LITHUANIAN UNIVERSITY OF HEALTH SCIENCES

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LITHUANIAN UNIVERSITY OF HEALTH

SCIENCES

Institute of Neuroscience

Iliya Oksman

Alzheimer’s disease: integrating neuroscience data into computational models for understanding impaired synaptic plasticity in the hippocampus.

Master’s Thesis

Thesis Supervisor:

Dr. Aušra Saudargienė

Faculty of Medicine

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1. SUMMARY

Author: Iliya Oksman

Scientific Supervisor: Dr. Aušra Saudargienė

Research Title: Alzheimer’s disease: integrating neuroscience data into computational models

for understanding impaired synaptic plasticity in the hippocampus.

Aim: To understand the interaction of amyloid β (Aβ)-induced pathologies of long-term synaptic

plasticity in hippocampal CA1 pyramidal neurons in Alzheimer’s disease (AD) by integrating neuroscience data into computational models.

Objectives of Study: 1. To review the clinical literature on AD.

2. To build a computational model of Aβ-induced pathological changes of long-term synaptic plasticity at hippocampal CA3-CA1 synapses in AD.

3. To analyse the modeling data to understand the Aβ-induced pathological changes of long-term synaptic plasticity in AD.

4. To relate and translate results obtained to the clinical picture and possible treatment targets.

Methodology: Computational modeling approach was employed to analyse the Aβ-induced

pathological changes of synaptic plasticity at a hippocampal CA3-CA1 synapse in hippocampal CA1 pyramidal neuron in AD.

Results: We modelled the Aβ-induced pathological eﬀects on glutamate transmission, A type

potassium current IA, calcium-calmodulin dependent protein kinase II, N-methyl-D-aspartate receptor, and analysed altered intracellular calcium dynamics and resulting impairment of long-term synaptic plasticity at a hippocampal CA3-CA1 synapse. We showed rescuing effect of drugs Ifenprodil and magnesium L-threonate on deficits in hippocampal long-term synaptic plasticity.

Conclusion: Computational modeling is a powerful modern technique to analyse complex

processes and their interactions in the brain in health and disease providing a consistent way to examine experimental data in controlled conditions with the option of gradually increasing the complexity of the models by integrating new biomedical knowledge.

Recommendations: 1. Big data neuroscience projects, such as the EU FP7 FET Flagship

Programme Human Brain Project, need to present experimental guidelines to allow for more efficient translation of experimental data to computational models.

2. More research needs to be done into the effect of anti-inflammatory drugs on AD progression and combination therapy as well as the role of NMDAR in Alzheimer’s disease.

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1. SANTRAUKA

Autorius: Iliya Oksman

Vadovas: Dr. Aušra Saudargienė

Pavadinimas: Alzheimerio liga: neuromokslo duomenų ir kompiuterinių modelių integravimas siekiant suprasti sutrikusį sinapsių plastiškumą hipokampe.

Tyrimo tikslas: Suprasti beta amiloidų (Aβ) sukeltų patologinių pokyčių sąveikos poveikį hipokampo CA1 piramidinių neuronų ilgalaikio sinapsių plastiškumo savybėms integruojant neuromokslų duomenis ir kompiuterinius modelius.

Uždaviniai: 1. Apžvelgti mokslinę literatūrą apie Alzheimerio ligą (AL).

2. Sudaryti kompiuterinį modelį Aβ sukeltų patologinių pokyčių sąveikos įtakai hipokampo CA3-CA1 sinapsių ilgalaikio plastiškumo savybėms sergant AL analizuoti.

3. Išanalizuoti kompiuterinio modelio pagalba gautus duomenis siekiant suprasti Aβ sukeltų patologinių pokyčių sąveikos įtaką ilgalaikio sinapsių plastiškumo savybėms sergant AL. 4. Aptarti gautų rezultatų svarbą galimiems gydymo metodams.

Tyrimo metodika: Kompiuterinio modeliavimo metodika buvo taikoma Aβ sukeltų patologinių pokyčių sąveikai hipokampo CA3-CA1 sinapsėje sergant AL analizuoti.

Rezultatai: Mes modeliavome Aβ sukeltų patologinių pokyčių įtaką glutamato koncentracijai, A tipo kalio srovei IA, nuo kalcio/kalmodulino komplekso priklausomai protein-kinasei II, N-metil-D-aspartato receptoriui (NMDAr) ir tyrėme viduląstelinės kalcio dinamikos pokyčius, lemiančius sutrikusį hipokampo CA3-CA1 sinapsių ilgalaikį plastiškumą. Mes analizavome vaistų ifenprodilio ir MgT poveikį, atstatantį ilgailaikį sinapsių plastiškumą.

Išvados: Kompiuterinis modeliavimas yra galingas modernus metodas, skirtas analizuoti sudėtingus procesus ir jų sąveiką sveikose smegenyse ir esant psichiatriniams ir neurologiniams susirgimams. Šis metodas suteikia galimybę tirti eksperimentinius duomenis kontroliuojamomis sąlygomis, palaipsniui didinant modelių sudėtingumą ir integruojant naujas biomedicinines žinias.

Rekomendacijos: 1. Didžiųjų duomenų neuromokslų projektai, tokie kaip EU FP7 FET Human

Brain Project projektas, turėtų išleisti rekomendacijas eksperimentinių duomenų standartizuotam pateikimui siekiant efektyvesnio jų integravimo į kompiuterinius modelius. 2. Tikslinga atlikti daugiau tyrimų NMDAr įtakos, priešuždegiminių vaistų poveikio, kombinuoto gydymo taikymo Alzheimerio ligos progresavimui sustabdyti srityse.

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2. ACKNOWLEDGMENTS

Motivated by a lifelong dream I started this work hoping to achieve it. On the way I’ve met numerous people who inspired me to continue and I’d like to thank them all. Three though stood out in particular.

First and foremost, my sincerest gratitude to my supervisor, who pushed me to create this work which is beyond what I ever expected to accomplish when I started it out. It is thanks to her that I’ve learned so much about the field of Computational Neuroscience and am a step closer to achieving my dream.

I would also like to thank my girlfriend Daniela Levintan for keeping me sane during these two years of writing and last, but not least, my grandmother Anna Kaplinsky who was always there to listen and without her this work would not be of the same quality.

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3. CONFLICTS OF INTEREST

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4. PERMISSION OF ETHICS COMMITTEE

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5. ABBREVIATIONS

AP – Action potential

Aβ – Amyloid bBeta

ACh - acetylcholine AD – Alzheimer disease

AICD - amyloid precursor protein intracellular domain

AMPA - α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid

ApoE4 – Apolipoprotein E

APP - amyloid precursor protein

sAPP – soluble amyloid precursor protein

BBB – blood brain barrier

CA – cornu Ammonis

CaMKII – Ca2+/calmodulin-dependent protein kinase II

CSF – Cerebrospinal fluid

GABA - gamma-Aminobutyric acid

HBP - Human Brain Project LTP – Long term potentiation

LTD – Long term depression

MDM - monocyte derived macrophages

MiDM - microglia-derived microphages

MgT - Magnesium L-threonate

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10 NIA-AA - National Institute on Aging and the Alzheimer's Association

NMDA – N-Methyl-D-aspartate

NMADR - N-Methyl-D-aspartate receptor

PP2B - protein phosphatase 2B PET – positron emission therapy

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6. INTRODUCTION

In 1982[1] a landmark article predicted that the increase in lifespan will eventually result in an explosion of dementia cases, urging the scientific community to tackle the expected crisis. While much progress has been made, to this day we still don’t know the definite timeline of events that leads to AD let alone all its causes or how to cure it.

