Pathological mechanisms and therapeutic strategies for Alzheimer’s disease : Neural Regeneration Research

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Review

Pathological mechanisms and therapeutic strategies for Alzheimer’s disease

Ju, Yaojun; Tam, Kin Yip DPhil (Oxon),*

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Neural Regeneration Research: March 2022 - Volume 17 - Issue 3 - p 543-549
doi: 10.4103/1673-5374.320970
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Abstract

Introduction

Alzheimer’s disease (AD) is the most common form of dementia, and is estimated to affect 131.5 million by 2050 if no effective therapies are available (Cummings et al., 2016). The only 4 available Food and Drug Administration (FDA) approved agents for AD treatment offered limited effects on cognitive improvement. Though considerable efforts have been directed to tackle this disease, AD remains inexorable and incurable. The high failure rate of AD drug development was thought to be mainly due to our poor knowledge about the complex pathological mechanism of this disease (Cao et al., 2018). There are numerous factors playing a role in the prognosis of AD. A number of hypotheses concerning the root cause of AD reveal the complexity of the disease. Cholinergic deficiency (Ferreira-Vieira et al., 2016), amyloid beta (Aβ) toxicity (Selkoe and Hardy, 2016), tau protein hyperphosphorylation (Lewis and Dickson, 2016), synaptic dysfunction (Briggs et al., 2016), oxidative-stress (Kumar and Singh, 2015), and neuroinflammation (Calsolaro and Edison, 2016) were proposed to be responsible for AD development. Regardless what the root cause of AD is, all these factors intensify the progression of disease. For decades, the “one drug for one target” strategy has been dominant, but is still unable to conquer this multifactorial disease. It is hypothesized that the multifunctional strategy, which could simultaneously modify different pathological pathways, would be helpful to treat this multifaceted disease (Savelieff et al., 2019).

In this review, we will describe the pathological mechanisms of the multiple etiologies of AD, establish the associations with some potential therapeutic targets and follow with an outline of the treatments currently under clinical evaluations for tackling these therapeutic targets. Finally we will briefly highlight some studies using multi-target drug development for AD treatment.

Search Strategy and Selection Criteria

Studies cited in this review published from 1990 to 2020 were searched on PubMed or Google Scholar database using the following keywords: Alzheimer’s disease, neurodegenerative disease, therapeutic, choline, amyloid, tau, synapse, antioxidant, neuroinflammation, multifunction, synaptic plasticity, glutamatergic, GABA, dopaminergic, adrenergic, serotonergic, cannabinoid, orexin, presinilin, APOE, vascular, diabetes. All clinical trial references cited in this review were taken from U.S. National Library of Medicine ClinicalTrials.gov on November 22, 2020.

Synaptic Dysfunctions in Alzheimer’s Disease

The most common symptom of AD is learning and memory decline. Synaptic connectivity between neurons is dynamic and plastic, which is fundamental in learning and memory (Stuchlik, 2014). Compared with other biochemical indices [e.g., senile plaques, neurofibrillary tangles (NFTs)], synapse loss was reported to be strongly correlated with cognitive impairment in AD (Terry et al., 1991). Synapse loss decreased the efficacy of neural signal transmission and disintegrated the neuronal network leading to cognitive dysfunctions in AD transgenic mice (Kashyap et al., 2019). Multiple studies have demonstrated that alteration of synaptic protein expression and synaptic plasticity were early events during AD progression in human and AD mouse brain samples (Mango et al., 2019). “Synaptic plasticity” regulates the number, structure, and strength of the synaptic connections between neurons. Long term synaptic plasticity mainly consists of long-term potentiation (LTP) and long-term depression (LTD), in which potentiation and depression demonstrate the increase and decrease of synaptic signal strength. The inhibition of LTP and enhancement of LTD were found to be associated with the progressive memory impairment in AD (Jang and Chung, 2016).

The most extensively studied forms of synaptic plasticity are the LTP and LTD in CA1 region of the hippocampus. The predominant hypothesis is that the postsynaptic calcium signal within dendritic spines dictates whether LTP or LTD triggered, with LTP requiring a calcium increase beyond a threshold and LTD requiring a modest calcium increase (Malenka and Nicoll, 1993; Citri and Malenka, 2008). Specifically, LTP involves preferential activation of protein kinases such as the calcium/calmodulin (CaM)-dependent protein kinase II (CaMKII), the cyclic adenosine monophosphate-dependent protein kinase (PKA), the extracellular signal-regulated kinase (Erk)/mitogen-activated protein kinase (MAPK), Src kinase and protein kinase C; while LTD involves activation of phosphatases such as the calcium/calmodulin-dependent phosphatase calcineurin, protein phosphatase 1 or dephosphorylation of PKA and protein kinase C substrates. Following LTP, there is enhanced α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors (AMPARs) exocytosis and incorporation of AMPARs into postsynaptic density involving the phosphorylation by CaMKII, accompanied by growth of new dendritic spines; while following LTD, there is enhanced endocytosis and dissociation of AMPARs from postsynaptic density regulated by calcium-dependent dephosphorylation, accompanied by shrinkage in the size of dendritic spines. The increase of synapse size in LTP is dependent upon dendritic protein synthesis, thus transcription factors such as cAMP response element-binding protein presumably to supply critical proteins, are required for maintaining synapse strength.

To ameliorate synaptic dysfunctions in AD, drug development strategies to improve synaptic plasticity and neural regeneration have been tested in clinical trials (Additional Table 1). Four clinical trials have been undertaken on 3 phosphodiesterase inhibitors to improve synaptic functions in AD. Among these four clinical trials, cilostazol has been advanced in phase 3, indicating phosphodiesterase inhibitors could be promising in AD treatment. Moreover, sigma-1 receptor agonists have been investigated in AD drug development in 7 ongoing clinical trials with 6 of which in phase 3. Interestingly stem cell therapies have attracted considerable attention in recent years. All these therapies are currently in phase 1 or phase 2.

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Additional Table 1 Agents modifying synaptic dysfunction of AD in clinical trials (ClinicalTrials.gov on November 22, 2020)

Neurotransmission in Alzheimer’s Disease

Cholinergic hypothesis of AD

The nucleus basalis of Meynert in the basal forebrain is a major source of cortical acetylcholine, which was reported with significant neuronal loss in AD patients (Doucette et al., 1986). In cholinergic presynaptic neurons, acetylcholine is synthesized by the enzyme choline acetyltransferase (ChAT) from choline and acetyl-coenzyme A, and transported to synaptic vesicles by vesicular acetylcholine transporter. Following the depolarization of neurons, acetylcholine is released into the synaptic cleft. Acetylcholine binds to acetylcholine receptors (namely the ligand-gated channel nicotinic acetylcholine receptors, and the G-protein coupled muscarinic acetylcholine receptors) to enable neurotransmission. The acetylcholine presented at the synaptic cleft is rapidly decomposed by acetylcholinesterase into choline and acetate. The extracellular free choline can be uptake by choline transporters into the presynaptic neurons for acetylcholine synthesis.

