression. TRPV4 expression in the hypothalamus for n = 14/group (7M & 7F). Two-way ANOVA indicated statistical significance for sex irrespective of diet in the hypothalamus as denoted by * where p<0.05. No statistical differences were observed in the hippocampus or the cortex (data not shown). The results are depicted as mean ± standard error of the mean.

3.5 - Metabolic Measurements & Correlations to mRNA Expression

To ensure that high fat diet induced metabolic changes; body weights, serum insulin levels and fasting blood glucose levels were compared across animals. A two-way ANOVA was conducted on body weight, which indicated significant differences due to diet (F(1,24) = 8.137, p

= 0.009) and sex (F(1,24) = 23.264, p < 0.001), but no significant difference between the two

(F(1,24) = 1.003, p = 0.327) (data not shown). These results confirmed the success of the diet intervention.

Serum insulin levels and fasting blood glucose levels were also subjected to independent two-way ANOVAs. Results indicated no significant differences in fasting blood glucose levels due to diet(F(1,21) = 1.021, p = 0.324) , sex (F(1,21) = 2.758, p = 0.112) or an interaction between the two(F(1,21) = 0.142, p = 0.710). There were also no significant differences observed in serum insulin levels due to diet (F(1,19) = 0.086, p = 0.773), sex (F(1,19) = 1.549, p = 0.228) or an interaction between the two (F(1,19) = 0.128, p = 0.724) (data not shown).

Serum insulin levels & fasting blood glucose levels were then correlated to mRNA expression levels via Pearson’s Correlations to determine if there was any association between receptor expression and insulin or glucose levels. Expression levels of each receptor component from each region were correlated with insulin and glucose levels separately, in males and females.

A significant positive correlation was detected between hypothalamic CalcR expression and serum insulin levels in males (r = 0.667, n = 12, p = 0.018). A significant positive correlation was also detected between hypothalamic CalcR expression and fasting blood glucose levels in males (r =

0.607, n = 13, p = 0.028). All other correlations between glucose or insulin and each amylin receptor component in all regions studied were found to be nonsignificant (data not shown).

3.6 - Lentiviral Transduction Drives Genetic Overexpression

Following lentiviral transduction, antibiotic selection and cell sorting, cells were collected and subjected to qPCR to ensure infected cells exhibited overexpression of the gene of interest.

The Delta CTs obtained from each sample and used to determine changes in gene expression with the 2^-Delta CT method. This provided a linear comparison between groups and were expressed as the fold change from cells infected with the negative control virus.

Delta CTs of RAMP1 expression in control virus-infected cells, wild type cells and AMY1 transduced cells were determined to be 18.84, 20.14 and 14.21, respectively. This correlated with

0.40- and 26.60-fold changes from control virus in wild type and AMY1 transduced cells, respectively, when quantified with the 2^-Delta CT method (Figure 6A). A one-way ANOVA indicated a significant difference (F(2,5) = 71.333, p < 0.001), and Bonferroni post-hoc tests indicated significant differences between AMY1 and control virus cells (p = 0.001), and between

AMY1 and wild type cells (p < 0.001) but not between wild type cells and control virus cells (p =

0.192) (Figure 6A). These results indicate that wild type cells express roughly half the RAMP1 observed in control virus-infected cells express, while AMY1 transduced cells express more than

26 times the amount of RAMP1 observed in control virus cells. Delta CTs of the CalcR were 27.68,

26.89 and 10.91 in control virus-infected cells, wild type cells and AMY1 transduced cells, respectively. This corresponded with 1.96- and 121,725-fold changes from control virus cells in wild type and AMY3 transduced cells, respectively. A one-way ANOVA indicated a significant difference (F(2,5) = 466.085, p < 0.001), and Bonferroni post-hoc tests indicated significant differences between AMY1 and control virus cells (p < 0.001), and between AMY1 and wild type cells (p < 0.001) but not between wild type cells and control virus cells (p = 0.873) (Figure 6C).

Using the same quantification method, AMY3 transduced cells expressed RAMP3 levels that were a 17,684-fold change from control virus cells, while wild type cells expressed a 1.28- fold RAMP3 expression change from control virus cells. The one-way ANOVA indicated significance (F(2,5) = 758.202, p < 0.001), and Bonferroni post-hoc tests indicated significant differences when comparing AMY3 cells to control virus cells (p < 0.001) and wild type cells (p

< 0.001). No difference was observed between control virus cells and wild type cells (p = 1.0)

(Figure 6B). CalcR levels changed 195,442-fold in AMY3 cells and 1.22-fold in wild type cells when compared to control virus cells. One-way ANOVA analysis indicated a significant difference

(F(2,5) = 833.837, p < 0.001), and Bonferroni post-hoc tests indicated significant differences when comparing AMY3 cells to control virus cells (p < 0.001) and wild type cells (p < 0.001). but not when comparing control virus cells to wild type cells (p = 1.0) (Figure 6D).

TRPV4 transduced cells and wild type cells were determined to express levels of TRPV4 that correlated with 1,473- and 1.59- fold changes from control virus cells, respectively. One-way

ANOVA indicated significance (F(2,5) = 679.732, p < 0.001), and Bonferroni post-hoc tests indicated significant differences when comparing TRPV4 cells to control virus cells (p < 0.001) and wild type cells (p < 0.001), but not when comparing control virus cells to wild type cells (p =

0.145) (Figure 6E). Collectively, these results indicate that lentiviral transduction successfully induced overexpression of the genes of interest at varying intensities, while transduction of the control virus cells with the negative control virus induced minor changes in gene expression.

Figure 6: Genetic Overexpression in Lentiviral Transduced Cells. Genetic upregulation of

RAMP1 (A), RAMP3 (B), CalcR (C & D) and TRPV4 (E) lentiviral transduction for n = 9 cell flasks/group (3 wild type, 3 control virus & 3 transduced cells). One-way ANOVA indicated statistical significance in transduced cells when compared to wild type and control virus cells for

RAMP1 (A), RAMP3 (B) and TRPV4 (E) expression, as denoted by * where p < 0.05. One-way

ANOVA also indicated statistical significance in CalcR expression in AMY1 (C) and AMY3 (D) transduced cells when compared to wild type and control virus cells as denoted by # where p <

0.05. The results are depicted as mean ± standard error of the mean.

3.7 - Lentiviral Transduction Drives Overexpression of RAMP3

Following confirmation of genetic overexpression, AMY3-expressing cells were differentiated, collected, sonicated and subjected to western blot analysis to assess expression levels of the proteins of interest. Bands of interest were quantified on ImageJ, and the ratio of each bands’ relative density to that of the actin control was quantified and compared across samples.

Western blots indicated a robust increase in RAMP3 monomer (p = 0.004) (Figure 7A) and

RAMP3 deglycosylated homodimer (p < 0.001) (Figure 7B) expression, but only a minor increase in CalcR expression (p = 0.378) (Figure 7C), when comparing cells infected with the AMY3 virus to cells infected with the negative control virus. Unfortuntely, this study was unable to probe

AMY1 and TRPV4 transduced cells for overexpression as reliable antibodies for RAMP1 or

TRPV4 proteins were unavailable.

Figure 7: RAMP3 & CalcR Protein Upregulation in AMY3 Transduced Cells. Protein levels of RAMP3 monomer (A), RAMP3 deglycosylated homodimer (B) and CalcR (C) in AMY3 and control virus cells and the associated western blot (D) for n = 3 cell flasks/group (3 control virus

& 3 AMY3). Independent Samples T-tests indicated statistical significance in AMY3 cells when compared to control virus cells for the RAMP3 monomer (A), and the RAMP3 deglycosylated homodimer (B), as denoted by * where p < 0.05. No statistical difference was observed in CalcR levels. The results are depicted as mean ± standard error of the mean.

