A Function of Amyloid-β in Mediating Activity-Dependent Axon/Synapse Competition May Unify Its Roles in Brain Physiology and Pathology

Abstract

Amyloid-β protein precursor (AβPP) gives rise to amyloid-β (Aβ), a peptide at the center of Alzheimer’s disease (AD). AβPP, however, is also an ancient molecule dating back in evolution to some of the earliest forms of metazoans. This suggests a possible ancestral function that may have been obscured by those that evolve later. Based on literature from the functions of Aβ/AβPP in nervous system development, plasticity, and disease, to those of anti-microbial peptides (AMPs) in bacterial competition as well as mechanisms of cell competition uncovered first by Drosophila genetics, I propose that Aβ/AβPP may be part of an ancient mechanism employed in cell competition, which is subsequently co-opted during evolution for the regulation of activity-dependent neural circuit development and plasticity. This hypothesis is supported by foremost the high similarities of Aβ to AMPs, both of which possess unique, opposite (i.e., trophic versus toxic) activities as monomers and oligomers. A large body of data further suggests that the different Aβ oligomeric isoforms may serve as the protective and punishment signals long predicted to mediate activity-dependent axonal/synaptic competition in the developing nervous system and that the imbalance in their opposite regulation of innate immune and glial cells in the brain may ultimately underpin AD pathogenesis. This hypothesis can not only explain the diverse roles observed of Aβ and AβPP family molecules, but also provide a conceptual framework that can unify current hypotheses on AD. Furthermore, it may explain major clinical observations not accounted for and identify approaches for overcoming shortfalls in AD animal modeling.

Keywords

Alzheimer’s disease amyloid-β anti-microbial peptide axon competition homeostatic plasticity inflammatory cytokine innate immunity microglia neuroinflammation tau phosphorylation

INTRODUCTION

Amyloid-β protein precursor (AβPP) gives rise to amyloid-β (Aβ), which accumulates in large quantities in the Alzheimer’s disease (AD) brain. Aβ production, however, also takes place in the healthy brain and is regulated by neural activity. This suggests that Aβ may have a physiological role in the normal brain and that this may be related to its pathological role. Large numbers of studies have shown that while Aβ oligomers at high concentrations are toxic, Aβ oligomers at low concentrations or Aβ monomers have in contrary protective effects on neurons. Similar contrasting activities have also been observed on microglia, resident immune cells of the brain. The concentration/oligomeric isoform-dependent effects of Aβ are reminiscent of anti-microbial peptides (AMPs), peptides employed by some bacterial species that perform trophic signaling at low concentrations in monomeric conformations but mediate competitive killing as oligomers. In this essay, I propose that a normal function of Aβ in the nervous system may be to act as an agent of circuit-level neural activity and mediate circuit-level activity-dependent axon/synapse competition and that the imbalance in Aβ-monomeric/oligomeric isoform activity that normally regulates this process may ultimately underlie AD development. I will first summarize principles of AMP deployment in bacterial competition and the concentration/oligomeric isoform-specific effects of Aβ that have been observed. I will then go through the major lines of experimental evidence that support a role of Aβ as mediators in activity-dependent axon/synapse competition. Lastly, I will discuss how this proposal may unify leading hypotheses of AD, explain clinical observations not accounted for previously, and identify new approaches for AD modeling.

AMPs AND BACTERIAL COMPETITION

When resources are scarce, some bacterial species deploy AMPs in both inter-species and intra-species competition to kill competitors and enhance their own survival. The intra-species competition is the most informative for our purpose since the competing cells are identical, which helps understand how a cell can deploy AMPs to kill other identical cells while protecting itself. There are many types of AMPs in bacterial competition, and they act in different ways, but all share common properties [1, 2]. Below I will use nisin, a 3.4 kD peptide bacteriocin secreted by Lactococcus lactis, as an example to illustrate the regulation of AMPs in this process [3] (Fig. 1).

Fig. 1

Roles of antimicrobial peptides (AMPs) in bacterial competition and self-protection. A) Genomic organization of the nisin gene cluster. Function of each gene group is listed below gene name(s). B) Hypothetical concentration of free nisin (monomer equivalent) from the surface of a secreting cell. The low concentration near cell surface is proposed to result from fast binding and sequestration of nisin by immunity proteins. C) Hypothetical two-dimensional view of monomeric and oligomeric nisin distribution surrounding a secreting cell.

At the genomic level, the nisin gene is organized together with several other related genes in a cluster [4, 5]. This includes genes responsible for the post-translational modification and secretion of nisin as well as genes encoding immunity proteins. The cluster also contains other genes encoding a so-called two-component system that includes a sensor histidine kinase receptor and a response regulator that controls the transcription of the gene cluster. The ligand for the histidine kinase receptor is nisin itself, which regulates the receptor in a mechanism known as quorum sensing, i.e., it activates the gene cluster expression and cell competition in a cell density-dependent manner [6]. In short, under a sparsely populated condition, nisin is produced at minimal levels and does not activate the receptor. However, upon crowding, nisin, in the common extracellular pool plenished and shared by all cells, reaches a threshold concentration and activates the receptor. This leads to two processes common to all cell competition, one of which induces the production of large amounts of nisin that form oligomers and inhibit/kill competitor cells, and the other induces immunity proteins for self-protection. Both depend on the unique property of nisin as an AMP, i.e., it can have opposite activities in different oligomeric conformations. At low concentrations, nisin exists mainly as monomers and binds to its receptor to activate expression of the immunity protein NisI (as well as more nisin). NisI prevents the suicidal effects of nisin through several mechanisms [7, 8]. 1) As a cell surface protein, NisI sequesters and prevents local nisin from aggregating into toxic oligomers near the cell surface. Some NisI is also secreted, which may further neutralize nisin locally. 2) Nisin binding to NisI can also induce cell clustering, which inhibits oligomer access to the clustered cells. Nisin signaling, however, also induces mass production of the AMP itself [9, 10], which, once reaching a high concentration, forms oligomers that inhibit or kill competitor cells [11 –13]. For example, they can induce the aggregation of the cell wall precursor lipid II and as a result inhibit peptidoglycan biosynthesis and cell growth. Aggregation of the nisin-lipid II complex can also cause membrane instability and pore formation, leading to cell death. Furthermore, nisin oligomers can decrease lipid packing density and increase membrane permeability independent of lipid II binding. Thus, the unique properties of nisin as an AMP play a key role in cell competition, enabling cells to self-protect at low concentrations through protective signaling while killing competitors at high concentrations through oligomer formation.

CONCENTRATION/OLIGOMERIC ISOFORM-SPECIFIC EFFECTS OF Aβ

The properties of nisin and other AMPs are reminiscent of Aβ, which has indeed been found to possess potent anti-microbial activity against several microbes [14]. Recent studies have further uncovered unique concentration/oligomeric isoform-specific effects of Aβ on neuronal physiology that parallel those of AMPs (Table 1). In short, studies by several labs have found that at low concentrations and likely as monomers and/or low-molecular-weight oligomers, Aβ increases presynaptic vesicle pool, vesicle release probability, and as a result miniature EPSC frequency [15 –17]. It also enhances long-term potentiation (LTP) in brain slices and several forms of learning and memory in vivo [17 –22]. Indeed, recent studies show Aβ monomers may in fact be synaptogenic [23]. In contrary, at high concentrations and likely as high-molecular-weight oligomers, Aβ inhibits neurotransmitter exocytosis and decreases presynaptic vesicle pool [16 , 24–27]. It also impairs LTP and learning and memory [18 , 28–31]. At the cellular level, studies also find Aβ monomers protect neurons [32 –34], while Aβ oligomers are well known to be neurotoxic. Importantly, at the molecular structural level, Aβ similarly shows opposite, concentration-specific effects [35]. At low concentrations, Aβ induces a desensitized conformation of the nicotinic acetylcholine receptor α7nACh that still responds to its cognate ligand, but at high concentrations, it induces a resting-state-like conformation that no longer responds to the ligand. These results indicate that Aβ does have AMP-like concentration/oligomeric isoform-specific properties that would be required for mediating cell/axon competition.