Evidence shows that the brain cortical cerebrospinal fluid acetylcholine levels were significantly lower in AD patients, which was correlated with cognitive impairment (Jia et al., 2004). Significant ChAT depletions were observed in postmortem AD brains, and the reduction of ChAT was reported to be correlated with the severity of dementia (Pappas et al., 2000). According to a longitudinal clinical study over 3 ± 1.5 years, the cholinergic basal forebrain atrophy rates were higher than the global brain shrinkage rates in the aging process, which was further increased in AD patients (Grothe et al., 2013). Significantly reduced nicotinic and muscarinic cholinergic receptors in nucleus basalis of Meynert of AD brains were observed according to the previous ligand binding studies in autopsied brains (Shimohama et al., 1986). The evidence of cholinergic innervation losses correlated with cognitive declines in AD patients formed the foundation of the “cholinergic hypothesis of Alzheimer’s disease”. Moreover, association between several strong anticholinergic drug exposure and increased risk of incident dementia were found in aged people (Coupland et al., 2019).

Based on the “cholinergic hypothesis”, three acetylcholinesterase inhibitors, including donepezil, rivastigmine and galantamine were approved by US FDA for AD treatment. To modify the deficits of cholinergic neurotransmission in AD, more cholinesterase inhibitors were developed and some of them are undergoing clinical trials (Additional Table 2). Nicotinic and muscarinic acetylcholine receptors agonists or positive allosteric modulators have entered clinical trials to evaluate the effects on enhancing cholinergic neurotransmission (Additional Table 2).

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Additional Table 2 Neurotransmission modifying agents for AD drug development in clinical trials (ClinicalTrials.gov on November 22, 2020)

Glutamatergic neurotransmission in AD

Glutamate is the primary excitatory neurotransmitter in the brain. Glutamate can be produced from glutamine by glutaminase and is the precursor of gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter. L-Glutamate is the most abundant free amino acid in brain and is the major excitatory neurotransmitter of the vertebrate central nervous system. Glutamatergic neurotransmission plays an important role in LTP, which is thought to be extremely important for learning and memory formation (Granger et al., 2013). Glutamate receptors are classified into two families: G protein-coupled metabotropic glutamate receptors (mGluRs) and the ligand-gated ionotropic glutamate receptors (iGluRs) (Reiner and Levitz, 2018). Glutamate binding to mGluRs leads to the production of inositol phosphate and second message signaling, affecting multiple signaling pathways within the cells. Glutamate binding to iGluRs [which comprises three subfamilies: AMPA receptors, kainate receptors, and N-methyl-D-aspartate (NMDA) receptors] produces fast excitatory currents. AMPA receptors and kainate receptors are extremely fast receptors at high glutamate concentrations. AMPA receptors are permeable to Na+ and Ca2+ and kainate receptors are mainly permeable to Na+ and K+. NMDA receptors show slower activation and higher Ca2+ permeability than AMPA and kainate receptors. Glutamate, together with the receptor co-agonist (glycine or D-serine) binding to NMDA receptors, combined with a strong postsynaptic membrane depolarization to release the magnesium ions (Mg2+) block of the receptor channels. The opened NMDA receptors allow the flow of Na+, K+, and Ca2+ into the cell leading to excitatory postsynaptic current.

Synapse losses and glutamatergic dysfunctions with AMPA receptors and NMDA receptors downregulation in the hippocampus were observed in AD patients (Jacob et al., 2007). However, AD drug development targeting on glutamatergic neurotransmission has been mainly focused on reducing glutamatergic neurotransmission. The inappropriate activation of glutamatergic signaling (mainly through NMDA receptors activation) results in excitotoxicity. Amyloid deposition increased the activation of Fyn to phosphorylate GluN2B subunit of NMDA receptors (NMDARs), and subsequently to strengthen the activity of NMDARs, through which excessive harmful levels of calcium ions fluxed into postsynaptic neurons and impaired synaptic functions (Rudy et al., 2015). Based on this theory, memantine, a non-competitive NMDA receptor antagonist was developed and approved for moderate to severe AD treatment in clinic. There are agents in clinical trials for AD drug development to exert neuroprotective effect via the reduction of glutamate release (Additional Table 2).

GABAergic neurotransmission in AD

GABA is the principal inhibitory neurotransmitter in the mammalian central nervous system. It plays an important role in maintaining excitatory and inhibitory balance in the brain (Smart and Stephenson, 2019). Literature evidence suggested that GABAergic remodeling contributed to the pathogenesis of Alzheimer’s disease (Govindpani et al., 2017). GABA is generated via α-decarboxylation of L-glutamate by the glutamic acid decarboxylase (GAD) with pyridoxal-5’-phosphate as cofactor to converse the inactive apo-GAD to the active holo-GAD. There are two isoforms of GAD [GAD65 (65 kDa) and GAD67 (67 kDa)] expressed in the brain; GAD65 is primarily located in presynaptic terminals and GAD67 is widely distributed in the cytosol. In presynaptic neurons, GABA is recruited into synaptic vesicles mediated by vesicular GABA transporter (vGAT). After being released into the synaptic cleft, GABA binds to either the ionotropic GABAA receptors (GABAARs) or metabotropic GABAB receptors (GABABRs) located on the postsynaptic membrane, to generate the inhibitory postsynaptic potential. GABA is cleared from the synaptic cleft and is taken up by neurons and astrocyte through membrane-bound GABA transporters [GATs, GABA transporter 1 (GAT1), GABA transporter 2 (GAT2), GABA transporter 3 (GAT3), and betaine-GABA transporter (BGT1)]. In astrocytes, GABA is catalyzed to succinate in a two-step reaction by GABA transaminase (GABA-T) and succinate semialdehyde dehydrogenase. Succinate is then recycled into the tricarboxylic acid cycle to generate glutamate, which is then converted to glutamine by glutamine synthase. Glutamine is then released from the astrocytes and transported to the presynaptic neurons.

The binding of GABA to the orthosteric site of GABAARs triggers the influx of Cl- and subsequent hyperpolarization and inhibition (Sivilotti and Nistri, 1991). The binding of GABA to the orthosteric site of GABABRs results in the dissociation of the coupled G protein into Gαi and Gβγ, and subsequently leads to the inhibition of the presynaptic Ca2+ influx channel and the activation of the postsynaptic K+ efflux channel (Sivilotti and Nistri, 1991; Terunuma, 2018). Gαi can reduce the intracellular cyclic AMP (cAMP) level by inhibiting the activity of adenylate cyclase. The cAMP signaling regulates the excitatory glutamatergic and cholinergic synaptic plasticity. Gβγ suppresses the influx of Ca2+ and triggers the release of the transmitter. Gβγ also promotes the K+ efflux through the K+ channel resulting in hyperpolarization and inhibition (Terunuma, 2018).