3.8 - ERK Phosphorylation Measurements

Once RAMP3 and CalcR protein overexpression was confirmed in AMY3 transduced cells, a single time-point preliminary study was carried out to determine whether this overexpression translated into functional changes in differentiated cells overexpressing RAMP3

& CalcR. Western blots and subsequent Independent Samples T-tests indicated no statistical significance between control virus cells or AMY3 cells in the overexpression study (p = 0.319) or at 0nM (p = 0.223), 10nM (p = 0.876) or 250nM (p = 0.848) in the dose response curve. One-way

ANOVAs indicated no statistical differences in control virus cells (F(2,13) = 0.018, p = 0.983) or

AMY3 cells (F(2,13) = 1.367, p = 0.289) when comparing across treatment groups in the dose response study (Figure 8).

Figure 8: ERK Phosphorylation Measurements in Transduced Cells. Protein levels of pERK, tERK and their respective GAPDH controls as determined by western blot analysis on n = 2 ERK phosphorylation assays with duplicate wells. Independent Samples T-tests indicated no significant differences between cell types at any treatment and one-way ANOVA indicated no significant differences across treatment groups. The results are depicted as mean ± standard error of the mean.

Chapter 4: Discussion

Amylin is increasingly being identified as the linking factor between T2D and AD.

However, conflicting data on whether amylin receptor signaling is protective or detrimental indicate that the signaling mechanisms by which amylin exerts its effects and the specific amylin receptor components responsible for such signaling remains unclear. One potential explanation for these conflicting findings and for the relevance of amylin signaling as a linking factor between

T2D and AD could be disease-dependent changes in receptor expression subtypes and/or regional levels in T2D. Therefore, in this thesis, to begin to address the questions mentioned above, this study identified transcriptional expression differences of the amylin receptor subtypes (AMY1,

AMY3) and TPV4 receptors, all known to signal for amylin, in T2D and AD. Changes produced by chronic high fat diet were identified in three areas relevant for AD and metabolic signaling and determined if changes vary by sex (gender). Lastly, three stable neuronal-like cell lines overexpressing these three receptors were created so that future work can identify the contribution of specific amylin receptor subtype signaling on neuroprotection and/or toxicity.

4.1 – Regional Expression Changes in Amylin Receptor Transcription

To address whether basal regional differences in transcriptional expression of various amylin receptors existed, mRNA levels in the cortex, hippocampus, and hypothalamus were examined in control animals. As expected, levels of CalcR, RAMP1, and RAMP3 were found to exhibit different mRNA expression patterns across these regions. One important and surprising finding was the lack of CalcR mRNA expression in the cortex. As discussed in the introduction,

45 both the CalcR and a RAMP are necessary to form the amylin receptor complex, therefore these data suggest that functional and neuronal changes associated with amylin signaling are not derived though direct cortical activation of its receptor. These data line up with previous findings, indicating robust amylin signaling primarily in the hippocampus104, rather than the cortex. To this end, copious expression of all three native amylin receptor components (RAMP1, RAMP3 and

CalcR) were identified in the hippocampus, as well as in the hypothalamus, supporting a direct role of amylin signaling in these regions.

First, this study sought to investigate that the intervention successfully produced the expected weight gain and the corresponding metabolic dysfunction that comes with chronic obesity. Body weights, serum insulin levels and fasting blood glucose levels were measured. As expected, high fat diet increased body weight in both males and females. Fasting blood glucose and serum insulin levels, however, did not change due to diet. This indicates that although differences in body weight were detected, there was no clear diabetic phenotype. One possibility could be the fact that these animals had not yet reached a stage of overt diabetes/metabolic syndrome despite the weight of these mice. However, another possibility is that insulin and glucose levels were analyzed from only one time point, and therefore unable to provide a full metabolic picture. It is well known that as T2D progresses, the initial increase in glucose leads to an increase in insulin levels. At a certain point, serum insulin levels hit a peak and begin to decline as pancreatic ß-cells begin to die off and insulin production decreases125. This point at which insulin levels are highest varies across individuals. It is therefore difficult to capture a diabetic phenotype across a group of animals based on one single time point. Correlations between hypothalamic

CalcR expression in males for both glucose and insulin levels suggest that the hypothalamus is undergoing adaptations to potentially adapt to the induced metabolic stress. However, future

46 research will have to include additional time points and metabolic stress measurements to gather a full picture.

Once the phenotype was verified, regional differences of CalcR, RAMP1, RAMP3 and

TRPV4 were addressed and differences between males and females investigated. Although

RAMP1 mRNA levels were not found to differ across regions, one interesting finding was that while females were found to express lower levels of RAMP1 in the hippocampus and the cortex, they expressed higher levels of hypothalamic RAMP1 when compared to males (Figure 2). The hypothalamus has been shown to mediate metabolic amylin signaling and its interaction with leptin69,71,72 . Importantly, amylin treatment has been shown to enhance the potency of leptin signaling, particularly when leptin resistance begins to manifest in states of obesity/T2D, correcting hypothalamic leptin resistance126,127. It is also important to note that amylin treatment increases hypothalamic RAMP1 mRNA expression, but not RAMP3, suggesting that AMY1 mediates amylin interaction with leptin69,71 and may be primarily involved in metabolic signaling.

Interestingly, data in both humans and animals indicate that females are more resistant to T2D development34. Based on this, these results suggest that higher basal levels of RAMP1 within the hypothalamus of females may be implicated in the regulation of mechanisms that confer increased metabolic dysfunction resistance.

Interestingly, this study was able to determine that female mice also exhibited more hypothalamic TRPV4 (Figure 5). The TRPV4 receptor serves many functions, including heat responses128. As the hypothalamus mediates thermoregulation, hypothalamic TRPV4 may serve as a transducer of warm stimuli, playing a role in hypothalamic-mediated core body temperature homeostasis. This would be in line with previous findings indicating the presence of the TRPV4 receptor in anterior hypothalamic structures involved in temperature sensation128. The

47 upregulation of hypothalamic TRPV4 expression may play a role in the slight increase of basal core temperature seen in females129.

Both RAMP1 and RAMP3 mRNAs as well as CalcR were all expressed in functionally relevant amounts in the hippocampus. This supports the notion that amylin signaling can regulate hippocampal function, an aspect that is already supported by a myriad of studies, both at a functional101,102,104 and a mechanistic105,110,111,119 level. In regards to hippocampal function, amylin treatment was shown to impact LTP in hippocampal slices; which was abolished following specific amylin receptor inhibition110,111. Parallelly, specific AMY3 receptor activation has also been shown to mediate several signaling pathways known to play a role in signaling pathways associated with hippocampal-mediated cognition, including increases in cAMP, as well as activation of Akt, ERK and PKA108,117. Together these data support and may explain the beneficial effects of amylin on cognition in models of aging100 and AD101-103,130.

In connection with the above findings, the leptin receptor is also highly expressed in the hippocampus78,79 and known to be sensitized in an amylin-receptor dependent manner, likely through AMY169,71,73. Previous studies demonstrate that leptin receptor activation facilitates LTP in hippocampal slices78,79. Also of relevance, leptin is intimately associated with AD development; where changes in levels of leptin impair cognition and accelerates AD progression, while AD can in turn impair leptin signaling, leading to a downward spiral (reviewed in McGuire, 2017)81. Leptin resistance, as manifested by leptin receptor downregulation, has been well documented in AD human brains as well as AD mouse models81,82. Importantly, leptin treatment has been shown to reduce amyloid burden in the hippocampus and improve memory in mouse models of AD83,131.