Table 1

Summary of concentration/oligomeric isoform-dependent Aβ effects

Effects of low-concentration Aβ
Presynaptic
100 pM mAβ₄₀ & 100 pM covalent Aβ₄₀ dimer	Increases releasable vesicles (assayed using FM1-43)	[15]
100 pM Aβ_40/42	Increases the recycling pool of synaptic vesicles	[16]
200 pm oAβ₄₂	Increases frequency of miniature EPSCs	[17]
	Decreases paired pulse facilitation (PPF)
	Increases docked vesicle number
	PPF effects blocked by α7nAChR knockout and acute inhibition
Postsynaptic
200 pm oAβ₄₂	Increases length of postsynaptic density	[17]
	Increases expression of plasticity-related proteins
Plasticity
200 pM oAβ₄₂	Enhances LTP	[22]
∼2 nM oAβ₄₂	Facilitates LTP induction and maintenance	[21]
200 pM oAβ₄₂	Restores L-LTP induction in APP-KO slices	[19]
200 pM oAβ₄₂	Enhances LTP	[18]
200 pm oAβ₄₂	Converts E-LTP into L-LTP	[17]
	Effects blocked by α7nAChR knockout and acute inhibition
	Effects blocked by inhibition of NO/cGMP production and
	PKG activation
Learning/memory
100 pM oAβ₄₂	Enhances fear-conditioning memory consolidation	[20]
200 pM oAβ₄₂	Enhances water maze performance	[18]
200 pm oAβ₄₂	Converts short-term memory into long-term memory	[17]
	Effects blocked by α7nAChR knockout
Effects on α7nAChR
100 pm oAβ₄₀/oAβ₄₂	Induces desensitized conformation responsive to Carb	[35]
	Effects of high-concentration Aβ
Presynaptic
50–500 nM Aβ₄₀	Reduces frequency of miniature currents	[24]
5–20 nM oAβ₄₂	Inhibits calcium-triggered exocytosis	[25]
	(in vitro single-vesicle content-mixing assay)
1μM Aβ	Decreases the recycling pool of synaptic vesicles	[16]
400 nM oAβ₄₂	Suppresses frequency of miniature EPSP	[26]
	Effects blocked by preventing presynaptic PIP₂ drop
500 nM covalent	Blocks glutamate reuptake promoting hyperactivity	[27]
Aβ₄₀ dimer
Plasticity
Conditioned medium	Inhibits LTP in vivo	[31]
∼1 nM oAβ
(1.5μl injected)
100 nM covalent	Inhibits LTP	[28]
Aβ₄₀ dimer
200 nM oAβ₄₂	Impairs LTP	[22]
500 nM oAβ₄₂	Impairs LTP	[29]
200 nM oAβ₄₂	Impairs LTP	[30]
200 nM oAβ_42,	20-min pretreatment impairs LTP	[18]
oAβ₄₀ and mAβ₄₂
Learning/memory
200 nM oAβ₄₂	20-min pretreatment impairs water maze performance	[18]
Effects on α7nAChR
100 nm oAβ₄₀/oAβ₄₂	Induces resting-state-like conformation unresponsive to Carb	[35]

The concentration/oligomeric isoform-specific effects of Aβ are also not restricted to neurons. Using fibrils of Aβ₄₂ or occasionally those of Aβ₄₀, many studies have reported pro-inflammatory effects of Aβ on macrophages/microglia [36 –51]. In contrary, non-fibrillar Aβ by itself lacks pro-inflammatory effects [49 –51]. In conference presentations, monomeric Aβ has further been reported to suppress macrophage/microglial pro-inflammatory activation. In the periphery, Aβ₄₀ and Aβ₄₂ also both inhibit T cell activation when employed under conditions that favor the monomer conformation [52]. This is consistent with findings that Aβ monomers activate PI3K/Akt [32], major mediators of anti-inflammatory signaling [53, 54]. Thus, these results indicate that Aβ also possesses concentration/oligomeric isoform-specific activity on innate immune cells, a cell type with key regulatory roles in axon/synapse pruning.

Aβ is also not the only mammalian peptide with such unique activities. The mammalian AMP LL-37 also activates trophic signaling in protected cells and inhibits pro-inflammatory activity of immune cells at low concentrations as monomers [55 –57], while acting in opposite manners at high concentrations as oligomers [58 –60]. Besides Aβ, there are also many other AMP-like peptides with critical functions in both the vertebrate and invertebrate nervous system [61, 62]. These peptides not only show sequence and structural similarities to AMPs but also possess functional anti-microbial activity. For example, substance P, a widely distributed 11 amino acid neurotransmitter and neuromodulator, has potent antimicrobial activity against S. aureus, E. coli, and other microbes [63]. Neuropeptide Y, a 36 amino acid peptide that regulates diverse processes such as feeding, behavior and metabolism, also has potent antifungal activity [64]. α-Melanocyte stimulating hormone (αMSH), a 13 amino acid peptide that regulates appetite, metabolism, and sexual behavior, is effective against S. aureus and C. albicans at concentrations (1fM to 1pM) far below those of most AMPs [65]. In Drosophila, diptericin B, a 9 kDa AMP active against Gram-negative bacteria, regulates long-term memory [62]. Nemuri, another Drosophila AMP, increases arousability when deleted and drives prolonged sleep when overexpressed [66]. Thus, AMPs appear to have been widely co-opted during evolution and play important roles in the nervous system.

HYPOTHESIS ON Aβ/AβPP PHYSIOLOGICAL FUNCTION IN THE NERVOUS SYSTEM

Based on the unique properties of Aβ, their similarities to AMPs, and other lines of evidence (see below), I hypothesize that the ancient function of Aβ/AβPP in unicellular precursors of metazoans may be to mediate cell competition. During evolution of multi-cellular metazoans and the nervous system, this function may have been co-opted for regulating one unique aspect of nervous system function, the sensing of circuit-level neural activity and the mediating of circuit-level activity-dependent axon/synapse competition and plasticity (Fig. 2). Since the discovery of ocular dominance columns by Hubel and Wiesel, the mechanisms of activity-dependent axon/synapse competition have been intensively studied [67 –69]. These studies have also led to a prediction of the existence in this process of protective and punishment signals that emanate from a stronger synapse and act locally to protect itself while eliminating a weaker synapse at a distance [70 –72]. The identity of these signals, however, has remained elusive. While many activity-regulated signals have been discovered, few appear to fit the bill. For example, since these signals can apparently mediate synapse elimination at a distance, they presumably must not only be produced in an activity-dependent manner, but also be protective at the stronger synapse yet able to diffuse across a significant distance and induce elimination of the weaker synapse. Of the few secreted molecules regulated by circuit-level activity, adenosine is indeed produced in such an activity-dependent manner, but studies have found it primarily regulate neural activity and sleep at the circuit level [73 –75]. Mature and pro-BDNF have also been proposed as the reward and punishment signal respectively [76]. However, while there is significant evidence implicating their pivotal roles in this process [76 –78], there is also difficulty regarding, for example, the relative large size of the pro-BDNF molecule (32 kDa) that presumably has to diffuse at least a distance of 50 μm [70, 71] to fulfill its potential role as a punishment signal. In contrast, Aβ appears to fulfill these requirements well. As discussed in the two earlier sections, Aβ is not only structurally similar to the AMP molecules that have been directly implicated in mediating cell competition but can also exist in different oligomeric conformations as these AMPs and function protectively as monomers and in a toxic manner as oligomers. In addition, Aβ also appears to operate in the same concentration range as AMPs in bacterial competition. Nisin activates trophic signaling as monomers at the concentration of 30 pM [3], while inhibiting bacterial growth at a minimum concentration of 3 μM [12]. Similarly, Aβ monomers enhance mammalian synaptic function at a concentration of 100 pM [15, 16], while the affinity of Aβ oligomers for PirB, one of the receptors that mediate their inhibitory effects is ∼180 nM [30]. This concentration range is also in agreement with the dose-effect relationship observed of Aβ in several other studies (see Table 1). Below I will go through other major lines of evidence that support the hypothesis.