According to WHO, dementia syndrome is the 7th_{leading cause of death in the world, with AD} being the cause of 60-70% of dementia cases and only ~12% of those over 90 years of age having normal cognition[2]; mainly in those with higher education. And although the Framingham Heart Study showed a significant and steady decrease in incidence of dementia since the study began in 1975[3], though again only in individuals who have at least a high school diploma thus validating again the “cognitive reserve” effect of AD[4–6], the increase in human life span worldwide results in continued growth of the elderly population and while it was estimated there were 46 million people affected by dementia worldwide in 2015 it is projected to affect 131 million by 2050[7].

According to Up-To-Date[8], definitive diagnosis of AD requires histopathological examination which is rarely done on the living. In practice, AD diagnosis is based on clinical criteria, most commonly from either the National Institute on Aging and the Alzheimer's Association (NIA-AA) or the Diagnostic and Statistical Manual of Mental Disorders, where physicians make a diagnosis of AD when patients already exhibit early cognitive losses.

The 2011 based NIA-AA criteria[9] separate preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. However, in their new recommendations[10], the NIA-AA suggests new research criteria and guidelines where AD is no longer diagnosed by the clinical consequences of the disease but is instead changed to the underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers and presenting a new ATN classification based on grouping biomarkers into Amyloid-beta plaques deposition, pathologic Tau, and neurodegeneration or neuronal injury [AT(N)].

What precedes this change is the understanding that AD isn’t caused by a single factor but by a continuum of pathologic changes in the brain, as well as the addition of new diagnostic methods like the Tau positron emission tomography(PET) [11,12], created in 2014 and added to the existing Amyloid-beta PET[13,14] scan from 2004. The combination of the two now allow medical practitioners and researchers to diagnose in vivo what was once only possible

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12 postmortem, which is finding and tracking deposition of Amyloid and Tau years before the onset of symptoms as well as better management of the pathologies they cause[15], as well as the suggestion of new more accessible biomarkers; one example being the eye[16].

However, what used to be the two main hypothesis for the cause of Alzheimer’s are no longer enough to explain the disease and its progression as in recent years inflammation was added as a key player in the pathogenesis[17], injecting a new hope in the search for a cure by adding a new avenue of exploration for research, with the Alzheimer's Drug Discovery Foundation dedicating a sixth of its drug discovery and development programs to neuroinflammation[18], but increasing the complexity of the endeavor by many factors at the same time.

More so, there are known differences between human neurons and animal neurons causing many efforts of developing drugs for AD that show promise in animal models to fail in human trials[19,20], suggesting a pressing need for studying AD in human model systems. Add to that the fact that there are many different forms of AD, each varying in onset and progression and it is no wonder that a new classification by the NIA-AA ATN has been put forth, as it tries to tackle the ever-growing puzzle that is pathology and diagnosis of AD.

One solution brought forth to tackle the complex problem is the quickly evolving field of Computational Neuroscience[21], an interdisciplinary field for development, simulation, and analysis of multi-scale models and theories of neural function from the level of molecules, through cells and networks, up to cognition and behavior. Enabling experimental data from all levels and fields to be combined and integrated into models[22], that give understanding of the data in relation to each other, allowing predictions for new experiments, identifying scale interactions and dynamics in neural structures and providing a framework for understanding the principles governing the work of neuronal systems and by extension how those systems can malfunction and lead to pathologies in the human brain.

In this work I’ll review the available literature on AD and try to form a picture of the process that happens in the brain during the pathology while explaining how that process affects the neurons and the changes they cause by using a single cell model, with which I will try to demonstrate the usefulness of the method and its versatility in translating and combining experimental and theoretical data into simulations that give a better representation of what the said data represent inside the brain.

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7. AIM

To understand the interaction of amyloid β (Aβ)-induced pathologies of long-term synaptic plasticity in hippocampal CA1 pyramidal neurons in Alzheimer’s disease (AD) by integrating neuroscience data into computational models.

8. OBJECTIVES

1. To review the clinical literature on Alzheimer’s disease.

2. To build a computational model of Aβ-induced pathological changes of long-term synaptic plasticity at hippocampal CA3-CA1 synapses in Alzheimer’s disease.

3. To analyse the modeling data to understand the Aβ-induced pathological changes of long-term synaptic plasticity in Alzheimer’s disease.

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9. LITERATURE REVIEW

9.1 Approaching Alzheimer’s disease through computational neuroscience

In the following literature review I try to collect enough information to understand the function of a CA3-to-CA1(cornu Ammonis) synapse and the changes that happen in the function under the AD pathogenetic factors. An understanding that will later be used to build a bottom-up model of said synapse to simulate experimental data from the referenced literature. Thus, demonstrating how experimental data can be added progressively to create complex simulations from a single model while providing a possible physiological basis behind the results and suggesting future avenues of wet lab experiments that will be useful for improving the model and understanding of AD.

First though, a short explanation on computational modeling is required, a field rooted in the early mathematical theories of Hodgkin’s and Huxley’s membrane potential equations of a squids giant axon[23]. The equations turn the length and diameter of an axon as well as each dendrite into an electrical circuit allowing neuroscience to accurately calculate the physiological processes and changes that happen in the nervous system and providing us with the fundamental equation of a compartmental model and allowing us to measure all currents flowing across a patch of axonal membrane.

𝐶

_𝑚

ⅆ𝑉

ⅆ𝑡

= 𝐺̅

𝑁𝑎

𝑚

3

_ℎ(𝐸

𝑁𝑎

− 𝑉) + 𝐺̅

𝐾

𝑛

4

(𝐸

𝑘

− 𝑉) + 𝐺

𝑚

(𝑉

𝑟𝑒𝑠𝑡

− 𝑉) + 𝐼

𝑖𝑛𝑗

(𝑡)

Thanks to Hodgkin’s and Huxley’s contribution the field of theoretical and computational neuroscience has grown enormously since 1952, with the Human Brain Project(HBP)[24] in Europe and Brain Research through Advancing Innovative Neurotechnology’s(BRAIN) initiative[25,26] in the U.S, with many more being established in Australia, Canada, China, Israel, Japan and more[27]; all aiming for a better understanding of the brain.

The field of neuroscience has grown so big that it fragmented into specializations and sub-specializations with labs working on genes, molecules and single-cell electrophysiology to cognitive neuroscience and psychophysics to name a few. With so many continually growing fields

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15 of research it is the role of Computational Neuroscience to try and bridge different levels of understanding by means of simulation and mathematical theory.

Table 1. Parameters of Hodgkin’s & Huxley’s equation

A bridge that can be built top-down, where known cognitive functions are modeled to understand the behavior of individual neurons and the they achieve these functions, an approach useful for analyzing large-scale datasets for correlations between genes and proteins but is difficult for designing experiments from the results. A bottom-up approach, where biochemistry and neurophysiology are used to explain phenomena observed on a higher level, is an approach that requires manually crafting detailed models, and although it can take many years, will result in simulations that can suggest wet lab experiments and even validate experimental data[28].