Up to 22% of AD patients experienced seizures (Mendez and Lim, 2003). Epileptiform discharge was observed in 22% of AD patients with no history or risk factors for epilepsy (Lam et al., 2020). Excitatory and inhibitory balance was found to be essential for brain oscillations, and disruption of functional oscillation contributed to memory deficits (Missonnier et al., 2020). GABAergic dysfunction has long been suggested to involve in the development of epilepsy and status epilepticus (Jones-Davis and Macdonald, 2003). Therefore, it has been hypothesized that targeting the enhanced GABAergic inhibition might be a valuable therapeutic option for AD treatment (Xu et al., 2020). Agents with anti-epilepsy efficacy (Additional Table 2) have been in clinical trials for AD treatment.

Monoaminergic neurotransmission in AD

Deficits in monoaminergic neurotransmission such as dopaminergic, noradrenergic and serotonergic neurotransmission were reported to be involved in AD. The monoamine neurotransmitters, which are synthesized and released from their presynaptic neurons, bind to the corresponding receptors on the postsynaptic membrane to exert functions. The excessive amount of monoamine neurotransmitters in the synaptic cleft is then degraded by monoamine oxidase or catechol-O-methyltransferase, or undergoes reuptake into the presynaptic terminal by monoamine transporters.

Dopaminergic deficits were most seen and investigated in Parkinson’s disease, a movement disorder characterized by rigidity, resting tremor, and bradykinesia (Cacabelos, 2017). More than 50% of patients with mild cognitive impairment or mild AD were diagnosed with concomitant Parkinsonism with rigidity, resting tremor, and DA transporter reduction in the basal ganglia (Sasaki, 2018). Dopaminergic deficits were associated with cognitive dysfunctions in AD patients, and restoration of dopaminergic neurotransmission rescued the pathologies and cognitive deficits in AD patients and AD mouse models (Koch et al., 2014; Cordella et al., 2018). Dopaminergic stimulation is identified as a potential therapeutic strategy for AD. However, the dopaminergic system is closely related to the brain reward. It has been suggested that dopaminergic dysfunction might account for neuropsychiatric symptoms in AD (Mitchell et al., 2011). Dopamine agonists and dopamine reuptake inhibitors have been in clinical trials (Additional Table 2) to improve neuropsychiatric symptoms in AD.

There have been reports of significant Locus coeruleus (LC) noradrenergic neurodegeneration, such as neuron loss and atrophy, associated with the severity of cognitive dysfunction in AD (Bondareff et al., 1987; Theofilas et al., 2017). Cognitive impairment exhibited correlations with LC tauopathy in aging, mild cognitive impairment and AD (Grudzien et al., 2007). Enhancing brain NE levels can reverse AD dysfunction, such as long-term potentiation deficits, cognitive decline, and neuroinflammation in AD animal models (Ardestani et al., 2017). Thus, the LC noradrenergic system is essential for maintaining cognitive function and could be targeted to improve cognition in AD. Agents aimed at maintaining normal noradrenergic neurotransmission are in clinical trials for AD treatment (Additional Table 2).

Extensive serotonergic denervation and serotonergic alteration were observed in both AD patients and AD animal models, and were suggested to be associated with AD pathogenesis (Ouchi et al., 2009; Ramos-Rodriguez et al., 2013). Restoration of serotonergic function by selective serotonin reuptake inhibitors, or serotonin receptor agonists or antagonists was proven to modulate behavioral and cognitive symptoms (Bianco et al., 2016; Bostancıklıoğlu, 2020). Thus, targeting the serotonergic system would be a promising approach for treating AD symptoms. Agents targeting serotonergic system in clinical trials for AD treatment are listed in Additional Table 2.

Other neurotransmission in AD

Other neurotransmissions such as the cannabinoid neurotransmission and orexinergic neurotransmission are also involved in motor learning and neuropsychiatric aspects. In the endogenous cannabinoid system, the endocannabinoids anandamide, for example, was generated firstly by transacylase to catalyze the conversion of phosphatidylethanolamine to N-acyl-phosphatidylethanolamine and then by phospholipase D cleavage. CB1 receptor activation was found to regulate intracellular Ca2+ concentration, glutamate release, neurotrophin expression and neurogenesis. CB2 activation was involved in the release of cytokine in microglia and had been suggested to play a role in the inflammatory pathology of AD (Talarico et al., 2019). Orexin is a hypothalamic neurotransmitter with functions to regulate wakefulness, appetite and mood. Investigations suggested that orexinergic signaling activation altered the sleep-wake cycle and induced Aβ and tau pathology mediated neurodegeneration (Liguori, 2017). Thus, there are cannabinoid and orexin related agents in clinical trials to modulate the symptoms in AD (Additional Table 2).

The agents targeting neurotransmission system in AD drug clinical trials are mainly for modulating AD symptoms, such as cognitive decline, epileptiform symptoms, insomnia and agitation. As shown in Additional Table 2, many agents are repurposed drugs specifically for these symptoms. It would be helpful to modulate AD symptoms based on the treatments developed for other neural disorders.

Amyloid Cascade Hypothesis in Alzheimer’s Disease

Senile plaques, which composed of Aβ peptides, are one of the most important pathological hallmarks in AD brains (Xiao et al., 2015). In pathological conditions, Aβ is the proteolytic product of amyloid precursor protein (APP) by β-secretase and then γ-secretase via an amyloidogenic pathway, while in physiological conditions, APP is catalyzed by α-secretase instead of β-secretase via a non-amyloidogenic pathway to form soluble APPα fragment (Soldano and Hassan, 2014).

The strongest support for the initial role of Aβ in this disease comes from the genetic evidence clarifying the formation of AD. APP, presenilin 1 (PSEN1), and presenilin 2 (PSEN2) are mutation genes responsible for familial AD or early-onset AD. Aβ, the major subunit composed of amyloid plaques, is the cleavage product of APP, whose coding gene is located on human chromosome 21 (Masters et al., 1985). The AD-like anatomy characteristics, namely the senile plaques and NFTs, were formed and distributed in people with Down syndrome, even at young ages, indicating the importance of APP in AD pathology (Mann and Esiri, 1989). Missense mutations in APP genes were shown to alter Aβ metabolism with either an accelerating or restraining effect on Aβ aggregation and cognitive decline in AD patients (Godbolt et al., 2006; Lan et al., 2014). AD symptoms formed in APP transgene mice models further verified the Aβ hypothesis (Hsiao et al., 1996). Mutations in PSEN1 and PSEN2 lead to an “aggressive forms of” Alzheimer’s disease by affecting γ-secretase activity to aggravate Aβ aggregation in AD patients (Bentahir et al., 2006). The strongest genetic risk factor for sporadic AD or late-onset AD is the apolipoprotein E (ApoE) (Musiek and Holtzman, 2015). APOE isoforms influence AD by regulating Aβ clearance differently, with the APOE ε4 allele markedly increases AD risk while the APOE ε2 allele decreases Aβ accumulation (Castellano et al., 2011).