Fig. 2

Proposed roles of Aβ in axonal competition. Like bacterial cells secreting nisin, axons may produce a two-layered cloud of oligomeric and monomeric Aβ. Unlike bacterial competition, however, Aβ-mediated activity-dependent competition involves not only the competing axons/synapses themselves but also microglia. Studies have shown the pruning of an axon terminal likely require coincident cytokine pathway activation in that axon and the presence of Aβ oligomers in the immediate vicinity of that axon. Cytokine signaling plays a key role in this process by inducing plasma membrane scrambling of targeted axon, to which the Aβ oligomers in the vicinity, besides exerting direct toxic effects, would then bind and potentially tag for elimination. In such ways, the monomeric Aβ secreted by the stronger axon (axon 1) may protect itself not only by directly activating trophic signaling in itself (green + symbol) but also by suppressing inflammatory activity of nearby microglia, thus preventing the triggering of either signal. In contrast, the oligomeric Aβ cloud axon 1 produces (at a distance from itself) may inhibit the competing weaker axon (axon 2) by provoking microglial activity near that axon, which would then facilitate the binding of Aβ oligomers near that axon (red - symbol). This two-signal system may conceivably narrow the spatial-temporal window of pruning activation, increase the precision of axon/synapse targeting during activity-dependent competition, and minimize potential problems that may be caused by the diffusible nature of molecules involved. (Note: astrocytes and other glial cell types intimately interact with microglia in the brain and likely also participate in this process but for simplicity reasons are not depicted in the model).

1) Aβ/AβPP POSSESSES AMP-LIKE CONCENTRATION/OLIGOMERIC ISOFORM-DEPENDENT ACTIVITY

This has been discussed above. There are also other observations along this line that support the proposed hypothesis. For example, full-length AβPP has been found to possess iron export activity [79], an activity employed in nutritional immunity [80], one of the oldest forms of cellular self-protection mechanism. This finding aligns well with a potential role of AβPP/Aβ in cell competition. The kinetics of Aβ oligomerization, a likely key factor in axon/synapse competition, has also been found regulated by Aβ_42/40 ratio [81], which is in turn regulated by neural activity [82]. Aβ₄₂ oligomerization is faster than Aβ₄₀ and is inhibited by Aβ₄₀ [83], while only Aβ₄₂ but not Aβ₄₀ oligomers form toxic membrane channels [84, 85]. These findings suggest evolution of intricate mechanisms that fine-tune Aβ oligomer species and activity in axon/synapse competition. Besides, AβPP family members APLP1/2 are also processed by similar steps of proteolytic cleavage and may potentially play complementary roles [86]. (To clarify, throughout the review, I refer to Aβ monomers as being protective and Aβ oligomers as toxic. This is a simplification for easier presentation. The protective effects of Aβ likely include both Aβ monomers and low-concentration and thus likely low-molecular-weight oligomers, while the toxic effects likely come mostly from high-concentration and high-molecular-weight oligomers).

2) Flower, a calcium channel essential for cell competition, regulates synaptic vesicle endocytosis, a process independently found to regulate neural activity-dependent Aβ production

A second line of evidence is that Aβ production/secretion is not only coupled to neural activity but also regulated by the same molecules that regulate cell competition. Cell competition in metazoans is best studied in Drosophila and one of the most interesting genes identified is flower, a calcium channel that regulates endocytosis [87, 88]. In non-neural tissues such as the Drosophila imaginal epithelia, Flower is uniformly expressed in all cells. Genetic removal of Flower results in apoptosis of mutant cells. But this only happens when Flower is removed from a subset of cells. When it is removed from all cells, mutant cells survive and grow normally. There is also a Flower isoform that, when overexpressed in a subset of cells, results in their apoptosis. However, when it is uniformly overexpressed, again all cells grow normally. Thus, Flower specifically regulates cell competition-related cell survival or death. In the nervous system, Flower localizes to synaptic vesicles at the Drosophila neuromuscular junction (NMJ) [88]. Upon vesicle fusion, it re-localizes to the presynaptic zone and regulates both clathrin-mediated endocytosis and activity-dependent bulk endocytosis [89]. These functions are conserved at mammalian synapses [89]. These findings thus indicate that endocytosis likely plays a key role in cell competition. Indeed, in the immune system, Flower regulates cytotoxic granule endocytosis and is essential for target cell killing by T lymphocytes [90]. In the nervous system, I propose Aβ may be an activity-regulated agent that mediates axon/synapse competition. As such, Aβ must, first of all, be coupled to neural activity and also share mechanisms known to regulate cell competition. In support, Aβ production in the brain is well known to be regulated by neural activity [91]. Aβ levels in the brain are directly influenced by neuronal endocytosis and inhibition of clathrin-mediated endocytosis, the same process regulated by Flower, leads to decreases in interstitial Aβ [92]. Furthermore, endosomes are a well-established subcellular site of β-secretase activity that produces Aβ [93 –96]. Interestingly, besides Flower, recent studies have found NMDA receptors, another key regulator of neuronal activity in the nervous system, also regulate cell competition between non-neuronal epithelial cells in Drosophila [97]. Thus, these findings support a role of Aβ in mediating activity-dependent axon competition.

3) Elimination of loser cells or axons requires similar interactions between immune cells, cytokines, and AMPs in cell and axon competition

Another line of evidence is that cell competition in Drosophila and axonal competition in the nervous system both require the same set of players, innate immune cells, cytokines, and AMP-like peptides, and similar interactions between them. In Drosophila, the elimination of losing tumor cells during cell competition requires participation of innate immune cells, the hemocytes, as well as coordinated activity of TNFα and AMPs [98 –100]. Hemocytes in the vicinity of a loser cell secrete TNFα, which induces phosphatidylserine exposure by the losing cell. Phosphatidylserine exposure renders losing cells sensitive to AMPs such as Defensin, which bind to the exposed phosphatidylserine and, together with other TNFα effectors, provoke cell death. The apoptotic cell is then removed by hemocyte-mediated phagocytosis. Similar interactions have been observed between TNFα and Defensin during mammal cell death [101]. The close coordination between local cytokines, AMPs, and innate immune cells likely ensures the specificity of target elimination.

Activity-dependent axonal competition and pruning in the vertebrate nervous system similarly involve innate immune cells (microglia) and cytokines such as TNFα. In the retinogeniculate system, microglia play an essential role in at least two activity-dependent processes, the segregation of eye-specific axonal terminals and the refinement (pruning) of axonal inputs per thalamic target neuron. Disrupting the complement cascade, which targets presynaptic elements with exposed phosphatidylserine for microglial engulfment [102], results in defective eye-specific segregation as well as multiply innervated neurons [72, 103]. In the visual cortex, disrupting the microglial P2Y12 receptor similarly alters microglial response to monocular deprivation and abrogates ocular dominance plasticity [104]. Similarly, activation of β₂-adrenergic receptors, which inhibits microglia surveillance function, also disrupts experience-dependent ocular dominance plasticity [105]. Furthermore, microglia mediate activity-dependent axon terminal/synapse remodeling through fractalkine-CX3CR1 signaling in the somatosensory cortex [106]. Thus, like in Drosophila cell competition, innate immune cells also play an essential role in activity-dependent axonal/synapse competition.

