Skip to main content
Download PDF

Enhanced prefrontal nicotinic signaling as evidence of active compensation in Alzheimer’s disease models

Translational Neurodegeneration volume 13, Article number: 58 (2024) Cite this article

Abstract

Background

Cognitive reserve allows for resilience to neuropathology, potentially through active compensation. Here, we examine ex vivo electrophysiological evidence for active compensation in Alzheimer’s disease (AD) focusing on the cholinergic innervation of layer 6 in prefrontal cortex. Cholinergic pathways are vulnerable to neuropathology in AD and its preclinical models, and their modulation of deep layer prefrontal cortex is essential for attention and executive function.

Methods

We functionally interrogated cholinergic modulation of prefrontal layer 6 pyramidal neurons in two preclinical models: a compound transgenic AD mouse model that permits optogenetically-triggered release of endogenous acetylcholine and a transgenic AD rat model that closely recapitulates the human trajectory of AD. We then tested the impact of therapeutic interventions to further amplify the compensated responses and preserve the typical kinetic profile of cholinergic signaling.

Results

In two AD models, we found potentially compensatory upregulation of functional cholinergic responses above non-transgenic controls after onset of pathology. To identify the locus of this enhanced cholinergic signal, we dissected key pre- and post-synaptic components with pharmacological strategies. We identified a significant and selective increase in post-synaptic nicotinic receptor signalling on prefrontal cortical neurons. To probe the additional impact of therapeutic intervention on the adapted circuit, we tested cholinergic and nicotinic-selective pro-cognitive treatments. Inhibition of acetylcholinesterase further enhanced endogenous cholinergic responses but greatly distorted their kinetics. Positive allosteric modulation of nicotinic receptors, by contrast, enhanced endogenous cholinergic responses and retained their rapid kinetics.

Conclusions

We demonstrate that functional nicotinic upregulation occurs within the prefrontal cortex in two AD models. Promisingly, this nicotinic signal can be further enhanced while preserving its rapid kinetic signature. Taken together, our work suggests that compensatory mechanisms are active within the prefrontal cortex that can be harnessed by nicotinic receptor positive allosteric modulation, highlighting a new direction for cognitive treatment in AD neuropathology.

Introduction

Cognitive reserve denotes an individual’s ability to withstand a higher degree of neurological decline before exhibiting cognitive impairment [1]. Lifestyle factors have been shown to promote cognitive reserve, decreasing risk of dementia and slowing cognitive decline in Alzheimer’s disease (AD) [2,3,4]. The impact of these factors is not limited to disease onset but persists even as neuropathology worsens [5,6,7,8,9]. In fact, cognitive reserve is hypothesized to allow for compensation during neuropathology [10, 11], generating a new or stronger response to sustain network recruitment [12, 13]. In AD and its preclinical models, there are now several diverse examples of neuronal compensation leading to cognitive maintenance [14, 15], but compensatory capacity in the cholinergic system has not been systematically evaluated.

Cholinergic pathways in prefrontal cortex are well positioned to contribute to mechanisms of cognitive reserve in AD [16, 17]. This modulation of layer 6 of prefrontal cortex is essential for attention, executive function, and learning [18,19,20,21,22,23,24]. Pro-cholinergic treatments improve cognition preclinically [25,26,27] and slow cognitive decline clinically [28,29,30,31]. While the remodelling of the cholinergic system in AD has been extensively probed, key clinical [32,33,34] and preclinical studies [35,36,37] focused on cholinergic neurodegeneration and synaptic loss. There has been relatively little functional investigation in early to mid-disease synaptic changes, except in the most swiftly-progressing genetic models of AD that preclude the use of littermate controls [38,39,40,41,42,43,44,45,46,47]. To detect and systematically investigate the mechanisms of compensatory plasticity, it is essential to use a well-charted model with appropriately-matched non-transgenic controls.

In this study, we used optogenetics and whole-cell electrophysiology ex vivo to investigate prefrontal acetylcholine pathways innervating layer 6 pyramidal neurons. In models of AD from two different species, we found a strong and significant upregulation of these cholinergic responses above non-transgenic levels after onset of pathology. To probe the mechanisms underlying this functional upregulation, we systematically manipulated pre- and postsynaptic elements of the cholinergic synapse. We discovered the upregulation is specific to nicotinic receptor signalling. Lastly, we assessed the functional impact of therapeutic interventions on cholinergic responses, contrasting current standard AD treatment with a novel nicotinic treatment. Both manipulations improved endogenous cholinergic responses, but only the targeted nicotinic treatment preserved the typical rapid timing essential for cue detection. Overall, we demonstrate evidence for active cholinergic upregulation and put forward a mechanism of cognitive compensation that remains accessible to further potentiation with treatment.