From assisting in designing drugs[29,30], improving treatment[31,32], explaining physiological processes or suggesting new ones[33], researching things that might be illegal to allowing simulating experiments on humans that are impossible or very difficult to get ethical permission for[34]. Computational modeling is a powerful and versatile tool for all scientific research from all fields of science, including medicine[35].

A tool that is inherently limited by the fact that science doesn’t know the full pathogenesis or the timeline of events that lead to many diseases, AD being one of them. As computational

Variable Explanation

𝐶𝑚 Membrane capacitance ⅆ𝑉

ⅆ𝑡

Rate of change of membrane potential with time. 𝐺̅_𝑁𝑎 Maximal sodium conductance = 120 mS/cm2

𝑚 Sodium channel gating variable (activating) ℎ Sodium channel gating variable (inactivating) 𝐸𝑁𝑎 Sodium reversal potential = 115 mV

𝑉 Electric potential.

𝑉_{𝑟𝑒𝑠𝑡} Resting membrane potential

𝐺̅𝐾 Maximal potassium conductance = 36 mS/cm2 𝑛 Potassium channel gating variable

𝐺_𝑚 Voltage independent "leak" conductance, does not depend on the applied voltage and remains constant over time. Measured by Hodgkin and Huxley, Gm =0.3 mS/cm2_{, corresponds to a passive membrane resistivity} of Rm = 3333 Ω • cm2

𝐼𝑖𝑛𝑗 Current injected via intracellular electrode. (𝑡) Time

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16 modeling relies on programing languages a proper chronology of pathological mechanisms is required for ideal models. Computational modeling also suffers from its code being linear and exponentially more computationally demanding as a model becomes larger and more detailed. And while quantum computing could one day help, it is still far from being useful.

Without access to supercomputers and teams of dedicated programmers, most computational neuroscientists are forced to settle for a small number of detailed neurons or large networks of neurons that lack detailed physiological processes. Giving rise to an ever increasing number of models and a situation where just choosing a model that best fits your research/hypothesis criteria is a lengthy process of its own with dozens of models for the CA1 region alone[36].

However, even an imperfect model can be useful as it provides an environment to test out hypothesis or play around with data to form new ones. Implementing and testing data in a virtual environment allows researchers to narrow down ideas and form a hypothesis to test without wasting precious time and money.

9.2 What is the hippocampus and why focus on this area?

Alzheimer’s is a brain wide phenomena, however, areas are affected differently both pathologically and chronologically, something which Braak et al put into stages in 1991[37], again in 2006[38] and more recently refined their findings in 2011[39] as well as showed that the disease process starts many decades before presentation of first symptoms, suggesting it might not be a disease of “old age” but simply a disease with a very slow progression whose symptoms often manifest in the elderly.

Using PET scans of Tau[40,41] and Aβ[14] researchers saw that in living patients their deposition aligns with Braak’s AD staging and since the CA1 region in the hippocampus is one of the most affected areas, mainly at early stages of AD when symptoms are just starting to be noticeable and possibly even before, it is on it this region that the review and model will focus on.

The hippocampus is part of the limbic system, it plays an important role in the consolidation of information from short to long-term memory as well as spatial memory which enables navigation. It is divided into different areas that form what is known as the hippocampal formation that consists of the dentate gyrus even though not anatomically part of it[42]. These areas form

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17 the basic hippocampal circuit, also known as the performant pathway, with the main flow of signals shown in Figure 2.

The CA1 region has around 20 or so cell types, with a recent review[43] suggesting that this diversity might enable parallel information processing although there isn’t yet understanding of how the cellular diversity might affect various functions. One cell type, an inhibitory interneuron[33], has been shown to be highly selective in its connectivity to specific dendritic

Figure 1: Braak’s Alzheimer stage progression with common symptoms. A - from Braak et al. 1991[37] (Neuropathological stageing of Alzheimer-related changes) colorized by the author.

B - from Villemagne et al. 2015 [41](Tau imaging: Early progress and future directions)

A

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18 branch types and, furthermore, it exhibited precisely targeted connectivity to the origin or end of individual branches.

Nonetheless, it is currently impossible to model every cell entirely let alone their interactions with each other, but as the field of Computational Neuroscience progresses and technology gets better the impossibility of reproducing all studied biological phenomena seems less impossible and more just a matter of time. Until such a future arrives current studied models are optimized to explore specific physiological and/or pathological properties[36]. Here, the literature review presents information and experimental data about the synapse between the axon terminal of a presynaptic CA3 pyramidal neuron with a dendritic spine of a postsynaptic CA1 pyramidal neuron in an effort of making a bottom-up computational model that can later be used to simulate not only AD pathological changes but possible treatment options as well.

9.3 CA3/CA1 Pyramidal Neuron Synapse

To build a computational model of the synapse it is required to start with normal

physiological structures and activity. These conditions are what the computational model is based on and are used to verify the validity of the simulations.

Figure 2: Hippocampal formation and the signal pathway. Information mainly travels from

entorhinal cortex (EC) to dentate gyrus (DG) and CA3 region and from there signal moves to CA1. PP= performant path; Mf=Mossy fibers; Sch= Schaffer collateral

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9.3.1 Spike timing dependent plasticity as the basis of memory

Synaptic plasticity is believed to underlie the biological basis of learning and memory[44]. Bidirectional long-term synaptic changes are induced by coincident activation of presynaptic and postsynaptic neurons[45,46]. If a presynaptic spike precedes a postsynaptic spike within a short time window, the synapse undergoes long-term potentiation (LTP), and it exhibits long-term depression (LTD) if the temporal order is reversed. Variations on this classic picture of spike timing

Figure 3: Diagram of hippocampal CA3 to CA1 pyramidal neuron synapse. Presynaptic action

potential (AP) releases glutamate into the synaptic cleft which opens AMPA receptors leading to postsynaptic AP. When action potential is strong enough it opens NMDA receptor which lets in Ca2+._{Intracellular calcium activates calmodulin (CaM), protein kinase A (PKA), CaMKII and} protein phosphatase 2B (PP2B); CaMKII phosphorylates and phosphatase PP2B dephosphorylates AMPA receptors, and these changes in AMPAR phosphorylation state are thought to underlie long-term potentiation (LTP) and long-term depression (LTD).

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20 dependent plasticity (STDP) have been found in the hippocampus, with the activity windows for LTP and LTD depending on the frequency of input–output spike pairing, the duration of such pairing and spike bursting in the postsynaptic cell.

α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAr) is permeable to Na+ while N-Methyl-D-aspartate (NMDA) is permeable to Na+_{and Ca}2+_{but is blocked by Mg++.} Situated on the CA3/CA1 synapse, they are responsible for long term potentiation(LTP) and long term depression(LTD)[47]. While LTP and LTD are wide spread phenomena, found in almost all synapses in the brain, the mechanism behind them varies between areas and neurons[48].

In the CA3/CA1 synapse when an action potential travels through the Schaffer collaterals, it leads to the release of glutamate into the synaptic space that then binds to both receptors, causing an influx of Ca2+ and an action potential in the synapse if there’s enough of it released. This process is the underlying mechanism behind signal transduction and synaptic plasticity in the brain.