Cytokines have similarly been implicated in activity-dependent axonal competition. In the retino-geniculate system, a TNFα receptor superfamily member (TNFRSF12a or Fn14) is required for both sensory experience-dependent reduction in the number of retinal inputs per target neuron and the strengthening of surviving connections [107]. The cytokine IL-33 is similarly involved in activity-dependent excess synapse elimination in this brain region [108]. Another TNFα receptor superfamily member (TNFRSF21 or DR6) is required for activity-dependent axonal competition in the retino-collicular system as well as in the somatosensory cortex [109, 110]. JAK/Stat, downstream mediators of cytokine signaling have been implicated in similar processes [111]. Furthermore, at the vertebrate NMJ, a classic model for the study of axonal competition, TNFα is essential for the elimination of supernumerary terminals in an activity-dependent manner [112]. Exogenous TNFα promotes terminal elimination while TNFα mutation delays this process. Thus, the role of cytokines in metazoan cell competition also appears to be conserved in activity-dependent competition in the nervous system.

Furthermore, while the direct role of Aβ in axon competition remains to be tested, acute overproduction of either axonal or dendritic Aβ has been found to reduce spine density and plasticity at nearby dendrites [113]. Oligomeric Aβ directly injected into the brain also induces significantly higher volumes of microglial engulfment of synaptic elements than monomeric Aβ [114]. Several findings are also consistent with the interpretation that, like AMPs in loser cell killing, Aβ may tag axonal terminals and recruit innate immune cells for their elimination. For example, Aβ has been found to bind to and activate several components of the complement cascade [115, 116], which in turn participate in several processes of competitive axonal pruning [72, 103]. The complement cascade appears not involved in the visual and somatosensory cortex [106, 117]. However, oligomeric Aβ can also activate other microglial receptors such as TREM2 [118], which may alternately mediate these effects. Indeed, studies found TREM2 can sense fibrillar Aβ-associated anionic and zwitterionic lipids typically exposed on damaged neurons [119]. TREM2 loss of function also results in impaired synapse elimination in vivo. Besides, several other high affinity oligomeric Aβ receptors such as PirB, cellular prion protein, and NgR are also expressed in microglial lineages and regulate their activity [121 –124] and may play additional roles (see further discussion below). Thus, these results further support a role of Aβ in activity-dependent axon/synapse competition.

4) Loss of function in AβPP, a mediator of oligomeric Aβ (oAβ) toxic effects, results in expansion of would-be losing axons during activity-dependent competition

I propose that Aβ oligomers may serve as a punishment signal in activity-dependent axon competition. If so, removing Aβ oligomers should result in not only survival and growth of would-be losing axons but also potential enhanced growth of normally winning axons since competition is a two-way process. Because of the complexity of Aβ regulation and the different effects of different isoforms, specifically determining the role of Aβ oligomers is challenging. However, several studies have shown that the neurotoxic effects of Aβ oligomers are mediated by AβPP. For example, in AβPP knockout animals, the deleterious effects of Aβ oligomers on synaptic plasticity, learning and memory, and other processes are all prevented [125, 126]. This provides a way to test the role of Aβ oligomers. Indeed, results compatible with a role of Aβ oligomers in mediating competitor elimination have been obtained in the retinocollicular system as well as in the somatosensory cortex. AβPP loss of function results in unpruned retinal axons persisting beyond their normal target zone in the superior colliculus [127]. In vivo two-photon imaging also shows cell autonomous loss of function in AβPP suppress mutant axon pruning during cortical rewiring induced by whisker plucking in the somatosensory cortex [128] (Fig. 3). Furthermore, at the NMJ, double mutations in AβPP and its homolog APLP2 result in exuberant axonal terminal sprouting, a phenotype consistent with potential defects in activity-dependent pruning [129]. Together, these results support the interpretation of Aβ oligomers as a punishment signal in activity-dependent competition.

Fig. 3

APP cell-autonomously mediates axonal pruning in sensory deprivation-induced plasticity of the somatosensory cortex. A) Whole-body APP mutation results in severely reduced axonal terminal retraction (in red) in comparison to wildtype (WT) during barrel cortex plasticity, consistent with a role of APP in mediating proposed pruning effects of oligomeric Aβ. B) Sparse deletion of APP from would-be retracting axons confirms a cell-autonomous requirement for APP in mediating the pruning effects of oligomeric Aβ. (Schematized based on data in Marik et al. (2016) [128]).

5) Loss of function in PirB, a high affinity receptor for oligomeric Aβ, also results in cortical expansion of normally losing axons that relay weaker input from the ipsilateral eye

Oligomeric Aβ has also been found to bind with high affinity to PirB, a receptor for major histocompatibility complex I (MHCI) [30]. This suggests that PirB may also mediate the punishment effects of oAβ. Indeed, results compatible with this interpretation have also been obtained in several studies. In the mouse visual cortex, monocular deprivation of input from the contralateral eye during the critical period results in expansion of the binocular zone. This in large part results from disinhibited growth of the normally weaker input from the ipsilateral (open) eye [130]. In PirB mutants, these effects of bilateral zone expansion are even more pronounced than in wildtype animals [131]. Thus, like AβPP, PirB also appears to mediate the toxic effects of oAβ, which, when removed, results in the growth of would-be losing axons. This suggests that AβPP and PirB may act in the same pathway that mediate oAβ effects. Consistent with this interpretation, AβPP family members have been found to associate with and regulate the stability of MHCI molecules [132, 133], which in turn can bind PirB both in cis and in trans [134]. Mutations in MCHI genes, like PirB, also result in exaggerated expansion of the binocular zone in the visual cortex following monocular deprivation [135]. Furthermore, in mouse AD models where oAβ is produced at elevated levels, a manipulation predicted to result in excessive pruning of both the would-be winning and losing axons, studies have indeed found a shrunken binocular zone following monocular deprivation. In addition, this shrinkage is prevented by the removal of PirB [30] (Fig. 4). Thus, these results further support a role of Aβ in axonal competition.

Fig. 4

PirB mediates axonal pruning in sensory deprivation-induced ocular dominance plasticity of the mouse visual cortex. A) Schematic diagram of the normal distribution pattern in the visual cortex of axon terminals relaying ipsi- and contralateral eye input as well as the site of ocular deprivation during experiment. B) PirB mutation results in expanded binocular zone (BZ), consistent with a role of oAβ-binding PirB in mediating proposed pruning effects of oligomeric Aβ. Increased oligomeric Aβ level (in APP/PS1 AD models) shrinks the BZ, also consistent with a role of oAβ in mediating pruning in this process. Furthermore, this effect is blocked by PirB mutation. (Adapted from Kim et al 2013 [30])

Mutations in MHCI also result in defective eye-specific retinal axon segregation in the thalamus (retino-geniculate projection) during normal development [136]. While PirB mutants do not show such defects, mutations in CD3zeta, a more widely expressed MHCI receptor (than PirB), similarly result in defective eye-specific terminal segregation [136]. In addition, MCHI promotes motor neuron terminal pruning at the NMJ [137]. At the molecular level, oAβ activates Syk family kinases [48 , 139], mediators of CD3zeta signaling [140] known to negatively regulate axonal growth [141]. Thus, oAβ appears to mediate activity-dependent axonal competition throughout the developing nervous system. Besides axons, oAβ has also been found to inhibit dendritic spine synapse development through Nogo receptors (NgR) [142 –144]. NgR mutation increases while oAβ decreases spine synapse density. Cell autonomous mutations in PirB and MHCI similarly increase spine synapse density [145, 146]. Of note, many of these molecules are also involved in the suppression of axonal regeneration as well as the termination of critical periods of cortical plasticity. For example, chondroitin sulfate proteoglycan, which activates NgRs [147], controls the closure of the critical window of ocular dominance plasticity [148]. Myelin associated factors, which inhibit axon regeneration through both PirB and NgR [149], also inhibit ocular dominance plasticity through NgR [150]. These findings suggest that plasticity-limiting mechanisms may potentially act through modulating the same process of axon/synapse competition. (A third oAβ-high affinity receptor, the cellular prion protein, has also been identified that directly binds oAβ [29, 144]. It is still unclear whether cellular prion proteins participate in axon/synapse competition. However, studies have shown, for example, that it regulates AβPP cleavage as well as TNFα signaling [121 , 151], raising possibilities of its involvement).