Materials and methods

Animals

Animal experiments were approved by the University of Toronto Temerty Faculty of Medicine Animal Care Committee and conducted in accordance with the guidelines of the Canadian Council on Animal Care (protocols #20011621, #20011658, #20011796). TgCRND8 transgenic mice expressing double human amyloid precursor protein (APP) Swedish and Indiana mutations (KM670/671NL/V717F) under the Prp gene promoter [48] on a C57BL/6 background were crossed with transgenic mice expressing channelrhodopsin (ChR2) in cholinergic afferents (ChATChR2; RRID:IMSR_JAX:014546, Jackson Laboratory, Bar Harbor, ME [49]). Cholinergic neurons originating from the nucleus basalis project throughout the brain and densely innervate the deep layers of the prefrontal cortex [49, 50], where we optogenetically stimulated their afferents. This transgenic model expresses ChR2 under the choline acetyltransferase promoter, localizing ChR2 expression to neurons that are cholinergic at the time of recording. This approach avoids expression of ChR2 in neurons that are only transiently cholinergic during development [51]. TgCRND8/ChATChR2 mice were compared to ChATChR2 littermates as controls. Male and female mice were weaned at postnatal day (P)21, separated by sex, and group-housed (2–4 mice per cage) in plastic cages with corn cob bedding, houses for environmental enrichment, and ad libitum access to food and water on a 12-h light/dark cycle with lights on at 7:00 AM. Mice were used at two age groups based on previously described progression [52,53,54,55,56]: an early to mid-disease group and controls, 3–6 months old (n = 30, mean 4.7 ± 0.2 months), and a later disease group and controls, 7–12 months (n = 26, mean 9.9 ± 0.3 months). Groups were balanced for sex and genotype.

TgF344 AD rats expressing the human APP Swedish mutation (KM670/671NL) and presenilin 1 with exon 9 excised, under the mouse prion promoter [57], were outbred on a Fischer strain. TgF344 AD rats were compared to F344 littermates as controls. Rats were bred at Sunnybrook Research Institute (protocol #22655), and housed in plastic cages with corn cobb bedding, 2 animals per cage, with houses and toys for environmental enrichment, on a 12-h light/dark cycle with ad libitum access to food and water. Rats were transferred to the University of Toronto Division of Comparative Medicine and housed for a minimum of 6 weeks before experiments. Rats were used at three age groups based on stages described previously [58,59,60,61]: an age group of 8 months for consideration of early AD and controls (n = 21, mean 8.4 ± 0.2 months), an age group of 12 months for mid-AD and controls (n = 23, mean 12.4 ± 0.2 months), and an age group of 18 months for later-AD and controls (n = 26, mean 17.6 ± 0.2 months). Groups were balanced for sex and genotype.

Electrophysiology and optogenetics

Animals were euthanized by decapitation following injection of chloral hydrate to render unconscious. This approach was justified because the cholinergic receptor targets of this investigation are sensitive to other anaesthetics [62,63,64,65,66,67]. The protocols were approved by the Animal Ethics Committee of the Temerty Faculty of Medicine at the University of Toronto (mice: #20011621, #20011658, rats: #20011796). The brain was rapidly removed in 4 °C sucrose ACSF (254 mM sucrose, 10 mM D-glucose, 26 mM NaHCO3, 2 mM CaCl2, 2 mM MgSO4, 3 mM KCl, and 1.25 mM Na2PO4). The 400-μm thick cortical slices of the prefrontal cortex (bregma 2.2–1.1) were obtained on a Dosaka linear slicer (SciMedia, Costa Mesa, CA). Slices were transferred to a prechamber (AutoMate Scientific, Berkeley, CA) where they recovered for at least 2 h in oxygenated (95% O2, 5% CO2) ACSF (128 mM NaCl, 10 mM D-glucose, 26 mM NaHCO3, 2 mM CaCl2, 2 mM MgSO4, 3 mM KCl, and 1.25 mM Na2PO4) at 30 °C before being used for electrophysiology.

For whole-cell patch-clamp electrophysiology, brain slices were transferred to a chamber mounted on the stage of a BX51WI (Olympus, Richmond Hill, ON, Canada) microscope and perfused with 30 °C oxygenated ACSF at 3–4 ml/min. Layer 6 pyramidal neurons in the prelimbic and anterior cingulate regions of the medial prefrontal cortex were identified by size, morphology, and proximity to white matter, visualized using infrared differential interference contrast microscopy. Recording electrodes were filled with patch solution containing 120 mM K-gluconate, 5 mM MgCl2, 4 mM K-ATP, 0.4 mM Na2-GTP, 10 mM Na2-phosphocreatine, and 10 mM HEPES buffer adjusted to pH 7.33 with KOH. Data were acquired and low-pass filtered at 20 kHz with Axopatch 200b amplifier (Molecular Devices, San Jose, CA) and Digidata 1440 digitizer and pClamp10.3 acquisition software (Molecular Devices). Responses from a homogenous population of layer 6 regular spiking pyramidal neurons [68, 69] were examined in voltage clamp at − 75 mV and in current clamp.