A low frequency action potential (AP) will release small amounts of Glutamate from presynaptic axon of CA3 neuron, opening the AMPA receptors and allowing Na+ to pass into the CA1 post synaptic cell, causing a slight depolarization. However, this amount of Glutamate is not enough to remove the Mg+ from the NMDA receptors and thus they remain closed.

A high frequency AP leaves the AMPA receptors open longer, allowing more Na+ to pass and resulting in a larger depolarization event in the postsynaptic cells; an event that repels the Mg+ blockade through a process called electrostatic repulsion, opening the NMDA receptors and allowing Ca++ and Na+ to pass into the cell. As such, NMDA receptors are also known as coincidence detectors as they require a presynaptic and a postsynaptic event for channel opening, but once opened cause AMPA receptor insertion and clustering at the surface of dendritic membranes[49] which gives LTP.

It should be taken into account that a low frequency AP and consequently less glutamate in the synaptic space is not enough to cause LTP. This fits with a long time known fact [50] that AD patients have reduced levels of glutamate[51], resulting in impaired LTP[52] as well as an increased risk of psychosis[53].

9.3.2 Importance of Mg2+

Magnesium is essential thanks to its role in more than 300 intracellular enzyme systems. Its concentration affects many biochemical mechanisms, including the NMDA-receptor response to excitatory amino acids, cell membrane fluidity and stability, and the toxic effects of calcium.

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21 What’s more, studies in animals found that elevated Mg+ levels in the brain show enchantment of learning and memory[54] and have a protective effect against AD progression[55,56].

AD patients have lower levels of Mg+ compared to healthy individuals by ~18%[57–59] with evidence showing lower Mg2+_{levels in AD patients related to worse} Mini-mental-state-examination(MMSE) scores[60] where even mild-to-moderate AD patients show lower Mg+ levels compared with the same aged healthy adults[59], and a drug containing L-Threonic acid Magnesium salt(MgT), which allows better crossing of BBB, demonstrates increase in brain synapse density and restoration of cognitive abilities[61,62].

Such drugs are important as it seems that there might be a difference in the BBB of AD patients compared with healthy individuals as long-term magnesium Mg2+_{supplementation} increases CSF and total brain magnesium by only a fraction and small decreases in blood levels having significantly lower levels in CSF and brain[57], something shown in long-term Mg2+ supplementation of rats as well[55].

9.3.3 CaMKII and its role in memory formation

The influx of postsynaptic Ca2+_{through the NMDA receptors acts as a secondary} messenger, activating many cellular cascades and contributing to two phases of LTP that lead to neuronal changes that can last from a day up to a lifetime. The process is divided into two phases: • Early phase – Ca2+_{binds to respective binding proteins causing an insertion of new AMPA} receptors onto the postsynaptic cell membrane at the active CA3/CA1 synapse, with changes lasting for only a few hours and requiring a brief increase of Ca2+_levels.

• Late phase - a prolonged influx of Ca2+_{causes an increase in transcription factors that} ultimately result in new AMPA receptors being inserted into the postsynaptic CA3/CA1 membrane, as well as an increase in the production of growth factors involved in the formation of new synapses (a basis for synaptic plasticity), and other events resulting in LTP.

Both phases work through the CamKII kinase that is a part of the physiological and pathological processes seen in the brain and playing a critical role in LTP and more[63].

The Ca2+_{/calmodulin-dependent protein kinase II}_{(CaMKII) family consists of 28 isoforms,} derived from four genes (a, b, g, and d), with a and b subunits predominant in the brain of rats[64] with different distributions of subunits according to brain area but no significant difference found in hippocampus[65,66].

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22 CaMKII is crucial for dendritic spine structure[67] with each isoform specific to certain structures[68], and is particularly enriched at synapses, where it plays a crucial role in the regulation of synaptic transmission, neurotransmitter release, and synaptic plasticity. Normally, CaMKII is inactive because its binding site is blocked, but following Ca2+_{elevation due to synapse} communication, the blockade is removed and CaMKII diffuses to the synapse and accumulates in the postsynaptic density (PSD), where it binds to NMDA receptors through the carboxy-terminal domain of the NR2B subunit[69], forming the CaMKII/NMDA complex.

Furthermore, the binding of CaMKII to NMDA receptors (NMDAR) increases calmodulin affinity for the kinase. This phenomenon, called trapping, is a way of preventing dissociation of CaMKII from synaptic sites by inhibiting autophosphorylation of a secondary site which is responsible for the kinase deactivation and release from synapses[63,70]. Rapid activation (∼0.3 s) and the relatively slow decay (∼6 s and ∼1 min) of CaMKII underlie the stepwise activation, revealing its function as a biochemical integrator of Ca2+_{signals. The integration window of} CaMKII (6–8 s) also defines the frequency of stimulation required for inducing plasticity[63,71].

Besides its role in synaptic transmission, CaMKII is also involved in the structural plasticity of spines, and more specifically in activity-dependent spine growth following NMDAR activation[67]. Slutsky et al [54]show that using MgT treatment, a drug that increases Mg levels in the brain, doesn’t change expression levels of CaMKII but increases activation, thus enhancing NMDAR dependent signaling and possibly underlying another mechanism explaining how decrease in Mg2+_{levels plays a role in the pathological changes seen in AD brains[57–59].}

Interestingly, it is possible to induce LTP without CaMKII, however, the resulting LTP is cell wide and not synapse specific[72].

9.3.4 GABA Receptor

GABA receptors are a class of receptors that respond to the neurotransmitter gamma-aminobutyric acid (GABA), the chief inhibitory compound in the mature vertebrate central nervous system.

• GABA-A receptors are ligand-gated ion channels with numerous isoforms, of which the predominant isoform of the adult brain, α1β2γ2 GABAA receptor, has its structure recently published, providing insight into its inner workings and understanding of its interactions with GABA[73].

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23 • GABA-B receptors are G protein-coupled receptors and are heterodimers composed of

GABAB1 and GABAB2 subunits, with both required for normal receptor functioning. o Presynaptic GABAB receptors are subdivided into auto and heteroreceptors that

control the release of GABA and other neurotransmitters, respectively. They restrict neurotransmitter release either by inhibiting voltage-sensitive Ca2+_{channels or} through a direct modulation of synaptic vesicle priming.

o Postsynaptic GABAB receptors induce slow inhibitory potentials by gating Kir3-type K+_channels.

Surprisingly, there’s enough difference in amount of GABAergic neurons between CA1 and CA3 to suggest that it is this increased amount of GABAergic neurons in CA1 region that can provide a morphological basis to death of CA1 pyramidal neurons while CA3 neurons survive after transient ischemia[74]. Other studies explain this phenomenon by showing Ca2+_{level changes,} with a recent study showing differences in Ca2+_{and Zn}2+_{dependent excitotoxic triggering events} between CA1 and CA3 pyramidal neurons explaining their differential susceptibilities[75]; with the authors suggesting that ongoing Zn2+_{mobilization from MT-III in CA1, compared to Ca-AMPA in} CA3, leading to accumulation in mitochondria of CA1 as an integral cause of delayed activation of CA1 apoptotic injury in cases of ischemia.

