Investigating the Effect of Scyllo-Inositol Treatment on the Brain in a Mouse Model of Alzheimer’S Disease

Investigating the Effect of scyllo-Inositol Treatment on the Brain in a Mouse Model of Alzheimer’s Disease

Qingda Hu

A thesis submitted in conformity with the requirements for the degree of Master’s of Science Department of Laboratory Medicine and Pathobiology University of Toronto

©Copyright by Qingda Hu 2016

Investigating the Effect of scyllo-Inositol Treatment on the Brain in a Mouse Model of Alzheimer’s Disease

Qingda Hu

Master’s of Science

Department of Laboratory Medicine and Pathobiology University of Toronto

2016

Abstract scyllo-Inositol is a potential therapeutic for the treatment of agitation and aggression in patients with Alzheimer’s disease. scyllo-Inositol reduces aggregation of beta-amyloid peptide, reduces amyloid plaques, and reduces myo-inositol concentration in the brain. The change in gene expression in the brain of TgCRND8 mice after scyllo-inositol treatment has not been previously investigated. I hypothesized that scyllo-inositol treatment would cause changes in expression of genes involved in neurodegenerative diseases and neuropsychiatric disorders. Affymetrix gene expression microarrays were used to analyze changes in the hippocampus and cerebral cortex of

TgCRND8 mice as well as in non-transgenic littermates after 30 days of scyllo-inositol treatment. Analysis of the data with the Database for Annotation, Visualization and Integrated

Discovery and Ingenuity Pathways Analysis program showed gene expression changes in synaptic function, calcium, dopamine receptor, glutamate receptor, and myo-inositol signalling pathways. In light of these results, I concluded that my hypothesis was correct.

Acknowledgments

I would like to thank Dr. JoAnne McLaurin for her guidance and support throughout my Master’s degree. This project would not have been possible without the assistance of Mary Brown. I would also like to thank all the other members of the McLaurin laboratory for their feedback and discussion. I would like to thank the members of my graduate advisory committee, Dr. Isabelle Aubert and Dr. Krista Lanctôt, for their assistance and feedback.

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Table of Contents

Acknowledgments...... iii

Table of Contents ...... iv

List of Tables ...... vi

List of Figures ...... vii

List of Abbreviations ...... ix

Chapter 1 Introduction ...... 1

1.1 Alzheimer’s disease ...... 1

1.2 Neuropsychiatric symptoms - Agitation and aggression ...... 3

1.3 scyllo-Inositol ...... 6

Chapter 2 Rationale, Objectives, and Hypothesis ...... 11

2.1 Rationale ...... 11

2.2 Hypothesis...... 11

2.3 Specific aims ...... 12

Chapter 3 Materials and Methods ...... 13

3.1 Animals ...... 13

3.2 RNA isolation ...... 13

3.3 Affymetrix microarray ...... 14

3.4 Functional clustering and pathway analysis ...... 15

3.5 RT-qPCR...... 16

3.6 Primer design ...... 17

3.7 Analysis of qPCR data ...... 21

Chapter 4 Results ...... 23

4.1 Effect of scyllo-inositol treatment in TgCRND8 mouse model of Alzheimer’s disease ...23 iv

4.1.1 Hippocampal microarray comparison between scyllo-inositol treated and untreated 100 day old TgCRND8 mice ...... 25

4.1.2 Cortical microarray comparison between scyllo-inositol treated and untreated 100 day old TgCRND8 mice ...... 39

4.1.3 Primer design, quality control, and choosing internal control for qPCR ...... 45

4.1.4 qPCR comparison between scyllo-inositol treated and untreated 100 day old TgCRND8 mice ...... 52

4.1.5 qPCR comparison between scyllo-inositol treated and untreated 150 day old TgCRND8 mice ...... 55

4.1.6 Hippocampal microarray comparison between scyllo-inositol treated and untreated 200 day old TgCRND8 mice ...... 60

4.1.7 Cortical microarray comparison between scyllo-inositol treated and untreated 200 day old TgCRND8 mice ...... 69

4.2 Investigating the Aβ dependent and Aβ independent effects of scyllo-inositol treatment ...... 71

4.2.1 Hippocampal microarray comparison between 200 day old TgCRND8 mice and non-transgenic littermates ...... 72

4.2.2 Cortical microarray comparison between 200 day old TgCRND8 mice and non-transgenic littermates ...... 80

4.2.3 Hippocampal microarray comparison between scyllo-inositol treated and untreated 200 day old non-transgenic littermates ...... 89

4.2.4 Cortical microarray comparison between scyllo-inositol treated and untreated 200 day old non-transgenic littermates ...... 95

Chapter 5 Discussion ...... 101

Chapter 6 Conclusion and future directions...... 106

6.1 Conclusion ...... 106

6.2 Future directions ...... 106

References or Bibliography ...... 108

List of Tables

Table 3.1 The default run method for standard comparative Ct using SYBR Green 17 detection with a melt curve Table 3.2 List of all the primers that were used in this thesis 18 Table 4.1 List of top enriched clusters identified by DAVID in the comparison of 30 hippocampal samples from 100 day old TgCRND8 mice treated and untreated with scyllo-inositol Table 4.2 Top upstream regulators identified in the IPA core analysis for hippocampal 39 comparison of treated and untreated 100 day old TgCRND8 mice Table 4.3 List of top enriched clusters identified by DAVID in the cortical comparison 42 of treated and untreated 100 day old TgCRND8 samples Table 4.4 Top upstream regulators identified in the IPA core analysis for cortical 44 comparison of treated and untreated 100 day old TgCRND8 mice. Table 4.5 The efficiency and melt curve peak temperature for all of the primers used 49 Table 4.6 Sample average Ct values from rt-qPCR of all 8 control genes of 10 samples 51 Table 4.7 Analysis by BestKeeper of the data from Table 4.6 51 Table 4.8 Clustering of annotation from DAVID of hippocampal comparison of 66 treated and untreated 200 day old TgCRND8 Table 4.9 The 19 probe sets and extra information for the cortical comparison of 200 70 day TgCRND8 mice Table 4.10 List of top enriched clusters identified by DAVID in the hippocampal 76 comparison of 200 day old TgCRND8 mice and non-transgenic littermates Table 4.11 List of top enriched clusters identified by DAVID for the common probe 80 sets between the treatment effect in 200 day old TgCRND8 and the transgene effect Table 4.12 List of top enriched clusters identified by DAVID in the cortical 84 comparison of 200 day old TgCRND8 mice and non-transgenic littermates Table 4.13 List of top enriched clusters identified by DAVID in the comparison of hippocampal samples from 200 day old non-transgenic mice treated and untreated with 92 scyllo-inositol Table 4.14 List of top enriched clusters identified by DAVID in the comparison of 98 hippocampal samples from 200 day old non-transgenic mice treated and untreated with scyllo-inositol

List of Figures

Figure 1.1 myo-Inositol signalling pathway 9 Figure 3.1 The settings used for Functional annotation clustering in DAVID 15 Figure 3.2 Settings for hierarchical clustering in Multiple Experiment Viewer (MeV) 22 Figure 4.1 Venn diagram for the top 4 clusters from DAVID annotation clustering for 31 hippocampal comparison in treated and untreated 100 day TgCRND8 mice Figure 4.2 Summary of IPA core analysis for hippocampal comparison of treated and 32 untreated 100 day old TgCRND8 mice Figure 4.3 The canonical pathways that were identified by IPA core analysis for 33 hippocampal comparison of treated and untreated 100 day old TgCRND8 mice Figure 4.4 RhoA signalling pathway for hippocampal comparison of treated and 34 untreated 100 day old TgCRND8 mice Figure 4.5 Visualization of RhoGDI signalling pathway in the core analysis for 35 hippocampal comparison of treated and untreated 100 day old TgCRND8 mice Figure 4.6 Visualization of glutamate receptor signalling pathway in the core analysis 36 for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice Figure 4.7 Role of NFAT in regulation of the immune response pathway for 37 hippocampal comparison of treated and untreated 100 day old TgCRND8 mice Figure 4.8 Visualization of Stathmin1 signalling pathway in the core analysis for 38 hippocampal comparison of treated and untreated 100 day old TgCRND8 mice Figure 4.9 Summary of IPA core analysis for cortical comparison of treated and 43 untreated 100 day old TgCRND8 mice Figure 4.10 Venn diagram showing common probe sets between the hippocampal and 44 cortical comparisons of scyllo-inositol treatment effect in 100 day old TgCRND8 mice Figure 4.11 Graph of the fold change of the common probe sets between the cortical 45 and hippocampal gene expression changes in 100 day old TgCRND8 treated with scyllo-inositol Figure 4.12 Sample standard curve plot used to calculate the efficiency 47 Figure 4.13 A sample melt curve plot showing only one peak 48 Figure 4.14 Agarose gel of PCR products for each primer pair 50 Figure 4.15 The fold difference in gene expression on the scyllo-inositol treated group 54 compared to the untreated littermates Figure 4.16 Hierarchical clustering of the RT-qPCR data with MeV for hippocampal 55 samples and cortical samples Figure 4.17 The fold difference in gene expression on the scyllo-inositol treated group 58 compared to the untreated control in 150 day old TgCRND8

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Figure 4.18 Hierarchical clustering of the RT-qPCR data with MeV for hippocampal 59 samples and cortical samples Figure 4.19 The hippocampal 100 and 150 day old TgCRND8 qPCR data 60 Figure 4.20 Summary of IPA core analysis for hippocampal comparison of treated and 67 untreated 200 day old TgCRND8 mice Figure 4.21Diagram showing common probe sets between hippocampal comparison 68 of 100 and 200 day old TgCRND8 mice treated and untreated Figure 4.22 Graph of the fold change of the common probe sets between the 100 and 68 200 day old hippocampal comparisons Figure 4.23 Venn diagram for the top clusters from DAVID annotation clustering 77 shown in Table 4.10 Figure 4.24 Summary of IPA core analysis for the hippocampal comparison of 200 78 day old TgCRND8 mice and non-transgenic littermates Figure 4.25 Venn diagram showing common probe sets between the hippocampal 79 comparison between treated and untreated 200 day old TgCRND8 mice and the hippocampal comparison of TgCRND8 mice with non-transgenic littermates Figure 4.26 The 144 probe sets that were common between the hippocampal treatment 79 effect in TgCRND8 mice and the hippocampal transgene effect between TgCRND8 and nontransgenic littermates Figure 4.27 Venn diagram for the top clusters from DAVID annotation clustering 85 shown in Table 4.12 Figure 4.28 Summary of IPA core analysis for hippocampal the hippocampal 86 comparison of 200 day old TgCRND8 mice and non-transgenic littermates Figure 4.29 Role of NFAT in regulation of the immune response pathway for cortical 87 comparison of TgCRND8 and non-transgenic littermates Figure 4.30 Venn diagram showing common probe sets between the hippocampal and 88 cortical comparisons of TgCRND8transgenic effect Figure 4.31 Graph of the fold change of the common probe sets between the cortical 88 and hippocampal comparisons of TgCRND8 mice compared to non-transgenic littermates Figure 4.32 Summary of IPA core analysis for hippocampal comparison of treated and 93 untreated 200 day old non-transgenic mice Figure 4.33 Visualization of the glutamate receptor signalling pathways from IPA core 94 analysis for hippocampal comparison of treated and untreated 200 day old non- transgenic mice Figure 4.34 Summary of IPA core analysis for cortical comparison of treated and 99 untreated 200 day old non-transgenic mice Figure 4.35 Graph of the fold change of the common probe sets between the cortical 90 and hippocampal comparisons of treated and untreated non-transgenic mice compared

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List of Abbreviations

AMPAR α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor APP amyloid precursor protein ARHGEF1 Rho guanine nucleotide exchange factor 1 Aβ beta-amyloid BDNF brain-derived neurotrophic factor CAMK Ca2+/calmodulin-dependent protein kinase CBP CREB binding protein CREB cAMP response elements binding CSF cerebral spinal fluid CTF C-terminal fragment DAG diacylglycerol DAVID Database for Annotation, Visualization and Integrated Discovery DNA deoxyribonucleic acid ERK extracellular signal-regulated kinase FDR false discover rate GABA gamma-Aminobutyric acid GLUL glutamine synthetase GPCR g-protein coupled receptor HTT huntingtin

IP3 myo-inositol 1,4,5-triphosphate IPA Ingenuity® Pathway Analysis KCNQ Potassium voltage-gated channel L-dopa L-3,4-dihydroxyphenylalanine LHX3 LIM homeobox 3 LTP long term potentiation MAPK mitogen-activated protein kinase MHC major histocompatibility complex NFAT nuclear factor of activated T-cells NMDR N-methyl-D-aspartate receptor

NPI-C neuropsychiatric inventory clinician NPS neuropsychiatric symptoms mTOR mammalian target of rapamycin PCR polymerase chain reaction PI3K phosphoinositide 3 PIP2 phosphatidylinositol 4, 5-bisphosphate PLC phospholipase C PPP1CB protein phosphatase 1 Catalytic Subunit Beta PSD95 post synaptic density protein 95 PTEN phosphatase and tensin homolog RAPGEF6 Rap guanine nucleotide exchange factor 6 RNA ribonucleic acid RRM RNA recognition motifs RT-qPCR reverse transcription real-time polymerase chain reaction SMIT sodium myo-inositol transporter THOP1 thimetoligopeptidase 1

Chapter 1 Introduction

1 Introduction

1.1 Alzheimer’s disease

Alzheimer’s disease is progressive neurodegenerative disease characterized by formation of amyloid plaques and neurofibrillary tangles in the brain, neuronal dysfunction and neuronal loss, and dementia (Hippius and Neundörfer, 2003). Alzheimer’s disease is the leading cause of dementia (Smetanin et al., 2010). Dementia is the loss of memory, judgment, and reasoning along with mood, behavioural changes and loss of ability to perform activities of daily living. Alzheimer’s disease currently has no cure. Some symptomatic treatments are available to improve quality of life for the patients. However, side effects and modest efficacy has plagued pharmacological treatment of cognitive, behavioural, and psychiatric symptoms. Our understanding of Alzheimer’s disease has made great strides since Alois Alzheimer published the description of his patient, August Deter in 1906 (Hippius and Neundörfer, 2003). In 1984, Glenner and Wong identified the Aβ peptides to be the major component of the amyloid plaques in patients. These peptides were generated through the cleavage of the amyloid precursor protein by β- and γ-secretases. Mutations in the amyloid precursor protein and subunits of the γ-secretase were found to be causes of inherited forms of Alzheimer’s disease. These familial cases of Alzheimer’s disease present much earlier than the sporadic cases, which do not have a single genetic cause. Although only a small portion of Alzheimer’s disease cases is familial, it shares many similarities with sporadic Alzheimer’s disease. This led to the formation of the amyloid hypothesis, which proposed that the accumulation of Aβ peptides is the driving force behind Alzheimer’s disease (Selkoe and Hardy, 2016).

Amyloid precursor protein is a type 1 transmembrane protein (Zheng and Koo, 2011). Degradation of amyloid precursor protein is accomplished by one of two pathways. The non- amyloidogenic pathway begins with cleavage by α-secretases to produce APPsα and APP-CTFα. The amyloidogenic processing pathway begins with β-secretase cleavage to produce APPsβ and APP-CTFβ fragments. The transmembrane fragments APP-CTFα and APP-CTFβ can then be

1 2 cleaved by γ-secretase. Cleavage of APP-CTFβ by γ-secretase produces Aβ peptides. The β- secretase responsible for cleavage of amyloid precursor protein in physiological conditions is BACE1 (Cai et al., 2001, Luo et al., 2001). Physiological α-secretase activity is mediated by ADAM10 (Kuhn et al., 2010). γ-Secretase is composed of presenilin, nicastrin, anterior pharynx defective 1, and presenilin enhancer (Edbauer et al., 2003). Soluble Aβ peptides accumulate and aggregate in the brain when there is an imbalance between the production and removal Aβ peptides (Selkoe and Hardy, 2016). Physiological removal of Aβ peptides occurs through perivascular or glymphatic clearance and degradation pathways. To date, attempts to increase clearance of Aβ peptides using immunotherapy or small molecules therapeutics have not stopped or reversed the disease (reviewed in Morrone et al., 2015). Pharmacological inhibition of the BACE1 and γ-secretase complex is problematic because these proteases cleave other proteins aside from amyloid precursor protein. BACE1 has a low affinity foramyloid precursor protein. The main BACE1 target appears to be neuregulin-1, which is important for myelination of peripheral nerves by Schwann cell during development (Hu et al., 2006; Willem et al., 2006). γ- Secretase cleaves more than 50 type I membrane proteins including Notch (Kopan and Ilagan, 2004). Nonselective inhibition of these secretases can result in undesirable outcomes, such as cancer (Vassar, 2014; Doody et al., 2013). Genetic mutations that increase the production of Aβ peptides cause familial Alzheimer’s disease. One example is the Swedish (K670N, M671L) mutation on the amyloid precursor protein at the β-secretase site (Haass et al., 1995). Mutation of the presenilins (PSEN1/2) or amyloid precursor protein mutations at the gamma secretase site such as the Indiana (V717F) mutation result in increased production of Aβ42 over Aβ40 (Tamaoka et al., 1994). Increasing theAβ42 to Aβ40 ratio alters the aggregation kinetics, increased synaptic dysfunction and neuronal cell death (Kuperstein et al., 2007). The amyloid hypothesis states that Aβ peptide production from processing of amyloid precursor protein drives Alzheimer’s disease. This process can be affected by genetic mutations, which cause familial Alzheimer’s disease. The accumulation and aggregation of Aβ peptides eventually leads to neuron dysfunction and cell death.

Neuronal dysfunction and cell death lead to functional impairments in Alzheimer’s disease (Morrison and Hof, 1997). Cholinergic deficits, such as reduction of acetylcholine, choline acetyl transferase, and high-affinity choline uptake, occur in the brains of Alzheimer’s disease patients and worsen with disease progression (Herholz et al., 2007; Iyo et al., 1997; Bohnen et al., 2005).

In Alzheimer’s disease, patients have approximately 50% loss of cholinergic neurons at the onset of symptoms (Francis et al., 1999; Bowen et al., 1982; Davis et al., 1999). Glutamatergic dysfunction and cell loss are also seen in Alzheimer’s disease (Morrison and Hof, 1997; Greenamyre et al., 1988) as well as changes to α-amino-3-hydroxy-5-methyl-4- isoxazolepropionic acid receptor(AMPAR) and N-methyl-D-aspartate receptor (NMDAR) expression and activity have been detected (Wakabayashi et al., 1999; Snyder et al., 2005; Greenamyre et al., 1987). Clearance of glutamate from the synaptic cleft by glial cells and the loading of glutamate into synaptic vesicles are also dysfunctional in the brain of Alzheimer’s disease patients (Procter et al., 1988; Westphalen et al., 2003; Kirvell et al., 2007). The lack of adequate glutamate clearance leads to impairments in long-term potentiation (LTP) and neurotoxicity (Greenamyre et al., 1988). The current approved treatments for Alzheimer’s disease are cholinesterase inhibitors, rivastigmine, galantamine, and donepazil, and NMDA receptor antagonist, memantine (Tan et al., 2014). Memantine treatment is neuroprotective against glutamate toxicity by blocking the NMDAR (Danysz et al., 2000; Chen et al., 1992). Systematic review of anticholinesterase treatment in Alzheimer’s disease was done by Hensen et al.(2008) and showed an overall modest benefit for slowing cognitive decline. Anticholinesterase treatments increase the duration acetylcholine remains in the synaptic cleft to compensate for the cholinergic deficit, by inhibiting the breakdown of acetylcholine by acetylcholinesterase (Wilkinson et al., 2004). The cholinesterase inhibitors are suggested for mild and moderate Alzheimer’s disease while memantine is suggested for moderate to severe Alzheimer’s disease (Ehret and Chamberlin, 2015). Based on studies on the brains of Alzheimer’s disease patients and the treatments for Alzheimer’s disease, cholinergic and glutamate signalling dysfunction contribute to the clinical symptoms of the disease.

1.2 Neuropsychiatric symptoms - Agitation and aggression

Although cognition is one of the major clinical presentations of Alzheimer’s disease, neuropsychiatric symptoms (NPS) are also a core component of the disease and are present in almost all Alzheimer’s disease patients. NPS in Alzheimer’s disease decreases the quality of life for patients and increases the burden on caregivers as well as the healthcare system (Allegri et

4 al., 2006; Finkel, 2003). Prevalence of NPS in Alzheimer’s disease patients are high, with 64% at initial presentation and 90% lifetime occurrence (Steinberg and Lyketsos, 2008; Devanand, 1997; Savva et al., 2009). Even in patients with mild cognitive impairment, prevalence of NPS is much higher than in the general population (Lyketsos et al., 2002; Geda et al., 2008). The presence of NPS is associated with more rapid decline in cognition (Hersch and Falzgraf, 2007; Taragano et al., 2009; Geda et al., 2011; Rosenberg et al., 2011). Increased brain myo-inositol levels in the anterior cingulate gyrus of patients with Alzheimer’s disease were associated with NPS (Shinno et al., 2007). The Neuropsychiatric Inventory is an assessment tool used to quantify neuropsychiatric symptoms in patients (Cummings, 1997; Lyketsos et al., 2011). Improvements on the Neuropsychiatric Inventory led to the development of the Neuropsychiatric Inventory Clinician (NPI-C)Rating (Steinberg and Lyketsos, 2008; de Medeiroset al. 2010). NPI-C allows for each domain to be evaluated individually and for clinicians to directly evaluate the patients rather than just interviewing the caregiver. A variety of treatments for NPS are used including antipsychotics, antidepressants, anticonvulsant mood stabilizers, and cognitive enhancers (Cummings, 2016), however, they all have serious caveats for treatment of this elderly population. Two of the domains of the NPI-C are agitation and aggression. Agitated behaviours include motor activities such as restlessness, pacing, anxiety, or abnormal vocalizations. Escalation of behaviours can lead to verbal aggression and physical aggression, including punching, kicking, or biting others. Agitation and aggression is present in about 50% of institutionalized patients and 20% outside (Lyketsos et al.,2002). These symptoms lead to decreased independence for the patients and decreased ability for patients to live in the community. Agitation and aggression increases the workload of caregivers and often results in the institutionalization of the patient. Reduction of agitation and aggression can improve the quality of life for patients and reduce the workload on the caretakers, therefore reducing health care costs.