To excite ChR2-containing cholinergic afferents optogenetically (opto-ACh), blue light (470 nm, 2 mW) was delivered in 5-ms pulses with a collimated LED (Thorlabs, Newton, NJ). This opto-ACh stimulus was delivered in a frequency-accommodating (50–10 Hz) eight-pulse train to stimulate cholinergic axons [68, 69] to mimic the activation pattern of cholinergic neurons [70,71,72]. This opto-ACh protocol elicits direct cholinergic inward current responses resilient to combined application of glutamatergic synaptic blockers [50, 68, 69, 73] and sensitive to combined cholinergic receptor antagonists [68].

Experimental design, analysis, and statistics

Animals of both sexes were used in pharmacological interventions. All experiments were performed on multiple rodents per intervention, and recordings were made from 1 to 3 neurons per brain slice of prefrontal cortex (2–3 slices from each mouse, and 3–4 slices from each rat). Pharmacological agents were pre-applied for 10 min and co-applied during optogenetic stimuli or exogenous acetylcholine bath application and recovery period. CNQX (50 µM) and D-APV (50 µM) were applied to block glutamatergic synaptic transmission; bicuculline (3 µM) and CGP55845 (1 µM) were applied to block GABA receptors; atropine (200 nM; Sigma-Aldrich) was applied to block muscarinic receptors; dihydro-β-erythroidine (DHβE; 3 µM) to block β2-containing nicotinic receptors; AF-DX 116 (300 nM) to block M2 muscarinic receptors; galantamine hydrobromide (1 µM) to block acetylcholinesterase, and NS9283 (1 µM) to potentiate nicotinic responses. Compounds were from Tocris Biosciences (Toronto, Canada) unless otherwise specified.

Data analysis was performed in Clampfit 10.3 (Molecular Devices) and Axograph and statistical analysis was performed with Graphpad Prism 10. To measure fast-onset kinetics, raw traces were used for calculating rising slope of current response within 50 ms of opto-ACh onset. To measure response magnitude, downsampled traces were used to fit triple exponentials to opto-ACh responses, from which the peak amplitude (pA) and decay constant (s), where applicable, were measured.

Firing rise was measured by the mean increase in firing frequency for the initial 0.5 s following the onset of the opto-ACh stimulus relative to the mean baseline firing frequency (calculated over 2 s before opto-ACh stimulus). Peak firing frequency was measured as the difference between the mean baseline firing frequency and fastest instantaneous firing frequency following opto-ACh stimulus. Genotype differences in opto-ACh responses were assessed with unpaired two-tailed t-tests. Pharmacological manipulations to assess synaptic components of the cholinergic response were calculated with unpaired, two-tailed t-tests. The effects of therapeutic interventions were assessed with paired, two-tailed t-tests. The impact of sex on cholinergic measures and interactions between sex and genotype were analyzed by two-way ANOVA.

To measure currents to exogenous ACh, 1 mM ACh was bath-applied for 15 s. Genotype differences in acetylcholine current magnitude were measured by peak amplitude. Acetylcholine firing response was measured from stimulus onset to peak firing. Both measures were graphed with a cumulative frequency distribution with 10 pA or 10 s bin width, allowing for direct comparison of each age group’s genotype differences. Genotype differences in these measures were calculated with a nonparametric Kolmogorov Smirnov (KS) test.

Intrinsic neuronal properties were assessed by current-clamp and voltage-clamp recordings at baseline and statistically analysed using unpaired two-tailed t-tests. To measure intrinsic neuronal excitability, input–output curves were generated by measuring neuronal firing frequency in response to increasing steps of injected current. These data were statistically analysed by performing a second-order polynomial nonlinear regression of input–output curves and a comparison of fit, analysed with an F test.