Also, GABAB receptors are shown to have different distribution in CA3-to-CA1 synapse with selective localization of GABAB1a to axons,GABAB1b to dendritic spines, and GABAB1a inhibiting glutamate release, while predominantly GABAB1b mediates postsynaptic inhibition[76,77]. More so, sushi domain on the receptor functions as an axonal targeting signal[78] with soluble amyloid precursor protein(sAPP) now shown to attach to it and modulate synaptic transmission by suppressing probability of presynaptic vesicle release[79].

9.4 Pathophysiology of Alzheimer’s disease and its effect on the synapse

As mentioned in the introduction, there are many types of dementia, AD being the most common. There are also multiple types of AD, all currently irreversible. The two hallmark features of AD are amyloid-beta(Aβ) accumulation and Tau protein aggregates in the brain with neuroinflammation and abnormal microglia being added in recent years as either a catalyst or exacerbator for the two.

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24 A variety of risk factors are applied to this triad, factors ranging from sex and genetics to life style, habits and diet; some increasing Aβ levels while others causing inflammation.

9.4.1 Amyloid beta hypothesis

Amyloid beta is produced by most cells in the body and is detectible in both plasma and cerebrospinal fluid (SCF) under normal physiological conditions[80]. Produced at a rate of ~7.6% an hour and cleared at ~8.3% an hour[81] through efflux of intact soluble Aβ (sAβ) to the peripheral circulation[82] or proteolytic degradation of both soluble and fibrillar forms of Aβ (fAβ) by the immune system, specifically microglia[83]. Various factors can affect Aβ levels, levels normally regulated by circadian cycle[80], with even one night of sleep deprivation increasing Aβ in the hippocampus and other areas of the brain[84] and insomnia increasing risk of AD in elderly[85] as well as day-time sleepiness being correlated to Aβ accumulation[86].

At the same time, clearance rates of Aβ in older mice were shown to be reduced with evidence showing Apolipoprotein E (ApoE) playing a role[87]. ApoE being a key factor in AD as its variations can increase or decrease Aβ accumulation and clearance[88,89], where even cognitively normal carriers of ApoE4(~13% of world population with lower distribution in Asia[90,91]) show increased Aβ levels and pathological changes[92]. Genetically editing ApoE4 to ApoE3 in human derived neurons shows return to normal levels of Aβ and Tau phosphorylation[93], suggesting a possible treatment for some AD patients.

Aβ’s physiological function has yet to be determined, and although a recent study showing that AB might even have a protective function against brain infection[94] we still don’t understand why Aβ is deposited the way it is in the brain; for example, in the CA1 region, the pyramidal layer contains most plaques with the middle part of it holding the most and the area closer to CA2 the least[95]. Interestingly, the earliest accumulation of Aβ has been traced to the default-mode network (DMN)[96] thus giving a possible explanation why meditation, known to affect the DMN[97], appears to have some protective effect on the brain against neuropathology[98], AD included[99].

Aβ is made from the amyloid precursor protein (APP), a large protein that sits in the membrane of the neuron near the synapse. When it is cut by β- and γ-secretases in several places it produces various sizes of Aβ, the main of which are 40 amino acid long and 42, which is the one that seems to form clumps[100]. Specific mutations of this large protein, of which 58 are known, most being harmless while some, like KM670/671NL produce more Aβ42 and therefore more clumps[101] that form what is known as destructive senile plaques. Down syndrome, caused

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25 by a trisomy of chromosome 21, is associated with early onset AD(<65 year old’s)[102] and is interesting because the gene for APP is located on the 21st_chromosome.

Although it is still unclear what APP does, it appears to be important for synapse[103] function possibly through modulation of Ca2+_{activity in astrocytes[104], with aged APP deficient} mice showing impaired LTP[105–107], dendritic branching and synaptic density[107]. Through an unidentified receptor, APP also appears to be mediated by the large soluble APP(sAPP). A product of APP cleavage by α-secretase that as mentioned previously has recently been shown to suppress probability of presynaptic release via GAΒAΒ receptors[79] with some data suggesting that sAPPα may function as a neurotrophic factor[108,109].

APP seems to also affect the synapse through the NMDA receptors through APP intracellular domain(AICD), a process that seems to become pathological in AD upon AICD increase in mature neurons and possibly contributing to synaptic failure seen in AD[110]. This process is further contributed to by a suggested new pathway where g-secretase cleaves APP, generating proteolytic fragments capable of inhibiting neuronal activity within the hippocampus and lowering LTP to a degree comparable to synthetic amyloid-b dimers[111].

Aβ’s effect changes depending on brain area of the synapse, ranging from directly blocking synapses to exacerbating effects of Tau and cholinergic pathology[112–114]; and although how Aβ leads to AD is still not entirely understood, one thing known for sure is that clearing Aβ, at least in mice, seems to reduce Tau and even reverse symptoms of AD[115]. With a vaccine for humans having been found safe and currently in phase 2 of clinical trials[116] and two other clinical trials,”A4” and the “LEARN” studies, on their way to completion in 2020[117,118].

What is known, is that Aβ affects uptake of glutamate from the synapse, not only in neurons but astrocytes as well, where it is turned into glutamine and returned into the presynaptic terminals where it is converted back to glutamate[119].

Glutamate, the most abundant neurotransmitter in the brain, is an essential excitatory neurotransmitter and its activity is tightly regulated by glutamate transporters with excess glutamate in the synaptic cleft and dysfunction of excitatory amino acid transporters shown to be involved in development of AD, although the precise regulatory mechanism is poorly understood[120,121]. Aβ appears to increase glutamate release presynaptically[122] and from microglia[123], inhibit clearance by astrocytes[124,125] and affects glutamate receptors such as NMDA[126,127]. It seems to disrupt LTP not only in a similar manner as glutamate reuptake

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26 inhibitors[52] which decrease glutamate receptor function but by decreasing their expression as well[125], possibly due to endocytosis.

9.4.1.1 Amyloid Beta in the synapse and the “paradox” of its effect on NMDA receptors

In the hippocampus, Aβ seems to inhibit LTP through NMDA receptor-dependent ways[126,127]. It is still debated whether Aβ affects NMDAR directly or locally at the synapse level but what is certain is that Aβ disrupts Ca2+_{homeostasis through the NMDAR, with there} being two “paradoxical” findings:

• On the one hand Aβ upregulates NMDAR function[128], that is why the NMDAR antagonist Memantine is used in AD treatment[129]

• On the other hand there is evidence suggesting downregulation of NMDAR as Aβ oligomer application mimicking a state of partial NMDAR blockade[130], endocytosis of the receptor[131–133] or through activated microglia[134].

One proposed reason for this contradiction is the difference in study methods, with either neuronal cultures or rodent brain slices being the most common. Another option is the “two-stage” model of AD in which neurons and their receptors react to Aβ differently early in the disease, when NMDAR seem to be hyperactive, compared to the late stages when they are hypoactive[135].

Olney et al also suggest that it is the hyperactivity of the early stages that eventually leads to the

hypo due to the excitotoxicity[136] resulting from increased Ca2+ _{going into the neuron. A progress} that is also suggested in the “two-hit” hypothesis[137,138] that observes different interaction of similar properties early and late in AD[139]; possibly explaining low usefulness of AD drugs as well as contradicting their use entirely [140].

Similar changes have been modeled with results suggesting endocytosis of NMDARs as the cause of loss of synapses by disruption of CaMKII-NMDAR complex formation[141], with experimental data confirming the role CaMKII seems to play in localization and function of NMDAR[71,142,143].