Although the causes of agitation and aggression are multifactorial, associations have been made with biological and environmental factors. For example, serotonin transporter polymorphism is associated with aggression in Alzheimer’s disease, suggesting a link to neurotransmission dysfunction (Sweet et al., 2001). Neurofibrillary tangles in the orbitofrontal cortex and anterior cingulate cortex as well as hypometabolism in the right frontal/temporal and bilateral cingulated cortices have been associated with agitation and aggression (Tekin et al., 2001; Sultzer et

5 al.,2011). External causes of agitation and aggression include pain, discomfort, or poor communication with caregivers (Ballard et al., 2009). Agitation and aggression caused by external factors can be resolved by directly dealing with the pain, discomfort, or misunderstanding (Husebo et al., 2011). Psychosocial interventions are aimed at helping caregivers to understand how best to meet any unmet needs of patients have been shown to reduce agitation and aggression (Cohen-Mansfield et al., 2007; Chenoweth et al., 2009). Therapeutic interventions with antipsychotics are commonly used to treat NPS (Koponen et al. 2015). Risperidone, olanzapine, and aripiprazole have shown some success in treating agitation and aggression (Ballard and Waite, 2006; Mahar et al., 2011). Rispiradone and olanzapine are dopamine receptor antagonists while aripriprazole is a dopamine receptor partial agonist. Antipsychotics also have some serotonin antagonism activities. However, side effects are associated with dopamine receptor antagonists such as extra pyramidal symptoms. The worst case is an increase in mortality that might be associated with antipsychotic use in patients with Alzheimer’s disease (Herrmann and Lanctot, 2005; Schneider et al., 2005). Benefits of using antipsychotics for agitation and aggression need to be weighed against the harms. Selective serotonin reuptake inhibitors, especially citalopram, may reduce agitation but more evidence is needed to demonstrate effectiveness at a safe dose (Gallagher and Herrmann, 2015). Cognitive enhancers used in Alzheimer’s disease may also reduce agitation and aggression (Cumbo and Ligori, 2014). Cholinesterase inhibitors have been shown to improve agitation and aggression in some clinical trials but failed in others (Holmes et al., 2007; Rodda et al., 2009; Howard et al., 2012). Memantine also had some success in treating agitation and aggression (Gauthier et al., 2008; Herrmann et al., 2013; Fox et al., 2012). Antiepileptic drug, valproate, showed no improvements over placebo and was poorly tolerated (Lonergan and Luxenberg,2009; Tariot et al., 2011). Melatonin and trazodone potentially reduce agitation and aggression (De Jonghe et al., 2010; Seitz et al., 2011). Benzodiazepines, haloperidol, cyproterone, and carbamazepine may be beneficial but concerns over tolerability prevent their use (Tampi and Tampi, 2014; Gallagher and Herrmann, 2014; Huertas et al., 2007). Although not all of these therapeutics can be used for treatment of agitation and aggression, they provide insight into NPS. Alteration in neurotransmission, especially serotonergic and dopaminergic pathways, seem to be the main causes for NPS in patients with Alzheimer’s disease.

1.3 scyllo-Inositol

Inositol is a six carbon ring polyol, also called 1,2,3,4,5,6-hexahydroxycyclohexane. scyllo- inositol is a stereoisomer of inositol with all of the hydroxyl groups in the equatorial position,

1,3,5/2,4,6-hexahydroxycyclohexane. scyllo-Inositol was shown to stabilize Aβ42 into a β- structure detected by circular dichroism and incubation of Aβ42 with scyllo-inositol prevented formation of fibrils detected by electron microscopy (McLaurin et al., 2000). Pre-incubation of

Aβ42 with scyllo-inositol rescued neuritic processes and reduced cell death in nerve growth factor-differentiated PC-12 cells. Reduction of Aβ42 accumulation on the membrane of cells was seen by fluorescence microscopy in the presence of scyllo-inositol (McLaurin et al., 2000). scyllo-Inositol treatment given orally was able to reverse spatial reference memory deficits in TgCRND8 mouse model of Alzheimer’s disease at 4 and 6 months of age (McLaurin et al., 2006). scyllo-Inositol treatment reduced soluble and insoluble Aβ peptides in the brain of TgCRND8 mice. scyllo-Inositol treatment did not have any effects on amyloid precursor protein processing, detected by measurements of full length amyloid precursor protein, APPs-α and APPs-β. Plasma Aβ peptide concentrations were not affected by scyllo-inositol treatment. Dot blot and western blot showed decreases in large oligomers and increases in trimers and monomers of Aβ peptides. These effects of scyllo-inositol treatment were dosage dependent. Loss of synaptophysin immunoreactivity in the hippocampus of TgCRND8 mice was reversed after scyllo-inositol treatment(McLaurin et al., 2006). scyllo-Inositol treatment prevents Aβ peptide induced inhibition of LTP in mouse hippocampal slice culture and Aβ peptide injection rat model (Townsend et al., 2006). Decrease in dendritic spine density caused by Aβ peptide treatment through a NMDAR dependent mechanism was also prevented by scyllo-inositol treatment (Shankar et al., 2007; Li et al., 2012). Protein expression of synaptophysin, syntaxin, and synapsin were shown to be increased after scyllo-inositol treatment (Ma et al., 2012; DaSilva et al., 2009). Decreases in AMPAR by Aβ peptide treatment were also shown to be prevented by scyllo-inositol treatment (Jin and Selkoe, 2015). Studies of scyllo-inositol in cell culture and animal models showed that scyllo-inositol treatment reversed toxic effects of Aβ peptides.

The TgCRND8 mouse model was used in this study to investigate scyllo-inositol treatment in the presence of an amyloid load. This model recapitulates the amyloidosis of Alzheimer’s disease

7 via the expression of human amyloid precursor protein with the Swedish (K670N, M671L) and Indiana (V717F) mutations under the hamster prion protein promoter on a C3H/C57 x C57 background (Chishti et al., 2001). The expression of the transgenic amyloid precursor protein is estimated to be 5 fold increase over the endogenous rodent amyloid precursor protein expression.

Aβ42 begins to accumulate after 1 month of age while Aβ40 levels are stable between 4 and 10 weeks of age. Deposition of amyloid was detected in all animals by 3-months of age. Aβ42 accumulates in the brain around a 5:1 ratio compared to Aβ40. Approximately 60% of TgCRND8 survive to age of 100 days with few mortalities after 3 months of age. Spatial memory deficits were seen at 11 weeks of age on the Morris water maze test. Although the prion promoter, and therefore APP, was expressed outside of the brain, amyloid deposits were not found by immunostaining outside of the brain (Peralta and Eyestone, 2009; Chishti et al.,2001). Amyloid plaques were found in the frontal cortex around 65 days of age and found in the hippocampus by around 100 days of age. These amyloid plaques contained β-sheet conformation identified by Thioflavin S staining and Congo Red birefringence (Chishti et al., 2001). Astrogliosis and microgliosis have been identified in this model (McLaurin et al., 2006). Object recognition memory was impaired in TgCRND8 at 8 weeks of age (Francis et al., 2012). Hippocampal brain derived neurotrophic factor (BDNF) expression was decreased at 6 weeks and 8 months of age but not at 9-10 weeks of age. Cortical BDNF was decreased after 9 weeks of age (Francis et al., 2012, Peng et al., 2009). Many aspects of Alzheimer’s disease such as amyloid aggregation, neuroinflammation, synaptic dysfunction, and memory deficits are recapitulated in this model.

Further studies of scyllo-inositol in mouse models shed light on effects of scyllo-inositol that are unrelated to Aβ peptides. scyllo-Inositol is transported across cell membranes and the blood brain barrier through the sodium myo-inositol transporter 1 and 2 (SMIT1/2) (Fenili et al. 2011). Most of the transport activity is through SMIT1 (Berry et al., 2003). SMIT1/2 expression does not change with age in TgCRND8 or non-transgenic littermate mice (Fenili et al., 2007; Fenili, 2010). SMIT1 expression is similar in the hippocampus and the cortex while SMIT2 expression is higher in the cortex in these mice (Fenili et al., 2011). After oral intake of scyllo-inositol, the concentration of scyllo-inositol is much higher in the brain than in the cerebral spinal fluid (CSF) or plasma (Fenili, 2010; Quinn et al., 2009). Active transport of scyllo-inositol across cell membranes concentrates scyllo-inositol in brain tissue. Peak levels of scyllo-inositol occur two hours in the plasma and eight hours in the brain after oral treatment (Fenili, 2010). scyllo-Inositol

8 concentration in the brain increased and myo-inositol concentration decreased after treatment with scyllo-inositol (Fenili et al., 2007). scyllo-Inositol and myo-inositol compete for transport across the membrane through SMIT1/2 (Fenili et al., 2011). Changes in myo-inositol concentrations by over-expressing SMIT1 can increase PIP and PIP2 in the cell, suggesting altering myo-inositol transport through SMIT1 can affect signalling pathways that require myo- inositol (Dai et al., 2016). Studies have shown that scyllo-inositol can affect myo-inositol concentration and this in turn may affect downstream signalling. myo-Inositol signalling is downstream of G-protein coupled receptors (GPCR). Activation of the

Gαq subunit of GPCR leads to hydrolysis of phosphatidylinositol 4, 5-bisphosphate (PIP2) by phospholipase C (PLC) into two second messengers, myo-inositol 1,4,5-triphosphate (IP3)and diacylglycerol (DAG). IP3 binds to inositol trisphosphate receptor to release intracellular calcium stores. The calcium and DAG activates proteins such as protein kinase C, Ca2+/calmodulin- dependent protein kinase, and calcinurin. IP3 is then recycled back into myo-inositol by inositol polyphosphate phosphatase and myo-inositol monophosphotase. myo-Inositol is joined together with DAG to form PIP2 (Figure 1.1). Many neurotransmitter receptors are in the Gαq family of GPCR. Serotonergic (5-HT2), muscarinic (M1,3,5), adrenergic (α1), glutamatergic (mGlu1, mGlu5), histaminergic (h1) receptors all signal through the myo-inositol signalling pathway (Fisher and Agranoff, 1987). Gαq GPCR signalling provides a mechanism for which reduction of myo-inositol by scyllo-inositol treatment can affect synaptic signalling and in turn affect NPS. myo-Inositol concentrations in the brain can be decreased genetically in animal models or with mood stabilizers lithium and antiepileptic valproate. Lithium treatment inhibits inositol polyphosphate phosphatase and myo-inositol monophosphotase, which reduces recycling of myo- inositol in the myo-inositol signalling pathway (Berridge et al., 1982; Serretti et al., 2009). Another effect of lithium treatment is down regulation of SMIT1 expression (van Calker and Belmaker, 2000). myo-Inositol depletion was proposed as one of the mechanisms of action for lithium treatment (Berridge, 1989). Using knockout mouse models, transport of myo-inositol was shown to be more important than synthesis of myo-inositol in the brain. SMIT1+/-, but not myo- inositol monophosphotase -/- mice, show decreased brain myo-inositol (Agam et al., 2009). Changes in the rate of myo-inositol transport were able to alter downstream signalling. SMIT1 over expression is able to alter PIP2 concentration in cells, suggesting that changes in myo- inositol uptake can affect downstream signalling (Dai et al., 2016). Valproate inhibits myo-

9 inositol-1-phosphate synthase and reduces the amount of myo-inositol synthesized from glucose (Shaltiel et al., 2004). Lithium and valproate are treatments for major affective disorders and there have been attempts to use them in the treatment of agitation and aggression in Alzheimer’s disease patients. Reduction of myo-inositol has been previously investigated to affect GPCR and have mood altering affects.

Figure 1.1 myo-inositol signalling pathway. scyllo-inositol competitively inhibits myo-inositol uptake into cells. Decreased intracellular myo-inositol concentration reduces G-protein coupled receptor (GPCR) signalling through Phospholipase C (PLC). PIP2Phosphatidylinositol 4,5- bisphosphate. DAG diacylglycerol. SMIT sodium myo-inositol transporter. IP inositol phosphate.

IP3 inositol triphosphate. ER endoplasmic reticulum. Image reproduced with permission from Hangyu Lin and Sunnybrook Research Institute.

Preclinical studies in cell culture and mouse models of Alzheimer’s disease strongly suggest that scyllo-inositol treatment was able to reach the brain. The results also indicated that scyllo-inositol treatment is able to reduce amyloid load and neuronal toxicity from Aβ peptides. These findings

10 suggest that scyllo-inositol could be a viable therapeutic for treating Alzheimer’s disease. A Phase 2 clinical trial for scyllo-inositol treatment of mild to moderate (MMSE 16-26) Alzheimer’s disease patients showed an increase in scyllo-inositol and decrease in myo-inositol levels in the brain (Salloway et al., 2011; Liang et al., 2009). This demonstrated that similar to the rodent studies, oral scyllo-inositol dosing results in changes to brain levels. Treatment emergent adverse effects were not different between placebo and scyllo-inositol treated patient groups. scyllo-Inositol was shown to have an acceptable safety profile. There was no overall improvement in cognition as a function of treatment however, subgroup analysis showed improvements on the Neuropsychological Test Battery in the low dosage group for mild Alzheimer’s disease patients (Salloway et al., 2011). The emergence of neuropsychiatric symptoms, specifically agitation and aggression, was potentially reduced in patients treated with scyllo-inositol compared with placebo (Lyketsos et al., 2012; Tariot et al., 2012). A subsequent clinical trial investigated the efficacy and safety of scyllo-inositol as a treatment for agitation and aggression in Alzheimer’s disease (Porsteinsson et al., 2015). In this trial, 350 patients with MMSE scores between 5 and 24 and NPI-C agitation and aggression score≥ 4 were randomized to placebo or 250 mg BID scyllo-inositol for 12 weeks. There was no difference in agitation and aggression in the overall analysis between placebo and treatment groups, however NPI-C agitation and aggression improved for patients with baseline score ≥ 22. Higher baseline NPI-C agitation and aggression score was linearly correlated with increased reduction of agitation and aggression in the scyllo-inositol treated group, but not placebo group. Numerical improvements were seen in 20 of 21 agitation and aggression categories of NPI-C (Porsteinsson et al., 2015). scyllo-Inositol treatment is a potential treatment to reduce agitation and aggression in Alzheimer’s disease patients with severe agitation and aggression. The mechanism of action is unknown, both Aβ-dependent and Aβ-independent effects may play a role.

Chapter 2 Rationale, Objectives, and Hypothesis

2 Rationale, Objectives, and Hypothesis

2.1 Rationale

Alzheimer’s disease is a condition with high impact on the lives of patients and families and costs for the healthcare system. There is currently no cure for Alzheimer’s disease. Symptomatic treatments are limited in effectiveness and have potential side effects. scyllo-Inositol is a small molecule therapeutic, which has been shown to reduce agitation and aggression in Alzheimer’s disease patients. scyllo-Inositol has also been shown to be safe at therapeutic dosage for Alzheimer’s disease patients. The exact mechanism of action for scyllo-inositol-induced treatment effects is unknown. Reduction of myo-inositol levels in the brain maybe one of the therapeutic mechanisms of scyllo-inositol. Studies on scyllo-inositol in models of Alzheimer’s disease have been focused on the reduction of Aβ peptide toxicity. This study goes beyond studying the direct interaction of Aβ peptides and scyllo-inositol molecules, focusing on transcriptomic changes, which have not been previously investigated.

Gene expression microarrays and real time PCR will be used to investigate the molecular action of scyllo-inositol by measuring gene expression changes. Analyses of microarray results with bioinformatics approaches will identify potential pathways targeted by scyllo-inositol treatment. This study will focus on two of the brain regions that experience dysfunction and lead to cognitive and behavioral deficits, the hippocampus and the cerebral cortex.

2.2 Hypothesis

I hypothesize that scyllo-inositol treatment will cause changes in expression of genes involved in neurodegenerative diseases and neuropsychiatric disorders.

2.3 Specific aims

1. Investigate the changes in gene expression in the hippocampus and the cortex of a mouse model of Alzheimer’s disease after treatment with scyllo-inositol as a function of increasing pathology.

2. Identify potential pathways which can mediate the therapeutic effect seen in the clinical trials with scyllo-inositol treatment.

3. Investigate the interaction between the amyloid precursor protein transgene and the scyllo- inositol treatment effects.

Chapter 3 Materials and Methods

3 Materials and Methods

3.1 Animals

Amyloid precursor protein (APP)transgenic mouse model of Alzheimer’s disease, TgCRND8 mice on out bred C3H/C57BL6 background, carries the Swedish (KM670.671NL) and Indiana (V717F) APP mutations under the control of the Syrian hamster prion promoter which targets the neurons of the central nervous were used in this study. The Animals were kept on a 12-hour light/dark cycle with food and water ad libitum. All experiments were performed in accordance with Canadian Council for animal Care and University of Toronto guidelines.

TgCRND8 and non-transgenic littermates were given 10mg/mL scyllo-inositol (kind gift from Transition Therapeutics Inc.) ad libitum in the drinking water for 30 days before being sacrificed. Animals were anesthetized with pentobarbital and exsanguinated by transcardial perfusion with PBS and heparin. Brain tissues were dissected on ice. Hippocampal and cortical regions are frozen in dry ice and stored in -86C freezer.

3.2 RNA isolation

Hippocampal and cortical RNA were isolated using phenol-chloroform extraction (Chomczynski and Sacchi, 1987). All work was performed on ice and all water are treated overnight with 1/1000 diethylpyrocarbonate (Sigma D5758-25ML Lot:SHBB2823V) stirred overnight followed by autoclave to inactivate diethylpyrocarbonate. Frozen brain regions were homogenized with a dounce homogenizer (Wheaton #358103) in 1mL lysis buffer. Lysis buffer was prepared with final concentration of 4M guanidium isothiocyanate (Bioshop GUA002 lot: 1224B42), 6mM sodium citrate (Bioshop CIT001 lot:92951003), 4mM N-lauryl sarcosine (Sigma L9150-50G batch:082K0028), 0.7% 2- mercaptoethanol (Sigma M2148-100mL lot SHBF1470V). DNA was

14 sheared by passage through 25-gauge needle (BD 305122) 5 times. 1/10 volume of 2M sodium acetate (Sigma S2889-250G lot 077K0062) pH 5, 1 volume of water saturated phenol (Sigma P1067-100G lot:BCBN7866V), and 1/5 volume of 24:1 chloroform (Sigma C2432-500ML lot:SHBF3553V) isoamyl alcohol (Sigma I9392-500ML lot: SHBC8015V) were added to the lysate, mixed vigorously, placed on ice for 10 minutes, and centrifuged (Eppendorf 5415R) at 16RCF at 4°C. The top aqueous phase containing the RNA was moved into a new tube, 1/40 volume of 1N acetic acid and 3 volumes of ethanol were added and mixed, and left at -20C overnight. Precipitate was centrifuged at 16RCF at 4°C for 20 minutes to pellet the RNA. The liquid was decanted and the pellet was washed three times with 70% ethanol with 20 minutes of centrifuge at 16RCF at 4°C between each wash. The pellet was resuspended in 20 μL of diethylpyrocarbonate-treated water, vortex vigorously, and stored at -80°C. RNA quality and quantity was assessed with NanoDrop 2000 UV-Vis Spectrophotometer (Thermo Scientific) measuring 260/280 nm and 260/230 nm.

3.3 Affymetrix microarray

RNA isolated from five animals per group were combined and sent to the Princess Margaret microarray center, now the Princess Margaret genomic center, for analysis in triplicate. All samples passed Affymetrix quality guidelines. 100 ng of total RNA for each sample was used as input RNA in Ambion® WT Expression Kit and 5.5 μg of cDNA for each samples was fragmented and labelled according to Affymetrix WT labeling and fragmentation protocol. Affymetrix Mouse 430 2.0 array were hybridized for 17 hrs at 45oC at 60 RPM. Arrays were washed using GeneChip Fluidics Station P450 fluidic station and were scanned with Affymetrix GeneChip Scanner 7G. Data was analyzed using the Genespring (Agilent) v 11.0.1 software package. Raw cell files obtained from Affymetrix scans were imported for analysis using the RMA summarization algorithm. probes with no signal defined as being in the lower 20th percentile in both groups for expression value, and then ran a moderated t-test. The data obtained from the Princess Margaret Genomics Center included p-value, corrected p-value, and fold change. For the comparisons between the treated and untreated 200 day old TgCRND8 and the comparisons between TgCRND8 and non-transgenic littermates, the data that was provided by

15 the Princess Margaret Genomic center additionally filtered all probe sets with lower than 2- foldchange and corrected p-value higher than 0.05. Additional filtering on the comparisons between treated and untreated 100 day old TgCRND8 and comparisons between treated and untreated 200 day old non-transgenic mice removed probe sets without any raw intensity values higher than 100 and probe sets with corrected p-value higher 0.05.

3.4 Functional clustering and pathway analysis

Gene Ontology annotation enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID ) Bioinformatics Resource (v6.7) developed by NIAID, at the National Institutes of Health (Huang et al. 2009a, Huang et al. 2009b). Filtered probe sets were uploaded onto DAVID website. The as AFFYMETRIX_3PRIMER_IVT_ID identifier and gene list type were selected for the submit list options. The gene lists were analyzed using the functional annotation tool. The default annotation categories were selected, COG_ONTOLOGY, SEP_PIR_KEYWORDS, UP_SEQ_FEATURE, GOTERM_BP_FAT, GOTERM_CC_FAT, GOTERM_MF_FAT, BIOCARTA, KEGG_PATHWAY, INTERPRO, PIR_SUPERFAMILY, SMART. Results were visualized using functional annotation clustering. The options for clustering were left on default except for the addition of false discovering rate (FDR) output (Figure 3.1).

Figure 3.1 The settings used for Functional annotation clustering in DAVID. All settings were left on default except for the inclusion of FDR in the output.