Results

Increased opto-ACh responses in TgCRND8 AD mice at early to mid-disease stage

To measure functional changes in the prefrontal cortex cholinergic signals in an AD model, we recorded whole-cell responses to endogenous acetylcholine released optogenetically (opto-ACh; Fig. 1a1, a2) in TgCRND8/ChATChR2 AD mice during early to mid-AD (3 to 6 months) and their ChATChR2 control littermates [52,53,54,55,56]. Cholinergic neurons from the nucleus basalis project throughout the brain and densely innervate the deep layers of the prefrontal cortex [49, 74], where the cholinergic afferents were optogenetically stimulated. Optogenetic responses were recorded from pyramidal neurons in layer 6 of the prelimbic and anterior cingulate areas of the prefrontal cortex. The layer 6 receives dense innervation of cholinergic afferents [74] and shows strong excitatory responses [75]. Responses from a homogenous population of regular spiking pyramidal neurons [68, 69] were examined in voltage-clamp at − 75 mV and in current-clamp. The brief opto-ACh protocol [68, 69, 73] elicited inward current responses resilient to combined application of glutamatergic synaptic blockers CNQX (20 µM) and D-APV (50 µM) in non-transgenic control (opto-ACh; 39.2 ± 14 pA, opto-ACh synaptic blockers: 40.5 ± 14.3 pA; paired t-test: t5 = 0.3, P = 0.8) and TgCRND8/ChATChR2 mice (opto-ACh; 82.7 ± 22 pA, opto-ACh synaptic blockers: 80.4 ± 19 pA; paired t-test: t4 = 0.3, P = 0.8), and resilient to combined application of GABA receptor blockers bicuculline (3 µM) and CGP (1 µM) in non-transgenic control (opto-ACh; 28.2 ± 6.5 pA, opto-ACh GABA blockers: 24.8 ± 5.9 pA; paired t-test: t5 = 2, P = 0.1) and TgCRND8/ChATChR2 mice (opto-ACh; 45.4 ± 11.9 pA, opto-ACh synaptic blockers: 43.8 ± 11.5 pA; paired t-test: t7 = 0.7, P = 0.5).

Fig. 1
figure 1

Endogenous opto-ACh responses are upregulated in early to mid-AD. a.1 Image depicts compound transgenic mouse cross between TgCRND8 AD mouse model and ChAT-ChR2 mouse model expressing channelrhodopsin in cholinergic neurons. Image depicts coronal brain section from these mice, showing the recording electrode positioned over layer 6 of the prefrontal cortex. a.2 Schematic adapted from Power et al., 2023, represents the cholinergic prefrontal synapse receiving optogenetic stimulus (0.5-s pulse train of decreasing frequency). Afferents release endogenous acetylcholine (ACh) which binds to nicotinic and muscarinic receptors, exciting postsynaptic pyramidal neurons. b Representative opto-ACh responses from non-transgenic (nTg) control (black) and TgCRND8 AD (grey) neurons measured in voltage clamp (Vm =  − 75 mV). c, d Graphs show significant increases in rise speed (P < 0.01) (c) and peak amplitude (P < 0.01) (d) of opto-ACh currents in TgCRND8 early AD responses relative to age-matched controls (3–6 months old). e Representative opto-ACh responses from WT control (black) and TgCRND8 AD (grey) neurons measured in current clamp. f, g Graphs show significant increase in firing rise (P < 0.0001) (f) and peak firing frequency (P < 0.05) (g) of opto-ACh firing responses in TgCRND8 early/mid AD responses relative to age-matched controls. Mice aged 3 to 6 months (nTg: 4.5 ± 0.4 months, n = 10 animals; 3–4 brain slices per animal, TgCRND8: 4.8 ± 0.3 months, n = 10 animals, 3–4 brain slices per animal)

Full size image

We found a significant increase in the opto-ACh current responses in early to mid-AD mice (3–6 months) (Fig. 1b), reflected by significantly greater rising slope (Fig. 1c, unpaired two-tailed t-test: t = 3.3, P = 0.002, df = 68) and peak amplitude (Fig. 1d, unpaired two-tailed t-test: t = 3, P = 0.004, df = 68).

This upregulation was also detected in the change of the firing response elicited by opto-ACh (Fig. 1e). Holding the neurons in current clamp and injecting current to elicit ~ 2–3 Hz action potential firing at baseline, opto-ACh elicited a significantly greater increase in the delta initial firing frequency or firing rise (Fig. 1f, unpaired two-tailed t-test: t = 4.2, P < 0.0001, df = 54) and the delta peak firing frequency (Fig. 1g, unpaired two-tailed t-test: t = 2.3, P = 0.02, df = 54) in AD compared to control.

To delve deeper into the opto-ACh result, we investigated the effect of sex, but did not detect a main effect of this factor (two-way ANOVA, F1, 64 = 1.4, P = 0.2), nor a significant interaction between sex and genotype (F1, 64 = 1.8, P = 0.4) on cholinergic current amplitude.

In addition, there was no difference in intrinsic membrane properties between TgCRND8/ChATChR2 and ChATChR2 mice (Additional file 1: Table S1). We also assessed neuronal excitability by measuring action potential firing rate in response to increasing steps of current injection and generating input–output curves. In the absence of opto-ACh, we found no significant difference in the excitability curves (nonlinear regression, comparison of fit, Additional file 1: Fig. S1a). These findings underscore the relative specificity of opto-ACh in this AD mouse model to increase the excitability of layer 6 pyramidal neurons during early to mid-disease stage.