Together, these data suggest hippocampal functional benefits associated with amylin receptor activation could be derived directly through AMY3 activation108,110,117, and/or indirectly, through

48 the ability of amylin to regulate leptin receptor sensitivity, and thus potentiate leptin receptor- mediated LTP facilitation. This thesis work cannot make any such claims as this aspect was not mechanistically addressed. It would, however, be interesting to determine whether amylin or

PRAM has an effect on cognition in leptin receptor knockout mice. If that were the case, one could rule out a role of the leptin receptor in mediating amylin-related effects on cognition.

As previously discussed, both the CalcR and a RAMP are necessary to form the amylin receptor complex. These data demonstrate that CalcR is expressed at very low levels, if expressed at all, in the cortex. On the other hand, it was determined that the highest expression of RAMP3 expression was found in the cortex (Figure 4). RAMPs have been shown to interact with several other receptors including calcitonin receptor like receptor (CRLR)118. While the role of CRLR and its interaction with RAMPs is beyond the scope of this thesis, RAMP3 has been shown to interact with the CRLR to form a potent adrenomedullin receptor, and adrenomedullin (ADM) synthesis is increased in response to a high fat diet115,132. Although these studies do not explain why the upregulation of RAMP3 was localized to the cortex, further studies investigating the interaction of the CRLR with RAMP3 and their role in ADM signaling in the T2D brain may bring clarity to this theory.

4.2 – Diet Induced Changes in Amylin Receptor mRNA Expression

Another goal of this thesis was to identify whether amylin receptor transcription was altered by high-fat diet/metabolic stress. Two novel findings of this work indicate high fat diet induced 1) a decrease in hippocampal RAMP3 mRNA levels and 2) an increase in cortical RAMP1 mRNA levels.

Both male and female mice exhibited downregulation of hippocampal RAMP3 in response to high fat diet (Figure 3). These findings indicate a potential mechanism by which loss of amylin signaling may impair cognition in response to a high fat diet. The underlying mechanism that governs down regulation of RAMP3 in the hippocampus remains unknown and could be a focus for future work. It is noted in the literature that G protein-coupled receptor (GPCR) synthesis, can be downregulated after prolonged exposure to an agonist drug62. Although this has not been reported for the CalcR, one could speculate that hyperamylinemia derived from diabetes could downregulate RAMP3 as shown when amylin is delivered acutely in the area postrema133.

However, what regulates the transcription of RAMP3 specifically is not known and the animals in this study did not show a clear diabetic phenotype. Furthermore, levels of amylin were not measured, thus any strong claims regarding the relevance of RAMP3 downregulation cannot be made at this point.

As discussed in the introduction, several reports suggest the prevalence of AMY3 in various amylin signaling cascades66,103,104,107, as well AMY3’s role in specific cognition-related signaling108,110,117. While there appears to be a trend in the field toward acceptance of AMY3 as the primary amylin receptor, there is still much debate as to whether amylin signaling exerts therapeutic100-103,130 or toxic104-108 effects. Furthermore, several reports have indicated the ability of Aß to signal through the amylin receptor110,111, and some reports have indicated Aß signaling specifically through AMY3107,108. There is also discussion as to whether amylin serves as a seed for Aß, and data have suggested that while fibrillar amylin is a seed for Aß aggregation and plaque formation90,91, monomeric amylin (similar to PRAM as it does not aggregate) on the other hand, may inhibit Aß aggregation92. This work was carried out in normal mice, not AD mouse models, therefore none of these aspects can be addressed. However, future studies using AD mouse models

50 under high fat conditions and genetic downregulation of RAMP3 in AD models could address the role of AMY3 in regulating Aß.

Also in relation to AD development, previous studies indicate a role of TRPV4 in several pathological features observed in T2D134-137. Specifically, TRPV4 has been shown to play a role in pro-inflammatory responses, increased production of reactive oxygen species (ROS) and neuronal apoptosis134,135. TRPV4 has also been shown to mediate toxic amylin119 and Aß138 signaling. One of the questions was whether chronic obesity/metabolic dysfunction would lead to an upregulation in TRPV4 transcription which could explain AD and cognition related pathogenic aspects. Unfortunately, this work was not able to identify any diet induced changes in hippocampal or cortical TRPV4. However, this may be partially due to lack of statistical power as TRPV4 data failed normality, forcing the use of the non-parametric statistical analysis. A two-way ANOVA on these data, prior to determining failure of the Levene’s normality test, reflected that both diet and sex altered hippocampal TRPV4 expression. Specifically, high fat diet lead to increases of TRPV4 in female mice. While, at this point, this is complete speculation given the results of the statistical analysis, these data could potentially explain why, despite females being more resistant to developing metabolic dysfunction (potentially through higher RAMP1 expression), they are yet more prone to AD development. TRPV4 expression changes are currently being verified in additional animals to increase power and clarify this exciting possibility.

Of interest, when examining each raw data point, it appeared as though animals either highly expressed the gene of interest, or they didn’t have it at all; contributing to the variation. A possible explanation for this observation is that TRPV4 receptors may be discretely localized and the dissections were not able to consistently harvest the exact areas where these receptors were

51 located. This would lead to the ‘all or none’ pattern such as the one observed. In-situ hybridization studies may be needed to clarify these aspects if higher n numbers do not resolve the variability.

As discussed above, another novel finding of this work was the observation that high fat diet increased cortical RAMP1 transcription (Figure 1). However, given that CalcR was expressed at very low levels in the cortex, if at all, the relevance of these increases is unlikely to relate to amylin signaling. The increase in cortical RAMP1 may represent an increase in calcitonin gene- related peptide (CGRP) signaling as RAMP1 interacts with the calcitonin-receptor-like receptor

(CRLR) to signal primarily for CGRP139. Vasodilation in cerebral arteries has been shown to be impaired in a rat model of T2D140, and CGRP is a potent vasodilator141. While beyond the scope of this thesis as its main focus is upon amylin signaling, this cortical RAMP1 upregulation may represent a compensatory mechanism as the body attempts to restore lost vasodilation in cerebral arteries.

Taken together, the results of the in vivo studies support the notion that a high fat diet induces changes in transcription of amylin receptor components, and some of these changes are sex-dependent. While this work supports the role of amylin receptor activation in mediating cognition via the hippocampus, these findings demonstrate that amylin signaling is unlikely to have an impact on cortical function directly, as there is very little expression of CalcR.

Future directions should first and foremost focus on co-immunoprecipitation examining the protein interaction of RAMPs and the CalcR. RAMPs and the CalcR are only pieces of a puzzle, and do not form the amylin receptor without the other piece. While levels of RAMPs or the CalcR may change, this does not necessarily mean that amylin receptor expression has also changed. This in turn would also rectify another caveat of this study in that only changes in mRNA levels were examined, as post-transcriptional modifications and regulations induce mRNA

52 changes such that levels don’t always directly translate to protein levels. Future studies warrant the investigation of RAMP1, RAMP3 and CalcR protein interaction in the hippocampus, cortex and hypothalamus.