The filtered probe sets are uploaded into QIAGEN’s Ingenuity® pathway analysis program (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity) build version 388455M and content version 27821452. Core analysis was performed with the following settings. Only data from mouse, human, and cell lines were considered. Only astrocytes, neurons, nervous system, CNS cell lines, and neuroblastoma were considered. All other default settings were retained. Canonical pathways and upstream regulators were exported into Microsoft Excel. Figures of canonical pathways were exported as images. Summary of the core analysis were exported as PDF. Summary figures used in this report are screenshots taken from IPA. Table of overlapping terms between comparisons was generated using Venn diagram tool from Bioinformatics Evolutionary Genomics (http://bioinformatics.psb.ugent.be/webtools/Venn/)

3.5 RT-qPCR

cDNA was synthesized from the RNA using superscript III first-strand synthesis supermix for qRT-PCR (Invitrogen cat. No. 11752-050) on Mastercycler gradient (Eppendorf) in 8-strip PCR tubes (DiaTEC DIAATEC420-1000 lot:15164) . 1ng of RNA is added to 2 μL of RT enzyme mix and 10 μL 2x RT reaction mix and the volume is topped off to 20 μL with diethylpyrocarbonate-treated water. After being mixed, the tube was incubated at 25°C for 10 minutes, 50°C for 30 minutes, then 85°C for 5 minutes. 1 μL of E. coli RNase H is added to each tube and incubated at 37°C for 20 mines. cDNA is frozen at -20°C until use. qRT-PCR was run on ViiA 7 (Applied Biosystems) using SYBR select master mix (Applied Biosystems REF 4472897) in 384-well clear optical reaction plates (Applied biosystems cat. 4309849) with 10 μL reaction volume in triplicates and analyzed with QuantStudioTM Realtime PCR Software (Applied Biosystems). 4 μL of 200 fold diluted cDNA, 1 μL of 5 μM forward and reverse primers, and 5 μL master mix was added to each well. The contents were mixed and centrifuged in an Allegra 6 centrifuge (Beckman-Coulter) with the MicroPlus carrier (Beckman 362394) at 1000 RPM for 5 minutes. Plates were sealed with MicroAmpTM optical adhesive film (Applied Biosystems REF 4311971) standard comparative Ct run using SYBR Green detection with a melt curve was performed using the ViiA 7 system. The default run method was

17 used with 40 cycles of PCR stages (Table 3.1). Ct values were determined using the automatic threshold settings in QuantStudio. Ct value is the interpolated cycle number at which the change in fluorescence signal, ∆Rn, reaches a threshold level. Wells that were tagged by QuantStudioTM for amplification errors were omitted. Relative gene expression levels were determined by ∆∆Ct method byQuantStudioTM (Livak and Schmittgen, 2001).

Table 3.1 The default run method for standard comparative Ct using SYBR Green detection with a melt curve. Rate of temperature change is 1.6 °C/s for all steps except melt curve step 3 which is at 0.05 °C /s. Temperature (°C) Hold time Hold step 1 50 2 minutes Hold step 2 95 10 minutes PCR step 1 95 15 seconds PCR step 2 60 1 minute Melt curve step 1 95 15 seconds Melt curve step 2 60 1 minutes Melt curve step 3 60 to 95 at 0.05/s

3.6 Primer design

Primers for Gapdh and Tbp were designed by Dr. Daniella Fenilli (Fenilli, 2010). All other primers were designed with NCBI primer blast of mRNA sequences from GenBank. All designed primers contained exon junction, were within the coding sequences, product size between 75 and 175 nucleotides, optimal melting temperature 60°C (Table 3.2). Primers were checked against Mus musculus (taxid:10090) Refseq mRNA database with primer-blast. Primers must have at least 2 total mismatches to unintended targets including at least 2 mismatches within the last 5 bps at the 3’ end. Amplification efficiency was calculated by measuring Ct value of 25, 100, 400, 1600 fold dilutions of cDNA. The efficiency is calculated by (10−1/푆푙표푝푒 − 1) × 100 %, where slope is calculated with the LINEST function on the Ct values and the logarithm of the relative concentration of cDNA in Microsoft Excel. Melt curves

18 and melt curve peaks were generated by QuantStudioTM. PCR product size was measured by agarose gel electrophoresis. Gel was made by adding 4g of agarose (Bioshop # AGA 001 lot: GI- 141103) to 100mL of TAE buffer (Wisent Inc Cat:880540-CL Lot: 880540024) followed by boiling until the solution was clear. Ethidium bromide was added to the agarose solution and mixed by swirling. The agarose solution was cased into gels. 10 μL of PCR product is mixed with 2 μL of 6x loading solution (Fermentas #R0611 lot: 9601) and pipette into wells in the gel. O’GeneRulerTM ready to use low range DNA ladder (Fermentas #SM1203 Lot: 00089816) was used to determine the size of the PCR products. Mini electrophoresis system (VWR) was set to run at 100V for 30 minutes. Gels were imaged with Genesnap software (Syngene). Control genes for comparative Ct are chosen with BestKeeper (Pfaffl et al., 2004). Ct values from all the samples in a comparison for all 8 control genes are inputted into BestKeeper and the 2 genes with the highest coefficient or correlation to the BestKeeper were used for that comparison.

Table 3.2 List of all the primers that were used. The primers and information about the primers are included. The predicted PCR product size is also included.

G P Direction of primer P P P P P P

rotein name rimer length rimer tm rimer gc% rimer complementarity rimer roduct size

ene symbol

Grin1 Mus musculus F 20 60.04 50 4 ATGCGCGTCTAC 116 glutamate receptor, AACTGGAA ionotropic, NMDA1 R 20 59.68 55 3 TTCTCTGCCTTG (zeta 1) GACTCACG Gria3 Mus musculus F 20 59.39 50 3 TCAGCATTAGGA 99 glutamate receptor, ACGCCTGT ionotropic, AMPA3 R 21 60.27 52 4 TTCCCCCTTATC (alpha 3) GTACCACCA Syt1 Mus musculus F 19 60.08 63 3 GGTCCTCGCTCC 88 synaptotagmin I AGTTTCC R 23 59.36 43 4 TGCAGAGGAGAC TTGACTAACAA Syn1 Mus musculus synapsin F 22 59.25 50 4 CAGCTCAACAAA 97 I TCCCAGTCTC R 20 59.4 55 4 TCTCAGCTTTCA CCTCGTCC

Syp Mus musculus F 20 60.53 55 3 GAGTGTGCCAAC 77 synaptophysin AAGACGGA R 21 59.93 47 5 TACACTTGGTGC AGCCTGAAT Stx1a Mus musculus syntaxin F 21 60.4 52 5 TCGAGTACAATG 101 1A TGGAGCACG R 20 62.91 60 6 GATCTTCTTCCT GCGCGCCT Dlg4 Mus musculus discs, F 20 59.52 55 4 AGCCCCAGGATA 90 large homolog 4 TGAGTTGC R 20 60.25 60 4 CCCAGACCTGAG TTACCCCT Actb Mus musculus actin, F 18 60.81 66 4 CGCAGCCACTGT 96 beta CGAGTC R 20 60.39 55 6 GTCATCCATGGC GAACTGGT Prkce Mus musculus protein F 20 61.83 60 3 CAGACCAAGGAC 115 kinase C, epsilon CGCCTCTT R 20 60.18 55 5 CTGCGGCATAGA ACCGAGAA Gria4 Mus musculus F 20 59.39 55 4 GGACCTCGAAAG 91 glutamate receptor, GTTGGCTA ionotropic, AMPA4 R 21 60 52 5 CGATAGCTGCTG (alpha 4) TGTCATTGC Creb3 Mus musculus cAMP F 20 59.69 55 4 GCAGCACTTGTG 114 responsive element TTCTGGTC binding protein 3 R 20 59.69 50 6 TGCGGTGCAACA CAACATAC Crebbp Mus musculus CREB F 20 59.82 50 4 TGGAAGAACTGC 87 binding protein ACACGACA R 20 59.14 50 4 TCCCAGGATGGT TTGTTGGT Camk2 Mus musculus F 20 59.46 55 4 AGCCTGCATCGC 167 a calcium/calmodulin- CTATATCC dependent protein R 19 60.68 57 5 TGGTCCTTCAAT kinase II alpha GCGGCAG Camk4 Mus musculus F 20 60.25 50 6 AAGCTTAAGGCA 79 calcium/calmodulin- GCGGTGAA dependent protein R 20 60.04 55 2 CTTGGATGCTGG kinase IV TGTGGCTA Akt1 Mus musculus F 20 59.68 55 5 TGAGAAGAAGCT 84 thymoma viral proto- GAGCCCAC oncogene 1 R 21 59.8 52 6 TGAGCTGTGAAC TCCTCATCG Pten Mus musculus F 20 59.55 55 6 GCGGAACTTGCA 96 phosphatase and tensin ATCCTCAG

homolog R 20 60.32 55 4 ACATGAACTTGT CCTCCCGC Pik3r2 Mus musculus F 20 59.9 55 2 TATTGCGAGGGA 90 phosphatidylinositol 3- AGCGAGAC kinase, regulatory R 20 60.25 60 3 CTTCGCCGTCTA subunit, polypeptide 1 CCACTACG (p85 alpha) Gapdh Mus musculus F 23 63.26 52 4 AAGAAGGTGGTG 112 glyceraldehyde-3- AAGCAGGCATC phosphate R 23 62.97 56 2 CGAAGGTGGAA dehydrogenase GAGTGGGAGTTG Tbp Mus musculus TATA F 20 58.33 55 3 GCCTTCCACCTT 102 box binding protein ATGCTCAG R 21 58.12 52 3 GAGTAAGTCCTG TGCCGTAAG Ppia Mus musculus F 20 60.25 55 5 GCTGGACCAAAC 72 peptidylprolyl ACAAACGG isomerase A R 20 60.69 50 3 ATGCTTGCCATC CAGCCATT B2m Mus musculus beta-2 F 22 59.35 45. 2 TGCTATCCAGAA 116 microglobulin AACCCCTCAA R 20 59.26 55 4 GGATTTCAATGT GAGGCGGG Rpl13a Mus musculus F 22 59.71 45 3 TGACAAGAAAA 126 ribosomal protein L13A AGCGGATGGTG R 20 59.96 55 5 GCTGTCACTGCC TGGTACTT Hprt Mus musculus F 20 58.45 50 6 AGCAGTACAGCC 90 hypoxanthine guanine CCAAAATG phosphoribosyl R 21 59.85 47 4 ATCCAACAAAGT transferase CTGGCCTGT Sdha Mus musculus F 20 59.96 55 4 TCGACAGGGGAA 136 succinate TGGTTTGG dehydrogenase R 20 59.81 55 5 TAATCTTCCCTG complex, subunit A, GCATGGGC flavoprotein Pgk1 Mus musculus F 20 59.96 55 4 CCACAGAAGGCT 114 phosphoglycerate GGTGGATT kinase 1 R 20 59.96 55 4 GTCTGCAACTTT AGCGCCTC

3.7 Analysis of qPCR data

Relative gene expression levels for each gene of interest within a comparison were determined by comparative Ct using QuantStudioTM. These relative gene expression values were compared between treated and untreated groups by 2-tailed, non-parametric TTEST on excel. P-value from the TTEST was corrected for multiple comparison according to the method described by Benjamini and Hochberg (1995) using an excel spreadsheet which can be found at https://www.marum.de/Binaries/Binary745/BenjaminiHochberg.xlsx. For display in bar graphs, the relative expression genes for the samples in the treated group were normalized to the average relative expression untreated group. The standard error of the means calculated as the root mean square of the errors of in the treated and untreated groups.

For comparison between the gene expression changes in 100 day old animals and 150 day animals, the normalized relative gene expression of treated group samples were compared between the 100 day old animals and the 150 day old animals by 2-tailed, non-parametric TTEST on excel. For display with Multiple Experiment Viewer (MeV), the relative expression of the genes was normalized so that the average relative expression of all the samples in a comparison for any specific gene is 1. There values were then inputted into MeV and Hierarchical clustering was performed (Figure 3.2). The resulting HCL tree was exported as a bitmap image file.

Figure 3.2 Settings for hierarchical clustering in Multiple Experiment Viewer (MeV). All settings were default except optimize gene lead order and optimize sample leaf order were selected.

Chapter 4 Results

4 Results

Mice were used to investigate the effect of scyllo-inositol treatment. Mouse models represent the physiology of humans better than cell culture, especially given the role active transport plays in loading scyllo-inositol into the brain. Animal models mimic the decrease in brain myo-inositol that was seen in human patients (Quinn et al., 2009). The TgCRND8 mouse model expressing mutant human amyloid precursor protein (Chishti et al., 2001) was used to study scyllo-inositol treatment in the presence of Aβ peptide accumulation (McLaurin et al., 2006). In light of these previous studies, I investigated the differences in the transcriptomes between scyllo-inositol treated TgCRND8 mice and untreated TgCRND8 mice. Microarray and RT-qPCR were used to measure mRNA levels in the hippocampus and the cerebral cortex of mice. Comparison between scyllo-inositol treated and untreated TgCRND8 mice was used to understand the cellular and molecular effects of the treatment in the context of Aβ peptide accumulation and aggregation. To investigate the proposed non-Aβ dependent effects such as inhibition of the myo-inositol signalling pathways, comparison between scyllo-inositol treated non-transgenic mice and untreated non-transgenic mice were used to understand non-Aβ effects of the treatment. A comparison was also made between TgCRND8 mice and non-transgenic littermates to identify the effect of the transgene in the TgCRND8 mouse model. Comparison of the transgenic effect, the treatment effect in the presence of Aβ peptide accumulation, and the treatment effect in the absence of Aβ peptide accumulation provided insight to the Aβ-dependent and Aβ-independent effects of scyllo-inositol treatment.

4.1 Effect of scyllo-inositol treatment in TgCRND8 mouse model of Alzheimer’s disease

The TgCRND8 mouse model of Alzheimer’s disease was used to study the effect of scyllo- inositol treatment within the hippocampus and the cerebral cortex. Animals were given scyllo- inositol starting at 70 days of age until they were sacrificed at 100 days of age. The treatment is given at the onset of plaque deposition in this model (Chishti et al., 2001, McLaurin et al., 2006).

The genes expressed were measured using whole genome microarrays. The microarray consists of probe sets that are 20 nucleotide sequences. These probe sets determine the concentration of single stranded DNA, which are complementary to the 20 nucleotide sequences of the probe set. Multiple probe sets can be mapped to different parts of the same gene. This redundancy allows for checks of consistency within the microarray. By mapping the probe sets to genes, the microarray data presents a genome wide view of gene expression. Comparison between microarrays can be made to determine differentially expressed genes between two samples. Comparison between treated and untreated mice identifies the treatment effect, while comparison between TgCRND8 and non-transgenic mice identifies the transgene effect. Due to the sheer number of probe sets present in the microarray analysis, looking at each probe set individually would be inefficient and would be vulnerable to false positives. False positives are genes that appear to be significantly different between two microarrays due to variance and chance but are not differentially expressed. An analysis of pathways and groups of genes rather than individual genes gives further insight into the effect of the treatment.

The database for annotation, visualization and integrated discovery (DAVID) offered by the National Institute of Allergy and Infectious Diseases is one such program which can be used to process the probe set data (Huang et al. 2009a, Huang et al. 2009b). DAVID considers 2 lists of genes. The first list is the list of genes which are identified as significantly altered as a function of treatment within the microarray comparison. The second list is the list of background genes, all the genes that were evaluated by the microarray probe set. The amount and the direction of gene expression changes were not taken into account. The DAVID knowledgebase, a data base of functional annotations for each gene, was used to categorize the genes. DAVID performs gene enrichment analysis, which identified functional annotation categories that contain more genes from the first list than expected from random chance. Clustering of these categories was done by DAVID to account for the large overlaps in many closely related categories. The redundancy exists because the DAVID knowledgebase acquires data from multiple individual databases. The output data from the DAVID functional annotation enrichment clustering identified the most likely pathways altered in the microarray comparison.

QIAGEN’s Ingenuity® Pathway Analysis (IPA®) utilized the Ingenuity Knowledge Base to analyze the microarray comparison data. Enrichment analyses are performed by IPA to identify canonical pathways, upstream regulators, and disease and biological functions. IPA also

25 calculated an activation Z-score by comparing the direction of gene expression changes measured by the microarray to the activator or inhibitor relationship between molecules and genes in the Ingenuity Knowledge Base. The Ingenuity Knowledge Base is a data base curate by QIAGEN, which identifies relationships between genes and molecules from published literature. Because microarrays measured changes in RNA concentration, effects on non-transcriptional events or RNA degradation were not directly measured. Upstream regulator analysis in IPA allowed for the prediction of proteins or molecules that were affected by evaluating the changes in downstream gene expression measured within the microarray. Lastly, IPA analysis for disease and function predicted the broad biological significance of the data set, which gave a broad overview of the differences between groups being compared in the microarray.

These two programs together, DAVID and IPA, provided a multiple level summary of the microarray data without needing to directly investigate hundreds of differentially expressed genes. Thus, the use of these two programs allowed us to address our hypothesis that scyllo- inositol treatment in TgCRND8 mice have effects in the hippocampus and the cerebral cortex on pathways and molecules related to Alzheimer’s disease and neuropsychiatric symptoms.

4.1.1 Hippocampal microarray comparison between scyllo-inositol treated and untreated 100 day old TgCRND8 mice

Affymetrix microarrays were used to measure the gene expression in hippocampal samples from scyllo-inositol treated and untreated 100 day old TgCRND8 mice to determine the scyllo-inositol treatment effect. Comparison between 35679 probe sets were generated and analyzed with help from the Princess Margret Genomic Center, formerly Princess Margret Microarray Center. After initial filtering as described in the methods, 6199 probes remained with 806 of those probe sets more than 1.5 fold differentially expressed between hippocampal samples of treated and untreated TgCRND8 mice. Of the 806 probe sets, 779 were recognized by DAVID in comparison to the total 35679 probe sets which were inputted as the background controls. Functional annotation clustering analysis using DAVID identified pathways and biological processes which are most likely changed between the treated and untreated samples based on the

26 microarray array data set (Table 4.1). The top clusters are RNA recognition motif, neuronal projection, synaptic transmission, lipoprotein, structural maintenance of chromosomes, microtubule binding, cytoskeletal binding, and C2 membrane targeting. Three of the top four clusters are neuronal or synaptic related functional clusters which share many genes in common (Figure 4.1). All 3 of these clusters are related. The majority of probe sets from Cluster 3 and 4 overlap (33/60). A large number of probe sets from cluster 2 are also in cluster 3 or 4 (16/36). This suggested that one major effect of scyllo-inositol treatment in the hippocampus of TgCRND8 mice is modulation of genes important for synaptic transmission, which plays an important role in neuropsychiatric symptoms. Neuronal projection cluster is a mixture of synaptic and cytoskeletal genes. RNA recognition motifs (RRM) are protein domains that bind to RNA. RNA binding proteins are important for regulating RNA splicing and regulating translation at synapses. Alternative splicing of BDNF receptor, TrkB has been shown in Alzheimer’s disease (Wong et al., 2012; Gao et al., 2007). Alternative splicing of PSEN1and PSEN2 in Alzheimer’s disease patients can lead to increased production of Aβ peptides (Cruts et al., 1998; Sato et al., 1999). RNA binding proteins are required for shuttling mRNA to synapses. CaMKIIα, beta actin, and BDNF all have been identified to contain dendritic targeting elements (An et al., 2008; Eom et al., 2003; Kobayashi et al., 2005). RNA binding proteins are important for synaptic plasticity and play a role in neuropsychiatric disorders (Klein et al., 2016). RNA binding proteins such as, the U1 small nuclear ribonucleoprotein has been shown to aggregate in amyloid plaques (Gozal et al., 2009). C2 and lipid modifications allows for proteins to translocate to and cluster at the cell membrane, which is important for cell signalling. Lipid modifications provide an anchor point for the protein to be secured to the cell membrane. The C2 domain is a calcium requiring phosphoinositide-binding protein (Corbalan-Garcia and Gomez- Fernadez, 2014). In the event of calcium signalling and increased intracellular calcium concentrations, C2 domain containing proteins, such as phospholipase C, phosphatase and tensin homolog (PTEN), and protein kinase C, cluster to the plasma membranes. The activation of these pathways affect neuronal survival and synaptic plasticity. C2 domains also play a role in neurotransmitter release. Synaptotagmin family of proteins contains two C2 domains which when bound to Ca2+ generates plasma membrane curvature required for membrane fusion and vesicular release (McMahon et al., 2010). Alterations in gene expression of proteins with C2 domain can play a role in the scyllo-inositol treatment effect. Functional annotation clustering using DAVID identified synaptic transmission changes to be enriched, which is potentially

27 modulating by changes in membrane associated signalling molecules, calcium sensors, microtubule and cytoskeleton binding proteins. The results support alteration in myo-inositol signalling as the mechanism of action.

Further pathway analysis was performed using IPA to identify pathways, molecules, and biological processes that are predicted to be altered in the hippocampus of 100 day old TgCRND8 mice after scyllo-inositol treatment. Of the 6199 probes inputted into IPA, 5906 of those probe sets were mapped to genes by IPA and 576 of the mapped genes met the 1.5-fold change cut off. Core analysis was performed by IPA (Figure 4.2). Ten canonical pathways were identified to meet the likely threshold determined by the IPA program (Figure 4.3). RhoA signalling and role of NFAT in regulation of the immune response were predicted to be activated while calcium signalling and RhoGDI signalling were predicted to be inhibited. IPA canonical pathways provide visual description of pathways on top of the enrichment analysis. The pathway diagram (Figure 4.4a) showed that gene expression of molecules downstream of RhoA are up regulated with scyllo-inositol treatment and this may be affecting cytoskeleton organization. Only protein phosphatase 1 Catalytic Subunit Beta (PPP1CB), Rho guanine nucleotide exchange factor 1 (ARHGEF1) and Rap guanine nucleotide exchange factor 6 (RAPGEF6) did not match with the expected change (Figure 4b). RhoGDI signaling was important for cytoskeleton organization involving PIP2 and for gene expression involving cAMP response elements binding (CREB) and CREB binding protein (CBP) (Figure 4.5), which agreed with annotation cluster 8. IPA indicated calcium signaling was affected by changes in Ca2+/calmodulin-dependent protein kinase (CAMK) upstream of CREB which can affect cell growth and development. Calcium signalling is an important part of and is regulated in part by myo-inositol signalling. Cell proliferation was affected in epithelial adherens junction signalling by changes to phosphatase and tensin homolog (PTEN) and protein kinase B (AKT). Both PTEN and AKT signal through

PIP2. IPA identified Glutamine biosynthesis I based on gene expression change of glutamine synthetase (GLUL). GLUL is important in the brain for recycling of glutamine from the synaptic junctions, a biological process that has been shown to be dysfunctional in Alzheimer’s disease (Kulijewicz-Nawrot et al., 2013; Robinson, 2000). GLUL was also part of glutamate receptor signalling which showed changes in genes required for glutamate recycling in astrocytes as well as glutamate receptors on the post synaptic membrane (Figure 4.6). This suggests that scyllo- inositol treatment may be able to reduce glutamate toxicity by increases glutamate reuptake by

28 astrocytes. Nuclear factor of activated T-cells (NFAT) is a family of transcription factors. NFAT1-4 is regulated by calcium signalling through the myo-inositol signalling pathway while NFAT5 is activates in response to osmotic stress (Macian, 2005). IPA identified “Role of NFAT” in regulation of the immune response because of the change to major histocompatibility complex MHC and myo-inositol related signalling pathways, Gα unit of the GPCR, phosphoinositide 3 (PI3K), AKT, and calcineurin (Figure 4.7). The MHC changes can be caused by neuroinflammation due to Aβ peptide toxicity while the signaling changes can be caused by changes in myo-inositol levels. It is important to consider how the pathways are biologically relevant as breast cancer regulation in the hippocampus is nonsensical. However, the gene listed in this pathway such as PLCβ, CAMK, and RHOGEF are important in the brain and explains why IPA identified this specific pathway (Figure 4.8). Canonical pathway analysis with IPA identified PIP2 related changes (CAMK, CREB, PTEN, AKT) to potentially affect cytoskeleton, cell proliferation, and immune response. Down regulation of glutamate signalling by increasing glutamate reuptake and decreasing postsynaptic ionotrophic glutamate receptors were also identified and may play a role in reduction of excitotoxicity and changes in synaptic plasticity.