Another strong support for the crucial role of Aβ is the synergistic neurotoxic effects on other pathologies. It was shown that plaques formed by Aβ aggregation activated the microglia and ensued progressive neural changes and dysmorphic neurites in in vivo models (Meyer-Luehmann et al., 2008). Aβ is considered a driving force for tau propagation. For instance, injection of Aβ42 into the brains of P301L mutant tau transgenic mice accelerated the AD symptom formation (Gotz et al., 2001). This was further supported by the test of crossing rTgTauEC transgenic mice with APP/PS1 mice, in which the amyloid deposition dramatically increased tau propagation and spread, as well as the tau-induced neuron loss (Pooler et al., 2015). Amyloid cascade was also supposed to be a driving force of neuronal hyperexcitation in AD. A recent study revealed that Aβ induced hyperexcitation in sensitive neurons and sustained the vicious cycle of neuronal hyperactivation (Zott et al., 2019). Another study revealed that secreted APP (sAPP) specifically bound to GABABR1a and suppressed synaptic release, suggesting that secreted APP-GABABR1a interaction might play a role in maintaining neural circuits homeostasis (Rice et al., 2019).

The amyloid cascade hypothesis has gained continuous support for nearly 30 years. Moreover, targeting amyloid transport, APP secretase enzyme, and amyloid aggregation and clearance were suggested as viable therapeutic strategies (Kumar et al., 2015). Therapies targeting Aβ have been studied extensively and intensively. The on-going anti-amyloid clinical trial studies are summarized in Additional Table 3. In these anti-amyloid strategies, targeting amyloid clearance seems to be rather popular. There are 10 immunotherapies in 18 clinical trials aiming to remove Aβ monomers, oligomers and plaques. Amongst them, 4 immunotherapies are currently in 10 phase 3 studies.

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Additional Table 3 Anti-amyloid agents for AD treatment in clinical trials (ClinicalTrials.gov on November 22, 2020)

Tau Toxicity Cascade in Alzheimer’s Disease

NFTs are another important histopathological characteristics in AD brains (Lewis and Dickson, 2016). The NFTs comprise of paired helical filaments, which assembled by microtubule-associated protein known as tau. Tau protein assembles tubulin into microtubules and stabilizes microtubules (Goodson and Jonasson, 2018). As major cytoskeletal components of the neuron, microtubules play a fundamental role in neuronal development and function (Kapitein and Hoogenraad, 2015). The dissociation of microtubule stabilizer tau protein in AD induces depolymerization of microtubules and then further destroys neural functions. Tau phosphorylation is a normal metabolic process in physiological conditions. In contrast, in some pathological conditions, Aβ toxicity, neuroinflammation, and other stress conditions lead to aberrant tau phosphorylation (Gao et al., 2018). In particular, dysequilibrium of tau kinase and phosphatase activities leads to abnormal tau phosphorylation, thereby contributing to tau aggregation. A variety of tau kinases, such as CK1/2, glycogen synthase kinase-3 (GSK-3), PKA, p38MAPK, Erk1/2, JNK1/3, CDK5, TTBK1/2, and CaMKII, have been summarized elsewhere (Martin et al., 2013). The hyperphosphorylated tau is prone to dissociation from microtubules and aggregation to form NFTs (Wang et al., 2013). The existence of NFTs and the dissociation of microtubules then lead to axonal transport impairment, mitochondrial and cytoskeletal dysfunction, neuroinflammation, oxidative stress, and synapses loss (Hoover et al., 2010). Messing et al. (2013) reported that in the tau toxicity cascade, dendritic spine loss was observed before aggregation and cell death in an early stage, and tau aggregation and cell death in the later stage, were found to be accompanied by caspase-3 activation. These authors also proved that a tau aggregation inhibitor could prevent the phosphorylation, aggregation, and dendritic spine loss in tau pathology. The repeat domain located in paired helical filaments showed a high binding affinity to truncated tau and was responsible for tau-tau binding. These have led to the study of inhibitors targeting this repeat domain to stop tau aggregation.

In clinical trials of AD drug development, strategies targeting microtubule stability, tau protein aggregation, tau production and clearance were adopted to treat tau toxicity. Additional Table 4 summarizes the agents to modulate tauopathy in AD clinical trials. Among these agents, therapies targeting tau protein clearance occupied most of the seats. However, none of these immunotherapies for tau protein clearance has entered phase 3 study yet. Tau aggregation inhibitor, TRx0237 (LMXT), is the only anti-tau agent currently in phase 3 study for AD treatment.

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Additional Table 4 Anti-tau agents for AD treatment in clinical trials (ClinicalTrials.gov on November 22, 2020)

Ageing Related Risk Factors in Alzheimer’s Disease

Ageing facilitates and accelerates cognitive impairment and is the most predominant risk factor for neurodegenerative diseases, including AD (Hou et al., 2019). In aged population, there are dysregulations of the immune system and decreased metabolism levels with higher risk of neuroinflammation, oxidative stress and vascular diseases as well as diabetes (Donato et al., 2018; Rea et al., 2018; Luo et al., 2020). These ageing related risk factors are supposed to involve in AD pathologies.

Multiple studies have shown that there were elevated inflammatory cytokines and chemokines and accumulated activated microglial at the damage region in AD brains (Calsolaro and Edison, 2016). In recent years, genome-wide association studies have identified several AD-risk single nucleotide polymorphisms associated with or related to microglial function, including TREM2, CD33, CR1, CLU, CD2AP, EPHA1, ABCA7, and INPP5D (Spangenberg and Green, 2017), indicating that microglia played a critical role in the development of AD. An updated meta-analysis from the cohort of the year 1995 to 2016 demonstrated that the use of non-steroidal anti-inflammatory drugs was significantly associated with the reduced risk of AD (Zhang et al., 2018). Anti-inflammatory agents for AD treatment currently in clinical trials are listed in Additional Table 5.

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Additional Table 5 Neuroprotective agents for AD treatment in clinical trials (ClinicalTrials.gov on November 22, 2020)

Oxidative stress, an imbalance between reactive oxygen species and antioxidants in biological system, is related to aging and involved in AD pathology to induce tau phosphorylation and synapse dysfunction in the brain (Kumar and Singh, 2015). Glutathione redox imbalance in the brain was found to contribute to the pathology of neurodegenerative diseases, suggesting that therapies aimed at improving the anti-oxidant level could be promising approaches for AD treatment (Gu et al., 2015). Natural products could provide many antioxidant agents, and have proved beneficial to AD patients. Polyphenols, such as curcumin, resveratrol and epigallocatechin-3-gallate, were suggested to have good potential for AD treatment with low frequency of adverse events (Syarifah-Noratiqah et al., 2018). The currently antioxidant agent in clinical trials for AD treatment are summarized in Additional Table 5.