More so, there is evidence suggesting different roles for synapticGluN2A-containing and extra-synaptic GluN2B-containing NMDAR’s, with the first mediating LTP and the second LTD[133,144,145] while GluN2B containing NMDA receptors accounting for about 50% of all NMDA receptors[146].

Endocytosis and removal of NMDA receptors, whether through striatal-enriched phosphatase(STEP)[132,147], C-terminal of NR2B subunit[148] or endocytic signals specific to each NMDAR type[149,150], is a normal process that happens during synapse maturation, LTD

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27 and in response to ligand binding. More so, endocytosis of NMDA receptors seems to down-regulate gating of remaining NMDAR; with Na+_{playing a pivotal role[151]. An important finding} considering NMDAR plays a key role in many neuropsychiatric pathologies including AD[152].

Under normal conditions NMDA receptors are upregulated by Sigma-1 receptors ( S -1Rs), activation of which leads to increase in de novo protein synthesis of GluN2A and GluN2B[153]. The loss of GluN2b-containing NMDAR in CA1 and cortex leads to learning deficits and reduced spine density[154], as well as GluN2B-containing NMDARs shown to be downregulated and suggested to be endocytosed after Aβ oligomers exposure[131,132,147,155]. The fact that there seems to be loss of Sigma binding site in the CA1 region in AD[156] even at early stages of the disease[157] could help further explain the downregulation of NMDAR in AD, or at least late stages of the disease.

Disruption in Ca2+_{homeostasis in neurons of AD brain, whether by activation/inhibition of} NMDAR by Aβ or other mechanisms, plays a critical role in the eventual atrophy and apoptosis of neurons seen at late stages of the disease. One proposed mechanism is the underlying disruption of axonal transport[158], or more specifically of mitochondria seen in Aβ affected neurons[159,160], a disruption that might be traced to how mitochondria are controlled by NMDAR[161] or the way they travel inside the neuron by microtubules[162,163]. Microtubules which give the neuron its form and are held together by the protein Tau[164].

The microtubule is built as a spiral cylinder with a positive charge on the growing leading edge and a minus charge on the other[165]. Transport away from the cell body carries lipids, proteins, energy producing mitochondria, vesicles of all types and other materials for the synapse. Transport back to the cell body is critical for mitochondrial going back and forth, removal of debris in vesicles and signals related to damage of distant axon regions[162,163,166].

In fact, defects in axonal transport might be the primary cause of Alzheimer’s disorder with increased levels of Aβ & Tau being directly related[158,167].

The two major motor proteins in the neuron are the Kinesin, which moves away from the cell center toward the synapse and the Dynein, which moves material toward the cell center[168]. The movement of mitochondria has a unique regulation, in which mitochondria are slowed near the synapse so they will stay there and provide energy. The signal to slow is increased levels of calcium from the neuron’s action potential at very particular places near the synapse. If they travel through an area of increased calcium they stop. Thus, when specific dendrites are very active, the mitochondria maintain a higher level of energy production.

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28 As explained previously in the part about Aβ effect on NMDAR’s, in AD there is dysregulation of Ca2+_{extracellularly and intracellularly[169]. Combined with the way organelles} move inside the neuron, especially mitochondria, there is a possible disruption in transportation of mitochondria by microtubules and subsequently the normal function of the neuron, with evidence showing that axonal transport is disrupted by improperly stationed mitochondria and other organelles[166].

9.4.3 Tau hypothesis

Tau is the major microtubule associated protein (MAP) of a mature neuron, the other two neuronal MAPs being MAP1 and MAP2. There are 6 types of Tau, differentiated by their alternate splicing of exon 2 (E2), E3 and E10 on the 16 exon segment that codes for Tau on chromosome 17Q21[170]. The gene that makes Tau is called MAPT for microtubule-associated protein tau gene and it is expressed differently during brain maturation, with one form only present during fetal stages [171,172] where it shows similarity with phosphorylated tau seen in AD and could be related to increased brain remodeling seen both in fetal and AD brains[173].

An established function of MAPs is their interaction with tubulin and promotion of its assembly into microtubules and stabilization of the microtubule network[164,174]. The microtubule assembly promoting activity of Tau, a phosphoprotein, is regulated by its degree of phosphorylation. A normal adult human brain has a concentration of ∼2 μM[175] and it binds to microtubules at a Kd of ∼100 nM.

The reason Tau is so important is that Tau holds the microtubules together in bundles [164], giving shape to neurons and helping growth and remodeling, and though there are other proteins that have a similar function only Tau works in both the axon and dendrites.

Little is known about Tau but the consensus is that too much of it is bad and leads to neurodegeneration and apoptosis, with it being implicated in more than 20 neurodegenerative diseases and only the alternate editing of exon 10 known to be associated with abnormal Tau and brain diseases[176]. However, contradicting this consensus there is some evidence suggesting that Tau overexpression can protect neurons from Ab-potentiated apoptosis[160,177] and even though Tau was shown to increase Aβ plaque size it didn’t increase Aβ-mediated synapse loss[178].

Tau neuronal damage in Alzheimer’s starts in the transentorhinal region of the temporal lobe. Then it affects the adjacent entorhinal cortex, a central hub for communication between the

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29 hippocampus and the neocortex, before spreading to the hippocampus and other regions of the cortex[37]. Although some evidence exists to localize early Tau accumulation to lower brainstem[39,179], it is still not clear what causes spread of Tau through the brain. Though it may be related to inflammation[180] and seems to spread through synapses[181], possibly through a prion-like manner[182,183], similar to Aβ’s activation of microglia[184].

The fact is that the pattern of sporadic Alzheimer’s is the same as the spread of Tau[37,40]; with Tau seeding happening one step ahead of the pathology[181,185]. Yet it is still not known for sure which type of Tau is spreading, what starts the process and what causes the eventual phosphorylation.

Three mechanisms seem to underline the pathogenesis of Tau in AD. Overexpression which prevents motor protein attachment to microtubules and normal axonal transport[167], formation of neurofibrillary tangles(NFT) and lastly, microtubule breakdown, with recent experiments showing that the breakdown might happen indirectly[186].

Although the full role of Tau in AD and other neurodegenerative disease is unknown, with most data leaning towards pathogenicity of Tau overexpression and hyperphosphorylation leading to Ca2+ _{dysregulation through disruption of mitochondrial activity and neuronal atrophy or} apoptosis[187,188]; some contradicting data suggests that Tau might protect neurons from apoptosis in AD and thus helps explain the characteristic neurodegeneration and atrophy seen in late stages of the disease[160,177] instead of simple neuronal cell death.

These contradictions and lack of concrete chronological pathogenetic process mean that much more research is still needed into the effects of the protein, both in physiology and pathogenesis. However, one difficulty of Tau research is that rodents don’t possess all types of tau found in humans, with different immunogenic response to the shared ones[189], and the distribution of isoforms seems to differ from humans as well[190–192]. Another problem in researching Tau is that it is very hydrophilic, solubility in vitro being ∼ millimolar and much higher than its ~micromolar concentration in cells, making it difficult to synthesize in laboratory conditions or replicate the hyperphosphorylation present in AD and subsequently to preform and gather experimental data; especially since the conditions that cause the hyperphosphorylation and aggregation are not entirely known. It is for these reasons that computational models of Tau are severely lacking.