Upregulated opto-ACh responses do not persist in later-disease in TgCRND8 AD mouse model

To ask what happens to the AD cholinergic response with progression of neuropathology, we recorded from TgCRND8/ChATChR2 AD mice and their age- and sex-matched non-transgenic control littermates at a more advanced stage of AD. In this older group (7–12 months), the opto-ACh current responses in AD mice were similar to the non-transgenic level (Fig. 2a–c; unpaired two-tailed t-test: rising slope t = 0.07, P = 0.9, df = 75; peak amplitude t = 0.5, P = 0.6, df = 75). Similar results were found for opto-ACh firing responses (Fig. 2d–f; unpaired two-tailed t-test: firing rise t = 0.6, P = 0.6, df = 60; peak firing t = 0.2, P = 0.8, df = 60). Cholinergic responses in the model were no longer significantly greater than controls at the later time point.

Fig. 2
figure 2

Cholinergic signaling did not differ from non-transgenic in late AD. a Representative opto-ACh responses from non-transgenic (nTg) control (black) and TgCRND8 AD (grey) neurons at late stage of disease measured in voltage clamp (Vm =  − 75 mV). b, c Graphs show no difference in rising speed (b) and peak amplitude (c) of opto-ACh currents in TgCRND8 late-AD responses compared to age-matched controls. d Representative opto-ACh responses from WT control (black) and TgCRND8 AD (grey) neurons at late stage of disease measured in current clamp. e, f Graphs show no difference in firing rise (e) and peak firing frequency (f) of opto-ACh firing responses in TgCRND8 late-AD responses compared to age-matched controls. Mice aged 7–12 months (nTg: 9.3 ± 0.5 months, n = 10 animals, 3–4 brain slices per animal, TgCRND8: 10.1 ± 0.6 months, n = 10 animals, 3–4 brain slices per animal)

Full size image

Consistent with the younger age group, we found no significant effect of sex (two-way ANOVA, F1, 73 = 0.1, P = 0.7) or significant interactions between sex and genotype (F1, 73 = 2.2, P = 0.1) on cholinergic current amplitude.

Further investigation of the intrinsic membrane properties of these neurons showed no significant genotype differences (Additional file 1: Table S1). Regarding neuronal excitability, input–output analysis revealed no significant genotype difference in excitability curves (Additional file 1: Fig. S1b; nonlinear regression, comparison of fit). These results suggest that the prefrontal endogenous cholinergic responses are upregulated in AD mice of early/mid-pathology but not of advanced disease stage.

Increased cholinergic responses at mid-disease in TgF344 AD rat model

To evaluate whether cholinergic upregulation in response to AD pathology is recapitulated across species, we consider the TgF344-AD rat model [57]. We compared TgF344-AD and WT littermate controls at three stages of disease: early-AD (8 months), mid-AD (12 months), and later-AD (18 months) [58,59,60,61]. Strikingly, we again found an upregulation in cholinergic currents in TgF344-AD rats compared to controls (Fig. 3a, b). This difference was specific to the mid-AD age group (KS test, P = 0.005, D = 0.4) (Fig. 3c–e). It was not observed in the early-AD group (KS test, P = 0.7, D = 0.2) or the later-AD group (KS test, P = 0.7, D = 0.2).

Fig. 3
figure 3

Early cholinergic upregulation conserved in different species and AD models. a Image depicts TgF344 AD rat model and a coronal brain section with the recording electrode positioned over layer 6 of the prefrontal cortex. b Representative responses to exogenous bath-applied acetylcholine from F344 non-transgenic (nTg) control (black) and TgF344 AD (grey) neurons measured in voltage clamp (Vm =  − 75 mV). c–e Graphs show that the cumulative frequency of peak amplitude of acetylcholine current was not different at 8 months (c), was significantly higher for TgF344 AD responses than controls at 12 months (P < 0.01) (d), and was not different at 18 months (e). Insets show the data in scattergram. f Representative responses to exogenous bath-applied acetylcholine from F344 WT control (black) and TgF344 AD (grey) neurons measured in current clamp. g, h Graphs show that the cumulative frequency of time to peak firing of acetylcholine response was not different at 8 months (g), was significantly faster for TgF344 AD responses than controls at 12 months (P < 0.01) (h), and was not different at 18 months (i). Insets show the data in scattergram. Rats aged in three cohorts: 8 months (nTg: 8.5 ± 0.2 months, n = 12 animals, 4–5 brain slices per animal, TgF344: 8.4 ± 0.2, n = 9 animals, 4–5 brain slices per animal), 12 months (nTg: 12.4 ± 0.2 months, n = 13, 4–5 brain slices per animal, TgF344 12.5 ± 0.2 months, n = 10 animals, 4–5 brain slices per animal), and 18 months (nTg: 17.7 ± 0.3 months, n = 14 animals, 4 –5 brain slices per animal, TgF344: 17.6 ± 0.2 months, n = 12 animals, 4–5 brain slices per animal)