To further assess the impact of high fat diet and metabolic changes on amylin receptor expression, multiple time points of glucose and insulin levels, as well as glucose and insulin tolerance tests, would provide more information as to potential mechanisms leading to changes amylin receptor expression and how a high fat diet impacts amylin signaling. Future studies should also examine the impact of removing specific receptor components in RAMP1, RAMP3 or CalcR knockout mice. If one were to use these animal models, one would be able to tease apart specific in vivo functions and signaling pathways mediated be each specific amylin receptor component.

The use of amylin or PRAM administration, as well as a high fat diet, would then allow one to begin to tease apart various functional effects of each amylin receptor component in states of health and disease, as well as their ability to mediate therapeutic or toxic functions of amylin signaling.

4.3 - Cell Line Overexpression and Function

Cell lines overexpressing AMY1, AMY3 and TRPV4 were generated to guide investigation into understanding how amylin signaling leads to neuroprotection100-103,130 and/or cellular death104-108 as several conflicting articles have shown. These cell lines can then potentially help to tease apart specific signaling mechanisms and the amylin receptor complexes activated by amylin as well as Aß.

These data indicated successful plasmid overexpression as qPCR analysis indicated significant increases in mRNA for all three plasmids. To further verify functionality of said overexpression, protein levels of the receptor components were measured for which reliable

53 antibodies were available; namely CalcR and RAMP3. Western blot analysis verified RAMP3 overexpression (Figure 7). On the other hand, CalcR levels were only slightly upregulated. While this is surprising given that both CalcR and RAMP3 were delivered in the same plasmid, and each resulted in robust mRNA upregulation, several events/limitations can explain these findings. The most likely explanation is that there may be an issue with the T2A linker sequence, as the CalcR open reading frame is downstream of RAMP3. Experts at VectorBuilder have reported this as an occasional issue with vectors containing multiple open reading frames.

There are also a number of post transcriptional modifications that can impact the efficiency at which proteins are synthesized142, which could have preferentially inhibited CalcR protein synthesis. CalcR is known to be subjected to splicing; as indicated by the presence of the CalcRα and CalcRß isoforms. Two other splice variants of the CalcR have been detected, but these transcripts translate into unfunctional or uncommon proteins115. It is possible that CalcR is subjected to additional post transcriptional modifications outside that of splicing.

Amylin receptor upregulation has previously been reported to increase pERK levels following amylin administration108,117. This inspired the ERK phosphorylation assay to ensure proper amylin receptor function in response to PRAM administration. Based on previous findings108,117, a preliminary study using a single time-point of 15-minute PRAM pre-incubation at doses known to drive this phosphorylation process was carried out. While only two ERK phosphorylation assay experiments were conducted, neither experiment produced any promising results.

One obvious caveat is the fact that only a limited number of doses were tested at only one time-point. This is particularly relevant as one study showed that amylin increased ERK activation

5- and 45-minutes following treatment, but not 15-minutes following amylin administration69. The

PRAM dose used for the ERK phosphorylation assay were chosen based on results of previous findings in our lab indicating the therapeutic effects of PRAM signaling at a concentration of

250nM130. These effects, however, were shown for PRAMs ability to reduce endogenous ROS levels, not signaling. Thus, proper dose-effect and time-course experiments have to be carried out to determine optimal ERK phosphorylation conditions.

The lack of expected increase in ERK phosphorylation following PRAM treatment in

AMY3 over-expressing cells compared to wild type cells may also be explained by the fact that levels of CalcR were equivalent between the two. Additionally, while alternative splicing of the

CalcR cannot explain the lack of over-expression of the CalcR by western blot, it could explain the lack of ERK phosphorylation as CalcRα is the only isoform that has been implicated in ERK phosphorylation108,117. Future studies should determine the splice variant types of the CalcR expressed in these cells to further clarify these aspects.

Lastly, another aspect that could potentially explain the lack of ERK activation is the dimerization of RAMPs observed in the western blots. Studies have indicated a 1:1 RAMP- receptor stoichiometry, suggesting that RAMP dimerization may serve as a regulatory mechanism limiting RAMP availability and functionality143. The use of co-immunoprecipitation and non- denaturing reagents investigating the levels of CalcR and RAMP3 expression, as well as the size of the receptor complex would determine 1) if the CalcR and RAMP3 are interacting and 2) if

RAMP3 is dimerizing.

While these cell lines may aid in understanding signaling mechanisms related to amylin doses as well as the ability of Aß to signal through each amylin receptor, it will not be able to fully clarify the role of these amylin receptors within a full metabolic dysfunction profile such as that observed in diabetes. This is primarily due to the fact that it is difficult to mimic a diabetic-like

55 environment in vitro. This said, studies in these cells using models of diabetes such as chronic treatment with high glucose may be able to provide some important insights.

4.4 – Concluding Remarks

The results of these studies indicate changes in the genetic expression of different specific amylin receptor components in response to high fat diet, differences due to sex, and differences in expression across brain regions. This study demonstrated the presence of amylin receptor components in the hippocampus and the hypothalamus but not in the cortex, given the low CalcR expression in this region. Together this work provides preliminary insight into potential relationships between amylin and metabolic stress and potential explanations for the opposing sex differences observed regarding metabolic dysfunction in males and AD development in females.

All of these conclusions, however, must be verified by studies investigating the interaction of

RAMPs with the CalcR via co-immunoprecipitation, along with a more in-depth verification of the diabetic phenotype. These data point toward avenues to pursue regarding potential involvement of RAMP3 and TRV4 signaling in AD pathogenesis. In order to address these questions, studies must be done in AD mouse models under diet conditions and genetic manipulation of these specific receptors. However, the production of the three cell lines over-expressing three amylin receptors;

AMY1, AMY3 or TRPV4 will be able to yield some preliminary answers toward these goals.

References

1 Association, A. s. 2018 Alzheimer's disease facts and figures. Alzheimer's & Dementia 14, 367-429 (2018). 2 Hebert, L. E., Weuve, J., Scherr, P. A. & Evans, D. A. Alzheimer disease in the United States (2010–2050) estimated using the 2010 census. Neurology 80, 1778-1783 (2013). 3 Barnes, J. et al. Alzheimer's disease first symptoms are age dependent: evidence from the NACC dataset. Alzheimer's & dementia 11, 1349-1357 (2015). 4 Masters, C. L. et al. Alzheimer's disease. Nature reviews. Disease primers 1, 15056, doi:10.1038/nrdp.2015.56 (2015). 5 Wu, L. et al. Early-onset familial Alzheimer's disease (EOFAD). The Canadian journal of neurological sciences. Le journal canadien des sciences neurologiques 39, 436-445 (2012). 6 van der Flier, W. M., Pijnenburg, Y. A., Fox, N. C. & Scheltens, P. Early-onset versus late-onset Alzheimer's disease: the case of the missing APOE varepsilon4 allele. The Lancet. Neurology 10, 280-288, doi:10.1016/s1474-4422(10)70306-9 (2011). 7 Golde, T. E., Eckman, C. B. & Younkin, S. G. Biochemical detection of Abeta isoforms: implications for pathogenesis, diagnosis, and treatment of Alzheimer's disease. Biochimica et biophysica acta 1502, 172-187, doi:10.1016/s0925-4439(00)00043-0 (2000). 8 LaFerla, F. M. & Oddo, S. Alzheimer's disease: Aβ, tau and synaptic dysfunction. Trends in molecular medicine 11, 170-176 (2005). 9 Smith, M. A., Rottkamp, C. A., Nunomura, A., Raina, A. K. & Perry, G. Oxidative stress in Alzheimer's disease. Biochimica et biophysica acta 1502, 139-144, doi:10.1016/s0925- 4439(00)00040-5 (2000). 10 Heneka, M. T. et al. Neuroinflammation in Alzheimer's disease. The Lancet. Neurology 14, 388-405, doi:10.1016/s1474-4422(15)70016-5 (2015). 11 Hoyer, S., Nitsch, R. & Oesterreich, K. Predominant abnormality in cerebral glucose utilization in late-onset dementia of the Alzheimer type: a cross-sectional comparison against advanced late-onset and incipient early-onset cases. Journal of Neural Transmission-Parkinson's Disease and Dementia Section 3, 1-14 (1991). 12 Niikura, T., Tajima, H. & Kita, Y. Neuronal cell death in Alzheimer's disease and a neuroprotective factor, humanin. Current neuropharmacology 4, 139-147 (2006). 13 Grundke-Iqbal, I. et al. Abnormal phosphorylation of the microtubule-associated protein tau (tau) in Alzheimer cytoskeletal pathology. Proceedings of the National Academy of Sciences of the United States of America 83, 4913-4917, doi:10.1073/pnas.83.13.4913 (1986). 14 Ballatore, C., Lee, V. M. & Trojanowski, J. Q. Tau-mediated neurodegeneration in Alzheimer's disease and related disorders. Nature reviews. Neuroscience 8, 663-672, doi:10.1038/nrn2194 (2007). 15 Mandelkow, E. M. & Mandelkow, E. Tau in Alzheimer's disease. Trends in cell biology 8, 425-427 (1998). 16 Haass, C., Kaether, C., Thinakaran, G. & Sisodia, S. Trafficking and proteolytic processing of APP. Cold Spring Harbor perspectives in medicine 2, a006270, doi:10.1101/cshperspect.a006270 (2012).