In non-neural cell competition, AMP activity on target cells is coordinated with that of cytokines [98 –100]. Since microglia are the primary producer of cytokines in the brain, this suggests that besides directly engaging axons, Aβ may also concomitantly modulate microglial activity. This appears to be the case. As mentioned, in line with the protective effects of monomeric Aβ on neurons [32 –34], it has been reported that monomeric Aβ suppresses microglial expression of pro-inflammatory cytokines, while oligomeric Aβ provokes secretion of pro-inflammatory cytokines [36 –51]. Furthermore, macrophages mutant for oAβ receptors PirB and cellular prion protein both show altered cytokine secretion [122, 152]. Thus, Aβ may regulate axon competition by both directly acting on axonal targets and indirectly through regulating microglial activity.

6) The neuron-Aβ/glia-cytokine module regulates homeostatic synaptic plasticity in the adult brain

Axonal/synaptic competition is most prominent during development. In the adult brain, a large body of works suggests that the neuron-Aβ/glia-cytokine module proposed to regulate axon/synapse competition may be conserved for the regulation of synaptic plasticity. Astrocytes play a big role in this process. Since astrocytes tightly coordinate with microglia in cytokine regulation [153], these glial cell types likely regulate plasticity in concert. The proposed Aβ/cytokine function in the adult brain is supported by studies of a unique form of plasticity, homeostatic synaptic plasticity, a mechanism by which central synapses maintain overall balance of activity by up-scaling synaptic efficiency when activity is low and down-scaling efficiency when activity is high. Glial secretion of TNFα plays a key role in this process. Glial secretion of TNFα is on one hand inhibited by neural activity, but it on the other hand promotes postsynaptic AMPA receptor insertion and synaptic transmission enhancement [154, 155]. The effects of neural activity on TNFα in this loop are consistent with mediation by Aβ (Fig. 5), since, as discussed above, neuronal Aβ production is positively regulated by activity while Aβ monomers negatively regulate glial TNFα secretion. Besides, Arc, an activity-induced cytoskeletal protein that mediates AMPAR endocytosis in homeostatic plasticity has also been found to in parallel promote neuronal Aβ production [156, 157]. This further supports a role of Aβ in homeostatic plasticity. Moreover, Aβ has been independently shown to depress synaptic transmission and act as an endogenous negative feedback that keeps hyperactivity in check [158, 159], by mechanisms that may include induction of p35 cleavage and cdk5 and plk2 activation [160, 161]. It has also been directly implicated in homeostatic plasticity in a recent study [162]. The roles of glial TNFα in homeostatic plasticity are also not restricted to the hippocampus. In the visual cortex, TNFα is required for the enhanced response to the open eye induced by monocular deprivation [163]. In the spinal cord, glial secretion of TNFα and other messengers also results in a unique form of LTP that travels long distances via the cerebrospinal fluid [164]. Besides homeostatic plasticity, other forms of plasticity are also regulated by cytokines such as IL-1β and IL-6 [165 –168]. In addition, antibody blocking studies have implicated a role of endogenous Aβ in hippocampal LTP as well as learning and memory [20 , 169]. Thus, these results strongly suggest that the Aβ/cytokine signaling module that regulates axonal competition during development may be conserved and regulate homeostatic synaptic plasticity in the adult brain.

Fig. 5

Role of Aβ and TNFα in mediating homeostatic synaptic plasticity. Glial secretion of TNFα, which is inhibited by neuronal activity, has been found to promote AMPA receptor (AMPAR) insertion and increase postsynaptic strength at excitatory synapses. Aβ secretion instead is promoted by neuronal activity and Aβ monomers suppress glial inflammatory cytokine secretion. This supports a potential role of Aβ in mediating the regulation of homeostatic plasticity by neural activity. The fact that Arc, an activity-induced cytoskeletal protein that promotes AMPAR removal in homeostatic plasticity, also regulates Aβ production in parallel further supports this interpretation.

In sum, a significant body of data on AMPs, Aβ, and activity-dependent plasticity are coming into alignment supporting the hypothesis that Aβ may act as protective and punishment signals that mediate activity-dependent axonal competition in the nervous system (Fig. 2). Its dual role as both protective and punishment signals is potentially made possible by, above all, the unique concentration/oligomeric isoform-specific activity of Aβ against both neurons and glia. This hypothesis may not only provide a cohesive explanation for the array of biological functions observed of AβPP/Aβ but may also unify understanding of AD pathogenesis.

A CONCEPTUAL FRAMEWORK THAT MAY UNIFY CURRENT HYPOTHESES ON AD

Homeostatic synaptic plasticity protects synapses from destabilizing forces and is essential for maintaining lifelong normal brain function [170]. If it is regulated by Aβ and cytokines as proposed, this would necessitate safety mechanisms that keep toxic effects of both Aβ and cytokines in check. Long periods of neuronal inactivity, for example, could severely reduce Aβ, resulting in accumulation of dangerously high levels of pro-inflammatory cytokines, and vice versa. Studies have found that cytokines increase AβPP cleavage and Aβ production by neurons and astrocytes [171 –177]. Cytokines also induce expression of Arc, a plasticity protein that promotes Aβ production [157 , 179]. Both suggest evolution of negative feedbacks that take advantage of the neuron-Aβ/glia-cytokine module for maintaining brain cytokine homeostasis. Conversely, Aβ is cleared from the brain during sleep [180, 181], a process reciprocally regulated by cytokines [182, 183]. All of these suggest the evolution of multi-pronged safety mechanisms that maintain brain cytokine and Aβ homeostasis. Indeed, during microglia and astrocyte cytokine secretion, for example, it has been found that ATP is also secreted, which not only acutely amplifies pro-inflammatory glial activity [184, 185], but also triggers a temporally delayed program in which ATP is metabolized into adenosine, which may then induce sleep [73 –75]. Thus, robust safety mechanisms appear to have evolved to regulate Aβ and cytokines in the brain and provide a potential framework for a unified explanation of AD pathogenesis.