Full size image

A similar pattern was observed for changes in action potential firing in response to cholinergic stimulation (Fig. 3f). The TgF344-AD rat model showed an upregulation in cholinergic firing, as measured by the reduced time taken to attain peak firing rate relative to controls at mid-AD (Fig. 3g–i, KS test, P = 0.003, D = 0.4). However, this difference was not observed at early-AD (KS test, P = 0.8, D = 0.1) or later-AD (KS test, P = 1, D = 0.1).

To delve deeper into the cholinergic responses, we examined the impact of sex within each age group. We detected no sex differences in ACh currents (two-way ANOVA, 8 months: F1, 98 = 0.4, P = 0.5; 12 months: F1, 77 = 0.04, P = 0.8; 18 months: F1, 80 = 0.003, P = 0.9) or significant interactions between sex and genotype (8 months: F1, 98 = 2.7, P = 0.1; 12 months: F1, 77 = 0.09, P = 0.8; 18 months: F1, 80 = 0.3, P = 0.6).

The differences in cholinergic responses observed in the mid-AD (12 month) group occurred in the absence of differences in intrinsic properties (Additional file 1: Table S2). Examination of the excitability of these neurons with input–output analysis (Additional file 1: Fig. S2a–c) showed a significant decrease in the intrinsic excitability curve of TgF344 AD neurons at 12 months (Additional file 1: Fig. S2b; nonlinear regression, comparison of fit, F3,561 = 3.8, P = 0.01). Interestingly, this decrease of excitability in response to current injection coincided with the emergence of increased excitability to cholinergic stimulation (Fig. 3). This finding underscores the relative specificity of increased cholinergic excitation of layer 6 neurons at mid-AD in this rat model. In the early AD (8 months) and later-AD (18 months) groups, we observed no significant differences in layer 6 neuronal properties (Additional file 1: Table S2) or intrinsic excitability (Additional file 1: Fig. S2a,c).

Together, this work replicated upregulation of cholinergic responses in layer 6 pyramidal neurons in a different AD model of a different species, and with a different method of cholinergic stimulation. This conserved property underscores the importance of understanding the receptor mechanisms.

Upregulated responses arise from a selectively increased nicotinic signal

Since we found that the AD cholinergic responses were faster and had greater amplitude than non-transgenic controls, we hypothesized that nicotinic responses underlie the genotype difference, as these ionotropic receptors impart these characteristics to the endogenous response [68, 69, 73]. To investigate pre- and post-synaptic elements in the intact prefrontal cholinergic synapses, we used the opto-TgCRND8 AD mouse model. To investigate the nicotinic receptor contribution to this upregulated opto-ACh response in AD, we pharmacologically blocked these receptors using the antagonist DHβE (3 µM) (Fig. 4a). DHβE changed the cholinergic responses in both genotypes (Fig. 4b), significantly decreasing the rise speed (paired, two-tailed t-test: t = 4.3, P = 0.0002, df = 23) and the peak amplitude (paired, two-tailed t-test: t = 3.5, P = 0.002, df = 23). However, DHβE exerted a greater effect on the AD group, yielding a significantly greater change in rising slope (Fig. 4c, unpaired two-tailed t-test, t = 2.3, P = 0.03, df = 22) and peak amplitude (Fig. 4d, unpaired two-tailed t-test, t = 2.6, P = 0.01, df = 22). These results suggest that the increased opto-ACh responses in this preclinical AD model involved a prominent upregulation in nicotinic receptor signalling.

Fig. 4
figure 4

Early cholinergic upregulation in the AD model is specific to nicotinic receptor signalling. a Schematic depicts a cholinergic synapse in the presence of nicotinic receptor antagonist DHβE. b Representative opto-ACh responses from non-transgenic (nTg) control (black) and TgCRND8 AD (grey) neurons measured in voltage clamp (Vm =  − 75 mV) before and after DHβE. c, d Graphs show that DHβE caused greater declines in rise speed (P < 0.05) (c) and peak amplitude (P < 0.05) (d) of opto-ACh currents in TgCRND8 AD responses relative to controls (age range: 4.5 to 12.2 months, mean = 7.9 ± 0.7 months, n = 14 animals, 1–3 brain slices per animal). e Schematic depicts a cholinergic synapse in the presence of broad muscarinic receptor antagonist atropine. f Representative opto-ACh responses from non-transgenic (nTg) control (black) and TgCRND8 AD (grey) neurons measured in voltage clamp before and after atropine. Graphs show that atropine elicited changes in rising speed (g) and peak amplitude (h) that were not different between TgCRND8 AD and control responses (age range: 3.1 to 12.2 months, mean = 6.4 ± 0.7 months, n = 20 animals, 1–3 brain slices per animal). i Schematic depicts a cholinergic synapse in the presence of muscarinic M2 receptor antagonist AF-DX 116. j Representative opto-ACh responses from non-transgenic (nTg) control (black) and TgCRND8 AD (grey) neurons measured in voltage clamp before and after AF-DX 116. Graphs show that AF-DX 116 elicited changes in rising speed (k) and peak amplitude (i) that were not different between TgCRND8 AD and control responses (age range: 4.2 to 12.2 months, mean = 7.8 ± 0.9 months, n = 13 animals, 1–3 brain slices per animal)