17 Nhan, H. S., Chiang, K. & Koo, E. H. The multifaceted nature of amyloid precursor protein and its proteolytic fragments: friends and foes. Acta neuropathologica 129, 1-19, doi:10.1007/s00401-014-1347-2 (2015). 18 Steinerman, J. R. et al. Distinct pools of beta-amyloid in Alzheimer disease-affected brain: a clinicopathologic study. Arch Neurol 65, 906-912, doi:10.1001/archneur.65.7.906 (2008). 19 Scheuner, D. et al. Secreted amyloid beta-protein similar to that in the senile plaques of Alzheimer's disease is increased in vivo by the presenilin 1 and 2 and APP mutations linked to familial Alzheimer's disease. Nature medicine 2, 864-870 (1996). 20 De Strooper, B. et al. Deficiency of presenilin-1 inhibits the normal cleavage of amyloid precursor protein. Nature 391, 387-390, doi:10.1038/34910 (1998). 21 Citron, M. et al. Mutant presenilins of Alzheimer's disease increase production of 42- residue amyloid beta-protein in both transfected cells and transgenic mice. Nature medicine 3, 67-72 (1997). 22 Duff, K. et al. Increased amyloid-beta42(43) in brains of mice expressing mutant presenilin 1. Nature 383, 710-713, doi:10.1038/383710a0 (1996). 23 Tomita, T. et al. The presenilin 2 mutation (N141I) linked to familial Alzheimer disease (Volga German families) increases the secretion of amyloid beta protein ending at the 42nd (or 43rd) residue. Proceedings of the National Academy of Sciences of the United States of America 94, 2025-2030, doi:10.1073/pnas.94.5.2025 (1997). 24 Haass, C. & Selkoe, D. J. Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid beta-peptide. Nature reviews. Molecular cell biology 8, 101- 112, doi:10.1038/nrm2101 (2007). 25 Cline, E. N., Bicca, M. A., Viola, K. L. & Klein, W. L. The Amyloid-beta Oligomer Hypothesis: Beginning of the Third Decade. Journal of Alzheimer's disease : JAD 64, S567-s610, doi:10.3233/jad-179941 (2018). 26 Viola, K. L. & Klein, W. L. Amyloid beta oligomers in Alzheimer's disease pathogenesis, treatment, and diagnosis. Acta neuropathologica 129, 183-206, doi:10.1007/s00401-015- 1386-3 (2015). 27 de la Monte, S. M. Type 3 diabetes is sporadic Alzheimers disease: mini-review. European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology 24, 1954-1960, doi:10.1016/j.euroneuro.2014.06.008 (2014). 28 Stozicka, Z., Zilka, N. & Novak, M. Risk and protective factors for sporadic Alzheimer's disease. Acta virologica 51, 205-222 (2007). 29 Cheng, G., Huang, C., Deng, H. & Wang, H. Diabetes as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies. Internal medicine journal 42, 484-491, doi:10.1111/j.1445-5994.2012.02758.x (2012). 30 Garcia-Lara, J. M., Aguilar-Navarro, S., Gutierrez-Robledo, L. M. & Avila-Funes, J. A. The metabolic syndrome, diabetes, and Alzheimer's disease. Revista de investigacion clinica; organo del Hospital de Enfermedades de la Nutricion 62, 343-349 (2010). 31 Folch, J. et al. Metabolic basis of sporadic Alzeimer's disease. role of hormones related to energy metabolism. Current pharmaceutical design 19, 6739-6748 (2013). 32 Leibson, C. L. et al. Risk of dementia among persons with diabetes mellitus: a population-based cohort study. American journal of epidemiology 145, 301-308 (1997).

33 Kandimalla, R., Thirumala, V. & Reddy, P. H. Is Alzheimer's disease a Type 3 Diabetes? A critical appraisal. Biochimica et biophysica acta. Molecular basis of disease 1863, 1078-1089, doi:10.1016/j.bbadis.2016.08.018 (2017). 34 Kautzky-Willer, A., Harreiter, J. & Pacini, G. Sex and Gender Differences in Risk, Pathophysiology and Complications of Type 2 Diabetes Mellitus. Endocr Rev 37, 278- 316, doi:10.1210/er.2015-1137 (2016). 35 Palermo, A., Maggi, D., Maurizi, A. R., Pozzilli, P. & Buzzetti, R. Prevention of type 2 diabetes mellitus: is it feasible? Diabetes/metabolism research and reviews 30 Suppl 1, 4-12, doi:10.1002/dmrr.2513 (2014). 36 DeFronzo, R. A., Bonadonna, R. C. & Ferrannini, E. Pathogenesis of NIDDM: a balanced overview. Diabetes care 15, 318-368 (1992). 37 U.K. prospective diabetes study 16. Overview of 6 years' therapy of type II diabetes: a progressive disease. U.K. Prospective Diabetes Study Group. Diabetes 44, 1249-1258 (1995). 38 Grizzanti, J., Corrigan, R., Servizi, S. & Casadesus, G. Amylin Signaling in Diabetes and Alzheimer's Disease: Therapy or Pathology? (2019). 39 Awad, N., Gagnon, M. & Messier, C. The relationship between impaired glucose tolerance, type 2 diabetes, and cognitive function. Journal of clinical and experimental neuropsychology 26, 1044-1080, doi:10.1080/13803390490514875 (2004). 40 Schwartz, M. W. et al. Insulin binding to brain capillaries is reduced in genetically obese, hyperinsulinemic Zucker rats. Peptides 11, 467-472 (1990). 41 Wallum, B. et al. Cerebrospinal Fluid Insulin Levels Increase During Intravenous Insulin Infusions in Man*. The Journal of Clinical Endocrinology & Metabolism 64, 190-194 (1987). 42 Gil-Bea, F. J. et al. Insulin levels are decreased in the cerebrospinal fluid of women with prodomal Alzheimer's disease. Journal of Alzheimer's Disease 22, 405-413 (2010). 43 Ghasemi, R., Haeri, A., Dargahi, L., Mohamed, Z. & Ahmadiani, A. Insulin in the brain: sources, localization and functions. Mol Neurobiol 47, 145-171, doi:10.1007/s12035-012- 8339-9 (2013). 44 Berent, S. et al. Neuropsychological function and cerebral glucose utilization in isolated memory impairment and Alzheimer's disease. Journal of psychiatric research 33, 7-16 (1999). 45 Willette, A. A. et al. Association of Insulin Resistance With Cerebral Glucose Uptake in Late Middle-Aged Adults at Risk for Alzheimer Disease. JAMA neurology 72, 1013- 1020, doi:10.1001/jamaneurol.2015.0613 (2015). 46 de la Monte, S. M., Longato, L., Tong, M. & Wands, J. R. Insulin resistance and neurodegeneration: roles of obesity, type 2 diabetes mellitus and non-alcoholic steatohepatitis. Current opinion in investigational drugs (London, England : 2000) 10, 1049-1060 (2009). 47 de la Monte, S. M. & Wands, J. R. Review of insulin and insulin-like growth factor expression, signaling, and malfunction in the central nervous system: relevance to Alzheimer's disease. Journal of Alzheimer's disease : JAD 7, 45-61 (2005). 48 Grillo, C. A. et al. Hippocampal insulin resistance impairs spatial learning and synaptic plasticity. Diabetes 64, 3927-3936 (2015).