IPA core analysis also generates predictions for top upstream regulators, genes, and molecules, which may not be in the microarray data set but were likely to be affected by scyllo-inositol treatment. Predicted top upstream regulators were BDNF, ADAM10, L-dopa, LHX3, and HTT (Table 4.2). BDNF is a growth factor which is essential for development and plasticity. BDNF regulates growth, survival and differentiation of neurons. BDNF expression is decreased in TgCRND8 (Peng et al., 2009). Treatment with scyllo-inositol in TgCRND8 can ameliorate Aβ effects induced decrease in neurogenesis (Morrone et al., submitted). Microarray data indicates that BDNF gene expression was only increased 1.258fold, which did not meet that 1.5 fold cut off. Another top upstream regulator was the Disintegrin and metalloproteinase domain- containing protein 10 (ADAM10), a cell surface metalloprotease which can cleave amyloid precursor protein at the α-secretase site (Lammich et al., 1999). Cleavage of amyloid precursor protein by ADAM10 leads to the production of APPsα and reduction of Aβ. ADAM10 is also implicated in psychiatric and neurological diseases, such as epilepsy, fragile X syndrome and Huntington disease (Kuhn et al., 2016). Interactions between ADAM10 and scyllo-inositol have never been investigated. L-3,4-dihydroxyphenylalanine (L-dopa) is a precursor to the dopamine and the other catecholamine neurotransmitters. L-dopa is important for production of

29 catecholamines, a type of neurotransmitter. Atypical antipsychotics, which target dopamine receptors, are used to treat agitation and aggression in patients with Alzheimer’s disease (Liperoti et al., 2008; Herrmann et al., 2013). Analysis from DAVID suggested that scyllo- inositol potentially alters synaptic transmission, which may reduce agitation and aggression. LIM homeobox 3 (LHX3) is a transcription factor that is required for pituitary development and motor neuron specification. This transcription factor specifies motor neuron fate during differentiation (Lee et al., 2012) and is important for generation of induced pluripotent stem cells from patient somatic cells (Chinchalongporn et al., 2015). There has been no study looking at interactions between LHX3 and scyllo-inositol. Similar to Aβ peptides which aggregate in Alzheimer’s disease, mutant huntingtin (HTT) aggregates leading to transcriptional dysregulation, excitotoxicity, impaired axonal transport and altered synaptic transmission eventually leading to neuronal dysfunction and death (Roze et al., 2010;Harjes and Wanker, 2003). Gene expression changes in RNA and microtubule binding proteins, synaptic transmission and glutamate signalling were already shown by IPA and DAVID to be major effects of scyllo-inositol treatment. scyllo-Inositol treatment in vitro has shown to reduce mutant HTT accumulation and toxicity, although through a different mechanism compared to Aβ peptide accumulation and toxicity (Lai et al., 2014). The top upstream regulator analysis identified regulators that were important for neuronal and synaptic functions related to Alzheimer’s disease and neuropsychiatric symptoms. These results support my hypothesis that scyllo-inositol treatment alters expression of genes related to Alzheimer’s disease and neuropsychiatric.

Following the canonical pathway analysis, the disease and functions analysis provided by IPA identified broad themes that were differentially expressed between the treated and untreated samples. The top terms were neurological disease, psychological diseases, skeletal and muscular disorders, cancer, organismal injury and abnormalities, cellular assembly and organization, cellular function and maintenance, cellular development, cell-to cell signalling and interactions, cellular growth and proliferation, nervous system development and function, tissue development, organ morphology, organismal development, and embryonic development(Figure 4.2). Identification of neurological disease and psychological disorders suggested that scyllo-inositol treatment was altering gene expression in this model in a manner related to neuropsychiatric disorders. This provided evidence that this was a valid model to study scyllo-inositol treatment in the context of neurological and psychological disorders and supports my hypothesis that scyllo-

30 inositol treatment changes expression of genes related to neurodegenerative diseases and neuropsychiatric disorders. Enrichment for terms outside of neurological disease and psychological disorders was identified as well, likely due to importance of cellular proliferation, cytoskeleton, and cell to cell signalling for both neurological disease and cancer or skeletal muscular disorders. Synaptic regulation molecules such as HTT and BDNF also play important roles in development.

Overall, pathway enrichment analysis for genes more than 1.5 fold differentially expressed in treated and untreated 100 day old TgCRND8 hippocampal samples on the Affymetrix whole genome microarray system suggested the most important changes occurred in the myo-inositol signalling pathway. This supports myo-inositol depletion as an important effect of scyllo-inositol administration. Glutamatergic and dopaminergic signalling in the hippocampus may be mediating anti-agitation and anti-aggression effect of scyllo-inositol in patients.

Table 4.1 List of top enriched clusters identified by DAVID in the comparison of hippocampal samples from 100 day old TgCRND8mice treated and untreated with scyllo-inositol. The results have been filtered, removing all terms with false discovery rate higher than one. Annotation clusters 5 to 7 are not shown because no term in the cluster had FDR lower than 1. The annotation clusters are ranked by the cluster enrichment score. Enrichment Cluster # Score Term` FDR IPR012677:Nucleotide-binding, alpha-beta plait 3.91E-05 IPR000504:RNA recognition motif, RNP-1 4.35E-05 1 3.8 SM00360:RRM 4.50E-04 GO:0043005~neuron projection 0.001285 2 3.3 GO:0030424~axon 0.884637 GO:0019226~transmission of nerve impulse 0.264699 GO:0044456~synapse part 0.65476 3 2.9 GO:0007268~synaptic transmission 0.9199 4 2.4 GO:0044456~synapse part 0.65476 8 2.0 GO:0008092~cytoskeletal protein binding 0.51603

Figure 4.1Venn diagram for the top four clusters from DAVID annotation clustering for hippocampal comparison in treated and untreated 100 day TgCRND8 mice. Cluster 1 is nucleotide binding. Cluster 2 is neuronal projection. Cluster 3 and 4 are synaptic related. The numbers in the Venn diagram represent the number of probe sets. There are 52, 19, 15, and 9 probe sets unique to each cluster 1, 2, 3, and 4 respectively. Clusters 3 and 4 have 33 genes overlapping. Clusters 2, 3, and 4 have 16 probe sets overlapping. Cluster 1 has one overlapping probe set with cluster 2 and 1 with cluster 3. There are no probe sets common to all four clusters.

Figure 4.2 Summary of IPA core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. The top canonical pathways, upstream regulators and disease, and biological functions are shown. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.3 The canonical pathways that were identified by IPA core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. The ratio is the fraction of genes in the pathways that is altered by scyllo-inositol treatment. The grey bars indicate that no relationship between gene expression and pathway activation or inhibition is available for the genes that were inputted into IPA to calculate a Z-score. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.4 RhoA signalling pathway for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. A) Top, Visualization of RhoA signalling pathway in the core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. The red indicates higher gene expression in the treated samples. The green indicates lower gene expression in the treated samples. Grey means that the gene expression change did not meet the 1.5-fold change cut off. The white means that the gene was not included in the list inputted into IPA. B) Bottom, Genes of RhoA signalling pathway in the core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.5 Visualization of RhoGDI signalling pathway in the core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. The red indicates higher gene expression in the treated samples. The green indicates lower gene expression in the treated samples. Grey means that the gene expression change did not meet the 1.5-fold change cut off. The white means that the gene was not included in the list inputted into IPA. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.6 Visualization of glutamate receptor signalling pathway in the core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. The red indicates higher gene expression in the treated samples. The green indicates lower gene expression in the treated samples. Grey means that the gene expression change did not meet the 1.5-fold change cut off. The white means that the gene was not included in the list inputted into IPA. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.7Role of NFAT in regulation of the immune response pathway for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. A) Top, Visualization of NFAT pathway the red indicates higher gene expression in the treated samples. The green indicates lower gene expression in the treated samples. Grey means that the gene expression change did not meet the 1.5-fold change cut off. The white means that the gene was not included in the list inputted into IPA. B) Bottom, Genes of NFAT pathway in the core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.8 Visualization of Stathmin1 signalling pathway in the core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. The red indicates higher gene expression in the treated samples. The green indicates lower gene expression in the treated samples. Grey means that the gene expression change did not meet the 1.5-fold change cut off. The white means that the gene was not included in the list inputted into IPA. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Table 4.2 Top upstream regulators identified in the IPA core analysis for hippocampal comparison of treated and untreated 100 day old TgCRND8 mice. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity) Upstream Exp Activati p-value Target molecules in dataset Regulator Fold on z- of Change score overlap BDNF 1.258 0.036 8.12E-07 ARPP21,C5orf34,CAMK2A,CP,GAD2,GNAI1,K LC1,LYPD1,MALAT1,MAP1B,MBP,P4HA1,PO MC,PTEN,RAB14,RGS4,SORL1,SOSTDC1,SPR ED2,TAGLN,TMED2,TTC3 ADAM10 3.27E-06 ATRX,CACNA2D1,CAMK2A,DCLK1,DTNA,G AD2,GNA13,MCHR1,NR2E1,QKI,RGS4,SYT1 L-dopa -0.825 1.11E-05 ABI2,ACTA2,AI987944 (includes others),APLP1,ARPP21,CAP1,CLIC6,CLIP4,CO RO2B,DGKB,EDNRB,GABRB3,GAS7,GNA13, GPD2,GRIA2,HLA- A,HMP19,HPCA,HS6ST2,KCND2,KIAA1551,K LF6,KLF9,LDAH,LYPD1,MBP,NEDD4L,NPAS 4,PALM,PDE4DIP,PFKP,PLPPR5,RASGRP1,RB M6,REEP3,SH3GL2,SYN1,Tgoln1,ZEB2,ZMYN D8 LHX3 3.83E-05 CGA,CSHL1,POMC,PRL HTT -1.404 -0.474 4.67E-05 ARPP21,ATP2B2,BCL11B,BMP1,CAMK2A,CLI C6,COL6A1,CORO2B,DLST,EDNRB,ETNPPL, GAS7,GLUL,HBA1/HBA2,HMP19,HPCA,KLF9 ,MGP,MOBP,PLCB1,POLB,PPARGC1A,PURB, RGS4,RPH3A,Scd2,SLC1A2,SMC2,SYN1,VAM P3

4.1.2 Cortical microarray comparison between scyllo-inositol treated and untreated 100 day old TgCRND8 mice

Affymetrix microarrays were used to measure the gene expression in cortical samples from scyllo-inositol treated and untreated 100 day old TgCRND8 mice to determine the scyllo-inositol treatment effect. Comparison between 35550 probe sets were generated and analyzed with help from the Princess Margret Genomic Center. After initial filtering as described in the methods, 3406 probes remained with 57 of those probe sets more than 1.5 fold differentially expressed between cortical samples of treated and untreated TgCRDN8 mice. Of the 57 probe sets, 55 were

40 recognized by DAVID in comparison to the total 35550 probe sets that were inputted as the background controls. Functional annotation clustering analysis using DAVID identified pathways and biological processes that are most likely changed between the treated and untreated samples based on the microarray array data set (Table 4.3). The top clusters were secretory granule, membrane proteins, neuroactive ligand-receptor interaction, cell migration, synapse, and serine and threonine kinase. Membrane proteins, secretory granules neuroactive ligand-receptors are all synaptic transmission related function. Synaptic transmission pathways were also identified by DAVID analysis in the hippocampal comparison. The serine and threonine kinases that were differentially expression in the cortex were CAMK, AMP-dependent protein kinase, and cyclin dependent kinase. These are important kinases in the myo-inositol signalling pathway.

Further pathway analysis was performed using IPA to identify pathways, molecules, and biological processes that are predicted to be altered in the cortices of 100 day old TgCRND8 mice by scyllo-inositol treatment. Core analysis was performed using IPA (Figure 4.9). IPA analysis identified dopamine receptor signalling and neuroprotective role of THOP1 in Alzheimer’s disease, as the top canonical. Dopamine signalling is important in treatment of agitation and aggression as previously mentioned. Atypical antipsychotics, which target dopamine receptors, are used to treat agitation and aggression in patients with Alzheimer’s disease (Liperoti et al., 2008; Herrmann et al., 2013). Thimetoligopeptidase 1 (THOP1) is a kininase that cleaves peptides for antigen presentation. THOP1 can also cleave short peptides such as Aβ. Pollio et al. showed in TgCRND8 that THOP1 is neuroprotective response against toxicity of Aβ peptides (Pollio et al., 2008). Interactions between THOP1 and scyllo-inositol have not been reported. Even though low number of genes was used in these pathways predictions, the biological relevance of these pathways garnering evidence that the pathways identified within the cortex have validity.

IPA core analysis also generates predictions for top upstream regulators, genes, and molecules, which may not be in the microarray data set but were likely to be affected by scyllo-inositol treatment. LHX3, L-dopa, PCSK1, beta-estradiol, HTT were predicted to be top upstream regulators (Table 4.4). LHX3, L-dopa, and HTT are common between the hippocampal and cortical comparisons. LHX3 and HTT may be interacting with scyllo-inositol. L-dopa was predicted to be inhibited by IPA. Inhibition of dopamine signalling by antipsychotics can reduce

41 agitation and aggression. These results suggest that perhaps scyllo-inositol inhibits dopamine signalling resulting in anti-agitation and anti-aggressive effects. Proprotein convertase subtilisin/kexintype 1 (PCSK1) is a protease which cleaves prohormones. Expression of pro- opiomelanocortin (POMC), a target of PCSK1, was altered by scyllo-inositol treatment in the cortex. POMC is the precursor to several melanocortins, including α-MSH. α-MSH rescued spatial memory deficits and reduced anxiety by attenuating GABAergic neuronal loss in TgCRND8 (Ma and McLaurin, 2012). Rescue of GABAergic deficits by increasing expression of POMC may be another mechanism of the scyllo-inositol treatment effect. Beta-estradiol is a steroid sex hormone. Estrogen is linked with neuroprotective effects. Gender differences in Alzheimer’s disease prevalence is associated with the loss of estrogen in women post-menopause (Peri and Serio, 2008). These upstream regulators present as molecules with potential interaction with scyllo-inositol.

The disease and functions analysis provided by IPA identified broad themes that were differentially expressed between the treated and untreated samples. The top diseases and biological functions were cancer, endocrine system disorders, organismal injury and abnormalities, reproductive system disease, neurological disease, molecular transport, nucleic acid metabolism, small molecule biochemistry, cell morphology, cell-to-cell signalling and interactions, endocrine system development and function, nervous system development and function, organ morphology, tissue morphology, and organismal development. Neurological disease, cancer, organismal injury and abnormalities, cell-to-cell signalling and interactions, nervous system development and function, organ morphology, and organismal development were also identified in the hippocampal comparison. Some of these results were not as specific to categories relevant to Alzheimer’s disease and neuropsychiatric symptoms as in the hippocampal comparison, perhaps due to the low number of genes that met the filtering requirements or the effect of scyllo-inositol treatment on the brain may be different from in the hippocampus. Pathway analysis DAVID and IPA identified pathways in the cortical comparison similar to the hippocampal comparison such as dopamine signalling and synaptic transmission but different pathways such as neuroprotection through PCSK1, THOP1, and beta-estradiol.

The number of differentially expressed probe sets that met the filtering requirements in the cortical comparison of treated and untreated 100 day old TgCRND8 mice was fewer than in the hippocampal comparison. To investigate the relation between the hippocampal and cortical

42 scyllo-inositol treatment effect, the probe sets ID from the filtered comparisons were compared. 57 probe sets from the cortical comparison met the filtering criteria while 806 probe sets from the hippocampal comparison met the filtering criteria. Of these probe sets, 24 probe sets were differentially expressed in both the hippocampus and cortices of treated mice compared to untreated littermates (Figure 4.10). The expression change in the hippocampus and cortices of the 24 common probe sets were of compared (Figure 4.11). The line of best fit showed that hippocampal and cortical gene expression were correlated for the commonly affected genes. The expression change in the cortex was approximately 67% of hippocampal expression change. In summary, the cortical treatment effect had components that were strongly correlated to the hippocampal treatment effect, but also contained distinct changes. The cortical treatment effect is weaker than the hippocampal treatment for genes that were altered in both comparisons.

Table 4.3 List of top enriched clusters identified by DAVID in the cortical comparison of treated and untreated 100 day old TgCRND8 samples. Only terms with FDR less than 40 are shown. The annotation clusters are ranked by the cluster enrichment score. FDR for each term is calculated individually by DAVID. Cluster # Enrichment Score Term FDR GO:0030141~secretory granule 0.3787 GO:0005179~hormone activity 1.957 Hormone 15.74 GO:0031410~cytoplasmic vesicle 23.79 1 1.7 GO:0031982~vesicle 25.52 3 0.7 mmu04080:Neuroactive ligand-receptor interaction 15.43 7 0.6 GO:0044459~plasma membrane part 35.04 9 0.3 SM00220:S_TKc 36.09

Figure 4.9 Summary of IPA core analysis for cortical comparison of treated and untreated 100 day old TgCRND8 mice. The top canonical pathways, upstream regulators and disease, and biological functions are shown. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Table 4.4 Top upstream regulators identified in the IPA core analysis for cortical comparison of treated and untreated 100 day old TgCRND8 mice. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity) Upstream Predicted Activation p-value of Target molecules in dataset Regulator Activation State z-score overlap LHX3 6.40E-07 CSHL1,POMC,PRL L-dopa Inhibited -3.148 3.52E-06 ARC,CAP1,CLIC6,DLK1,ECE L1,HLA- A,HMP19,KCNA5,PPP1R1B,S LC10A4 PCSK1 7.15E-06 CSHL1,POMC beta- 0.218 9.74E-06 ARC,CSHL1,POMC,PRL estradiol HTT 1.22E-05 CLIC6,DRD2,ETNPPL,HBA1/ HBA2,HMP19,NTS,PDE10A,P PP1R1B

Figure 4.10 Venn diagram showing common probe sets between the hippocampal and cortical comparisons of scyllo-inositol treatment effect in 100 day old TgCRND8 mice. 782/784 probe sets were unique to the hippocampal comparison while 33/57 probe sets were unique to the cortical comparison. 24 probe sets were common between the two comparisons.

Comparison of cortical and hippocampal scyllo-inositol treatment effect in 100 day old TgCRND8 mice 2 2 5 4 3 y = 0.672x 2 R² = 0.945

1 fold change) fold 0 -4 -2 -1 0 2 4 6 8

Cortical gene expression change (log change expression gene Cortical -2 Hippocampal gene expression change (log2 fold change)

Figure 4.11 Graph of the fold change of the common probe sets between the cortical and hippocampal gene expression changes in 100 day old TgCRND8 treated with scyllo-inositol. Only the probe sets that have gene expression change greater than 1.5 folds in both the hippocampal and cortical comparisons were included in this graph. 24 probe sets from the overlapping regions of Figure 4.10 are plotted. The X-value is the logarithm to the base two of the fold change in the hippocampus between treated and untreated 100 day old TgCRND8 mice while the Y-value is the logarithm to the base two of the fold change in the cerebral cortex between treated and untreated TgCRND8 mice.

4.1.3 Primer design, quality control, and choosing internal control for qPCR

The microarray analysis of global gene expression changes concluded that synaptic transmission changes and pathways related to myo-inositol signalling were altered by scyllo-inositol treatment. Replication of the microarray experimental design with reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used to investigate the changes in gene expression for pre-synaptic and post-synaptic pathways. Synaptotagmin (Syt1), syntaxin (Stx1a), synapsin (Syn1), and synaptotagmin (Syp) were chosen as representative pre-synaptic genes. These

46 proteins are present at the pre-synaptic membrane and are required for vesicular release of neurotransmitter. NMDAR (Grin1), AMPAR (Gria3, Gria4), post synaptic density protein 95 (PSD95) (Dlg4) were chosen to detect changes in post synaptic genes. NMDAR and AMPAR are ionotropic glutamate receptors. PSD95 is a membrane bound kinase that clusters at the post synaptic density of neurons with ionotropic glutamate receptors and potassium channels. Ca+/Calmodulin dependent kinase (Camk2a, Camk4), phosphatidylinositol 3-kinase (Pik3r2), phosphatase and tensin homolog (Pten), protein kinase B (Akt1), protein kinase C (Prkce), cAMP response elements binding (Creb3), and CREB binding protein (Crebbp) were chosen to detect changes in downstream signalling after treatment with scyllo-inositol. By evaluating the expression of these genes with RT-qPCR, synaptic and signalling pathways identified in the microarray analysis can be verified.

The primers for the target and control genes were designed using NCBI primer blast (Ye et al., 2012). Full list of primers as well as details for quality control process can be found in section 3.6 of the materials and methods. The target primers were checked to ensure the presence of only a single predicted product (Figure 4.12). All primers had amplification efficiency between 90- 110% (Table 4.5). All primers only produced a single melt curve peak (Figure 4.13). This indicated that each primer pair only produced a single product. The size of PCR products were determined by agarose gel electrophoresis (Figure 4.14). All the sizes of the target products matched the predicted size, indicating that the primers were amplifying the intended target gene. When primers did not meet quality control, a new primer was designed and tested. All primers that were used had amplification efficiency close to 100% and were specific to the targeted gene.