Full size image

Since G-protein coupled muscarinic receptors contribute both pre- and post-synaptically to prefrontal cholinergic synapses [68], we next evaluated whether muscarinic components of the cholinergic synapses were altered. Blocking muscarinic receptors with the broad-spectrum antagonist atropine (200 nM; Fig. 4e) increased the amplitude of cholinergic responses in both genotypes (Fig. 4f; paired two-tailed t-test: t = 7.4, P < 0.0001, df = 22), but did not change the rising slope (paired two-tailed t-test: t = 1.1, P = 0.3, df = 22). However, there was no significant genotype difference in the effect of atropine on either of these measures (rising slope: unpaired two-tailed t-test: t = 0.3, P = 0.8, df = 21; peak amplitude: unpaired two-tailed t-test: t = 0.5, P = 0.6, df = 21) (Fig. 4g, h). Consistent with our interpretation that atropine increases opto-ACh response amplitude by blocking presynaptic autoinhibition, targeted blocking of presynaptic muscarinic autoreceptors with AF-DX 116 (Fig. 4i) also increased opto-ACh responses in both AD and control (Fig. 4j). AF-DX 116 increased the opto-ACh response amplitude (paired, two-tailed t-test: t = 4.2, P = 0.005, df = 19) but did not change the rising slope (paired, two-tailed t-test: t = 1.7, P = 0.1, df = 19). There was no significant genotype difference in the effect of AF-DX 116 on either of these measures (rising slope: unpaired two-tailed t-test: t = 0.5, P = 0.7, df = 18; peak amplitude: unpaired two-tailed t-test: t = 1, P = 0.3, df = 18) (Fig. 4k, l). These findings suggest that neither pre- nor post-synaptic muscarinic receptors are substantially altered in this preclinical AD model.

Treatment strategies: acetylcholinesterase inhibition and nicotinic potentiation amplify cholinergic upregulation

To probe the impact of treatment intervention on this upregulated cholinergic signalling, we measured the effects of current standard-of-care treatment and a novel treatment strategy on the amplitude and kinetics of the opto-ACh responses of neurons in the TgCRND8 AD mice at early-to-mid and advanced disease stages.

The pro-cognitive standard-of-care treatment galantamine inhibits acetylcholinesterase (Fig. 5a), allowing acetylcholine to remain longer at the synapse. Applying galantamine to opto-ACh AD responses (Fig. 5b) showed a trend of increasing the rising speed (Fig. 5c, paired, two-tailed t-test, t = 2.3, P = 0.06, df = 7) and significantly increased the peak amplitude (Fig. 5d, paired, two-tailed t-test, t = 4.4, P = 0.003, df = 7). However, the greatest impact of galantamine was to significantly prolong the decay constant (Fig. 5e, paired two-tailed t-test, t = 3.6, P = 0.008, df = 7). This effect of galantamine was consistent between TgCRND8 mice and non-transgenic controls (Additional file 1: Fig. S3a–c) and consistent in TgCRND8 mice between early-to-mid and advanced AD stages (Additional file 1: Fig. S4a–c). Galantamine modestly increases the peak response magnitude; however, it prolongs the overall kinetics of the usually brief cholinergic response.