New methods and models for researching tau are being proposed which will hopefully lead to better understanding of Tau’s role in the brain[193–195]. Nonetheless, whatever Tau’s role in

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30 AD may be, the first-in-man vaccine against pathologically modified Tau has been created[196] and its safety and immunogenicity tested and found to be favorable[197,198] and is now investigated in phase 2 trials.

9.4.4 Neuroinflammation in AD and how it connects all hypotheses together

Not only do Alzheimer patients have increased inflammatory markers[199–201] but long-term non-steroidal anti-inflammatory drug(NSAID) use was found to be protective against AD[202] with a meta-analysis by Maheswhari et al.[203] showing a strong correlation and new evidence of a direct connection between bacterial infection and the disease[94,204–207]. And although the protective effect wasn’t identical to all NSAID’s, there was a clear decrease in risk of AD with use of some NSAID’s, Ibuprofen showing the strongest protective effect while also shown to reduce AD pathology in mice[208,209].

At first it was thought that when tissue was destroyed in the brain due to AD, it resulted in inflammation, a finding similar to many dementias[210], however, there is some evidence to suggest that inflammation is a part of the reason for early destruction[200]. Whatever the order may be, it is undeniable that neuroinflammation plays a significant role in AD progression[211], directly through immune cells of the brain such as microglia [180,212] or indirectly by the effects of Aβ and Tau on the neurons and immune cells[134,213–216].

Microglia, first emerging from embryonic yolk sac at days 8-10 out of a line of immune macrophages, settle in the brain before the formation of the BBB and become full time brain cells as well as immune cells. There also exists another type of microglia called monocyte derived macrophages(MDM) that travel to the brain during an individual’s lifetime due to infections or other reasons and stay in the brain working together, or instead of microglia-derived microphages(MiDM)[217]. However, MDM’s can’t perform all of MiDM’s functions and react differently to stimuli[218,219]

Microglia are responsible for Aβ clearance[83], regulation of brain development and synapse pruning[220–222], phagocytic activity of microbes through toll-like receptors(TLR) or apoptotic debris through triggering receptor expressed on myeloid cells 2 (TREM2), as well as release of cytokines, reactive oxygen species(ROS), proteinases and other toxic molecules in response to inflammation[223].

Activated microglia undergo morphological and functional alterations and can stimulate formation of an inflammasome[224,225], a multiprotein oligomer that promotes maturation and release of pro-inflammatory cytokines and interleukins that lead to pyroptosis[226], a highly

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31 inflammatory form of programmed cell death. Activated microglia have been linked to neuropathology[227,228], can be activated by Aβ[184,229,230], help spread tau by internalization of it[180,231,232], with evidence showing microglial activation being correlated in vivo with both[233].

9.4.5 The neuroinflammatory cycle of AD

Once activated[234], microglia lose focus of their normal functions and in AD seem to begin a self-reinforcing cycle where there is decreased Aβ clearance and subsequent accumulation; resulting in unregulated microglia activation and formation of inflammasomes, eventually leading to constant neuroinflammation, neuronal damage, propagation and hyperphosphorylation of Tau, induction of neurotoxic astrocytes[235] and more.

Thus, neuroinflammation leads to constant, progressively worsening damaging processes which potentiate reactive microgliosis[234,236] culminating in the characteristic neuronal atrophy and apoptosis seen at late stages of AD, with many studies showing different mechanisms by which it affects the brain and various possible therapeutic approaches to decrease it.

One example is altered gamma frequency, measured by electroencephalography (EEG) normally a pattern of neural oscillation with a frequency of 25 to 100 Hz with 40 Hz being the most typical. It has been observed in multiple brain regions in several neurological and psychiatric disorders[237–239], including a reduction in spontaneous gamma synchronization in patients with AD[240,241] and reduced gamma power in multiple AD mouse models[242,243].

Relieving neuroinflammation and returning microglia to normal allows the brain to clear itself of accumulated Aβ, and Gamma frequencies were shown to do just that. Suggesting that 40Hz stimulation causes an alteration in the state of microglia and their gene regulation leading to reduced levels of amyloid-β (Aβ)1–40 and Aβ 1–42 isoforms in mice[244] with a provocative, not yet peer reviewed paper even claiming 40Hz acoustic stimulation can be used for therapy of AD[245].

Another example of the neuroinflammatory cycle is the brain-derived neurotrophic factor (BDNF) protein, a member of the neurotrophin growth factors it works in neurons of the hippocampus, cortex and basal forebrain by encouraging growth and differentiation of new neurons and synapses, making it important in memory formation through NMDA receptors activation, supporting synapse stability and signaling through AMPA receptor, suppression of GABAergic signaling through GABAA, stimulation of dendrite remodeling and growth as well as

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32 of neuronal stem cells, all of which lead to eventual differentiation of new neurons and synapses in a process of neurogenesis[246].

While BDNF seems to play a role in depression and anxiety[247], one possible physiological explanation on how physical exercise helps elevate those symptoms and improve memory in AD patients through increasing production of BDNF[248–250], the literature is still lacking to make a definite conclusion[251]. However, one definite underlying link to BDNF and hippocampus has been found through Fibronectin type III domain-containing protein 5(FNDC5)and its secreted form “Irisin”[252], part of the Irisin-BDNF axis.

BDNF is interesting from a neuroinflammation point of view in AD because not only is BDNF produced by microglia, but autocrine BDNF can further activate microglia[253] thus adding to the reactive microgliosis[236] seen in AD. At late stage of AD, BDNF levels have been found to be decreased[254] and while this makes it less useful as a biomarker for diagnosis of AD it does correspond with neurodegeneration seen at late stage of the disease[37,38] and might be a possible therapeutic avenue.

Slutsky et al.[54] show that MgT treated mice have increased CREB and CaMKII activation

that leads to increased NMDAR-dependent signaling which can also be confirmed by increased(36%) BDNF protein expression. With therapeutic effect of MgT repeated in multiple rodent models[54,56,62] and human trials[61].

ApoE4 and Astrocytes

However, it is possible that what leads to microglia losing their function is simple aging[255] with one of the mechanisms for this change being ApoE4’s role in Aβ clearance[87,89,256] and microglia pathological activation[256] with triggering receptor expressed on myeloid cells 2 (TREM2) playing a main role early in the disease[257]. ApoE4 itself is a known genetic risk factor for AD[91,92] and now that it’s known to affect not only microglia[256,258] but astrocytes as well[259], it is more important than ever to research therapeutic options through the lens of neuroinflammation and not only due to astrocyte role in glutamate metabolism[124,125].

Since astrocytes also show changes with age, having been found presenting phenotypical changes similar to neuroinflammatory reactive astrocytes[260], they are also implicated in the neuroinflammatory hypothesis of AD as they can become reactive in response to microglia[235] as well as contribute to pathological Aβ load[261]. Like activated microglia, reactive astrocytes undergo functional and morphological changes and in AD are found as integral components of

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33 neuritic plaques, particularly prominent around Aβ deposits both in the brain parenchyma and the cerebrovasculature; possibly because of their role in degrading plaques[262].

Nonetheless, since astrocytes don’t present a homogenous group of cells and like neurons they differ in morphology and function between brain regions[263,264], there is still much to learn before they can be a target for therapy.