Control genes were used to account for total cDNA differences between samples. Eight controls genes were chosen from different pathways. The best two controls were determined for each comparison and used in to control for total cDNA amount. Multiple controls ensure that the control gene used to balance the loading is not affected by the treatment. Glyceraldehyde 3- phosphate dehydrogenase (Gapdh), Phosphoglycerate Kinase 1 (Pgk1), Succinate dehydrogenase complex (Sdha), and Hypoxanthine-guanine phosphoribosyltransferase (Hprt) are part of metabolic pathways. TATA-binding protein (Tbp) is involved with transcriptional initiation. Peptidylprolyl isomerase A (Ppia) is involved in intracellular signalling. β₂ microglobulin (B2m) is a structural protein. Ribosomal Protein L13a (Rpl13a) is part of the protein synthesis complex. The consistency between the control genes was an indication for RNA degradation. RNA levels

47 of all eight control genes for each comparison were measured using RT-qPCR. Expressions of all the controls were inputted into BestKeeper program to determine the most consistent control gene (Table 4.6). BestKeeper uses Pearson correlation coefficients to compare the control genes to each other (Table 4.7). Ct is the interpolated cycle number at which the fluorescent value detected by the sensors reach a threshold value. Ct is inversely proportional to the log of the concentration of the cDNA of the gene of interest. ∆∆Ct is the determination of how much the expression for a gene of interest is changed between two treatment groups by comparing the differences between the gene of interest and the control genes in both groups. The difference between the differences between the gene of interest and the control gene is why the method is called ∆∆Ct. The 2 most consistent gene was used for ∆∆Ct measurements in the following sections.

Standard curve for Gapdh 25 20 15

Ct y = -3.320x + 15.42 R² = 0.992 10 5 0 -2 -1.5 -1 -0.5 0 0.5 Logarithm of relative concentration of cDNA

Figure 4.12 Sample standard curve plot used to calculate the efficiency. This curve is for Glyceraldehyde 3-phosphate dehydrogenase (Gapdh). The logarithm of the relative concentration of cDNA is plotted against the Cycle threshold (Ct) value in triplicate. The line of best fit is performed on Microsoft Excel.

Figure 4.13 A sample melt curve plot showing only one peak. This one is Ppia primer set. The red line shows the derivative of the florescence signal. The vertical blue line shows the temperature at the maxima of the red line. The graph is generated with Applied Biosystems QuantStudio™.

Table 4.5 The efficiency and melt curve peak temperature for all of the primers used. The efficiency is calculated in Microsoft Excel. Efficiency Melt curve LINEST (%) peak (°C) A kt1 -3.19731 105.4767 81.6 B2m -3.24194 103.4499 81.7 Camk2a -3.19185 105.7302 89.4 Camk4 -3.19475 105.5953 85.2 Creb3 -3.21955 104.4574 83.5 Crebbp -3.17818 106.3695 80.6 Dlg4 -3.18954 105.8378 80.4 Gapdh -3.32086 100.0447 84.6 Gria3 -3.28709 101.4746 78.2 Gria4 -3.25338 102.9422 78.6 Grin1 -3.19254 105.6982 87.4 Hprt -3.23031 103.9706 80.8 Pik3r2 -3.18975 105.8278 84.7 Pkg1 -3.1289 108.7376 82.7 Ppia -3.42721 95.78655 79.7 Prkce -3.18219 106.1811 81.6 Pten -3.18864 105.8798 81.6 Rpl13a -3.1414 108.1272 85.4 Sdha -3.29077 101.3169 85.4 Stx1a -3.36839 98.09695 85.4 Syt1 -3.2547 102.884 78.5 Syn1 -3.19153 105.745 84.3 Syp -3.4344 95.5114 80.4 Tbp -3.15826 107.3147 83.1

Figure 4.14 Agarose gel of PCR products for each primer pair. The name of the gene and the size of the product are given in green. The size of the ladder is given in yellow. All PCR products were the expected size.

Table 4.6 Sample average Ct values from rt-qPCR of all eight control genes of 10 samples. This sample is the hippocampal samples from treated and untreated 150 day old TgCRND8. Samples 1 to 5 are treated with scyllo-inositol. Samples 6-10 are untreated. The numbers in the graph represent Ct values. CP data input: gapdh tbp ppia b2m rp113 hprt sdha pgk1 sample 1 19.604 27.466 20.711 24.099 20.959 23.789 21.737 22.599 sample 2 19.612 27.849 20.943 24.195 20.818 23.980 22.021 23.130 sample 3 19.672 27.532 20.764 23.947 20.889 23.679 21.699 22.649 sample 4 19.685 28.014 21.143 23.963 20.761 24.204 22.412 23.084 sample 5 19.095 27.309 20.334 23.046 20.215 23.566 21.430 22.287 sample 6 19.240 27.376 20.368 23.360 20.521 23.519 21.448 22.477 sample 7 18.859 27.000 20.128 22.932 20.325 23.087 21.033 22.066 sample 8 18.565 27.150 20.262 23.543 20.671 23.381 21.422 22.252 sample 9 19.398 27.539 20.638 23.841 20.704 23.522 21.317 22.438 sample 10 19.617 27.369 20.780 23.737 20.829 23.694 21.619 22.820

Table 4.7 Analysis by BestKeeper of the data from table 4.6. The pair wise Pearson correlation coefficients were calculated between control primers. At the bottom in red are the controls compared to the idea control determined by BestKeeper. Pearson correlation coefficient ( r ) vs. gapdh tbp ppia b2m rp113 hprt sdha pgk1 HKG 2 0.769 ------p-value 0.009 ------HKG 3 0.878 0.928 ------p-value 0.001 0.001 ------HKG 4 0.734 0.760 0.851 - - - - - p-value 0.016 0.011 0.002 - - - - - HKG 5 0.655 0.535 0.725 0.932 - - - - p-value 0.040 0.111 0.018 0.001 - - - - HKG 6 0.779 0.939 0.935 0.762 0.588 - - - p-value 0.008 0.001 0.001 0.010 0.073 - - - HKG 7 0.680 0.908 0.900 0.721 0.572 0.971 - - p-value 0.031 0.001 0.001 0.019 0.084 0.001 - - HKG 8 0.810 0.901 0.946 0.794 0.657 0.927 0.908 - p-value 0.004 0.001 0.001 0.006 0.039 0.001 0.001 -

BestKeeper vs. gapdh tbp ppia b2m rp113 hprt sdha pgk1 coeff. of corr. [r] 0.877 0.923 0.986 0.899 0.778 0.946 0.911 0.954 p-value 0.001 0.001 0.001 0.001 0.008 0.001 0.001 0.001

4.1.4 qPCR comparison between scyllo-inositol treated and untreated 100 day old TgCRND8 mice

Replication of the initial microarray study looking at hippocampus and cerebral cortex of treated and untreated 100 day old TgCRND8 mice was done using RT-qPCR. Animals were treated for 30 days with scyllo-inositol ad libitum starting at 70 days of age and brain samples were collected at 100 days of age. This treatment regime would be translated to prophylactic treatment of patients. The results from the microarray study concluded that synaptic transmission and signalling pathways related to them were altered in the hippocampus and cortex. Fewer genes met the cut off in the cortical compared to the hippocampal comparison. Genes common between the two comparisons showed greater fold change in the hippocampal comparison than the cortical comparison. Therefore, I hypothesized that the synaptic and signalling genes will be differentially regulated in the hippocampus and the cortex. I also hypothesized that the effect in the cortex will be less than in the hippocampus.

Further analysis looking at the individual animals was done using hierarchical clustering on MultiExperiment Viewer (MeV) (Eisen et al., 1998). Hierarchical clustering compares the gene

53 expression between animals and produces a tree, which helps visualize the similarity between animals. Animals those were more similar to each other cluster into one branch of the tree. The vertical length of the branches represents amount of difference between gene expression patters between animals. Similarly, clustering of the genes was performed by comparing the expression of one gene in all the animals to the expression of another gene in all the animals. Clusters of genes indication that genes are similarly expressed across the different animals. Hierarchical clustering of the individual animals with MeV showed that the animals separated into two distinct groups (Figure 4.16a). Untreated animals (reg1-6) clustered together in one branch. The treated animals also clustered together indicating they were more similar to each other than the untreated cluster. However, one of the untreated animals showed gene expression levels that were more similar to the treated animals than the other untreated animals. Clustering of the genes showed that the majority of the genes clustered together with the exception of Gria4, Gria3, Prkce, and Creb3. Pten,Pik3r2, and Syn1clustered closer to the scyllo-inositol responsive genes that to Gria4, Gria3, Prkce, and Creb3, suggesting they may have been affected by scyllo- inositol treatment but the changes were not detectable due to biological variation between animals. Variations between animals can have numerous causes. The low numbers of animals that were used in this experiment makes it difficult to investigate the variation within the treatment groups. Even with the variation, it is still evident that gene expression changes were detected for pre-synaptic, post-synaptic, and signalling genes in the hippocampus of scyllo- inositol treated TgCRND8 compared to untreated littermates.

Gene expression in the cortex of 100 day old TgCRND8 mice treated with scyllo-inositol for 30 days were compared with gene expression in the hippocampus of untreated littermates. No genes were significantly altered after correcting for multiple testing (Figure 4.15). Without correction, Pik3r2 was significantly down regulated in the cortex of 100 day old TgCRND8 mice after scyllo-inositol treatment. Hierarchical clustering of the individual animals with MeV showed no pattern in animals or genes (Figure 4.16b). scyllo-Inositol treatment had significant effects on pre-synaptic, post-synaptic, and signalling genes in the hippocampus but not the cortex in the TgCRND8 mouse model of Alzheimer’s disease at the onset of plaque deposition.

Gene expression determined by qPCR in the hippocampus and cortex of 100 day old TgCRND8 mice 4

Hippocampus inositol

- 1 Cortex scyllo

0.5

Syp

Syt1

Pten

Dlg4

Akt1

Syn1

Prkce

Grin1 Gria4 Gria3

Stx1a

Creb3

Pik3r2

Camk4

Crebbp Camk2a Fold change of gene expression after treatment with treatment after expression gene of change Fold

Figure 4.15 The fold difference in gene expression on the scyllo-inositol treated group compared to the untreated littermates. The red star above the bar indicates p<0.05 using ttest function in Microsoft Excel with Benjamini–Hochberg correction.

A) B)

Figure 4.16 Hierarchical clustering of the RT-qPCR data with MeV for A) hippocampal samples and B) cortical samples. The expression of each gene is normalized to one. The red mean the gene was expressed higher than the average expression in that animal. The green means that the gene expression is lower than average in that animal. The vertical line for the animal clustering and the horizontal line for the gene clustering indicate the branch length, a visual representation of the amount of difference between clusters. Reg indicates the animals were untreated while SI indicates that the animal was treated with scyllo-inositol.

4.1.5 qPCR comparison between scyllo-inositol treated and untreated 150 day old TgCRND8 mice

Alzheimer’s disease is a progressive neurodegenerative disease, meaning the disease becomes more serious over time. The TgCRND8 model shows increased amyloid load in the brain over time. In addition, scyllo-inositol treatment in the 100 day TgCRND8 models prophylactic treatment. This requires treatment to start before detectable symptoms appear in patients. Treatment often starts after the onset of plaque deposition. Initial hippocampal amyloid deposition starts around 100 days of age, so studying scyllo-inositol treatments starting at 120

56 days will allow shown gene expression changes in a model with Aβ peptide deposition in the hippocampus at the start of the treatment.120 day old TgCRND8 were treated for 30 days with scyllo-inositol to investigate effect of scyllo-inositol treatment on animals with plaque load before the start of the treatment. The same pre-synaptic, post-synaptic, and signalling genes were investigated as previous were used to gauge the effect of the treatment on the hippocampus and the cerebral cortex.

Gene expression in the hippocampus of 100 day old TgCRND8 mice treated with scyllo-inositol for 30 days were compared with gene expression in the hippocampus of untreated littermates using student’s t-test with Benjamini–Hochberg correction. Details of statistical analysis can be found in section 3.7 of the materials and methods. Syt1, Stx1a, Syn1, Syp, Dlg4, Grin1, Camk2a, Camk4, Pten, Akt1, Crebbp, and Prkce were up regulated in the hippocampus by scyllo-inositol treatment (Figure 4.17). Expression of Gria4, Gria3, and Creb3 were not significantly different between the hippocampus of TgCRND8 treated with scyllo-inositol compared with untreated littermates. Compared to the 100 day old TgCRND8 mice, more genes were up regulated in the 150 day old TgCRND8 mice. All of the genes that were up regulated in the 100 day old TgCRND8 were up regulated in the 150 day old TgCRND8 (Figure 4.18a). Additionally, Syn1, Pten, Akt1, Pik3r2 were not up regulated in the hippocampus of 100 day old but were up regulated in the 150 day old TgCRND8 mice. The fold change in gene expression was numerically greater for all genes except Dlg4 in 150 day old compared to 100 day old TgCRND8 mice. Although only treatment effect in the hippocampus is significantly different for Gria3 and Crebbp were significantly different between 150 day old and 100 day old TgCRND8 mice (Figure 4.19). There is a greater hippocampal treatment effect in the 150 day old TgCRND8 mice compared to the 100 day old, both in terms of number of genes and in terms of the fold change. This could be due to greater scyllo-inositol effect or greater Aβ effect in the 150 day old TgCRND8. If there are more genes altered by the increased accumulation of Aβ peptides in the hippocampus, then reversing the gene expression changes caused by Aβ peptides with scyllo- inositol will result in a greater gene expression change.

Further analysis looking at the individual animals was done using hierarchical clustering on MultiExperiment Viewer (MeV). Hierarchical clustering compares the gene expression between animals and produces a tree that helps visualize the similarity between animals as previously explained. Hierarchical clustering of the genes showed that all the altered genes except Prkce

57 clustered together. This same clustering pattern was detected in 100 day old TgCRND8 mice. Although fewer genes showed statistically different expression in the hippocampus of 100 day old TgCRND8 mice compared to the 150 day old TgCRND8, the clustering pattern was the same in both. This suggested that changes in Syn1, Pten, Akt1, and Pik3r2were likely present but the effect on the gene expression was too small to be detected. Hierarchical clustering of the individual animals with MeV showed that the animals separated into two distinct groups. However, one treated animal and one untreated animal did not cluster with their respective groups. Variations between animals can have numerous causes. The low numbers of animals that were used in this experiment makes it difficult to investigate the variation within the treatment groups. Even with the variation, it is still evident that gene expression changes were detected for pre-synaptic, post-synaptic, and signalling genes in the hippocampus of scyllo-inositol treated 150 day old TgCRND8 compared to untreated littermates.

Cortical treatment effect in the 150 day old TgCRND8 was similar to the effect in the 100 day old TgCRND8 mice. Gene expression in the cortex of 150 day old TgCRND8 mice treated with scyllo-inositol for 30 days were compared with gene expression in the hippocampus of untreated littermates. No genes were significantly altered after correcting for multiple testing (Figure 4.17). Without correction, Syt1, Gria4, Gria3 were down regulated by scyllo-inositol. Hierarchical clustering of the individual animals with MeV did not show two distinct groups (Figure 4.18b). Furthermore, the treated animals did not cluster together. The clustering does not group Syt1, Gria4, and Gria3together in one group. These results showed no detectable cortical scyllo- inositol treatment effect in the 150 day old TgCRND8. scyllo-Inositol treatment has significant effects on synaptic and signalling genes in the hippocampus but not the cortex in 100 day old and 150 day old mice TgCRND8 mice.

Comparison between the 100 and 150 day old TgCRND8 showed that there is likely a greater treatment effect in animals with amyloid load at onset of treatment. This could be due to increased pathology and dysfunction being present in the older animals. The increased amyloid plaques mean there is more Aand a greater gene expression change for the scyllo-inositol treatment to counter act. Studying scyllo-inositol treatment effect in older TgCRND8 mice with established amyloid pathology may show greater gene expression changes.

Gene expression determined by qPCR in the hippocampus and cortex of 150 day old TgCRND8 mice 4

inositol - Hippocampus

scyllo 1 Cortex

0.5

treatment with treatment

Syp

Syt1

Pten

Dlg4

Akt1

Syn1

Prkce

Grin1 Gria4 Gria3

Stx1a

Creb3

Fold change of gene expression after after expression gene of change Fold

Pik3r2

Camk4 Crebbp

Camk2a

Figure 4.17 The fold difference in gene expression on the scyllo-inositol treated group compared to the untreated control in 150 day old TgCRND8. The red star above the bar indicates p<0.05 using ttest function in Microsoft Excel with Benjamini–Hochberg correction.

A) B)

Figure 4.18Hierarchical clustering of the RT-qPCR data with MeV for A) hippocampal samples and B) cortical samples. The expression of each gene is normalized to one. The red mean the gene was expressed higher than the average expression in that animal. The green means that the gene expression is lower than average in that animal. The vertical line for the animal clustering and the horizontal line for the gene clustering indicate the branch length, a visual representation of the amount of difference between clusters. Reg indicates the animals were untreated while SI indicates that the animal was treated with scyllo-inositol.

Comparison of scyllo-inositol treatment effect in the

hippocampus between 100 and 150 day old TgCRND8 inositol - 1.6

scyllo 100 day 150 day

0.8

treatment with with treatment Fold change of gene expression after after expression gene of change Fold

Figure 4.19 The hippocampal 100 and 150 day old TgCRND8 qPCR data together. The red star above the bar indicates the gene expression is significantly different between the100 day old animals and 150 day old animals p<0.05 using ttest function in Microsoft Excel.

4.1.6 Hippocampal microarray comparison between scyllo-inositol treated and untreated 200 day old TgCRND8 mice

The 200 day time point was chosen for further studies as it better represented Alzheimer’s disease at clinical onset. The amyloid load in the brain of 200 day old TgCRND8 mice is comparable to human patients when they are typically diagnosed with probably Alzheimer’s disease (Chishti et al., 2001). Data from single microarray comparisons are venerable to potentially erroneous results due to random chance. Multiple microarrays together have a much lower chance of being erroneous on pathways or regulators that show up in multiple analyses. I expect many similar results from the analyses compared to the 100 day TgCRND8 comparison. Comparison of synaptic and signalling gene expression in 100 and 150 day old TgCRND8 by RT-qPCR suggested that gene expression changes in the 200 day old TgCRND8 mice will be

61 greater than the 100 day old TgCRND8 mice. Therefore, I also expected that the gene expression changes would be greater in the hippocampus of 200 day old TgCRND8 than 100 day old TgCRND8 mice.

TgCRND8 mice were given scyllo-inositol at 170 days of age until they were sacrificed at 200 days of age. Affymetrix microarrays were used to measure the gene expression in hippocampal samples from scyllo-inositol treated and untreated 200 day old TgCRND8 mice to determine the scyllo-inositol treatment effect. An increased fold change cut off was used for studying 200 day old animals to keep the number of probe sets similar to the previous analysis. Larger number of probe sets is recommended by functional annotation programs as they most significant gene expression changes are buried under less significant gene expression changes. After filtering, 541 probe sets that were differentially expressed by at least a two-fold change. These 541 probe sets were inputted into DAVID, which recognized 514 of those probe sets. Functional annotation clustering analysis using DAVID identified pathways and biological processes that are most likely changed between the treated and untreated samples based on the microarray array data set (Table 4.8). RNA binding motifs, neuronal projection, voltage-gated channels, synaptic transmission, and circulatory system processes were the clusters identified by DAVID. The effect on genes that express proteins with RNA binding motifs and genes important for synaptic transmission and neuronal projection are enriched similar to the 100 day old TgCRND8 comparison. Potassium, calcium, and sodium channels were all differentially expressed between treated and untreated 200 day old TgCRND8. Copy number variation of voltage gated calcium channels have been linked to increased risk of Alzheimer’s disease (Villela et al., 2016). Voltage-gated channels are also involved in synaptic transmission, on both the pre-synaptic and post synaptic membrane. Voltage-gated channels are also required for the propagation of action potentials through the axon. Synaptic dysfunction causes cognitive and behavioural symptoms of Alzheimer’s disease (Marcello et al., 2012). Circulatory system processes were an unexpected cluster. DAVID indicted more uncertainty with the functional terms in this cluster, higher false discovery rate than the other clusters. Changes in α-MSH, voltage-gated calcium and potassium channels, and nischarin led to the prediction of circulatory system processes by DAVID. α-MSH and voltage channels have already been discussed and are important in Alzheimer’s disease and neuropsychiatric symptoms. Nischarin is a noradrenergic imidazlin-1 receptor that affects cytoskeletal organization (Sano et al., 2002). Although nischarin is present in cardiac tissue,

62 expression of nischarin is also present in neurons where nischarin plays a role in Rho mediated cell motility in neurons (Ding et al., 2013). Since the RNA in the comparison was isolated from the hippocampus, it is unlikely to be measuring changes in circulatory system process. It is far more likely that similar pathways that play a role in both circulatory processes and neuronal functions were altered. Functional enrichment processes can make biologically irrelevant predictions that need to be filtered out based on knowledge of the biological context. Overall, functional annotation clustering with DAVID showed that the similar neuronal related clusters were identified in the hippocampal 200 day old TgCRND8 mice comparison and the hippocampal 100 day old TgCRND8 mice comparison.

Further pathway analysis was performed using IPA to identify pathways, molecules, and biological processes that are predicted to be altered in the hippocampus of 200 day old TgCRND8 mice by scyllo-inositol treatment. Of the 6199 probes inputted into IPA, 5906 of those probe sets were mapped to genes by IPA and 576 of the mapped genes met the 1.5 fold change cut off. Core analysis was performed using IPA (Figure 4.20). Calcium signalling was a top canonical pathway for both the 100 and 200 day old TgCRND8 hippocampal comparisons. This supports the role of myo-inositol depletion by scyllo-inositol treatment regulating calcium signalling through the myo-inositol signalling pathway. Another pathway that was identified in both 100 day and 200 day hippocampal comparison is the role of NFAT in regulation of the immune response. Changes in myo-inositol signaling were again indicated, in the same way as was shown in the hippocampal comparison in 100 day old TgCRND8 mice. This pathway indicated changes in MHC class II and myo-inositol signaling pathways. The other canonical pathways were not enriched in the hippocampal comparison of 100 day old TgCRND8 mice. However, the role of NFAT in cardiac hypertrophy pathway is similar to the role of NFAT in regulation of the immune response. The signalling pathways for NFAT are still through PLC, Protein kinase A (PKA), CAMK, AKT but with IL6 instead of MHC class II. Identification of autoimmune thyroid disease signalling enrichment was based on increases in MHC and glycoprotein hormone peptide alpha. Increase in MHC expression was likely caused by Aβ peptide accumulation in the brain leading to astrogliosis and microgliosis (McLaurin et al., 2006). Glycoprotein hormone peptide alpha is the identifiable half of human chorionic gonadotropin, luteinizing hormone, follicle-stimulating hormone, and thyroid-stimulating hormone. Hormone processing was enriched in the hippocampal comparison of 100 day

TgCRND8 with changes in POMC. Regulation of gonadotropin-releasing hormone by neurotransmitters epinephrine, norepinephrine, or dopamine has been long since recognized (Swartz and Moberg, 1986; Liu and Herbison, 2013). These changes can be caused by the modulation of neurotransmitter release. Sildenafil is an inhibition of cGMP degradation. The changes in gene expression in this pathway due to scyllo-inositol treatment were voltage gated sodium and potassium channels, PLC, PKA, myosin, and actin. These familiar pathways are involved in neuronal projection, myo-inositol signalling, and synaptic transmission. Interestingly, sildenafil can improve cognition in transgenic mouse of Alzheimer’s disease through cytoskeletal changes and BDNF without affecting Aβ peptide accumulation (Cuadrado-Tejedor et al., 2011). Canonical pathways identified a wild variety of pathways although the genes that were altered in these pathways mostly related to myo-inositol signalling, similar to the treatment effect analysis in the 100 day old TgCRND8 mice. One exception was autoimmune thyroid disease signaling pathways that was enriched due to immune and hormonal changes.