Certain vascular lesions such as cerebral amyloid angiopathy, microvascular degeneration, and periventricular white matter lesions are evident in almost all cases of AD (Kalaria and Ballard, 1999). In the two-hit vascular hypothesis of AD etiology, on one hand, the disrupted BBB leads to a reduced clearance of neurotoxins including Aβ; on the other hand, brain oligemia leads to overexpression and enhanced processing of APP, and brain hypoperfusion (Nelson et al., 2016). According to a meta-analysis, treatment of vascular risk factors with antihypertensives and statins reduced the incidence of dementia and AD (Larsson and Markus, 2018). Thus, vascular risk factors treatment might be a potential strategy to slow cognitive decline in AD. To restore vascular function in AD, some vascular protection agents, such as angiotensin receptor blockers, angiotensin converting enzyme inhibitor, calcium channel blocker, cholesterol agent, omega-3 fatty acid, and direct thrombin inhibitor are now in clinical evaluations for AD treatment (Additional Table 5).

Diabetes has been implicated as a major risk factor of AD development (Vignini et al., 2013; Baglietto-Vargas et al., 2016). The pathological features of diabetes, such as insulin/insulin-like growth factor resistance, hyperglycemia and glucose metabolism dysfunction, were observed to induce AD pathologies in Aβ production, tauopathy, neuroinflammation and cognitive impairment. Antidiabetic agent or agent regulating metabolism are thought to be helpful against AD. Sex steroid hormones, such as estrogen and androgen, exert neuroprotective benefit in adult brains (Pike, 2017). Insufficiency of sex hormones in male and female both enhance the vulnerability to AD. In Additional Table 5, agents in AD drug development clinical trials with potential to modulate metabolism and endocrine related risk factors are summarized.

Although the mechanisms of how these aging related risk factors play roles in AD etiology are still poorly understood, considerable research effort has been undertaken to tackle these factors for AD treatment. As shown in Additional Table 5, there are 50 agents (including 21 anti-inflammatory agents, 6 anti-oxidation agents, 9 vascular modifying agents, 12 metabolism modifying agents and 2 endocrine modifying agents) and 53 clinical trials to modulate the aging related risk factors for AD treatment.

Conclusions

AD is a complex neurodegenerative disease with various pathological factors. Although a number of promising therapeutic strategies have been evaluated, more extensive and intensive fundamental studies are still needed. To date, there is still no effective drug that can cure AD patients. Therapies developed based on cholinergic deficiency offered only limited cognitive improvement. The up-to-now disease modifying drugs failed to improve cognition in clinical trials. What the previous failures indicating is that targeting on single factor alone may not necessarily work well on disease caused by multiple factors. Consequently, the disease’s complex mechanisms and the interplay between the multiple factors call for the come out of all-powerful therapies with multiple curing functions.

Indeed, multitarget strategy has already been put into practice in the clinic and clinical trials. A combination of one of the cholinesterases inhibitors (donepezil) with memantine is the fifth FDA approved prescription for moderate-to-severe Alzheimer’s patients (Bennett et al., 2019). Blarcamesine, a multifunctional drug as the sigma-1 and muscarinic dual agonist and GSK-3β inhibitor, is currently in phase 3 clinical trial for AD treatment. Multitarget therapies, mainly the combination of several agents with different aspects of anti-AD functions, and multitarget agents currently in AD drug clinical trials are summarized in Additional Table 6. 13 multi-targeting agents and 22 clinical trials are on-going for AD treatment, including 6 agents in phase 3, 6 agents in phase 2 and 1 agent in phase 1 clinical studies. Among these therapies, ANAVEX2-73 is expected to modulate synaptic dysfunction, cholinergic neurotransmission, tauopathy by regulating the sigma-1 receptor, muscarinic receptors and GSK-3β.

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Additional Table 6 Multitarget therapies for AD treatment in clinical trials (ClinicalTrials.gov on November 22, 2020)

It is noted that many therapeutic targets play roles in multiple pathological pathways. Thus, therapeutically modulations of these targets could be beneficial in AD treatment via multiple mechanisms of action. For example, apart from metabolic function, GLP-1R agonists were observed to modulate neuroinflammation (Yun et al., 2018) and neurovascular functions (Zhao et al., 2020) in neurodegenerative disease models. Moreover, sigma-1 receptor (Jin et al., 2015) and GSK-3β (Lauretti et al., 2020) are regarded as multi-functional therapeutic targets. These therapeutic targets with multiple mechanisms of action could offer great potential in multitarget AD drug development.

Considering the complexity of AD pathology, multifunctional agents designed with multitarget potential could lead to a breakthrough in AD therapeutic development. Preclinical studies on different pathologies and multitarget treatments (Wang et al., 2019; Ju et al., 2020; Ju and Tam, 2020) may provide a pool of lead compounds for future clinical investigations. There is no royal road to overcome AD, but multifunctional drug is likely to give hope for AD treatment.