AD hallmarks include accumulation of amyloid plaques and neurofibrillary tangles, microglial activation, and cytokine elevation [186, 187]. Several major hypotheses have been proposed over its pathogenic mechanism, including the amyloid cascade, the tau, the neuroinflammation, and the antimicrobial protection hypothesis. While strong evidence supports each of these hypotheses, there are also major missing links or conflicting evidence. The concept that Aβ and cytokines mediate axon competition during development and continue to regulate plasticity in the adult brain provides a framework that may unify these hypotheses. As mentioned, because of the toxicity of high-concentration Aβ and cytokines, robust mechanisms such as Aβ-mediated negative feedback are in place to keep toxicity in check. I propose that defects in this feedback pathway, arising from different primary perturbations in different forms of AD, may ultimately result in the same outcome of chronic microglial activation and chronic brain cytokine elevation and that this lies at the core of AD (Fig. 6). Briefly, in familial AD, genetic mutations may lead to Aβ overproduction and/or increased Aβ_42/40 ratio and as a result Aβ aggregation into oligomers/fibrils/plaques. This may deplete the effective pool of Aβ monomers in the brain parenchyma (since aggregation not only reduces the physical concentration of Aβ monomers, but because the aggregates act as de facto decoy receptors, it also reduces their effective concentration), and as a result impair Aβ-mediated anti-inflammatory feedback signaling and lead to chronic microglial hyperactivity. Chronic microglial hyperactivity will in turn lead to cytokine elevation, which increasing evidence indicates leads to tauopathy (see further discussion below in section on tau hypothesis). Aβ oligomers can also directly activate a number of tau kinases [160 , 188–196] and may interact with cytokines to further promote tauopathy. Cytokine elevation may also activate compensatory increases in Aβ production (through, for example, increasing synaptic strength and neural activity [154, 155]), exacerbating Aβ aggregation and setting off a vicious cycle. In support of this interpretation, studies have found that in AD brains, soluble Aβ₄₀ is severely reduced, dropping from 50% of total Aβ in normal control and 8% in pathological aging to 2.7% in AD [197]. In mouse models of cerebral amyloid angiopathy, plaque formation is also found to divert Aβ away from blood vessels [198], indicating a depleting effect. On the other hand, in sporadic AD, while Aβ overproduction and/or defective clearance may play a primary role in subsets of cases, defective negative regulation of microglial inflammatory activation and/or defective pro-resolving microglial phagocytic activity may play a primary role in the majority (see also sections below on the neuroinflammation hypothesis and AD risk factors). These defects may render microglia hyperactive when exposed to immune stimulants such as associated with infection, sleep-disordered breathing, traumatic brain injury, and other factors during aging and lead to chronic microglial activity and chronic cytokine elevation. This may in turn lead to increases in Aβ production and consequent amyloidosis that further exacerbates neuroinflammation, and result in tauopathy (as similarly described above for familial AD). Thus, the Aβ/cytokine module that normally regulates homeostatic plasticity in the brain provides a potential unified explanation for familial and sporadic AD.

Fig. 6

A unifying model for AD pathogenesis. I hypothesize Aβ monomers normally act a negative feedback signal to prevent uncontrolled neuroinflammation (and maintain homeostatic plasticity) in the healthy brain. This loop may be perturbed, directly by Aβ aggregation-induced monomer depletion in familial AD (as well as potentially subsets of sporadic AD), or indirectly by defective microglial anti-inflammatory signaling in potentially most sporadic AD that results in increased cytokine and then increased Aβ (feedback signal) production and aggregate formation. Both may ultimately lead to the same outcome of effective-pool Aβ monomer depletion, chronic neuroinflammation, cytokine elevation, and tau pathology on one hand, and toxic oligomer accumulation and synaptic dysfunction on the other hand. The direct neurotoxic effects of Aβ oligomers may also further interact with effects of inflammatory cytokines and promote tauopathy development. This model has potential of reconciling leading hypotheses on AD as well as explaining clinical observations previously unaccounted for. (Note: astrocytes communicate intimately with microglia in regulating brain immune signaling, but for simplicity reasons are not depicted in this model). NFT, neurofibrillary tangle; TLRs, Toll-like receptors.

This explanation is not only compatible with leading AD hypotheses [199], but also fills in missing links and provides potential answers for several key clinical observations not accounted for previously. For example, the amyloid cascade hypothesis posits that Aβ deposition is the initiating step of AD pathogenesis, which then leads to tau deposition, followed by neuronal and synaptic loss and cognitive decline. This hypothesis is strongly supported by genetic data from familial AD, in which Aβ aggregation is almost certain the primary triggering factor [199, 200]. The model I propose in this review is compatible with this hypothesis since, as mentioned, Aβ aggregation, besides forming toxic oligomers, is predicted to also deplete the effective pool of Aβ monomers and lead to microglial hyperactivity. One difference in my model is that Aβ aggregation need not always be the primary initiating factor. In sporadic AD, Aβ aggregation, due to increased production and/or defective clearance, may play a primary role. However, defective microglial anti-inflammatory and/or pro-resolving signaling by monomeric Aβ and/or other pathways, caused by genetic, epigenetic, or other factors, may also serve as primary factors triggering the vicious cycle of escalating cytokines and escalating Aβ. Indeed, studies have found functional perturbation of a large number of sporadic AD risk genes all (>25) result in increased microglial lineage pro-inflammatory activity and/or impaired pro-resolving phago/endocytic pathway activity [201 –228]. As such, the model I propose in this review can potentially explain the dominance of microglia-related risk genes in sporadic AD [229]. More importantly, the model also provides plausible explanations for several clinical observations not accounted for by the amyloid cascade hypothesis. For example, against that hypothesis, minimal correlation has been observed between the severity of amyloid deposit and cognitive decline or between the severity of amyloid deposit and regional brain hypometabolism in AD patients [230, 231]. This may potentially be explained by a sufficient level of monomeric Aβ anti-inflammatory signaling despite Aβ aggregation in subpopulations of patients or subregions of the brain. It may also explain rare cases of familial AD that show only minimal cognitive impairment or neurodegeneration despite unusually high amyloid load [232]. Indeed, recent studies show, in both familial and sporadic AD patients, high soluble brain Aβ₄₂, which by chemical law also means likely high brain Aβ monomers [233, 234], in fact preserves normal cognition in AD patients despite increasing amyloidosis being detected in their brains [235 –237]. Furthermore, the model in this review provides a potential reason for the failure of most anti-amyloid clinical trials so far since almost all target both Aβ monomers and oligomers [238], which may not only fail to restore Aβ monomer anti-inflammatory signaling, but may unwittingly compromise it further.

The tau hypothesis proposes that tau pathology is the primary driver of cognitive decline and neurodegeneration in AD. This is also compatible with the model underlying this review since chronic microglial hyperactivity lies at the core of my model while numerous recent studies have elucidated an increasingly clear causative role of abnormal microglial activity in tau pathology. For example, increased IL-1β signaling has been found to result in tau hyperphosphorylation and aggregation via p38 MAPK in the mouse brain [239]. IL-1β has also been found to increase neuronal calcium influx [168], leading to prolonged activation of cdk5, a neuronal kinase with critical roles in both amyloid and tau pathology [160, 240]. Conversely, ablation of microglia has been found to ameliorate APOE4-driven tau pathology and neurodegeneration [241]. Clearance of senescent microglia and astrocytes similarly prevents tau-dependent pathology and cognitive decline [242]. Furthermore, blockade of inflammasome activation, which regulates IL-1β secretion, reduces tau hyperphosphorylation and aggregation, by altering the activity of tau kinases and phosphatases such as GSK3β [243]. One issue of the tau hypothesis is that it offers no specific explanation for the universal presence of amyloidosis in sporadic AD. The model underlying this review fills in this missing link. As discussed, I propose Aβ-mediated negative feedback is a key mechanism in brain cytokine homeostasis. If elevated cytokines cause tauopathy, brain cytokine levels should be rising well before the development of tauopathy. These rising cytokines would certainly have also activated this negative feedback and increased Aβ production. Increased Aβ production, meanwhile, has been causatively linked to amyloidosis in familial AD. Thus, the Aβ anti-inflammatory pathway provides a potential explanation for why tau pathology spreading is always accompanied by amyloid pathology in sporadic AD.