49 Skeberdis, V. A., Lan, J.-y., Zheng, X., Zukin, R. S. & Bennett, M. V. Insulin promotes rapid delivery of N-methyl-D-aspartate receptors to the cell surface by exocytosis. Proceedings of the National Academy of Sciences 98, 3561-3566 (2001). 50 Zhao, W. Q. & Alkon, D. L. Role of insulin and insulin receptor in learning and memory. Molecular and cellular endocrinology 177, 125-134 (2001). 51 Watson, G. S. & Craft, S. The role of insulin resistance in the pathogenesis of Alzheimer’s disease. CNS drugs 17, 27-45 (2003). 52 Luchsinger, J. A., Tang, M. X., Shea, S. & Mayeux, R. Hyperinsulinemia and risk of Alzheimer disease. Neurology 63, 1187-1192, doi:10.1212/01.wnl.0000140292.04932.87 (2004). 53 Medina, M., Garrido, J. J. & Wandosell, F. G. Modulation of GSK-3 as a Therapeutic Strategy on Tau Pathologies. Frontiers in molecular neuroscience 4, 24, doi:10.3389/fnmol.2011.00024 (2011). 54 Zhao, W. Q. et al. Insulin receptor dysfunction impairs cellular clearance of neurotoxic oligomeric a{beta}. The Journal of biological chemistry 284, 18742-18753, doi:10.1074/jbc.M109.011015 (2009). 55 Pearson-Leary, J. & McNay, E. C. Intrahippocampal administration of amyloid-β 1-42 oligomers acutely impairs spatial working memory, insulin signaling, and hippocampal metabolism. Journal of Alzheimer's Disease 30, 413-422 (2012). 56 Zhang, Y. et al. Amyloid-β induces hepatic insulin resistance by activating JAK2/STAT3/SOCS-1 signaling pathway. Diabetes 61, 1434-1443 (2012). 57 Shiiki, T. et al. Brain insulin impairs amyloid-β (1-40) clearance from the brain. Journal of Neuroscience 24, 9632-9637 (2004). 58 Messier, C. & Teutenberg, K. The role of insulin, insulin growth factor, and insulin- degrading enzyme in brain aging and Alzheimer's disease. Neural plasticity 12, 311-328 (2005). 59 Qiu, W. Q. et al. Insulin-degrading enzyme regulates extracellular levels of amyloid β- protein by degradation. Journal of Biological Chemistry 273, 32730-32738 (1998). 60 Bennett, R. G., Hamel, F. G. & Duckworth, W. C. An insulin-degrading enzyme inhibitor decreases amylin degradation, increases amylin-induced cytotoxicity, and increases amyloid formation in insulinoma cell cultures. Diabetes 52, 2315-2320 (2003). 61 Hwang, J. J., Chan, J. L., Ntali, G., Malkova, D. & Mantzoros, C. S. Leptin does not directly regulate the pancreatic hormones amylin and pancreatic polypeptide Interventional studies in humans. Diabetes care 31, 945-951 (2008). 62 Hay, D. L., Chen, S., Lutz, T. A., Parkes, D. G. & Roth, J. D. Amylin: pharmacology, physiology, and clinical potential. Pharmacological reviews 67, 564-600 (2015). 63 Hull, R. L. et al. Increased dietary fat promotes islet amyloid formation and β-cell secretory dysfunction in a transgenic mouse model of islet amyloid. Diabetes 52, 372-379 (2003). 64 Wang, J. et al. Overfeeding rapidly induces leptin and insulin resistance. Diabetes 50, 2786-2791 (2001). 65 Fernandes-Santos, C. et al. Amylin acts in the central nervous system to increase sympathetic nerve activity. Endocrinology 154, 2481-2488 (2013). 66 Barth, S. W., Riediger, T., Lutz, T. A. & Rechkemmer, G. Peripheral amylin activates circumventricular organs expressing calcitonin receptor a/b subtypes and receptor- activity modifying proteins in the rat. Brain research 997, 97-102 (2004).

67 Lutz, T., Mollet, A., Rushing, P., Riediger, T. & Scharrer, E. The anorectic effect of a chronic peripheral infusion of amylin is abolished in area postrema/nucleus of the solitary tract (AP/NTS) lesioned rats. International journal of obesity 25, 1005 (2001). 68 Mollet, A., Gilg, S., Riediger, T. & Lutz, T. A. Infusion of the amylin antagonist AC 187 into the area postrema increases food intake in rats. Physiology & behavior 81, 149-155 (2004). 69 Lutz, T. A. et al. Amylin selectively signals onto POMC neurons in the arcuate nucleus of the hypothalamus. Diabetes 67, 805-817 (2018). 70 Riediger, T., Zuend, D., Becskei, C. & Lutz, T. A. The anorectic hormone amylin contributes to feeding-related changes of neuronal activity in key structures of the gut- brain axis. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 286, R114-R122 (2004). 71 Le Foll, C. et al. Amylin-induced central IL-6 production enhances ventromedial hypothalamic leptin signaling. Diabetes 64, 1621-1631 (2015). 72 Roth, J. D. et al. Leptin responsiveness restored by amylin agonism in diet-induced obesity: evidence from nonclinical and clinical studies. Proceedings of the National Academy of Sciences 105, 7257-7262 (2008). 73 Levin, B. E. & Lutz, T. A. Amylin and leptin: co-regulators of energy homeostasis and neuronal development. Trends in Endocrinology & Metabolism 28, 153-164 (2017). 74 Mollet, A., Meier, S., Riediger, T. & Lutz, T. A. Histamine H1 receptors in the ventromedial hypothalamus mediate the anorectic action of the pancreatic hormone amylin. Peptides 24, 155-158 (2003). 75 Sakata, T. et al. Blockade of the histamine H1-receptor in the rat ventromedial hypothalamus and feeding elicitation. Brain research 441, 403-407 (1988). 76 Seth, R., Terry, D. E., Parrish, B., Bhatt, R. & Overton, J. M. Amylin–leptin coadministration stimulates central histaminergic signaling in rats. Brain research 1442, 15-24 (2012). 77 Mollet, A. et al. Histamine H1 receptors mediate the anorectic action of the pancreatic hormone amylin. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 281, R1442-R1448 (2001). 78 Luo, X., McGregor, G., Irving, A. J. & Harvey, J. Leptin induces a novel form of NMDA receptor-dependent LTP at hippocampal temporoammonic-CA1 synapses. eNeuro 2 (2015). 79 McGregor, G. & Harvey, J. Leptin regulation of synaptic function at hippocampal TA- CA1 and SC-CA1 synapses: implications for health and disease. Neurochemical research 44, 650-660 (2019). 80 Bliss, T. V. & Collingridge, G. L. A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361, 31 (1993). 81 McGuire, M. J. & Ishii, M. Leptin dysfunction and Alzheimer’s disease: evidence from cellular, animal, and human studies. Cellular and molecular neurobiology 36, 203-217 (2016). 82 Lee, E. B. Obesity, leptin, and Alzheimer's disease. Annals of the New York Academy of Sciences 1243, 15 (2011). 83 Greco, S. J. et al. Leptin reduces pathology and improves memory in a transgenic mouse model of Alzheimer's disease. Journal of Alzheimer's Disease 19, 1155-1167 (2010).