IPA core analysis also generates predictions for top upstream regulators, genes, and molecules. Several of the predicted top upstream regulators were similar to those predicted for 100 day old TgCRND8 mice, such as BDNF, ADAM10, and LHX3. Repeated identification of pathways and regulators are less likely due to random chance. These three genes are important effects of scyllo- inositol effect in TgCRND8 mice. BDNF and neurogenesis has been shown to be affected by scyllo-inositol treatment but the link to ADAM10 and LHX3 is unclear(Morrone et al. submitted). ROR1 and ROR2 are receptor tyrosine kinase-like orphan receptors and play a role in Wnt signalling. ROR1-ROR2 complex has been shown to modulate synapse formation in hippocampal neurons (Paganoni et al., 2010). Down regulation of either receptor led to decrease synapse formation. Wnt signalling through ROR activates calcium response through PLC cleavage of PIP2 (Mill and George, 2012). These results indicate that pathways activated in the 200 day old TgCRND8 are similar to the pathways activated in the 100 day old TgCRND8. myo- Inositol signalling is enriched in the hippocampal comparison between treated and untreated 200 day old TgCRND8 as well.

In addition to the canonical pathway analysis, the disease and functions analysis provided by IPA identified broad themes that were differentially expressed between the treated and untreated samples. The top terms were neurological disease, psychological disorder, skeletal muscular disorder, hereditary disorder, organismal injury and abnormalities, cellular assembly and

64 organization, cellular function and maintenance, cellular development, cellular growth and proliferation, cell-to-cell signalling and interaction, nervous system development and function, organ development, tissue development, tissue morphology. Neurological and psychological diseases were the top disease and disorders identified by IPA in both the hippocampal 100 and 200 day old TgCRND8 comparisons. Single appearances of enriched terms can be due to random change, but it is much more unlikely that terms reappear multiple times when they are erroneous. This strongly supports my hypothesis that scyllo-inositol affects expression of genes that play a role in Alzheimer’s disease and neuropsychiatric symptoms. The top cellular functions identified by IPA were identical for both the hippocampal 100 and 200 day old TgCRND8 comparisons. The physiological system development and function was also almost identical. The top disease and biological functions identified by IPA showed that the scyllo-inositol treatment effect in 100 and 200 day old TgCRND8 are highly related and both affect genes related to neurological disease, psychological disorders, and nervous system development and function.

Both the DAVID and IPA analyses indicated high similarities between the gene expression changes after scyllo-inositol treatment in the 100 day old and the 200 day old TgCRND8 mice. A direct comparison of the probe sets between the treatment effect in 100 and 200 day old hippocampal TgCRND8 mice was done to further investigate the common treatment effect in TgCRND8 mice. The common genes represent the effect of scyllo-inositol treatment regardless of disease progression in the brain. The 541 probe sets from the 200 day comparison were compared to the 806 probe sets of the 100 day old animals. Of those probe sets, 399 were differentially expressed in both hippocampal comparison of treated and untreated 100 day and 200 day old TgCRND8 mice (Figure 4.21). The gene expression fold change after scyllo-inositol treatment between the hippocampal comparisons of 100 day old and 200 day old TgCRND8 were compared (Figure 4.22). The coefficient of determination is close to one, indicating a strong dependence of the fold changes in the different aged animals. The slope of the line is 1.464, which means that the treatment effect was on average 1.464 times greater in the 200 day old animals than the 100 day old TgCRND8 mice. This result agrees with the numerical increase in gene expression change in the between the comparison of treated and untreated 100 and 150 old TgCRND8 mice by qPCR. The larger age difference between the 100 and 200 day old TgCRND8 resulted in a larger difference in gene expression fold change. To determine what pathways these 399 genes were involved in, functional annotation clustering with DAVID was

65 performed. The top clusters were RNA binding motifs, neuronal projection, GTP binding, regulation of blood pressure and microtubule binding proteins. Synaptic and C2 domains were the 13th and 14th clusters. Although synaptic genes are highly enriched in both the individual comparisons, the overlapping genes did not show as much enrichment in synapse or synaptic transmission clusters. This suggest that the changes to the synapse and synaptic transmission pathways is not identical in the hippocampus of 100 and 200 day old TgCRND8 mice. The genes that are affected as the disease progresses are not the same throughout time. Interaction of scyllo- inositol treatment effect on expression of synaptic related genes and Aβ pathology in TgCRND8 mouse model is affected by the progression of the disease. Another cluster identified was blood pressure pathways. This pathway was identified due to gene expression changes of myosin, PLC, POMC, voltage-gated channels, actin and nischarin. As previously discussed, these genes also have a role in the neurons alongside having a role in regulating blood pressure. GTP binding proteins, such as Rho and Rac, have been identified in IPA analysis of 100 day old treated and untreated TgCRND8 to mediate scyllo-inositol signalling effects. Microtubule associated protein and neuronal project greatly overlap. These gene are altered by scyllo-inositol treatment in the hippocampus of both 100 and 200 day old TgCRND8 mice Lastly, genes of proteins with RNA binding motif was identified to be the major scyllo-inositol treatment effect. These genes include RNA binding region (RNP1, RRM) containing three, CUG triplet repeat, RNA binding protein 2, and RNA binding motif protein 11/16/18/25 are all involved in RNA splicing. RNA binding proteins changes suggest that scyllo-inositol treatment can modulate RNA splicing. In summary, the genes altered in the hippocampus by scyllo-inositol treatment were similar for 100 and 200 day old TgCRND8. RNA splicing, neuron projection, cytoskeletal genes, and myo-inositol and calcium signalling were all conserved features of scyllo-inositol treatment effect. Treatment in the 200 day TgCRND8 with scyllo-inositol resulted in greater fold gene expression changes than in the 100 day TgCRND8.

Table 4.8 Clustering of annotation from DAVID of hippocampal comparison of treated and untreated 200 day old TgCRND8. Only terms with FDR less than 1 are shown Enrichment Cluster # Score Term FDR IPR000504:RNA recognition motif, RNP-1 0.028 IPR012677:Nucleotide-binding, alpha-beta plait 0.121 1 2.9 SM00360:RRM 0.358 2 2.8 GO:0043005~neuron projection 0.296 voltage-gated channel 0.097 ionic channel 0.427 GO:0022832~voltage-gated channel activity 0.523 GO:0005244~voltage-gated ion channel activity 0.523 GO:0046873~metal ion transmembrane transporter activity 0.547 6 2.0 GO:0005261~cation channel activity 0.989 GO:0007268~synaptic transmission 0.027 GO:0019226~transmission of nerve impulse 0.370 8 1.9 GO:0007267~cell-cell signalling 0.502

Figure 4.20 Summary of IPA core analysis for hippocampal comparison of treated and untreated 200 day old TgCRND8 mice. The top canonical pathways, upstream regulators and disease, and biological functions are shown.(IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.21 diagram showing common probe sets between hippocampal comparison of 100 and 200 day old TgCRND8 mice treated and untreated. 407/806 probe sets were unique to the 100 day old comparison while 142/541 were unique to the 200 day comparison. 399 probe sets were common between the two comparisons.

Hippocampal 200 day old vs 100 day old scyllo-inositol

treatment effect in TgCRND8 mice 2

(log 3

2 untreated 1 y = 1.464x R² = 0.976 0

fold changein fold gene expression) -1 -0.5 0 0.5 1 1.5 2 200 day treated vs day 200 treatedvs -1 100 day treated vs untreated (log2 fold change in gene expression)

Figure 4.22 Graph of the fold change of the common probe sets between the 100 and 200 day old hippocampal comparisons. 399 probe sets that were common between the hippocampal and cortical comparison (Figure 4.21) are plotted. The X-value is the logarithm to the base 2 of the fold change in the hippocampus between treated and untreated100 day old TgCRND8 mice while the Y-value is the logarithm to the base 2 of the fold change in the hippocampus between treated and untreated 200 day old TgCRND8 mice.

4.1.7 Cortical microarray comparison between scyllo-inositol treated and untreated 200 day old TgCRND8 mice

Cortical microarray comparison of treated and untreated 100 day old TgCRND8 mice showed fewer genes changes compared to the hippocampal comparison. RT-qPCR comparison of treated and untreated 100 and 150 day old TgCRND8 mice showed no detectable changes in synaptic and signalling genes expression. I expect that the treatment effect in the hippocampus will be greater than in the cortex.

Affymetrix microarrays were used to measure the gene expression in cortical samples from scyllo-inositol treated and untreated 200 day old TgCRND8 mice to determine the scyllo-inositol treatment effect. After the same filtering process that was applied to the hippocampal comparison of treated and untreated 200 day old TgCRND8 was applied to the cortical comparison, 19 probes set comparisons were generated and analyzed with help from the Princess Margret Genomic Center (Table 4.9). The gene expression changes were much fewer than in the hippocampus as predicted. DAVID and IPA analysis was not performed because there were too few probe sets for meaningful enrichment analysis. The increase in age did not result in large increases in the gene expression in the cortices as it did in the hippocampus. This was expected as the exponential increase of fold change in gene expression between younger and older animals means that larger fold changes change more than smaller fold change. Because cortical changes were small in 100 day old TgCRND8, any increases are also small. It is unclear as to why cortical treatment effect is much smaller than hippocampal. Comparison of TgCRND8 and non- transgenic littermates can determine if there are differences in the transgene effect in the hippocampus and cortex.

In light of the results of the comparison between scyllo-inositol treated TgCRND8 mice with untreated controls, the major effects of scyllo-inositol on gene expression in the hippocampus were RNA binding, cytoskeletal, synaptic, GTP binding, and calcium signalling proteins. scyllo- Inositol treatment affected genes related to Alzheimer’s disease and neuropsychiatric disorders in the hippocampus but not the cortex of TgCRND8 mice. Further investigation is required to determine whether these effects are Aβ-dependent or independent.

Table 4.9 The 19 probe sets and extra information for the 200 day cortical comparison PFTAIRE protein kinase 1 LIM homeobox protein 8 S100 calcium binding protein A5 similar to polynucleotide phosphorylase-like protein; polyribonucleotide nucleotidyltransferase 1 hemoglobin alpha, adult chain 2; hemoglobin alpha, adult chain 1 protocadherin 21 Prolactin growth hormone growth hormone growth hormone growth hormone alanine-glyoxylate aminotransferase 2-like 1 gamma-aminobutyric acid (GABA) A receptor, subunit alpha 6 a disintegrin-like and metallopeptidase (reprolysin type) with thrombospondin type 1 motif, 4 predicted gene 7120 dolichyl-phosphate mannosyltransferase polypeptide 3 cerebellin 3 precursor protein

4.2 Investigating the Aβ-dependent and Aβ-independent effects of scyllo-inositol treatment

Comparison of gene expression in TgCRND8 mice treated and untreated with scyllo-inositol identified the treatment effect in transgenic mice. RNA binding motifs, synaptic and myo-inositol signalling were major pathways affected by scyllo-inositol treatment in the hippocampus of TgCRND8 mice but not in the cortex. One possible explanation for the lack of gene expression changes in the cortex is that transgene is not causing any gene expression changes. Therefore, treatment with scyllo-inositol, which reverses the Aβ effect, also does not result in gene expression changes. This is unlikely because amyloid plaques and neuroinflammation have been shown to be present in the cortex of TgCRND8 mice (Chishti et al., 2001, McLaurin et al., 2006).

To investigate whether the difference in treatment effect in the hippocampus and cortex could be explained by differences in the effect of the transgene. Gene expression in the hippocampus and cortex were measured in 200 day old non-transgenic littermates and compared to 200 day old TgCRND8 mice. Comparison between the TgCRND8 and non-transgenic littermate identifies the transgene effect and will help to determine or eliminate explanations for cortical treatment effect in TgcRND8 mice. No differences between the hippocampal and cortical transgene effect suggest that the difference in the scyllo-inositol treatment is not caused by lack of transgene effect in the cortex.

Measurement of the transgene effect is also useful for determining which gene expression changes from the scyllo-inositol treatment are likely due to attenuation of Aβ peptide toxicity. It has been shown that scyllo-inositol treated reduced aggregation and toxicity of Aβ peptides (McLaurin et al., 2000; Jin and Selkoe, 2015). The gene expression changes of the treatment effect in TgCRND8 that are also altered by transgene effects suggest those treatment effects are Aβ-dependent.

To determine which gene expression changes are Aβ-independent, hippocampus and cortices from scyllo-inositol treated non-transgenic mice were compared to untreated non-transgenic mice. Genes that are differentially expressed in this comparison are independent of Aβ peptide

72 aggregation and toxicity effects of scyllo-inositol. These effects are likely due to alternations in myo-inositol signalling pathway (Fenilli et al.,2007; Quinn et al., 2009; Lyketsos et al., 2012).

4.2.1 Hippocampal microarray comparison between 200 day old TgCRND8 mice and non- transgenic littermates

Comparison of the gene expression between 200 day oldTgCRND8 and 200 day old non- transgenic littermates was conducted to identify the transgene effect. Knowing the hippocampal transgene effect is important to determine which pathways from the treatment effect in TgCRND8 are affected by scyllo-inositol-Aβ interactions. It is important to know if there is similar Aβ effects in the cortex compared to the hippocampus.

Affymetrix microarrays were used to measure the gene expression in hippocampal samples from 200 day old TgCRND8 mice and 200 day old non-transgenic littermates. Microarray comparisons were generated and analyzed with help from the Princess Margret Genomic Center. After filtering, 321 probe sets were identified with at least 2-fold expression change between transgenic and non-transgenic mice. These 321 probe sets were inputted into DAVID, which recognized 301 of the probe sets. The top clusters were disulfide bond, signal peptide, immune response, and plasma membrane part (Table 4.10). Clusters 1 and 2 over lapped with each other and clusters 3, 5, and 6 overlapped with each other (Figure 4.24a). About half of the combined signal peptide and disulfide bond clusters were immune related genes (Figure 4.24b). The issue with the disulfide bond and signal peptide clusters is that they are structural groups rather than functional groups, which makes the clustering difficult to interpret for the biological relevance of enrichment in these clusters. The immune component of the gene expression changes are expected due to the astrogliosis and microgliosis described in TgCRND8 mice (Chishti et al., 2001; McLaurin et al., 2006). Neuroinflammation has been shown and studied in many animal models of neurodegenerative disorders besides the TgCRND8 mouse model (Schwab et al., 2009; Dudal et al., 2004). Neuroinflammation is also present in the brains of patients with Alzheimer’s disease (Heneka et al., 2015). Plasma membrane cluster included voltage-gated calcium and potassium channels, CAMK, synaptotagmin, GABA receptors, which are similar to

73 the genes altered by the treatment effects in TgCRND8 mice. GABAergic deficits in TgCRND8 have been previous described (Ma and McLaurin, 2012). The plasma membrane part cluster also contains MHC, Fc receptor IgE and IgG, which are immune-related. Investigation of the transgene gene effect showed similarity between the transgene effect and the treatment effect in the TgCRND8 mice. However, the treatment effect was more enriched for synaptic pathways rather than immune pathways, while the transgene effect affected mainly the immune pathways.

Further pathway analysis was performed using IPA to identify pathways, molecules, and biological processes that are predicted to be altered by the transgene expression in the hippocampus. Core Analysis was run on IPA (Figure 4.25). The top canonical pathways were antigen presentation pathway, allograft rejection signalling, and communication between innate and adaptive immune cells, OX40 signalling pathways, and cytotoxic T lymphocyte-mediated apoptosis of target cells as enriched canonical pathways. Similar genes were used by IPA to identify these pathways. Changes in gene expression of beta 2 microglobulin, major histocompatibility complex classI/II, Fc fragment of IgG were common in all the top canonical pathways. Similar to the analysis with DAVID, the majority of the enriched pathways were immune related pathways.

IPA core analysis also generates predictions for top upstream regulators, genes, and molecules, which may not be in the microarray data set but were likely to be affected by scyllo-inositol treatment. Predicted top upstream regulators were ESR1, PSEN1, PSEN2, HTT, APP. PSEN1 and PSEN2 subunits of the gamma secretase complex, which the cleave APP into Aβ peptides. Identification of PSEN1, PSEN2, and APP as upstream regulators validates the results from this analysis. All the changes that are detected in the TgCRND8 and the non-transgenic animal comparison were caused by mutant APP over-expression. Another upstream regulator ESR1, estrogen receptor has important neuroprotective effect in Alzheimer’s disease (Lan et al., 2015). Polymorphisms of ESR1 have been linked to increased risk and earlier onset of Alzheimer’s disease (Lee and Song, 2015). The prediction from IPA is that ESR1 is inhibited based on the downstream molecules. This suggests a loss of neuroprotection pathways due to the Aβ peptide toxicity in TgCRND8 mice. HTT was also a top upstream regulator for scyllo-inositol treatment effect. HTT is involved in transcriptional regulation, energy metabolism, excitotoxicity, axonal transport and synaptic transmission (Roze et al., 2010). Aggregation of HTT also activates immune pathways (Ellrichmann et al., 2013). The top upstream regulator analysis with IPA

74 identified the cause of the changes in genes between the 2 groups of animals. The analysis also identified that pathways downstream of HTT and ESR1 that were affected by Aβ peptide accumulation.

The disease and functions analysis provided by IPA identified broad themes that were differentially expressed between the treated and untreated samples. The top terms were neurological disease, skeletal and muscular disorder, inflammatory response, psychological disorders, developmental disorders, cell morphology, cell death and survival, cellular development, cellular growth and proliferation, cell-to-cell signalling and interaction, nervous system development and function, tissue morphology, organ morphology, organismal development, and tissue development. The major difference between the scyllo-inositol treatment effect and the transgene effect is the enrichment in the inflammatory response. The others terms were similar to those in the treatment effect comparisons. The genes that were affected by the transgene and the treatment effect were both related to neurological disease and psychological disorders, and nervous system development and function. Similarity between the disease and function that were identified in this comparison and the treatment effect comparisons support the viability of scyllo-inositol as a treatment for Aβ peptide accumulation in the hippocampus. Disease and function analysis supported the TgCRND8 mouse model as an appropriate model to study effects related to Alzheimer’s disease and neuropsychiatric symptoms, as the transgene expression caused changes in the hippocampus that were related to neurological disease and psychological disorders.

The DAVID and IPA analysis provide evidence that scyllo-inositol treatment is affecting some of the same pathways as the transgene effect. To understand whether the scyllo-inositol treatment is counter acting the changes caused by the mutant amyloid precursor protein transgene or exacerbating the changes, a comparison of the fold change in gene expression of the common probe sets was performed. The 541 probe sets that were differentially expressed between the hippocampus of treated and untreated 200 day old TgCRND8 mice was compared to the 321 probe sets that were differentially expressed between the hippocampus of TgCRND8 mice and non-transgenic littermates. 144 probe sets were differentially expressed in both of these comparisons (Figure 4.25). The fold changes in gene expression for each of the 144 probe sets was plotted and a line of best fit was generated using Microsoft excel (Figure 4.26). Almost every common gene showed inverse relationship between the treatment effect and the transgene

75 effect. Genes that were down regulated in the hippocampus of TgCRND8 mice compared to the hippocampus of non-transgenic littermates were up regulated by scyllo-inositol treatment. The outliers are golgi reassembly stacking protein 2 and ring finger protein 114. The fold change between the two comparisons also showed high degree of correlation. The fold change due to the treatment effect was very close to the fold change for the transgene effect, with the exception of growth hormone which increased to a greater extent by scyllo-inositol treatment than it was decreased by transgene effect. This suggests that scyllo-inositol reversed the gene expression of all of these genes to the level of the non-transgenic littermates. Functional annotation clustering analysis with DAVID for these 144 probe sets showed that the top clusters were phosphoprotein and RNA splicing, microtubule and cytoskeletal organization, nucleoplasm part (transcription factors and DNA binding domains) (Table 4.11). These results showed that changes in RNA and microtubule genes are altered by the presence of the transgene, however the large amount of immune-related gene changes masked gene changes in any other pathways when examined in pathway enrichment analysis. Interesting, immune pathway changes were not identified. These results indicate that scyllo-inositol treatment almost exactly reverses the changes in the RNA splicing, phosphoproteins, microtubule and cytoskeletal, and transcriptional factor changes caused by mutant amyloid precursor protein but not the immune related changes.

In summary, the top enriched pathways between the hippocampus of TgCRND8 mice compared to non-transgenic littermates using DAVID and IPA were immune-related. However, scyllo- inositol treatment reversed the effect of the transgene in pathways unrelated to immune response. These other pathways which are in common with the treatment effect are overshadowed by the overwhelming immune changes in the TgCRND8 mice.

Table 4.10 List of top enriched clusters identified by DAVID in the hippocampal comparison of 200 day old TgCRND8 mice and non-transgenic littermates. Only terms with FDR less than 0.1 are shown. The annotation clusters are ranked by the cluster enrichment score. The false discovery rate that is used to filter the results is given for each term. Cluster Enrichment # Score Term FDR disulfide bond 9.91E-04 Signal 0.01186 disulfide bond 0.02098 1 4.2 signal peptide 0.05975 Signal 0.01186 signal peptide 0.05975 2 3.6 Secreted 0.09942 GO:0006955~immune response 6.87E-07 immune response 1.68E-04 GO:0006952~defense response 7.46E-04 GO:0050778~positive regulation of immune response 0.00933 GO:0002478~antigen processing and presentation of exogenous peptide antigen 0.01105 GO:0048584~positive regulation of response to stimulus 0.02550 GO:0019884~antigen processing and presentation of exogenous antigen 0.03074 3 2.8 GO:0002684~positive regulation of immune system process 0.06568 immune response 1.68E-04 GO:0048002~antigen processing and presentation of peptide antigen 2.70E-04 GO:0002478~antigen processing and presentation of exogenous peptide antigen 0.01105 GO:0019884~antigen processing and presentation of exogenous antigen 0.03074 GO:0002474~antigen processing and presentation of peptide 5 2.6 antigen via MHC class I 0.06998 6 2.5 GO:0050778~positive regulation of immune response 0.00933

A) B)

Figure 4.23 Venn diagram for the top clusters from DAVID annotation clustering shown in Table 4.10. A) Each cluster is shown individually. There are eight genes common between all the clusters. Very few genes are unique to each cluster with the exception of cluster 1. Cluster 1 is disulfide bond and signal peptide. Cluster 2 is signal peptide. Cluster 3, 5, and 6 are all immune response related. B) Clusters 1 and 2 are combined. Clusters 3, 5, and 6 are combined. 37 genes are common between the immune and signalling clusters.