The neuroinflammation hypothesis proposes that inflammation is a central mechanism that may play a causative role in AD [244, 245]. This is the same overall conceptual framework as the model underlying this review, in which I further propose how different primary factors that affect Aβ production, clearance, monomeric Aβ and/or other anti-inflammatory signaling may all eventually lead to the same outcome of chronic microglial hyperactivity and vicious cycles of escalating cytokines and Aβ. The neuroinflammation hypothesis is strongly supported by genetic studies that implicate a large number of microglial function-related risk genes in sporadic AD [229]. An integrated systems approach employing postmortem human brain tissues also identifies an immune- and microglia-specific gene regulatory-network as the dominant module linked to late-onset AD [246]. Extensive studies have further shown many of these genes normally suppress microglial proinflammatory activity [201 –203]. Moreover, human imaging shows that inflammation can be observed in the brain of mild cognitive impairment subjects before amyloid deposition [245]. One issue for the neuroinflammation hypothesis is the well-accepted primary role of amyloidosis in familial AD. While Aβ aggregates may play a direct role in aggravating neuroinflammation in AD especially in late stages, the model I propose in this review provides a reason why it may trigger chronic neuroinflammation early on in familial AD, since, as discussed, Aβ aggregation will deplete the brain of monomers and may compromise anti-inflammatory signaling that would normally revolve neuroinflammation and prevent it from getting out of control in a timely manner at an early stage. Moreover, my proposal that microglial hyperactivity lies at the core of AD is also supported by recent studies that uncover profound effects of aging that lead to microglial hyperactivity, and may potentially explain why age is the biggest risk factor for AD. For example, studies have associated aging with systematic changes including mitochondrial dysfunction that are linked to chronic inflammation [247, 248]. Inflammasome, a major sensor of these changes, has been further found responsible for the chronic elevation of pro-inflammatory cytokines in the brain during aging [249]. Aging has also been found to result in the buildup of lipid-droplet-accumulating microglia, which are not only defective in phagocytosis but also produce high levels of reactive oxygen species as well as proinflammatory cytokines [250], all key contributors to AD pathology. Besides changes within the brain, age-related peripheral factors can also impact microglia. Studies show that, for example, β2-microglobulin, a systemic pro-aging factor elevated in the bloodstream during aging, can not only induce pro-inflammatory phenotypes in peripheral macrophages but also enter the brain and impact microglia in a similar fashion [251 –253]. Aged blood has also been found to activate microglia via brain endothelial cells [254]. Furthermore, at the genomics level, brain transcriptome analysis reveals aging has the most profound impact on the microglial Trem2 pathway [255]. Thus, the model underlying this review also provides a plausible explanation for why age is the biggest risk factor for AD.

Lastly, the antimicrobial protection hypothesis proposes that Aβ deposition is an early innate immune response to genuine, or mistakenly perceived, immune challenge in the brain and plays a primary role in AD pathology [256]. The model underlying this review is also compatible with this hypothesis. The function I propose of Aβ in cell competition is in essence an immune mechanism for unicellular organisms. Aβ, with its oligomeric isoform-specific activity, and full-length AβPP, with its iron export activity, may both be part of an ancient program of cell competition and immunity [14, 79]. In this process, Aβ monomers may serve in self-protection, while Aβ oligomers inhibit or kill competitors or pathogens. Full-length AβPP may, on the other hand, participate in this process by exporting iron and activating a nutritional immunity program against intracellular pathogens.

HOW GENETIC AND NON-GENETIC RISK FACTORS MAY AFFECT MICROGLIAL ACTIVITY

One of the potential issues for the hypothesis underlying this review is how to explain the link between different functional groups of AD risk genes and microglial activity. Several functional groups of genes have been linked to AD risks, including genes in endosomal trafficking, immune response, and cholesterol metabolism [257]. Perturbed function in many endosomal trafficking genes has been found to result in increased Aβ production [258 –261], suggesting they may potentially increase AD risks through mechanisms similar to familial AD. Immune response genes such as Trem2 normally directly or indirectly regulate microglial inflammatory and/or phagocytic activity and perturbation of their function may clearly impact microglial activity and brain immune homeostasis [201 –228]. Cholesterol metabolism genes include, among others, APOE, the E4 allele of which is the highest genetic risk factor for sporadic AD. APOE is unique in that it is a pleiotropic gene that regulates multiple AD-related processes. For example, APOE is a ligand for Trem2 and may thus impact microglial activity through Trem2 [262 –264]. APOE4 also competes with Aβ for LRP1 binding and may impede Aβ clearance [265, 266]. It also appears to increase neuronal Aβ production [267, 268]. Furthermore, APOE4 may contribute to microglial hyperactivity through affecting blood-brain barrier [269, 270]. Lastly, APOE is a key carrier for cholesterol trafficking from astrocytes to other cell types in the brain [271] and plays a fundamental role in brain cholesterol metabolism [267 , 273].

Importantly, recent studies show that perturbed brain cholesterol metabolism alone may by itself impact microglial activity through a multitude of mechanisms. This is in large part due to that cholesterol synthesis appears to be a major part of the microglial pro-inflammatory program and there exist a large number of feedforward mechanisms through which cholesterol synthesis enhances microglial activity. Microglial cholesterol synthesis is normally activated during inflammation to facilitate immune receptor signaling as well as fine-tune plasma membrane composition for self-protection against AMPs being released [274 –276]. In all cells, the level of cholesterol synthesis is regulated by the transcription factors SREBPs [277], the activity of which is in turn determined by resting cellular cholesterol level. When the level is low, SREBP is released from sequestration and enters the nucleus, where it activates cholesterol synthesis-promoting genes. A key factor affecting resting cholesterol level is extracellular availability. In the brain, astrocytes synthesize the bulk of cholesterol and since cholesterol does not normally cross the blood-brain barrier, low astrocytic cholesterol synthesis and trafficking will result in increased microglial cholesterol synthesis during microglial activation [278]. Increased SREBP activity and cholesterol synthesis can in turn enhance microglial pro-inflammatory activity through a number of feedforward mechanisms.

Activated SREBP2 has been found to promote the translocation of NLRP3 inflammasome to sites near mitochondria [279]. Since mitochondria play a critical role in inflammasome activation and release of cytokines such as IL-1β, this enhances microglial pro-inflammatory activity [280].

Activated SREBP2 also binds to the promoters of inflammatory genes in macrophages and directly stimulate immune response independent of its function in sterol metabolism [281].

Active SREBP2 further primes the trafficking and activation of STING, an endoplasmic reticulum sensor that positively promotes cellular interferon response [282].

Increased cholesterol synthesis produces a large number of metabolites including mevalonate, which induces enhanced innate immune activity (trained immunity) through mTOR activation and histone modification of inflammatory pathway genes [283, 284].

Increased cholesterol synthesis is also linked to glutaminolysis and glutamine replenishment of the TCA cycle, which result in accumulation of fumarate, a metabolite that facilitates enhanced immune activity (trained immunity) through inhibiting the KDM5 histone demethylase [285].

Glutaminolysis in addition leads to the accumulation of a third metabolite, succinate, which stabilizes and enhances the activity of hypoxic factor HIF-1α and induces inflammatory cytokines including IL-1β [286]. Oxidation of succinate, together with elevation of mitochondrial membrane potential, also induces pro-inflammatory gene expression [287].

Thus, low resting cholesterol in microglia may promote cholesterol synthesis and microglial hyperactivity through a multitude of epigenetic and non-epigenetic mechanisms. This may explain the prominence of cholesterol metabolic genes as AD risk factors.

The epigenetic regulation of microglial activity also provides a potential mechanism linking non-genetic risk factors to microglial hyperactivity and as such a coherent explanation for all AD risk factors. As alluded to above, cholesterol metabolism is intimately linked to innate immune memory in microglial lineage cells. Like adaptive immune cells, innate immune cells also possess lasting memory. Depending on the conditions of initial exposure, macrophages may increase or decrease response upon subsequent exposure to stimulants (trained immunity or tolerance). Studies have found that metabolites in both the cholesterol synthesis pathway and the TCA cycle play key roles in this process. For example, β-glucan induced trained immunity has been found to increase pro-inflammatory cytokine response thorough epigenetic mechanisms mediated by mevalonate and succinate [283]. β-glucan can also enhance trained immunity through inhibition of genes responsible for the synthesis of the tolerance-inducing metabolite itaconate [288]. Importantly, recent studies show that innate immune memory may indeed play a role in AD. For example, endogenous immune stimulants such as age-associated oxidized lipids common in AD have been found to induce innate immune memory [289]. Among the gene loci epigenetically modified during macrophage immune memory are also a large number of AD risk genes [290 –295], including EphA4, CTB-104H12.6, TREML2, PSEN2, SLC2A5, SORL1, NME8, SLC24A4, HLA-DRA/DRB5/DQA1, GAL3ST4, CLU, MS4A6E, TREM1, ABCA1, SAMSN1, BCL3, and RELB [296], of which PSEN2 is most notable for its role in familial AD. Furthermore, strong evidence indicates that non-genetic AD risk factors such as viral activity, sleep apnea/hypoxia, and traumatic brain injury [297 –299] may all contribute to AD by epigenetically altering microglia, which, due to their longevity, exert lasting impact on the brain. For example, microglial depletion followed by repopulation, which erases their acute-phase memory, has been found to reduce chronic neuroinflammation and neurodegeneration in animal models of traumatic brain injury [300, 301]. Peripherally applied inflammatory stimuli have also been found to induce innate immune memory in microglia and alter disease pathology in AD models [302]. Aging, the biggest risk factor for AD, also prominently affects microglial activity (see previous section). Thus, these findings provide further support for a central role of microglial hyperactivity in AD pathogenesis.