Morphological changes happen in neurons as well and physiological observations suggest that the form of plasticity at a synapse depends not only on the timing of the presynaptic and postsynaptic activity[45,46], but also on the location of the synapse on the dendritic tree[265,266]. Even at early stages of AD, morphological changes of the brain can be found, however, there is some evidence to suggest that these changes are compensatory in nature, where the brain tries to save important functions by sacrificing stable structure[267,268]. Making it more important than ever to study AD pathology chronologically, as not only can this morphological change affect experimental data and computational models but treatment as well.

9.5 Treatment of AD

Only ﬁve treatments are currently approved by the United States Food and Drug Administration (FDA) for AD, namely, Rivastigmine, Galantamine, Tacrine, Donepril and Memantine. These are all cholinesterase inhibitors with the exception of Memantine, which is an NMDA (N-methyl-D-aspartate) receptor antagonist[269], and they delay the worsening of the symptoms in AD for some 6 to 12 months and work in about half of patients[140].

9.5.1 Cholinergic hypothesis

The reason cholinesterase inhibitors are used is due to one of the oldest AD theories, the “Cholinesterase Hypothesis of AD”. Support for this perspective came in the mid-1970s[270] with reports of substantial neocortical deficits in the enzyme responsible for the synthesis of acetylcholine (ACh), choline acetyltransferase (ChAT). Subsequent discoveries of reduced choline uptake, ACh releaseand loss of cholinergic perikarya confirmed a substantial presynaptic cholinergic deficit[271].

Together with the emerging role of ACh in learning and memory, the hypothesis proposed that degeneration of cholinergic neurons in the basal forebrain and the associated loss of cholinergic neurotransmission in the cerebral cortex and other areas contributed significantly to the deterioration in cognitive function seen in patients with AD.

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34 Almost 40 years since the origins of the cholinergic hypothesis, data from numerous studies have challenged its veracity as an explanation for the syndrome of dementia in AD, and today ACH dysfunction is considered a side effect of AD pathogenesis that affects symptoms indirectly.

As it is accepted that AD patients have decreased cerebral acetylcholine synthesis and impaired cortical cholinergic function, cholinesterase inhibitors (donepezil, rivastigmine, and galantamine) which increase cholinergic transmission by inhibiting cholinesterase at the synaptic cleft, provide modest symptomatic benefit in some patients with dementia, especially at early stages where majority of newly diagnosed AD patients are offered a trial of a cholinesterase inhibitor.

However, there is no convincing evidence that cholinesterase inhibitors are neuroprotective or have the ability to alter the underlying disease trajectory or have significant benefit for late stage disease[140,272]. If anything a recently published study found that cholinesterase inhibitors might even worsen prognosis of AD and speed up cognitive decline[273]. More so, the side effects range from nausea and vomiting to death[274], making them a risky treatment with questionable benefits.

NMDAR Antagonists

Memantine, which is the drug of choice for moderate to severe AD, improves mental function and ability to perform daily activities for some people but can cause side effects, including headache, constipation, confusion and dizziness. The further the disease progresses the less effect from drugs is seen and at very late stages of the disease, hospice is the only option.

A newer drug called Ifenprodil shows promise as it is more selective, working mainly on NR2b subunit of the NMDA receptor[275,276].

9.6 Future Directions

What this means is that for all the years of research and scientific advancements, there is no approved treatment targeting the pathophysiological mechanisms underlying AD; and all current therapies, like in most psychiatric and neurological pathologies, are symptomatic care only. Current candidate AD drugs include those that target either Aβ, APP, or tau metabolism by preventing oligomer eﬄux, modulating enzyme secretases, prevent aggregation, facilitate clearance and vaccination induced immunological clearance[277].

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35

With vaccines for Aβ and Tau in clinical trials[116,196], the first steps in tackling and preventing the underlying pathology have been taken, Aβ and Tau PET scans[12,13] for earlier diagnosis in vivo and a possible supplementation with MgT to increase Mg levels in the brain of AD patients[61]. This might all be enough to delay the onset of the disease and control its symptoms, but even if it all works, it is not a cure.

And if the latest failure of AD drugs targeting Aβ in clinical trial teaches us anything[19,20], it is that AD most likely cannot be cured unless the factor that connects all the various pathologies of AD, neuroinflammation, is tackled.

However, to cure the characteristic triad of AD, we must first understand it fully. And with how many factors are in play and all of them interconnected with each other, to combine everything together in laboratory conditions might be impossible. Or if it is, then the scope of the endeavor will overwhelm even the largest of institutions and budgets. To truly test the “two hit”/”two stage” theory of AD and make progress towards a cure, a way to combine the different scientific fields and research levels is needed.

9.6.1 Computational modelling, a powerful tool for studying the brain

This is where Computational Neuroscience comes in. This is why billions have been invested into the BRAIN initiative[25,26], HBP[24] and lesser known China Brain Project[278], all in the hope of developing better tools which are needed for understanding the complexity of the human brain.

Already the HBP’s Brain Simulation Platform (BSP) provides researchers with user friendly online tools for reconstructing and simulating data-driven models of neurons and whole brain tissue, allowing testing of experimental data on simulated single neurons or whole systems[279]. Another resource is SenseLab’s various free databases[280] for neuroscientists and anyone interested in the field, with ModelDB giving access to thousands of models for free[281]. Together with the growing field of Machine Learning and its use of artificial neural networks[282], computational neuroscience merged into a new field called Cognitive Computational Neuroscience[283], presenting us with a key for unlocking the mysteries of the brain.

Unfortunately, most medical practitioners are not aware of the field and its results in advancing our understanding of human physiology and pharmacological development, or the free tools at their disposal. Indeed, computational neuroscience suffers from a large setback which is the difficulty of translating results of models and their simulations to practical or clinical application.

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36 Yet its ability to find flaws, test experimental data or suggest new avenues of research is undeniable[36]. The following part of the thesis explains the method in which is computational neuroscience works and shows how medical practitioners can implement their knowledge into neuronal models to simulate results and form future hypothesis.

9.7 Computational models of Alzheimer disease

ModelDB[281] currently has more than 1400 free models for researchers to choose from, with 125 models of hippocampal CA1 pyramidal cells. Amongst them it’s possible to find biochemical, single cell, biophysical spiking and system level models[36].

Much of modeling has been focused on Aβ as there is more experimental data available, however, with the recent spike in Tau research in past years new models of Tau are starting to come out as well[284]. Computational modelling power is also being leveraged to find new avenues of diagnosis and treatment[29] and efforts are made to understand the chronological progression of AD[285].

Nonetheless, the wide variety and connectivity of pathological effects leading to AD, as seen in Fig.13, is a daunting task. So instead of tackling it all in one, various small teams work on specific aspects of the pathogenesis, finding answers and raising better questions for future research to tackle.

The HBP[24] and other brain research initiatives across the world then combine the best models to run large scale simulations on supercomputers. The model developed in this work will focus around the NMDA receptor, tackling a few aspects of the early stage hyperactivation and late stage inhibition, marked by red arrow in Fig. 13. Microglia and astrocytes won’t be modelled as they are too large an undertaking for one programmer in the time frame provided for this work. Nonetheless, they can be added to the model in the future, by the creators or other groups.

LITHUANIAN UNIVERSITY OF HEALTH SCIENCES