1. Ardestani PM, Evans AK, Yi B, Nguyen T, Coutellier L, Shamloo M. Modulation of neuroinflammation and pathology in the 5XFAD mouse model of Alzheimer’s disease using a biased and selective beta-1 adrenergic receptor partial agonist Neuropharmacology. 2017;116:371–386
2. Baglietto-Vargas D, Shi J, Yaeger DM, Ager R, LaFerla FM. Diabetes and Alzheimer’s disease crosstalk Neurosci Biobehav Rev. 2016;64:272–287
3. Bennett CF, Krainer AR, Cleveland DW. Antisense oligonucleotide therapies for neurodegenerative diseases Annu Rev Neurosci. 2019;42:385–406
4. Bentahir M, Nyabi O, Verhamme J, Tolia A, Horre K, Wiltfang J, Esselmann H, De Strooper B. Presenilin clinical mutations can affect gamma-secretase activity by different mechanisms J Neurochem. 2006;96:732–742
5. Bianco OA, Manzine PR, Nascimento CM, Vale FA, Pavarini SC, Cominetti MR. Serotoninergic antidepressants positively affect platelet ADAM10 expression in patients with Alzheimer’s disease Int Psychogeriatr. 2016;28:939–944
6. Bondareff W, Mountjoy CQ, Roth M, Rossor MN, Iversen LL, Reynolds GP, Hauser DL. Neuronal degeneration in locus ceruleus and cortical correlates of Alzheimer disease Alzheimer Dis Assoc Disord. 1987;1:256–262
7. Bostancıklıoğlu M. Optogenetic stimulation of serotonin nuclei retrieve the lost memory in Alzheimer’s disease J Cell Physiol. 2020;235:836–847
8. Briggs CA, Chakroborty S, Stutzmann GE. Emerging pathways driving early synaptic pathology in Alzheimer’s disease Biochem Biophys Res Commun. 2016;483:988–997
9. Cacabelos R. Parkinson’s disease: from pathogenesis to pharmacogenomics Int J Mol Sci. 2017;18:551
10. Calsolaro V, Edison P. Neuroinflammation in Alzheimer’s disease: current evidence and future directions Alzheimers Dement. 2016;12:719–732
11. Cao J, Hou J, Ping J, Cai D. Advances in developing novel therapeutic strategies for Alzheimer’s disease Mol Neurodegener. 2018;13:64
    12. Castellano JM, Kim J, Stewart FR, Jiang H, DeMattos RB, Patterson BW, Fagan AM, Morris JC, Mawuenyega KG, Cruchaga C, Goate AM, Bales KR, Paul SM, Bateman RJ, Holtzman DM. Human apoE isoforms differentially regulate brain amyloid-beta peptide clearance Sci Transl Med. 2011;3:89ra57
    13. Citri A, Malenka RC. Synaptic plasticity: multiple forms, functions , and mechanisms Neuropsychopharmacology. 2008;33:18–41
    14. Cordella A, Krashia P, Nobili A, Pignataro A, La Barbera L, Viscomi MT, Valzania A, Keller F, Ammassari-Teule M, Mercuri NB, Berretta N, D’Amelio M. Dopamine loss alters the hippocampus-nucleus accumbens synaptic transmission in the Tg2576 mouse model of Alzheimer’s disease Neurobiol Dis. 2018;116:142–154
    15. Coupland CAC, Hill T, Dening T, Morriss R, Moore M, Hippisley-Cox J. Anticholinergic drug exposure and the risk of dementia: a nested case-control study JAMA Intern Med. 2019;179:1084–1093
    16. Cummings J, Aisen PS, DuBois B, Frolich L, Jack CR, Jones RW, Morris JC, Raskin J, Dowsett SA, Scheltens P. Drug development in Alzheimer’s disease: the path to 2025 Alzheimers Res Ther. 2016;8:12
      17. Donato AJ, Machin DR, Lesniewski LA. Mechanisms of dysfunction in the aging vasculature and role in age-related disease Circ Res. 2018;123:825–848
      18. Doucette R, Fisman M, Hachinski VC, Mersky H. Cell loss from the nucleus basalis of Meynert in Alzheimer’s disease Can J Neurol Sci. 1986;13:435–440
      19. Ferreira-Vieira TH, Guimaraes IM, Silva FR, Ribeiro FM. Alzheimer’s disease: targeting the cholinergic system Curr Neuropharmacol. 2016;14:101–115
      20. Gao Y, Tan L, Yu JT, Tan L. Tau in Alzheimer’s Disease: mechanisms and therapeutic strategies Curr Alzheimer Res. 2018;15:283–300
      21. Godbolt AK, Beck JA, Collinge JC, Cipolotti L, Fox NC, Rossor MN. A second family with familial AD and the V717L APP mutation has a later age at onset Neurology. 2006;66:611–612
      22. Goodson HV, Jonasson EM. Microtubules and microtubule-associated proteins Cold Spring Harb Perspect Biol. 2018;10:a022608
        23. Gotz J, Chen F, van Dorpe J, Nitsch RM. Formation of neurofibrillary tangles in P301L tau transgenic mice induced by A beta 42 fibrils Science (New York, NY). 2001;293:1491–1495
          24. Govindpani K, Guzman BCF, Vinnakota C, Waldvogel HJ, Faull RL, Kwakowsky A. Towards a better understanding of GABAergic remodeling in Alzheimer’s disease Int J Mol Sci. 2017;18:41
            25. Granger AJ, Shi Y, Lu W, Cerpas M, Nicoll RA. LTP requires a reserve pool of glutamate receptors independent of subunit type Nature. 2013;493:495
            26. Grothe M, Heinsen H, Teipel S. Longitudinal measures of cholinergic forebrain atrophy in the transition from healthy aging to Alzheimer’s disease Neurobiol Aging. 2013;34:1210–1220
            27. Grudzien A, Shaw P, Weintraub S, Bigio E, Mash DC, Mesulam MM. Locus coeruleus neurofibrillary degeneration in aging, mild cognitive impairment and early Alzheimer’s disease Neurobiol Aging. 2007;28:327–335
            28. Gu F, Chauhan V, Chauhan A. Glutathione redox imbalance in brain disorders Curr Opin Clin Nutr Metab Care. 2015;18:89–95
            29. Hoover BR, Reed MN, Su J, Penrod RD, Kotilinek LA, Grant MK, Pitstick R, Carlson GA, Lanier LM, Yuan LL, Ashe KH, Liao D. Tau mislocalization to dendritic spines mediates synaptic dysfunction independently of neurodegeneration Neuron. 2010;68:1067–1081
            30. Hou Y, Dan X, Babbar M, Wei Y, Hasselbalch SG, Croteau DL, Bohr VA. Ageing as a risk factor for neurodegenerative disease Nat Rev Neurol. 2019;15:565–581
            31. Hsiao K, Chapman P, Nilsen S, Eckman C, Harigaya Y, Younkin S, Yang FS, Cole G. Correlative memory deficits, A beta elevation, and amyloid plaques in transgenic mice Science (New York, NY). 1996;274:99–102
              32. Jacob CP, Koutsilieri E, Bartl J, Neuen-Jacob E, Arzberger T, Zander N, Ravid R, Roggendorf W, Riederer P, Grunblatt E. Alterations in expression of glutamatergic transporters and receptors in sporadic Alzheimer’s disease J Alzheimers Dis. 2007;11:97–116
              33. Jang SS, Chung HJ. Emerging link between Alzheimer’s disease and homeostatic synaptic plasticity Neural Plasticity. 2016;2016:7969272
              34. Jia JP, Jia JM, Zhou WD, Xu M, Chu CB, Yan X, Sun YX. Differential acetylcholine and choline concentrations in the cerebrospinal fluid of patients with Alzheimer’s disease and vascular dementia Chin Med J. 2004;117:1161–1164
              35. Jin JL, Fang M, Zhao YX, Liu XY. Roles of sigma-1 receptors in Alzheimer’s disease Int J Clin Exp Med. 2015;8:4808–4820
                36. Jones-Davis DM, Macdonald RL. GABA(A) receptor function and pharmacology in epilepsy and status epilepticus Curr Opin Pharmacol. 2003;3:12–18
                37. Ju Y, Tam KY. 9R, the cholinesterase and amyloid beta aggregation dual inhibitor, as a multifunctional agent to improve cognitive deficit and neuropathology in the triple-transgenic Alzheimer’s disease mouse model Neuropharmacology. 2020;181:108354