Figure 4.24 Summary of IPA core analysis for hippocampal the hippocampal comparison of 200 day old TgCRND8 mice and non-transgenic littermates. The top canonical pathways, upstream regulators and disease, and biological functions are shown. Image is generated with IPA.

Figure 4.25 Venn diagram showing common probe sets between the hippocampal comparison between treated and untreated 200 day old TgCRND8 mice and the hippocampal comparison of TgCRND8 mice with non-transgenic littermates. The numbers represent probe sets.

Comparison between hippocampal scyllo-inositol treatment effect and transgene effect in TgCRND8 mice 5 y = -0.962x R² = 0.696 0

fold change in change fold -4 -2 0 2 4 6 8 10 2

-5 gene expression) gene -10 200 day old treated/untreated TgCRND8 (log2 fold change in gene

expression) TgCRND8/NTg (log TgCRND8/NTg

Figure 4.26 The 144 probe sets that were common between the hippocampal treatment effect in TgCRND8 mice and the hippocampal transgene effect between TgCRND8 and nontransgenic littermates. The probe sets in quadrant 1 and 3 are golgi reassembly stacking protein 2, ring finger protein 114, and an unmapped probe. Growth hormone was increased much more by scyllo inositol treatment than it was decreased by transgene effect. Graph and line of best fit generated in Microsoft excel.

Table 4.11 List of top enriched clusters identified by DAVID for the common probe sets between the treatment effects in 200 day old TgCRND8 and the transgene effect. Only terms with FDR less than 1 are shown. The annotation clusters are ranked by the cluster enrichment score. The false discovery rate that is used to filter the results is given for each term. Cluster Enrichment Term FDR score phosphoprotein 0.177 1 3.7 splice variant 0.258 alternative splicing 0.328 GO:0031110~regulation of microtubule polymerization or 0.387 2 1.5 depolymerization GO:0070507~regulation of microtubule cytoskeleton 0.821 organization 3 1.3 GO:0044451~nucleoplasm part 0.377

4.2.2 Cortical microarray comparison between 200 day old TgCRND8 mice and non- transgenic littermates

Cortical comparison between treated and untreated TgCRND8 showed fewer gene expression change than in the hippocampus. It was unknown whether gene expression changes in the cortex of TgCRND8 compared to non-transgenic mice was also reduced compared to the hippocampus. Measurement of the cortical transgene effect may explain the difference in the treatment effect in the hippocampus and cortex. The gene expression was measured with Affymetrix microarray in the cortex of 200 day old TgCRND8 mice treated for 30 days with scyllo-inositol compared to untreated TgCRND8 mice and identified 134 filtered probe sets that were differentially expressed by at least a 2-fold change. These 134 probe sets were inputted into DAVID, which recognized 131 of the probe sets. The top clusters are signal peptide and immune response (Table 4.12). Clusters 5, 6 and 7, the clusters for chemotaxis and lysosomes largely overlap with signal peptide, and immune response (Figure 4.27). This means that all of the clusters are closely related. Even the clusters that are not listed as immune response contain mostly immune response genes. Functional clustering with DAVID showed enrichment for immune-related clusters.

Further pathway analysis was performed using IPA to identify pathways, molecules, and biological processes that are predicted to be altered by the transgene expression in the cortex. Core Analysis was run on IPA (Figure 4.28). The top canonical pathways were dendritic cell maturation, complement system, Nur77 signalling in T-lymphocytes, role of NFAT in regulation of immune response, and systemic lupus erythematosus signalling. All of the pathways were immune-related. The prediction of these pathways were made based on complement proteins, MHC class I/II, and Fc fragment of IgE/G. Interesting the role of NFAT in regulation of immune response was also in the hippocampal comparison of treated and untreated 200 day old TgCRND8 as well as the treated and untreated 100 day old TgCRND8 mice. However, the gene expression changes that led to the prediction were not the same. In the hippocampal comparison of treated and untreated 100 day old TgCRND8, expression of Gα, PLC, calcineurin, AKT, PI3K, CKI, MEF2 and MHCII were altered (Figure 4.7). In the cortical comparison between 200 day old TgCRND8 mice and non-transgenic littermates, the expression of FCγR, FCεR, TCR, cFOS, and MHCII were altered (Figure 4.29). Almost no common genes were altered in these pathways with the exception of MHCII. The transgene effect on NFAT is unrelated to myo- inositol signalling pathways. Similar to the analysis with DAVID, the top enriched pathways on IPA were immune-related pathways. These were not the same pathways that were enriched in the canonical pathways analysis of the hippocampal transgene effect.

The top upstream regulators are IL6, APP, PTGER4, PSEN2, and PSEN1. APP. PSEN1 and PSEN2 are part of the gamma secretase complex, which cleave APP into Aβ peptide. PSEN1, PSEN2, and APP are the upstream regulators that are expected from an animal model of Alzheimer’s disease. All the gene expression changes are caused by Aβ peptide accumulation and toxicity. Mutations that impair the function of PSEN1 or PSEN2 lead to familial Alzheimer’s disease(De Strooper, 2007). IPA detected inhibition of the genes downstream of PSEN1 and PSEN2, suggesting changes associated with familial Alzheimer’s disease. These results offer validity to the TgCRND8 mouse as a model of amyloidosis in Alzheimer’s disease. Another upstream regulator is Interleukin-6 (IL6), a cytokine that is up-regulated in Alzheimer’s disease patients and mutations of IL6 have been linked to increase risk of Alzheimer’s disease (Cojocaru et al., 2001, Licastro et al., 2003). This reflects the enrichment in immune-related functions in the analysis using DAVID. Prostaglandin E2 receptor 4 (PTGER4) is a GPCR which binds prostaglandin E2. PTGER4 has been shown to affect cognition in other models of

Alzheimer’s disease (Hoshino et al. 2012). G-protein coupled receptors were identified to be important in the scyllo-treatment effect due to participation in the myo-inositol signalling pathways. Although, none of the genes related to PTGER4 in the cortical transgene comparison were related to myo-inositol signalling. The upstream regulator analyses with IPA not only identified the cause of gene expression change in the TgCRND8 model, it also identified upstream regulators of immune response.

Next, the disease and functions analysis provided by IPA identified broad themes that were differentially expressed between the treated and untreated samples. The top terms were inflammatory response, neurological disease, psychological disorder, skeletal and muscular disorder, cancer, free radical scavenging, cell-to-cell signalling and interaction, cellular movement, cell death and survival, cell morphology, hematological system development and function, immune cell trafficking, tissue morphology, nervous system development and function, and tissue development. Inflammatory response was the top disease identified, which was the conclusion from hippocampal comparison of TgCRND8 mice and nontransgenic littermates. Neurological disease and psychological disease as well as nervous system development and function justify the use of the cortical region to study Alzheimer’s disease and neuropsychiatric symptoms. IPA disease and function analysis identified similar terms as in the hippocampal transgene effect and similar terms with the treatment effect.

To confirm that the lack of treatment effect in the cortex of TgCRND8 mice was not caused by reduction of transgene effect in the cortex of TgCRND8 mice, the 321 probe sets from the hippocampal comparison between TgCRND8 and non-transgenic littermates and the 134 probe sets from the cortical comparison of TgCRND8 and non-transgenic littermates were compared to each other. 70 probe sets were common between the two comparisons (Figure 4.30). Functional annotation clustering with these 70 probe sets with DAVID showed results very similar to the clustering of the cortical transgene effect overall with top cluster signal peptide and disulfide bond and the remainder being immune-related clusters. The fold change in gene expression of the probe sets in the two comparisons was plotted against each other. The hippocampal and cortical transgene effects were similar in terms of direction of gene expression change and the fold change (Figure 4.31). The transgene effects in the cortex and hippocampus were also similar. These results showed that the reduced gene expression after scyllo-inositol treatment in the cortex of TgCRND8 mice compared to the gene expression after scyllo-inositol treatment in

83 the hippocampus of TgCRND8 was likely not due to reduction in transgene gene induced changes.

In summary, cortical transgene effect was predominantly immune-related. Fold change in gene expression of common probe sets between the hippocampal and cortical transgene effect showed very strong positive correlation. The pathways identified in the transgene effect comparison were not similar to any of the treatment effect comparisons. However, diseases and biological functions were similar with treatment effect analyses. This suggests that the reduced treatment effect in the cortex of TgCRND8 mice was not caused by a reduction of transgene effect.

Table 4.12 List of top enriched clusters identified by DAVID in the cortical comparison of 200 day old TgCRND8 mice and non-transgenic littermates. Only terms with FDR less than 0.001 are shown. Additionally, terms were not included from cluster 3 higher than 2E-6. The annotation clusters are ranked by the cluster enrichment score. The false discovery rate that is used to filter the results is given for each term. Enrichment Cluster # Score Term FDR Signal 5.26E-07 signal peptide 4.38E-06 disulfide bond 4.45E-06 1 7.3 disulfide bond 3.84E-05 GO:0050778~positive regulation of immune response 8.93E-06 GO:0048584~positive regulation of response to stimulus 1.46E-05 GO:0002684~positive regulation of immune system 2 4.8 process 4.21E-05 GO:0006952~defense response 3.22E-15 GO:0006955~immune response 1.67E-13 GO:0006954~inflammatory response 5.76E-08 GO:0009611~response to wounding 1.79E-07 GO:0048002~antigen processing and presentation of 3 4.2 peptide antigen 1.56E-06 GO:0042330~taxis 1.96E-05 GO:0006935~chemotaxis 1.96E-05 5 3.5 inflammatory response 5.23E-04 GO:0042330~taxis 1.96E-05 6 3.5 GO:0006935~chemotaxis 1.96E-05 GO:0005764~lysosome 1.44E-04 GO:0000323~lytic vacuole 1.51E-04 7 3.2 GO:0005773~vacuole 5.11E-04

Figure 4.27 Venn diagram for the top clusters from DAVID annotation clustering shown in Table 4.12. Cluster 1 is signal peptide. Cluster 2 and 3 are immune response. Cluster 5 and 6 are taxis. Cluster 7 is lysosome. Seven genes are common between all the groupings.

Figure 4.28 Summary of IPA core analysis for hippocampal the hippocampal comparison of 200 day old TgCRND8 mice and non-transgenic littermates. The top canonical pathways, upstream regulators and disease, and biological functions are shown. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.29 Role of NFAT in regulation of the immune response pathway for cortical comparison of TgCRND8 and non-transgenic littermates. The red indicates higher gene expression in the treated samples. The green indicates lower gene expression in the treated samples. Grey means that the gene expression change did not meet the 1.5-fold change cut off. The white means that the gene was not included in the list inputted into IPA. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.30 Venn diagram showing common probe sets between the hippocampal and cortical comparisons of TgCRND8transgenic effect. 251/321 probe sets were unique to the hippocampal comparison while 64/134 were unique to the cortical comparison. 70 probe sets were common between the two comparisons.

Comparison of cortical and hippocampal TgCRND8 transgenic effect 8 6 4 2 y = 0.956x

R² = 0.877 fold change) fold

2 0

(log -4 -2 -2 0 2 4 6 8 -4

Hippocampal gene expression change (log2 fold change) Cortical gene expression change change expression gene Cortical

Figure 4.31Graph of the fold change of the common probe sets between the cortical and hippocampal comparisons of TgCRND8 mice compared to non-transgenic littermates. 70 probe sets that were common between the hippocampal and cortical comparison are plotted (Figure 30). The X-value is the logarithm to the base 2 of the fold change in the hippocampus between treated and untreated TgCRND8 mice while the Y-value is the logarithm to the base 2 of the fold change in the cerebral cortex between treated and untreated TgCRND8 mice. The line of best fit is performed on Microsoft Excel.

4.2.3 Hippocampal microarray comparison of scyllo-inositol treated and untreated 200 day old non-transgenic littermate mice

My previous microarray analysis showed that gene expression changes of RNA binding motif, microtubule binding, synaptic and calcium signalling are altered in the hippocampus of TgCRND8 mice and were altered by scyllo-inositol treatment. Gene expression changes of RNA splicing proteins, phosphoproteins, microtubule binding proteins and transcription factors pathways in TgCRND8 mice were shown to be reversed by scyllo-inositol treatment. It is important to determine whether these effects are due to inhibition of Aβ peptide toxicity or alterations of pathways unrelated to Apeptides. Thus, a comparison between scyllo-inositol treated non-transgenic mice and untreated non-transgenic mice will determine if these are Aβ- independent changes.

Affymetrix microarrays were used to measure the gene expression in hippocampal samples from scyllo-inositol treated and untreated 200 day old non-transgenic mice to determine the scyllo- inositol treatment effect in the absence of Aβ peptide accumulation. Comparison between 35451 probe sets were generated and analyzed with help from the Princess Margret Genomic Center. After initial filtering as described in the methods, 8322 probes remained with 471 of those probe sets more than two-fold differentially expressed between hippocampal samples of treated and untreated non-transgenic mice. DAVID recognized 461of the 471 probe sets. The total 35451 probe sets which were inputted as the background controls. Functional annotation clustering analysis using DAVID identified pathways and biological processes that are most likely changed between the treated and untreated samples based on the microarray array data set. The top clusters are myristoylation, microtubule, cytoskeletal protein binding, SH3 domain, synapse, and synaptic vesicles (Table 4.13). Myristoylation is the process of attaching a lipid molecule to the N-terminus of a protein. Genes altered in the SH3 domain cluster included voltage-gated calcium channel and members of the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK), PI3K, and Rho signalling pathways. Myristoylation and SH3 domains locate proteins to the membrane. Synaptic change included synaptotagmin, synaptophysin, synapsin, GABA transporters, voltage gated sodium, potassium, and calcium channels, metabotropic and ionotropic glutamate receptors (AMPA, NMDA, Kainate). Protein lipid modification, microtubule binding, cytoskeletal binding and synapse were also among the

90 top enriched terms in the hippocampal comparison of 100 day old TgCRND8 mice. While synapse was the only one of the top clusters from the hippocampal treatment effect in non- transgenic mice to overlap with the hippocampal treatment effect in 200 day old TgCRND8 mice. This suggest that the treatment effect in non-transgenic mice affected more similar pathways to the treatment effect in 100 day old TgCRND8 mice, which have less amyloid load, than in 200 day old TgCRND8. Functional annotation clustering analysis with DAVID showed that scyllo-inositol treatment effect on myo-inositol signalling pathway, presynaptic and post synaptic proteins, microtubule and cytoskeletal binding protein were all independent of mutant amyloid precursor protein over expression.

Further pathway analysis was performed using IPA to identify pathways, molecules, and biological processes that are predicted to be altered in the hippocampus of 200 day old non- transgenic mice by scyllo-inositol treatment. Of the 8189 probe sets that were mapped to genes by IPA, 576 of the mapped probe sets met the two-fold change cut off. Core Analysis was run on IPA (Figure 4.34). The top canonical pathway is glutamate receptor signalling, which was also enriched in the hippocampal 100 day TgCRND8 mouse comparison. Unlike the previous analysis, pre- and post-synaptic genes rather than astrocytic and post-synaptic gene were altered. Glutamate receptor signalling pathway visualization on IPA for the comparison between treated and untreated 100 day old TgCRND8 mice showed decreased glutamate receptors on the postsynaptic membrane and increased glutamate uptake pathways in astrocytes (Figure 4.7). Glutamate receptor signalling pathway visualization on IPA showed changes to glutamate receptors on the postsynaptic membrane and changes on the presynaptic membrane but not in the glutamate reuptake pathway (Figure 4.35). This is most likely due to the over abundance of glutamate at the synaptic cleft in the TgCRND8 mice but not the non-transgenic mice. Looking into the details of glutamate receptor signalling in transgenic and non-transgenic mice showed that which genes were affected by scyllo-inositol treatment depended on the presence of pathology in the brain. The other top canonical pathways are cleavage and polyadenylation of pro-mRNA, integrin signalling, and geranylgeranyldiphosphate biosynthesis, and trans, trans- famesyldiphosphate biosynthesis. Although RNA binding proteins and RNA splicing was not identified in the analysis using DAVID, IPA canonical pathway identified the scyllo-inositol treatment effect on RNA splicing. Geranylgeranyldiphosphate biosynthesis and trans, trans- famesyldiphosphate biosynthesis are pathways for synthesizing cholesterol and all the steroid

91 hormones that require cholesterol. Cholesterol is important for the pathogenesis and development of Alzheimer’s disease, although the underlying mechanism is unclear (Xue-Shan et al., 2016). Farnesyldiphosphate synthase has been associated with risk for Alzheimer’s disease (Wollmeret al., 2007). IPA canonical pathways analysis showed that glutamate receptors signalling effect and RNA splicing signalling effects are at least partially independent of scyllo-inositol-Aβ interactions.

IPA core analysis generates predictions for top upstream regulators, genes, and molecules, which may not be in the microarray data set but were likely to be affected by scyllo-inositol treatment. Predicted top upstream regulators were HTT, BDNF, and L-dopa, HDAC4, and ADORA2a. HTT and BDNF are upstream regulators for every hippocampal analysis within this thesis. L- dopa was also identified in the hippocampal treatment effect in TgCRND8 mice at both age points. The dopamine pathway is important for drugs used to treat agitation and aggression. IPA also identified histone deacetylase 4 (HDAC4). Histone deacetylases modify histones to help regulate gene expression and chromosome structure. HDAC4 has been shown to regulate neuronal death (Bolger and Yao, 2005) and has been considered as a target for therapeutics in Alzheimer’s disease (Xu et al., 2011; Mielcarek et al., 2015). Structural maintenance of chromosomes was also identified by analysis with DAVID in 100 day old TgCRND8 mice after scyllo-inositol treatment. Adenosine A2A receptor (ADORA2a) is a GPCR, which signals through the second messenger cAMP and can interact with D2 dopamine receptors (Kayimaet al., 2003). Genetic or pharmacological blockade of ADORA2a improved memory in both mouse models of Aβ and Tau injury (Laurent et al., 2016). Caffeine, an adenosine receptor antagonist, consumption has been found to inversely correlate with incidence of Alzheimer’s disease and reduce memory impairments in animal models (Maiaand de Mendonca, 2002; Arendash et al., 2006; Dall’Igna et al., 2007). Pharmacological blockade of ADORA2a prevented loss of presynaptic markers, synaptophysin and SNAP-25, in a p38 MAPK dependent but cAMP/PKA independent pathway (Canas et al., 2009). Upstream regulator analysis using IPA showed that interactions between BDNF, HTT, and L-dopa that were detected in the TgCRND8 mice were Aβ-independent. Adenosine receptor and histone deacetylase also interact with scyllo-inositol treatment in non-transgenic mice.

Taking a step back from specific molecules, the disease and functions analysis provided by IPA identified broad themes that were differentially expressed between the treated and untreated non

92 transgenic samples. The top terms were developmental disorder, neurological disease, organismal injury and abnormality, psychological disorders, cancer, cellular growth and proliferation, cellular development, cell morphology, cellular assembly and organization, cellular function and maintenance, tissue development, nervous system development and function, tissue morphology, embryonic development and organ morphology. These diseases and biological functions are largely similar to those in the hippocampal comparisons of treatment effect in TgCRND8 mice and the transgene effect. It is promising that the Aβ-independent effects of scyllo-inositol treatment are related to neurological disease and psychological disorders. This provides evidence that scyllo-inositol treatment may alter synaptic signalling outside of the context of Alzheimer’s disease and Aβ peptide aggregation.

In summary, the gene expression changes due to scyllo-inositol that was detected in both transgenic and nontransgenic mice are independent of the direct interaction between Aβ peptides and scyllo-inositol that has been the focus of research on scyllo-inositol in Alzheimer’s disease so far. There needs to be a shift in focus to the non-Aβ dependent effects of scyllo-inositol treatment that were shown in this study to affect gene expression in synaptic transmission, microtubule and cytoskeletal organization, RNA splicing, and myo-inositol signalling pathways.

Table 4.13 List of top enriched clusters identified by DAVID in the comparison of hippocampal samples from 200 day old non-transgenic mice treated and untreated with scyllo-inositol. The results have been filtered, removing all terms with false discover rate higher than one. Cluster # Enrichment Score: Term FDR lipid moiety-binding region:N-myristoyl glycine 0.012039 1 4.4 Myristate 0.010912 Microtubule 0.133144 2 2.8 GO:0005874~microtubule 0.929426 4 2.1 GO:0008092~cytoskeletal protein binding 0.315293 Synapse 0.030984 GO:0044456~synapse part 0.081607 GO:0007268~synaptic transmission 0.140503 6 1.9 GO:0019226~transmission of nerve impulse 0.171038

Figure 4.32 Summary of IPA core analysis for hippocampal comparison of treated and untreated 200 day old non-transgenic mice. The top canonical pathways, upstream regulators and disease, and biological functions are shown. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

Figure 4.33 Visualization of the Glutamate receptor signalling pathways from IPA core analysis for hippocampal comparison of treated and untreated 200 day old non-transgenic mice. The red indicates higher gene expression in the treated samples. The green indicates lower gene expression in the treated samples. Grey means that the gene expression change did not meet the 1.5-fold change cut off. The white means that the gene was not included in the list inputted into IPA. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

4.2.4 Cortical microarray comparison between scyllo-inositol treated and untreated 200 day old non-transgenic littermates

My previous microarray analysis showed that scyllo-inositol treatment had very little effect in the cortices of TgCRND8 mice. Cortical transgene effect was shown to be predominantly immune-related. Hippocampal comparison of treated and untreated non-transgenic mice showed that the pathways that were related to neuropsychiatric symptoms in Alzheimer’s disease were altered without the presence of Aβ peptides. Cortical comparison of treated and untreated non- transgenic littermates will determine if there are any Aβ-independent effects of scyllo-inositol treatment in this brain region.