WHY AβPP OVEREXPRESSION MOUSE AD MODELS DO NOT PRODUCE TANGLES

A well-known issue in current AD research is that none of the mouse models overexpressing familial AD genes show robust neurofibrillary tangles. There are a number of potential explanations, including the much shorter lifespan of mice. However, based on the hypothesis underlying this review, a potential factor may be that overexpression of AβPP, even of mutant forms, may increase basal levels of monomeric Aβ. Increased monomeric Aβ is predicted to inhibit microglial pro-inflammatory activity and as a result inhibit tau pathology development. Indeed, studies have found that the level of soluble Aβ₄₀ in 5xFAD mice is five time as high as that in the control [303]. If so, a follow-up prediction will be enhancing microglial inflammatory activity in these animals should promote tau pathology. This has indeed been observed in many studies.

The 5xFAD mouse, which carries five familial AD mutations in AβPP and Presenilin 1 (PS1), is one of the most widely used AD models that show minimal tau pathology. Deletion of ATG5 and Rubicon, which increases microglial pro-inflammatory response, has been found to result in tau hyperphosphorylation and accelerated neuronal death in these animals [304]. Similarly, introduction of APOE4 homozygosity, which increases microglial pro-inflammatory activation in comparison to APOE3, also results in increased cdk5 activity and site-specific tau phosphorylation in 5xFAD mice [305]. The APPPS1 model, which overexpresses two mutations in AβPP and Presenilin 1, also does not normally show significant tau pathology. However, knockout of Trem2, a gene that normally suppress microglial pro-inflammatory activity, or replacement with Trem2^R47H, a variant associated with AD risk, both facilitate the seeding and spreading of tau aggregates in APPPS1 animals [306]. Similarly, deficiency in membrane anchored Cx3cl1, a ligand that normally suppresses microglial activation through CX3CR1, also results in increased expression of inflammatory cytokines and enhanced neuronal tau phosphorylation in these animals [307]. Moreover, deletion of CX3CR1 from the hAPP-J20 mouse, which overexpresses two mutations in AβPP, also exacerbates microglial activation and increases tau phosphorylation [308]. In addition, blocking the function of transthyretin, a protein that normally inhibits myeloid cell pro-inflammatory cytokine production, results in tau phosphorylation and neuronal loss in the Tg2576 mouse, a model that overexpresses a single AβPP mutant allele [309]. Lastly, a spontaneously hypertensive stroke-prone (SHRSP) genetic background that increases neuroinflammation has been also found to exacerbate tau pathology in a rat model of AD [310]. Thus, these results strongly indicate that muted microglial activity and suppressed cytokine levels may be responsible for the lack of robust tau pathology in AβPP-overexpressing animal models.

This conclusion is further supported by studies in additional AD and related disease models. Because of the lack of robust tau pathology in animals overexpressing AβPP/PS1, studies have further introduced tau mutations. The 3xTgAD mouse, which harbors human mutant AβPP, PS1, as well as tau, is widely employed. Results from these animals also support a causative role of pro-inflammatory cytokines in tau pathology development. For example, lipopolysaccharide (LPS) injection has been found to stimulate brain inflammation, induce cdk5 activation, and increase tau hyperphosphorylation in these animals [311]. Similarly, inducible IL-1β overexpression also results in robust increases in tau phosphorylation despite reductions in amyloid load [312]. Conversely, chronic dosing with an IL-1R blocking antibody suppresses inflammatory activity and markedly attenuates tau pathology in these animals [313]. Blocking Aβ₄₂ accumulation, which likely increases monomeric Aβ, also delays the progression of tau pathology [314].

Several in vitro models of AD similarly reveal a key role of microglia and inflammatory cytokines in tau pathology. For example, in a 3D human triculture system using neurons, astrocytes and microglia that overexpresses mutant AβPP, the addition of microglia increases the secretion of pro-inflammatory cytokines and induces neuronal loss in an interferon-gamma and Toll like receptor 4-dependent manner [315]. The severity of tau pathology in this model is positively linked to Aβ_42/40 ratio but not to total Aβ level [316]. This is consistent with the model in this review since Aβ₄₂ is known to be more prone to aggregation than Aβ₄₀. Aβ_42/40 ratio will thus determine the severity of Aβ aggregation, effective-pool monomer depletion, and defective anti-inflammatory signaling. iPSC-derived neurons have also been generated from AD patients that show increased tau phosphorylation in culture [317]. This is in apparent contradiction to the proposed role of microglia in tau pathology. However, these cultures, even though purified by cell sorting, still contain up to 10% non-neuronal cells including potentially microglia and astrocytes. In support, studies have found that iPSCs spontaneously differentiate into microglia in brain organoids [318]. Moreover, in support of a role played by cytokines, a drug screening has identified a large number of anti-inflammatory small molecules that suppress tau phosphorylation in this model [319]. Thus, many lines of evidence indicate that conventional AD modeling may have inadvertently elevated anti-inflammatory signaling, resulting in a distinct microglial phenotype. Indeed, several recent genomics studies show that the disease associated microglia in mouse AD models are remarkably different from microglia isolated from AD patient brains, with the latter displaying a more reactive/aging-related (i.e., inflammatory) phenotype [320 –322]. On the other hand, it has been reported that disrupting the monomeric Aβ signaling pathway appears to result in AD-like tau pathology in mice. Thus, the hypothesis underlying this review may also help find new approaches for better modeling AD.

CONCLUDING REMARKS

In this review, I present a large body of converging evidence that supports the interpretation that Aβ monomers and oligomers may be the protective and punishment signals long predicted to mediate activity-dependent axon/synapse competition in neural development. The outcome of this competition appears to be determined by the balance between trophic Aβ monomers and toxic Aβ oligomers near the competing axons and nearby glia. In the adult brain, this regulatory circuit, especially the cytokine-inhibiting anti-inflammatory feedback mediated by Aβ monomers, appears to play a critical role in the regulation of homeostatic synaptic plasticity and brain cytokine homeostasis. Disruption of this feedback during aging due to perturbation of Aβ-monomer/oligomer ratio/balance, either directly by genetic mutations that favor oligomer formation or indirectly by defective microglial anti-inflammatory signaling or pro-resolving phagocytic activity that secondarily leads to increases in Aβ production and oligomer formation, may be responsible for the same ultimate outcome of vicious cycles of escalating cytokines and escalating Aβ, and resultant tauopathy in different forms of AD. This hypothesis has the potential of providing a unified explanation for the physiological and pathological roles of Aβ in the brain.

Footnotes

ACKNOWLEDGMENTS

The author thanks late Dr. D. Oertel (UW-Madison) for critical reading of an earlier version of the hypothesis underlying this review.

FUNDING

Funding for this project was provided in part by NIH/NCATS through CTSA award UL1TR002373 to the UW Institute for Clinical and Translational Research.

CONFLICT OF INTEREST

The author has no conflict of interest to report.

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