                38. Ju Y, Chakravarty H, Tam KY. An isoquinolinium dual inhibitor of cholinesterases and amyloid beta aggregation mitigates neuropathological changes in a triple-transgenic mouse model of Alzheimer’s disease ACS Chem Neurosci. 2020;11:3346–3357
                  39. Kalaria RN, Ballard C. Overlap between pathology of Alzheimer disease and vascular dementia Alzheimer Dis Assoc Disord 13 Suppl. 1999;3:S115–123
                    40. Kapitein LC, Hoogenraad CC. Building the neuronal microtubule cytoskeleton Neuron. 2015;87:492–506
                    41. Kashyap G, Bapat D, Das D, Gowaikar R, Amritkar RE, Rangarajan G, Ravindranath V, Ambika G. Synapse loss and progress of Alzheimer’s disease - A network model Sci Rep. 2019;9:6555
                    42. Koch G, Di Lorenzo F, Bonnì S, Giacobbe V, Bozzali M, Caltagirone C, Martorana A. Dopaminergic modulation of cortical plasticity in Alzheimer’s disease patients Neuropsychopharmacology. 2014;39:2654–2661
                    43. Kumar A, Singh A. A review on mitochondrial restorative mechanism of antioxidants in Alzheimer’s disease and other neurological conditions Front Pharmacol. 2015;6:206
                      44. Kumar A, Singh A, Ekavali. A review on Alzheimer’s disease pathophysiology and its management: an update Pharmacol Rep. 2015;67:195–203
                        45. Lam AD, Sarkis RA, Pellerin KR, Jing J, Dworetzky BA, Hoch DB, Jacobs CS, Lee JW, Weisholtz DS, Zepeda R, Westover MB, Cole AJ, Cash SS. Association of epileptiform abnormalities and seizures in Alzheimer disease Neurology. 2020;95:e2259–2270
                        46. Lan MY, Liu JS, Wu YS, Peng CH, Chang YY. A novel APP mutation (D678H) in a Taiwanese patient exhibiting dementia and cerebral microvasculopathy J Clin Neurosci. 2014;21:513–515
                        47. Larsson SC, Markus HS. Does treating vascular risk factors prevent dementia and Alzheimer’s disease? A systematic review and meta-analysis J Alzheimers Dis. 2018;64:657–668
                        48. Lauretti E, Dincer O, Pratico D. Glycogen synthase kinase-3 signaling in Alzheimer’s disease Biochim Biophys Acta Mol Cell Res. 2020;1867:118664
                        49. Lewis J, Dickson DW. Propagation of tau pathology: hypotheses, discoveries , and yet unresolved questions from experimental and human brain studies Acta Neuropathol. 2016;131:27–48
                        50. Liguori C. Orexin and Alzheimer’s disease Current topics in behavioral neurosciences. 2017;33:305–322
                          51. Luo J, Mills K, le Cessie S, Noordam R, van Heemst D. Ageing, age-related diseases and oxidative stress: What to do next? Ageing Res Rev. 2020;57:100982
                          52. Malenka RC, Nicoll RA. NMDA-receptor-dependent synaptic plasticity: multiple forms and mechanisms Trends in neurosciences. 1993;16:521–527
                          53. Mango D, Saidi A, Cisale GY, Feligioni M, Corbo M, Nisticò R. Targeting synaptic plasticity in experimental models of Alzheimer’s disease Front Pharmacol. 2019;10:778
                            54. Mann DM, Esiri MM. The pattern of acquisition of plaques and tangles in the brains of patients under 50 years of age with Down’s syndrome J Neurol Sci. 1989;89:169–179
                            55. Martin L, Latypova X, Wilson CM, Magnaudeix A, Perrin M-L, Yardin C, Terro F. Tau protein kinases: Involvement in Alzheimer’s disease Ageing Res Rev. 2013;12:289–309
                            56. Masters CL, Simms G, Weinman NA, Multhaup G, McDonald BL, Beyreuther K. Amyloid plaque core protein in Alzheimer disease and Down syndrome Proc Natl Acad Sci U S A. 1985;82:4245–4249
                            57. Mendez MF, Lim GTH. Seizures in elderly patients with dementia Drugs Aging. 2003;20:791–803
                            58. Messing L, Decker JM, Joseph M, Mandelkow E, Mandelkow EM. Cascade of tau toxicity in inducible hippocampal brain slices and prevention by aggregation inhibitors Neurobiol Aging. 2013;34:1343–1354
                            59. Meyer-Luehmann M, Spires-Jones TL, Prada C, Garcia-Alloza M, de Calignon A, Rozkalne A, Koenigsknecht-Talboo J, Holtzman DM, Bacskai BJ, Hyman BT. Rapid appearance and local toxicity of amyloid-beta plaques in a mouse model of Alzheimer’s disease Nature. 2008;451:720–724
                            60. Missonnier P, Prévot A, Herrmann FR, Ventura J, Padée A, Merlo MCG. Disruption of gamma-delta relationship related to working memory deficits in first-episode psychosis J Neural Transm (Vienna). 2020;127:103–115
                            61. Mitchell RA, Herrmann N, Lanctôt KL. The role of dopamine in symptoms and treatment of apathy in Alzheimer’s disease CNS Neurosci Ther. 2011;17:411–427
                            62. Musiek ES, Holtzman DM. Three dimensions of the amyloid hypothesis: time, space and ‘wingmen’ Nat Neurosci. 2015;18:800–806
                            63. Nelson AR, Sweeney MD, Sagare AP, Zlokovic BV. Neurovascular dysfunction and neurodegeneration in dementia and Alzheimer’s disease Biochim Biophys Acta. 2016;1862:887–900
                            64. Ouchi Y, Yoshikawa E, Futatsubashi M, Yagi S, Ueki T, Nakamura K. Altered brain serotonin transporter and associated glucose metabolism in Alzheimer disease J Nucl Med. 2009;50:1260–1266
                            65. Pappas BA, Bayley PJ, Bui BK, Hansen LA, Thal LJ. Choline acetyltransferase activity and cognitive domain scores of Alzheimer’s patients Neurobiol Aging. 2000;21:11–17
                            66. Pike CJ. Sex and the development of Alzheimer’s disease J Neurosci Res. 2017;95:671–680
                            67. Pooler AM, Polydoro M, Maury EA, Nicholls SB, Reddy SM, Wegmann S, William C, Saqran L, Cagsal-Getkin O, Pitstick R, Beier DR, Carlson GA, Spires-Jones TL, Hyman BT. Amyloid accelerates tau propagation and toxicity in a model of early Alzheimer’s disease Acta Neuropathol Commun. 2015;3:11
                              68. Ramos-Rodriguez JJ, Molina-Gil S, Rey-Brea R, Berrocoso E, Garcia-Alloza M. Specific serotonergic denervation affects tau pathology and cognition without altering senile plaques deposition in APP/PS1 mice PLoS One. 2013;8:e79947
                              69. Rea IM, Gibson DS, McGilligan V, McNerlan SE, Alexander HD, Ross OA. Age and age-related diseases: role of inflammation triggers and cytokines Front Immunol. 2018;9:586
                                70. Reiner A, Levitz J. Glutamatergic signaling in the central nervous system: Ionotropic and metabotropic receptors in concert Neuron. 2018;98:1080–1098
                                71. Rice HC, de Malmazet D, Schreurs A, Frere S, Van Molle I, Volkov AN, Creemers E, Vertkin I, Nys J, Ranaivoson FM, Comoletti D, Savas JN, Remaut H, Balschun D, Wierda KD, Slutsky I, Farrow K, De Strooper B, de Wit J. Secreted amyloid-beta precursor protein functions as a GABABR1a ligand to modulate synaptic transmission Science (New York, NY). 2019;363:eaao4827