84 Jaikaran, E. T. & Clark, A. Islet amyloid and type 2 diabetes: from molecular misfolding to islet pathophysiology. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease 1537, 179-203 (2001). 85 Westermark, P. & Wilander, E. The influence of amyloid deposits on the islet volume in maturity onset diabetes mellitus. Diabetologia 15, 417-421 (1978). 86 Banks, W. A. & Kastin, A. J. Differential permeability of the blood–brain barrier to two pancreatic peptides: insulin and amylin. Peptides 19, 883-889 (1998). 87 Jackson, K. et al. Amylin deposition in the brain: a second amyloid in Alzheimer disease? Annals of neurology 74, 517-526 (2013). 88 Srodulski, S. et al. Neuroinflammation and neurologic deficits in diabetes linked to brain accumulation of amylin. Molecular neurodegeneration 9, 30 (2014). 89 Verma, N. et al. Intraneuronal Amylin Deposition, Peroxidative Membrane Injury and Increased IL-1β Synthesis in Brains of Alzheimer’s Disease Patients with Type-2 Diabetes and in Diabetic HIP Rats. Journal of Alzheimer's Disease 53, 259-272 (2016). 90 Oskarsson, M. E. et al. In vivo seeding and cross-seeding of localized amyloidosis: a molecular link between type 2 diabetes and Alzheimer disease. The American journal of pathology 185, 834-846 (2015). 91 Ono, K. et al. Exogenous amyloidogenic proteins function as seeds in amyloid β-protein aggregation. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease 1842, 646-653 (2014). 92 Qiu, W. Q. & Zhu, H. Amylin and its analogs: a friend or foe for the treatment of Alzheimer's disease? Frontiers in aging neuroscience 6 (2014). 93 Cummings, J. L., Morstorf, T. & Zhong, K. Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimer's research & therapy 6, 37 (2014). 94 Hyde, C. et al. Evolution of the evidence on the effectiveness and cost-effectiveness of acetylcholinesterase inhibitors and memantine for Alzheimer's disease: systematic review and economic model. Age and ageing 42, 14-20 (2012). 95 Westermark, P., Engström, U., Johnson, K. H., Westermark, G. T. & Betsholtz, C. Islet amyloid polypeptide: pinpointing amino acid residues linked to amyloid fibril formation. Proceedings of the National Academy of Sciences 87, 5036-5040 (1990). 96 Hollander, P. A. et al. Pramlintide as an adjunct to insulin therapy improves long-term glycemic and weight control in patients with type 2 diabetes. Diabetes care 26, 784-790 (2003). 97 Wang, H., Ridgway, Z., Cao, P., Ruzsicska, B. & Raleigh, D. P. Analysis of the ability of pramlintide to inhibit amyloid formation by human islet amyloid polypeptide reveals a balance between optimal recognition and reduced amyloidogenicity. Biochemistry 54, 6704-6711, doi:10.1021/acs.biochem.5b00567 (2015). 98 Qiu, W. Q. et al. Positive association between plasma amylin and cognition in a homebound elderly population. Journal of Alzheimer's Disease 42, 555-563 (2014). 99 Qiu, W. Q. et al. Association between amylin and amyloid-β peptides in plasma in the context of apolipoprotein E4 allele. PloS one 9, e88063 (2014). 100 Adler, B. L. et al. Neuroprotective effects of the amylin analogue pramlintide on Alzheimer's disease pathogenesis and cognition. Neurobiology of aging 35, 793-801 (2014).

101 Zhu, H. et al. Intraperitoneal injection of the pancreatic peptide amylin potently reduces behavioral impairment and brain amyloid pathology in murine models of Alzheimer's disease. Molecular psychiatry 20, 252 (2015). 102 Zhu, H. et al. Amylin receptor ligands reduce the pathological cascade of Alzheimer's disease. Neuropharmacology 119, 170-181 (2017). 103 Wang, E. et al. Amylin Treatment Reduces Neuroinflammation and Ameliorates Abnormal Patterns of Gene Expression in the Cerebral Cortex of an Alzheimer’s Disease Mouse Model. Journal of Alzheimer's Disease 56, 47-61 (2017). 104 Soudy, R. et al. Cyclic AC253, a novel amylin receptor antagonist, improves cognitive deficits in a mouse model of Alzheimer's disease. Alzheimer's & dementia (New York, N. Y.) 3, 44-56, doi:10.1016/j.trci.2016.11.005 (2017). 105 Lim, Y.-A., Ittner, L. M., Lim, Y. L. & Götz, J. Human but not rat amylin shares neurotoxic properties with Aβ42 in long-term hippocampal and cortical cultures. FEBS letters 582, 2188-2194 (2008). 106 Jhamandas, J. H. & MacTavish, D. Antagonist of the amylin receptor blocks beta- amyloid toxicity in rat cholinergic basal forebrain neurons. J Neurosci 24, 5579-5584, doi:10.1523/jneurosci.1051-04.2004 (2004). 107 Jhamandas, J. H. et al. Actions of β-amyloid protein on human neurons are expressed through the amylin receptor. The American journal of pathology 178, 140-149 (2011). 108 Fu, W. et al. Amyloid β (Aβ) peptide directly activates amylin-3 receptor subtype by triggering multiple intracellular signaling pathways. Journal of Biological Chemistry 287, 18820-18830 (2012). 109 Jhamandas, J. H. & Mactavish, D. beta-Amyloid protein (Abeta) and human amylin regulation of apoptotic genes occurs through the amylin receptor. Apoptosis : an international journal on programmed cell death 17, 37-47, doi:10.1007/s10495-011- 0656-3 (2012). 110 Kimura, R., MacTavish, D., Yang, J., Westaway, D. & Jhamandas, J. H. Pramlintide Antagonizes Beta Amyloid (Aβ)-and Human Amylin-Induced Depression of Hippocampal Long-Term Potentiation. Molecular neurobiology 54, 748-754 (2017). 111 Kimura, R., MacTavish, D., Yang, J., Westaway, D. & Jhamandas, J. H. Beta amyloid- induced depression of hippocampal long-term potentiation is mediated through the amylin receptor. Journal of Neuroscience 32, 17401-17406 (2012). 112 Christopoulos, G. et al. Multiple amylin receptors arise from receptor activity-modifying protein interaction with the calcitonin receptor gene product. Molecular pharmacology 56, 235-242 (1999). 113 Tilakaratne, N., Christopoulos, G., Zumpe, E. T., Foord, S. M. & Sexton, P. M. Amylin receptor phenotypes derived from human calcitonin receptor/RAMP coexpression exhibit pharmacological differences dependent on receptor isoform and host cell environment. Journal of Pharmacology and Experimental Therapeutics 294, 61-72 (2000). 114 Hay, D. L., Christopoulos, G., Christopoulos, A., Poyner, D. R. & Sexton, P. M. Pharmacological discrimination of calcitonin receptor: receptor activity-modifying protein complexes. Molecular pharmacology 67, 1655-1665 (2005). 115 Poyner, D. R. et al. International Union of Pharmacology. XXXII. The mammalian calcitonin gene-related peptides, adrenomedullin, amylin, and calcitonin receptors. Pharmacological reviews 54, 233-246 (2002).