Affymetrix microarrays were used to measure the gene expression in hippocampal samples from scyllo-inositol treated and untreated 200 day old non-transgenic littermates to determine the scyllo-inositol treatment effect. Comparison between 35679 probe sets were generated and analyzed with help from the Princess Margret Genomic Center. After initial filtering, 35686 probes remained with10475 probe sets remained with 524 of those probe sets more than two-fold differentially expressed between cortical samples of treated and untreated TgCRND8 mice and 508 probe sets were recognized by DAVID. The total 35686 probe sets were inputted as the background control data for analyses. Functional annotation clustering analysis using DAVID identified pathways and biological processes that are most likely changed between the treated and untreated samples based on the microarray array data set (Table 4.14). The top clusters were neuronal projection, synapse, synaptic transmission, long-term potentiation, membrane fraction, calmodulin binding, and lipoprotein. Neuronal projection, synapse, synaptic transmission, and membrane associated proteins were identified in the hippocampal treatment effect in TgCRND8 mice as well as non-transgenic mice. Calcium signalling and synaptic changes have previously been linked to changes in myo-inositol signalling pathways in this study. It was unexpected that similar Aβ-independent effects are detected in the cortex of non-transgenic mice as were detected in the hippocampus, as this was not the case in TgCRND8 mice. Cortical expression of genes in synaptic, calcium signalling, membrane proteins pathways were all altered by scyllo- inositol treatment in non-transgenic mice.

Further pathway analysis was performed using IPA to identify pathways, molecules, and biological processes that are predicted to be altered in the cortex of 200 day old non-transgenic mice by scyllo-inositol treatment. Of the 10475 probes that were inputted into IPA, 10239 probe sets were mapped to genes and419 of the mapped probe sets met the two-fold change cut off. Core Analysis was run on IPA (Figure 4.34). Synaptic long term potentiation, melatonin signalling, calcium signalling, glutamate receptor signalling, and neuropathic pain signalling in dorsal horn neurons are the top canonical pathways identified by IPA. Glutamate receptor signalling, calcium signalling and synaptic long term potentiation are mediated through similar pathways. Changes to glutamate receptor signalling were identified in the hippocampal treatment effect in non-transgenic mice and hippocampal treatment effect in 100 day old TgCRND8 mice. Analysis of the changed genes in IPA showed only post-synaptic glutamate receptor changes were detected in the cortices of non-transgenic mice. No glutamate reuptake pathways changes associated with astrocytes were detected. Melatonin signalling is important for circadian rhythm. Sleep disturbances are part of neuropsychiatric symptoms in Alzheimer’s disease. Melatonin may improve agitated behaviour in patients with Alzheimer’s disease (De Jonghe et al., 2010). The genes changed in melatonin and neuropathic pain signalling were shown by IPA to be mediated through PLC, PKC, and CAMK changes. These changes suggest myo-inositol signalling as the mechanism of action for scyllo-inositol treatment. Canonical pathways analysis using IPA identified several pathways that have been shown to be important in Alzheimer’s disease and neuropsychiatric symptoms. Changes in these pathways indicate that changes in gene expression are in myo-inositol signalling pathways.

IPA core analysis also generates predictions for top upstream regulators, genes, and molecules, which may not be in the microarray data set but were likely to be affected by scyllo-inositol treatment. Predicted top upstream regulators were BDNF, HTT, MKNK1, ESR1, SLC30A3 (Figure 4.34). HTT and BDNF were identified in the hippocampal treatment effects in TgCRND8 and non-transgenic mice. ESR1 was identified as a top upstream regulator for both the transgene and treatment effects. This showed that Aβ-independent effect of scyllo-inositol could overlap with Aβ peptide induced changes. MAP kinase-interacting serine/threonine- protein kinase 1 is a serine and threonine kinase that is important in the MAPK singling pathway. MAPK and ERK signalling is downstream of myo-inositol signalling pathway. SLC30A3 gene encodes for ZnT3 synaptic vesicle zinc transporter and has been shown to be up regulated in

97 other models of Alzheimer’s disease (Friedlich et al., 2004). The top disease and biological functions showed that cortical treatment effect in non-transgenic mice was similar to the hippocampal treatment effect in the TgCRND8 and non-transgenic mice.

Additionally, the disease and functions analysis provided by IPA identified broad themes that were differentially expressed between the treated and untreated samples. The top terms were cancer, neurological disease, organismal injury and abnormalities, metabolic disease, psychological disorder, cellular assembly and organization, cellular development, cellular growth and proliferation, cell-to cell signalling and interaction, cell morphology, nervous system development and function, organ morphology, organismal development, tissue development, and tissue morphology. The identification of neurological disease, psychological disorder, nervous system development and function support the results from the canonical pathway, upstream regulator, and DAVID analyses. The treatment effect in the cortex of non-transgenic mice shared many similarities with treatment effect in the hippocampus of TgCRND8 mice and the treatment effect in the hippocampus of non-transgenic mice.

The cortical treatment effect in non-transgenic mice, in contrast to TgCRND8 mice, showed abundant similarities with hippocampal changes in analyses with DAVID and IPA. Fold change in gene expression for cortical treatment effect in TgCRND8 mice was found to be lower than the hippocampal treatment effect. Direct comparison of common genes between the cortical and hippocampal treatment effect in non-transgenic mice was performed to determine if there are also similar reduction in gene expression changes as was seen in the TgCRND8 mice. Comparison of the 204 probe sets that were common between the cortical and the hippocampal comparisons of scyllo-inositol treatment effect in non-transgenic mice showed no differences in the general trend of gene expression in the two comparisons (Figure 4.35). The change in gene expression was very similar between the hippocampus and cortex of non-transgenic mice unlike the effect of scyllo-inositol treatment in TgCRND8 mice.

This study showed that scyllo-inositol treatment in non-transgenic mice responded to scyllo- inositol treatment at the transcriptional level similarly in the cerebral cortex and the hippocampus. Unlike in the TgCRND8 mice, which showed greater number of genes and larger fold changes in the hippocampus compared to the cortex. Gene expression changes in the hippocampus of 200 day old TgCRND8 mice, both the hippocampus and cortex of 100 day old

TgCRND8 mice and 200 day old non-transgenic mice supported myo-inositol signalling pathway as a mechanism of action for scyllo-inositol treatment of neuropsychiatric symptoms of Alzheimer’s disease.

Table 4.14 List of top enriched clusters identified by DAVID in the comparison of hippocampal samples from 200 day old non-transgenic mice treated and untreated with scyllo-inositol. The results have been filtered, removing all terms with false discover rate higher than 1. Cluster # Enrichment Score Term FDR 1 4.8 GO:0043005~neuron projection 1.26E-04 GO:0044456~synapse part 3.14E-04 GO:0045202~synapse 0.00215 Synapse 0.00448 postsynaptic cell membrane 0.03081 GO:0045211~postsynaptic membrane 0.05669 2 4.6 GO:0030054~cell junction 0.08757 GO:0007268~synaptic transmission 1.65E-04 GO:0019226~transmission of nerve impulse 0.00131 GO:0007267~cell-cell signalling 0.00394 GO:0001505~regulation of neurotransmitter levels 0.01508 GO:0006836~neurotransmitter transport 0.01886 3 3.6 GO:0007269~neurotransmitter secretion 0.02113 4 3.5 mmu04720:Long-term potentiation 0.00176 6 3 GO:0005516~calmodulin binding 0.1

Figure 4.34 Summary of IPA core analysis for cortical comparison of treated and untreated 200 day old non-transgenic mice. The top canonical pathways, upstream regulators and disease and biological functions are shown. (IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity)

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Comparison between the scyllo-inositol treatment effect in the hippocampus and in the cortex of nontransgenic mice

fold fold 2 4

2 y = 1.004x R² = 0.911 0 -6 -4 -2 0 2 4 6

-2 change in gene expression) gene in change -4

-6 Cortical treated/untreated nontransgenic mice (log mice nontransgenic treated/untreated Cortical hippocampal treated/untreated nontransgenic mice (log2 fold change in gene expression)

Figure 4.35 Graph of the fold change of the common probe sets between the cortical and hippocampal comparisons of treated and untreated non-transgenic mice compared. 204 probe sets that were common between the hippocampal and cortical comparison are plotted. The X- value is the logarithm to the base 2 of the fold change in the hippocampus between treated and untreated non-transgenic mice while the Y-value is the logarithm to the base 2 of the fold change in the cerebral cortex between treated and untreated non-transgenic mice. The line of best fit is performed on Microsoft Excel.

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Chapter 5 Discussion

5 Discussion

Gene expression in scyllo-inositol treated and untreated TgCRND8 mice as well as treated and untreated non-transgenic mice were compared to elucidate the effect of scyllo-inositol treatment. Gene expression changes in synaptic function, glutamate receptor signalling, calcium signalling, myo-inositol signalling pathways, and dopamine receptor signalling were identified to be scyllo- inositol treatment effects. These pathways play a role in Alzheimer’s disease and neuropsychiatric symptoms.

Glutamate receptor signalling was identified as an enriched canonical pathway by IPA in hippocampal comparison of treated and untreated 100 day old TgCRND8 mice and both the hippocampal and cortical comparison of treated and untreated 200 day old non-transgenic mice. Memantine has been shown to improve cognition and reduce behavioural symptoms in patients with Alzheimer’s disease(Parsons et al., 2007). NMDARs are generally composed of two GluN1 and two GluN2 subunits. GluN1 subunits are encoded by the Grin1 gene. Grin1 was shown by qPCR to be affected by scyllo-inositol treatment in the hippocampus but not the cortex of TgCRND8 mice at 100 and 150 days of age. NMDARs, activated by glutamate binding, are important for synaptic long term potentiation (Tang et al., 1999; Hawasli et al., 2007). Synaptic long term potentiation was identified as an enriched canonical pathway by IPA cortical comparison of treated and untreated 200 day old non-transgenic mice. NMDAR activation results in Ca2+ influx through the channel that triggers downstream signalling. CAMK and CREB are phosphorylated which lead to gene transcription needed for LTP. This neural plasticity process is required for learning and memory formation (Silva, 2003). NMDAR also activates PKA and Ras pathway (Matynia et al., 2002). While Ras activation leads to MAPK/ERK and PI3K/Akt/mammalian target of rapamycin (mTOR) pathways, which are important for neuronal survival (Hetman and Kharebava, 2006). NMDAR antagonists activate mTOR leading to increase spine density and synaptic activity in the prefrontal cortex (Li et al., 2010). Glycogen synthase kinase 3 is a key kinase related to synaptic transmission and influences NMDAR trafficking. Inhibition of glycogen synthase kinase 3 results in increased NMDAR internalization and reduced NMDAR activity (Chen et al., 2007). In Alzheimer’s disease, Aβ oligomers disrupt

102 calcium homeostasis, axonal transport, cause inflammation, and synaptic dysfunction (Paula- Lima et al. 2013). NMDAR mediated calcium overload is a proposed mechanism of excitotoxicity and cell death in Alzheimer’s disease. Interaction between Aβ peptides and NMDAR has been shown to stimulate each other, leading to increase Aβ peptide production and NMDAR activation (Parsons et al., 2007; Alberdi et al., 2010; Butterfield and Pocernich, 2003). Changes in glutamate receptor signalling are linked to changes in calcium signalling, as NMDARs are permeable to calcium. Glutamate build up in synaptic cleft leads to extra synaptic activation of metabotropic glutamate receptors, which activate a number of signalling pathways (such as p38 MAP kinase or ERK) and stimulate release of intracellular calcium stores through PLC cleavage of phosphatidylinositols. These changes lead to post-synaptic endocytosis of AMPARs and pre-synaptic decrease of neurotransmitter release (Shankar and Walsh, 2009). In animal models, NMDAR activity was found to regulate aggressive behavior in cats and agitation and aggression in rodents (Siegel and Schubert, 1995; Peeters et al., 1989; Wedzony, 2008). Reuptake of glutamate was shown to be modulated by scyllo-inositol treatment in the hippocampus of TgCRND8 mice but not in the hippocampus of non-transgenic mice. Astrocyte glutamate reuptake transporters, SLC1A2/3 and SLC38A, and glutamate synthetase were up regulated in the hippocampus of treated TgCRND8 mice compared to untreated TgCRND8 mice. These genes were not differentially expressed between the TgCRND8 and the non-transgenic mice, therefore up regulation of these genes is not the result of scyllo-inositol inhibition of Aβ peptide related changes. The exact mechanism of action is unknown; however, scyllo-inositol treatment may reduce excitotoxicity at the synapses by increasing clearance of glutamate in the synaptic cleft by astrocytes. Modulation of glutamate and calcium signalling maybe a mechanism of action of scyllo-inositol.

In addition to glutamate receptor signalling, dopamine receptor signaling was also altered by scyllo-inositol treatment. Dopamine receptor signalling was identified as an enriched canonical pathway by IPA in cortical comparison of treated and untreated 100 day old TgCRND8 mice and the hippocampal comparison of treated and untreated 200 day old TgCRND8 mice. Dopaminergic signalling to the hippocampus has been shown to improve memory persistence in animal models (McNamara et al., 2014).Changes to the gene expression of DRD2 were only identified in the cortical comparison of treated and untreated 100 day old TgCRND8 mice. This suggested a potential effect of scyllo-inositol treatment on the mesocortical dopaminergic

103 pathway, which plays a role in controlling behavior. Dopamine receptor signalling was not enriched in the non-transgenic animals. In addition, L-dopa was identified as an enriched upstream regulator in all comparisons. L-dopa is a naturally occurring compound in the body and a precursor for the catecholamines, dopamine, epinephrine, and norepinephrine. Dysfunction of norepinephrine signaling in the brain of patients with dementia was suggested to lead to agitation and aggression (Herrmann et al, 2004). Drugs that target dopamine receptors such as antipsychotic drugs like aripriprazole have been shown to reduce agitation and aggression in patients with Alzheimer’s disease (Maher et al., 2011). Dopamine and metabolites have been found to be decreased in the brains of Alzheimer’s disease patients, thus compromised signalling may contribute to behavioural changes seen in disease (Storga et al., 1996;Vermeiren et al., 2014; Reinikainen et al., 1988). Dopamine receptors, DRD2, DRD3, and DRD4have be linked to agitation and aggression in patients with Alzheimer’s disease (Sato et al., 2009; Tanaka et al., 2003; Pritchard et al., 2009). Furthermore, specific alleles of dopamine transporter, DAT 10R allele, and catechol-O-methyltransferase, COMT G allele, are associated with agitation in Alzheimer’s disease (Proitsi et al., 2012). Based on previous research, dopamine signalling is implicated in Alzheimer’s disease and neuropsychiatric symptoms. My results suggested that catecholamine signalling may be altered by scyllo-inositol treatment although changes to dopamine receptor signalling pathway was not identified in the comparison of treated and untreated non-transgenic mice nor in the comparison of TgCRND8 and non-transgenic mice, suggesting this effect is neither Aβ-independent nor solely Aβ-dependent. The identification of the brain regions for which dopamine receptor signalling was indicated to be affected varied with differences between the 100 day and 200 day old TgCRND8 comparisons. One explanation for this could be that the gene expression changes are transient or region specific. Results from this study support a potential dopaminergic effect of scyllo-inositol treatment.

Another upstream regulator that was consistently identified as altered as a function of scyllo- inositol treatment was BDNF. BDNF regulates synaptic plasticity, neuronal differentiation, and survival of neurons (Budni et al., 2015). Expression of BDNF in TgCRND8 mice has been shown to be decreased (Francis et al., 2012). Deficits in BDNF correlate with poor learning performance in animals (Petzold et al., 2015). BDNF binds to tropomyosin-related kinase (Trk) receptors and is crucial to learning and memory. BDNF receptors decrease with age and maybe a cause for age related cognitive decline (Rage et al., 2007). BDNF has been shown to be

104 decreased in patients with Alzheimer’s disease before decline of choline acetyltransferase activity and worsen with disease progression (Peng et al., 2005; Gezen-Ak et al., 2013; Platenik et al., 2014). Increases in both BDNF and TrkB have been shown early in the disease, perhaps as a compensatory response (Faria et al., 2014; Kao et al., 2012). Caffeine treatment has been shown to increase BDNF and TrkB as well as memory impairments in mouse model of Alzheimer’s disease, linking adenosine signalling with BDNF (Han et al., 2013). Viral delivery of BDNF into the entorhinal cortex of mouse models of Alzheimer’s disease reversed synapse loss and learning and memory deficits (Nagahara et al., 2009). BDNF levels in patients have been shown to correlate with aggression (Nagata et al., 2014), thus linking it to neuropsychiatric symptoms of dementia. My results suggest that scyllo-inositol treatment alters gene expression downstream of BDNF through a mechanism unrelated to the expression of BDNF. The scyllo- inositol treatment effect on gene expression downstream of BDNF was seen in both transgenic and non-transgenic mice suggesting that this effect is independent of Aβ peptide accumulation and aggregation.

The most commonly identified upstream regulator was HTT. Mutations in HTT cause Huntington’s disease, a dominantly inherited progressive neurodegerative disease. However, HTT is expressed both inside and outside of the nervous system and expression in the brain is not limited to the regions that degenerate in Huntington’s disease (Marques Sousa and Humbert, 2013). HTT is important during development as knockouts are embryonic lethal (Duyao et al., 1995). HTT is implicated in diverse cellular function such as transcription, RNA splicing, endocytosis, trafficking, and cellular homeostasis (Harjes and Wanker, 2003; Saudou and Humbert, 2016). These are all functions that are affected after scyllo-inositol treatment in the microarray comparisons as identified by gene annotation enrichment with DAVID. The role of HTT in the transport of synaptic precursor vesicles, BDNF containing vesicles, and APP positive vesicles are the most relevant for Alzheimer’s disease (Zala et al., 2013). Mutant HTT causes dysfunction of autophagy pathways though inactivation of mTOR (Kegel et al., 2000; Ravikumar et al., 2004; Martin et al., 2014). Previous work by Lai et al. found that scyllo-inositol treatment reduced mutant HTT protein levels in a mutant HTT expressing PC12 cells (Lai et al., 2014). Identification of HTT an upstream regulator suggests downstream changes related to synaptic dysfunction and neurodegerative diseases are present. My results suggested that the effects on vesicular trafficking were Aβ-independent, enriched in the analyses with DAVID in both the

105 transgenic and nontransgenic mice. On the other hand, RNA splicing was Aβ-dependent, as enrichment for RNA binding proteins was only seen in TgCRND8 mice and not non-transgenic mice when treated with scyllo-inositol.

The pathways that were affected by scyllo-inositol treatment shown in this study have been implicated in Alzheimer’s disease and neuropsychiatric symptoms. Functional annotation clustering with DAVID and canonical pathways analysis with IPA identified calcium signalling, glutamate signalling, dopamine signalling, and synaptic long term potentiation as major effects of scyllo-inositol treatment. Upstream regulator analysis with IPA identified HTT and BDNF, which are implicated in both Alzheimer’s disease and neuropsychiatric disorders. Disease and biological function analysis with IPA showed that neurological disease and psychological disorders were the main effect of scyllo-inositol treatment. scyllo-Inositol treatment effected expression of genes involved in Alzheimer’s disease and neuropsychiatric disorders.

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Chapter 6 Conclusion and future directions 6 Conclusion and future directions

6.1 Conclusion

In this thesis, I tested the hypothesis that scyllo-inositol treatment will cause changes in expression of genes involved in neurodegenerative diseases and neuropsychiatric disorders. My study identified, in the comparison between scyllo-inositol treated TgCRND8 mice and untreated TgCRND8 mice, gene expression changes in synaptic function and calcium signalling which are dysregulated in Alzheimer’s disease. Excessive intracellular calcium signalling in neurons causes synaptic dysfunction eventually leading to synaptic loss and cell death in Alzheimer’s disease. My study also identified, in the comparison between treated and untreated non-transgenic mice as well as treated and untreated TgCRND8 mice, gene expression changes in dopamine, glutamate, and myo-inositol signalling which are dysregulated in patients with neuropsychiatric disorders. Drugs targeting dopamine receptors, glutamate receptors, and intracellular myo- inositol concentration reduce agitation and aggression in patients with neuropsychiatric disorders. Considering these results, I conclude that my hypothesis was correct.

6.2 Future directions

Based on the results from my study, further investigation of scyllo-inositol treatment effects are warranted. Many potential pathways were identified from the microarray analyses. At the synapse, AMPA and NMDA glutamate receptor, adenosine receptors, GABA receptors, and dopamine receptors were shown be important for the scyllo-inositol treatment effect. Signalling through CREB, AKT, mTOR, GSK3β, PI3K, PTEN, PKC, HDAC, and MAPK are altered by scyllo-inositol treatment, in turn affecting transcription, synaptic transmission, microtubule assembly, and cell survival. Changes in these genes at the mRNA level need to be reproduced in

107 a study with biological replicates by qPCR. qPCR results from my study suggest that there was a large variance in the gene expression change in response to scyllo-inositol treatment between animals. Replication with larger number of animals will provide further insight into the gene expression changes.

Going beyond the transcriptomic studies, protein modification and translation are important regulator processes for many of the signalling and synaptic proteins that are not solely regulated by transcription. Mass spectrometry, ELISA and western blot will be able to identify phosphorylation, acetylation, palmitoylation, ubiquitination, sumoylation, degradation, and translocation changes to proteins within the pathways I have identified. Alternative transcriptomic techniques such as Translating Ribosome Affinity Purification/RiboTag, Laser Capture Microdissection, and RNA-sequencing will generate spatially or cell type specific data and be able to identify isoform changes due to potential scyllo-inositol effect on RNA binding proteins. RNA-sequencing will also be able to identify alternative splicing, which is suggested by the enrichment in RNA binding proteins identified in my results. Further investigation of the molecular mechanism of scyllo-inositol treatment in animal models is possible with different techniques.

More studies should be done to investigate scyllo-inositol treatment effects in vivo and in vitro. The effect of scyllo-inositol on synaptic changes seems independent of Aβ peptide accumulation. If possible, establishment of a cell culture model for screening signalling pathways can be used to investigate the potential pathways identified by this study. Pathway specific inhibitors and activators can be used to evaluate the necessity of specific pathways, such as PI3K, AKT, and GSK3β, for the scyllo-inositol treatment effect. Animal models can be used to verify these pathway specific modulators to affect behavioral changes. Transgenic or non-transgenic animals can be evaluated for agitation and aggression using behavioural tests, such as assessment of social interaction behaviours. Inhibitors or modulators from the cell culture assays can be used on the animals to validate those findings in vivo. Further understanding of scyllo-inositol as a therapeutic not only allows for better future targets for treatment but also maybe providing ways to separate the Alzheimer’s disease patient population into subpopulations which may have different needs in terms of treatment targets.

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