                                  72. Rudy CC, Hunsberger HC, Weitzner DS, Reed MN. The role of the tripartite glutamatergic synapse in the pathophysiology of Alzheimer’s disease Aging Dis. 2015;6:131–148
                                  73. Sasaki S. High prevalence of parkinsonism in patients with MCI or mild Alzheimer’s disease Alzheimers Dement. 2018;14:1615–1622
                                  74. Savelieff MG, Nam G, Kang J, Lee HJ, Lee M, Lim MH. Development of multifunctional molecules as potential therapeutic candidates for Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis in the last decade Chem Rev. 2019;119:1221–1322
                                  75. Selkoe DJ, Hardy J. The amyloid hypothesis of Alzheimer’s disease at 25 years EMBO Mol Med. 2016;8:595–608
                                  76. Shimohama S, Taniguchi T, Fujiwara M, Kameyama M. Changes in nicotinic and muscarinic cholinergic receptors in Alzheimer-type dementia J Neurochem. 1986;46:288–293
                                  77. Sivilotti L, Nistri A. GABA receptor mechanisms in the central nervous system Prog Neurobiol. 1991;36:35–92
                                  78. Smart TG, Stephenson FA. A half century of γ-aminobutyric acid Brain Neurosci Adv. 2019;3:2398212819858249
                                    79. Soldano A, Hassan BA. Beyond pathology: APP, brain development and Alzheimer’s disease Curr Opin Neurobiol. 2014;27:61–67
                                    80. Spangenberg EE, Green KN. Inflammation in Alzheimer’s disease: lessons learned from microglia-depletion models Brain Behav Immun. 2017;61:1–11
                                    81. Stuchlik A. Dynamic learning and memory, synaptic plasticity and neurogenesis: an update Front Behav Neurosci. 2014;8:6
                                      82. Syarifah-Noratiqah SB, Naina-Mohamed I, Zulfarina MS, Qodriyah HMS. Natural polyphenols in the treatment of Alzheimer’s disease Curr Drug Targets. 2018;19:927–937
                                      83. Talarico G, Trebbastoni A, Bruno G, de Lena C. Modulation of the cannabinoid system: a new perspective for the treatment of the Alzheimer’s disease Current neuropharmacology. 2019;17:176–183
                                      84. Terry RD, Masliah E, Salmon DP, Butters N, DeTeresa R, Hill R, Hansen LA, Katzman R. Physical basis of cognitive alterations in Alzheimer’s disease: synapse loss is the major correlate of cognitive impairment Ann Neurol. 1991;30:572–580
                                      85. Terunuma M. Diversity of structure and function of GABA(B) receptors: a complexity of GABA(B)-mediated signaling Proc Jpn Acad Ser B-Phys Biol Sci. 2018;94:390–411
                                        86. Theofilas P, Ehrenberg AJ, Dunlop S, Di Lorenzo Alho AT, Nguy A, Leite REP, Rodriguez RD, Mejia MB, Suemoto CK, Ferretti-Rebustini REDL, Polichiso L, Nascimento CF, Seeley WW, Nitrini R, Pasqualucci CA, Jacob Filho W, Rueb U, Neuhaus J, Heinsen H, Grinberg LT. Locus coeruleus volume and cell population changes during Alzheimer’s disease progression: a stereological study in human postmortem brains with potential implication for early-stage biomarker discovery Alzheimers Dement. 2017;13:236–246
                                        87. Vignini A, Giulietti A, Nanetti L, Raffaelli F, Giusti L, Mazzanti L, Provinciali L. Alzheimer’s disease and diabetes: new insights and unifying therapies Curr Diabetes Rev. 2013;9:218–227
                                        88. Wang JZ, Xia YY, Grundke-Iqbal I, Iqbal K. Abnormal hyperphosphorylation of tau: sites, regulation , and molecular mechanism of neurofibrillary degeneration J Alzheimers Dis 33 Suppl. 2013;1:S123–139
                                          89. Wang T, Liu XH, Guan J, Ge S, Wu MB, Lin JP, Yang LR. Advancement of multi-target drug discoveries and promising applications in the field of Alzheimer’s disease Eur J Med Chem. 2019;169:200–223
                                          90. Xiao YL, Ma BY, McElheny D, Parthasarathy S, Long F, Hoshi M, Nussinov R, Ishii Y. A beta(1-42) fibril structure illuminates self-recognition and replication of amyloid in Alzheimer’s disease Nat Struct Mol Biol. 2015;22:499–505
                                          91. Xu Y, Zhao M, Han Y, Zhang H. GABAergic inhibitory interneuron deficits in Alzheimer’s disease: implications for treatment Front Neurosci. 2020;14:660
                                          92. Yun SP, Kam TI, Panicker N, Kim S, Oh Y, Park JS, Kwon SH, Park YJ, Karuppagounder SS, Park H, Kim S, Oh N, Kim NA, Lee S, Brahmachari S, Mao X, Lee JH, Kumar M, An D, Kang SU, et al Block of A1 astrocyte conversion by microglia is neuroprotective in models of Parkinson’s disease Nat Med. 2018;24:931–938
                                          93. Zhang C, Wang Y, Wang D, Zhang J, Zhang F. NSAID exposure and Risk of Alzheimer’s disease: an updated meta-analysis from cohort studies Front Aging Neurosci. 2018;10:83
                                            94. Zhao L, Li Z, Vong JSL, Chen X, Lai HM, Yan LYC, Huang J, Sy SKH, Tian X, Huang Y, Chan HYE, So HC, Ng WL, Tang Y, Lin WJ, Mok VCT, Ko H. Pharmacologically reversible zonation-dependent endothelial cell transcriptomic changes with neurodegenerative disease associations in the aged brain Nat Commun. 2020;11:4413
                                              95. Zott B, Simon MM, Hong W, Unger F, Chen-Engerer HJ, Frosch MP, Sakmann B, Walsh DM, Konnerth A. A vicious cycle of beta amyloid-dependent neuronal hyperactivation Science. 2019;365:559–565

                                              Conflicts of interest:The authors declare no conflicts of interest.

                                              Financial support:This work was funded by University of Macau (File No. MYRG2016-00102-FHS) (to KYT).

                                              Copyright license agreement:The Copyright License Agreement has been signed by all authors before publication.

                                              Plagiarism check:Checked twice by iThenticate.

                                              Peer review:Externally peer reviewed.

                                              Open peer reviewer:Vasily Vorobyov, Russian Academy of Sciences, Russian Federation.

                                              Funding:This work was funded by University of Macau (File No. MYRG2016-00102-FHS) (to KYT).

                                              P-Reviewer: Vorobyov V; C-Editors: Zhao M, Liu WJ, Qiu Y; T-Editor: Jia Y

                                              Keywords:

                                              Alzheimer’s disease; pathological pathways; drug development; multiple pathologies

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