116 Ueda, T., Ugawa, S., Saishin, Y. & Shimada, S. Expression of receptor-activity modifying protein (RAMP) mRNAs in the mouse brain. Molecular brain research 93, 36-45 (2001). 117 Morfis, M. et al. Receptor activity-modifying proteins differentially modulate the G protein-coupling efficiency of amylin receptors. Endocrinology 149, 5423-5431 (2008). 118 Gingell, J. J., Burns, E. R. & Hay, D. L. Activity of pramlintide, rat and human amylin but not Aβ1–42 at human amylin receptors. Endocrinology 155, 21-26 (2014). 119 Zhang, N. et al. Multiple target of hAmylin on rat primary hippocampal neurons. Neuropharmacology 113, 241-251 (2017). 120 Arundine, M. & Tymianski, M. Molecular mechanisms of calcium-dependent neurodegeneration in excitotoxicity. Cell calcium 34, 325-337 (2003). 121 Sama, D. M. & Norris, C. M. Calcium dysregulation and neuroinflammation: discrete and integrated mechanisms for age-related synaptic dysfunction. Ageing research reviews 12, 982-995, doi:10.1016/j.arr.2013.05.008 (2013). 122 Magi, S. et al. Intracellular Calcium Dysregulation: Implications for Alzheimer's Disease. BioMed research international 2016, 6701324, doi:10.1155/2016/6701324 (2016). 123 Arruda, A. P. & Hotamisligil, G. S. Calcium Homeostasis and Organelle Function in the Pathogenesis of Obesity and Diabetes. Cell Metab 22, 381-397, doi:10.1016/j.cmet.2015.06.010 (2015). 124 Casas, S., Novials, A., Reimann, F., Gomis, R. & Gribble, F. M. Calcium elevation in mouse pancreatic beta cells evoked by extracellular human islet amyloid polypeptide involves activation of the mechanosensitive ion channel TRPV4. Diabetologia 51, 2252- 2262, doi:10.1007/s00125-008-1111-z (2008). 125 Fonseca, V. A. Defining and characterizing the progression of type 2 diabetes. Diabetes Care 32 Suppl 2, S151-156, doi:10.2337/dc09-S301 (2009). 126 Johnson, M. D. et al. Early postnatal amylin treatment enhances hypothalamic leptin signaling and neural development in the selectively bred diet-induced obese rat. American journal of physiology. Regulatory, integrative and comparative physiology 311, R1032-r1044, doi:10.1152/ajpregu.00326.2016 (2016). 127 Trevaskis, J. L., Parkes, D. G. & Roth, J. D. Insights into amylin–leptin synergy. Trends in Endocrinology & Metabolism 21, 473-479 (2010). 128 Guler, A. D. et al. Heat-evoked activation of the ion channel, TRPV4. J Neurosci 22, 6408-6414, doi:20026679 (2002). 129 McGann, K. P., Marion, G. S., Camp, L. & Spangler, J. G. The influence of gender and race on mean body temperature in a population of healthy older adults. Archives of family medicine 2, 1265-1267 (1993). 130 Patrick, S. et al. Neuroprotective Effects of the Amylin Analog, Pramlintide, on Alzheimer's Disease Are Associated with Oxidative Stress Regulation Mechanisms. Journal of Alzheimer's disease : JAD 69, 157-168, doi:10.3233/jad-180421 (2019). 131 Perez-Gonzalez, R. et al. Leptin gene therapy attenuates neuronal damages evoked by amyloid-β and rescues memory deficits in APP/PS1 mice. Gene therapy 21, 298 (2014). 132 Dong, Y., van der Walt, N., Pennington, K. A. & Yallampalli, C. Impact of adrenomedullin blockage on lipid metabolism in female mice exposed to high-fat diet. Endocrine, doi:10.1007/s12020-019-01927-8 (2019).

133 Liberini, C. G. et al. Amylin receptor components and the leptin receptor are co- expressed in single rat area postrema neurons. The European journal of neuroscience 43, 653-661, doi:10.1111/ejn.13163 (2016). 134 Liu, M. et al. TRPV4 Inhibition Improved Myelination and Reduced Glia Reactivity and Inflammation in a Cuprizone-Induced Mouse Model of Demyelination. Frontiers in cellular neuroscience 12, 392, doi:10.3389/fncel.2018.00392 (2018). 135 Hong, Z. et al. Enhanced Oxidative Stress Is Responsible for TRPV4-Induced Neurotoxicity. Frontiers in cellular neuroscience 10, 232, doi:10.3389/fncel.2016.00232 (2016). 136 Dalvi, P. S. et al. High fat induces acute and chronic inflammation in the hypothalamus: effect of high-fat diet, palmitate and TNF-alpha on appetite-regulating NPY neurons. International journal of obesity (2005) 41, 149-158, doi:10.1038/ijo.2016.183 (2017). 137 Cavaliere, G. et al. Long Feeding High-Fat Diet Induces Hypothalamic Oxidative Stress and Inflammation, and Prolonged Hypothalamic AMPK Activation in Rat Animal Model. Frontiers in physiology 9, 818, doi:10.3389/fphys.2018.00818 (2018). 138 Bai, J. Z. & Lipski, J. Involvement of TRPV4 channels in Abeta(40)-induced hippocampal cell death and astrocytic Ca(2+) signalling. Neurotoxicology 41, 64-72, doi:10.1016/j.neuro.2014.01.001 (2014). 139 Flahaut, M., Rossier, B. C. & Firsov, D. Respective roles of calcitonin receptor-like receptor (CRLR) and receptor activity-modifying proteins (RAMP) in cell surface expression of CRLR/RAMP heterodimeric receptors. The Journal of biological chemistry 277, 14731-14737, doi:10.1074/jbc.M112084200 (2002). 140 Olver, T. D. et al. Insulin-Mediated Vasodilation in Cerebral Arteries is Impaired in Obese Rats with Type 2 Diabetes. The FASEB Journal 30, 1203.1205-1203.1205 (2016). 141 Brain, S., Williams, T., Tippins, J., Morris, H. & MacIntyre, I. Calcitonin gene-related peptide is a potent vasodilator. Nature 313, 54 (1985). 142 Kiss, T. Small nucleolar RNA-guided post-transcriptional modification of cellular RNAs. The EMBO journal 20, 3617-3622 (2001). 143 Sexton, P. M., Albiston, A., Morfis, M. & Tilakaratne, N. Receptor activity modifying proteins. Cellular signalling 13, 73-83 (2001).