Fig. 5
figure 5

Galantamine and a novel nicotinic treatment strategy further enhance cholinergic upregulation in AD model. a Schematic depicts a cholinergic synapse in the presence of acetylcholinesterase inhibitor galantamine. Galantamine slowed the degradation of acetylcholine, prolonging its availability at the synapse. b Representative opto-ACh responses from a TgCRND8 AD neuron before (grey) and after galantamine (purple) treatment. c–e Graphs show that galantamine elicited no change in the rising speed (c) but significant increases in peak amplitude (P < 0.01) (d) and response duration (e), as measured by the decay constant (P < 0.01) in TgCRND8 AD responses (age range 3–6 months: mean = 5.2 ± 0.6 months, n = 5 animals, 1–3 brain slices per animal). f Schematic depicts the activation of postsynaptic nicotinic receptors by acetylcholine and the action of nicotinic positive allosteric modulator NS9283 in increasing nicotinic receptor conductance. g Representative opto-ACh responses from a TgCRND8 AD neuron before (grey) and after (blue) NS9283 treatment. h–j Graphs show that NS9283 elicited increases in rise speed (P < 0.05) (h) and peak amplitude (P < 0.001) (i) with no change in the response duration (j) (age range 3–6 months: mean = 4.7 ± 0.4 months, n = 6 animals, 1–3 brain slices per animal)

Full size image

To explore treatment interventions targeting the specific nicotinic receptor upregulation seen in this AD model, we tested the nicotinic-selective positive allosteric modulator NS9283 which enhances endogenous cholinergic signalling (Fig. 5f). We found that NS9283 greatly boosted opto-ACh AD responses (Fig. 5g), significantly increasing the rising speed (Fig. 5h; paired, two-tailed t-test, t = 2.7, P = 0.02, df = 14) and the peak amplitude (Fig. 5i; paired two-tailed t-test, t = 3.2, P = 0.007, df = 14). Strikingly, these changes occurred without changes of the decay constant (Fig. 5j; paired two-tailed t-test, t = 1.3, P = 0.2, df = 14) of the opto-ACh response. The action of NS9283 was consistent between TgCRND8 mice and non-transgenic controls (Additional file 1: Fig. S3d–f) and consistent in TgCRND8 mice between early-to-mid and late AD stages (Additional file 1: Fig. S4d–f). This intervention strongly amplified peak response magnitude while retaining the typical rapid and brief response kinetics.

The current standard-of-care treatment galantamine significantly increased response amplitude (71% ± 16%) and showed a trend of increase in rising speed (35% ± 16%), but at the cost of significant slowing of the cholinergic response (2032% ± 993%). In comparison, the nicotinic-specific NS9283 induced significant enhancement of the rising speed (210% ± 68%) and a significant increase in amplitude (249% ± 87%), and modestly but not consistently prolonged response decay (77% ± 32%). There results suggest that NS9283 incites a greater increase in response magnitude and better conserves endogenous response timing and kinetics than the broad cholinergic standard-of-care treatment. Therefore, it is possible to use a targeted treatment such as NS9283 to further enhance upregulation of this cognitively crucial signalling pathway.

Discussion

In this study, we demonstrate a functional upregulation of layer 6 prefrontal cholinergic signalling in preclinical models of AD. Cholinergic upregulation occurs during early to mid-disease progression in two species models with differing pathology trajectories. Elevated functional nicotinic signalling plays a dominant role, and the apparent compensation is sensitive to further enhancement via pharmacological manipulation. The AD treatment with acetylcholinesterase inhibition boosts the cholinergic response but slows its time course. In contrast, targeted nicotinic positive allosteric modulation exerts a strong and significant potentiation with preserved kinetics. Taken together, our results suggest a potential active mechanism of cognitive compensation and demonstrate an effective approach to amplify it and potentially extend it to the late AD stage.

Cognitive reserve and neural compensation in AD

Cognitive reserve, or the brain’s ability to sustain neurological decline while maintaining cognitive processes, is well documented clinically in aging [12, 13, 76, 77] and in AD [78, 79]. Studies have explored the neurophysiological basis for cognitive resilience in AD [15, 80] including in the prefrontal cortex [81]. In preclinical models, plasticity related to AD has been detected in cortical neuronal morphology [82,83,84,85,86,87,88,89] and in neurotransmitter signalling [90, 91], including acetylcholine neuromodulation [92]. In the TgF344 AD rat model used here, for example, parvalbumin interneuron neuroplasticity is observed at mid-pathology, with coinciding cognitive resilience in executive function and cognitive flexibility [14]. Interestingly, here we found cholinergic upregulation in layer 6 prefrontal cortex at the same mid-disease timepoint.

Prefrontal cholinergic signalling is crucial for many cognitive functions maintained by cognitive reserve, including attention, cue detection, and working memory [18,19,20, 22, 23]. The nicotinic excitation of layer 6 pyramidal neurons is thought to play a key role in attention and cue detection [21, 24]. The importance of prefrontal nicotinic signalling in successful attention [93,94,95,96] becomes evident under demanding conditions, where locally stimulating nicotinic receptors improves performance [97] and deficient prefrontal nicotinic signalling worsens performance [21, 24, 98]. These cognitive processes are timescale-dependent [99,100,101], where configurations of the fast ionotropic nicotinic receptor that include the α5 subunit lead to faster responses to endogenous acetylcholine [69] and contribute to better attentional performance [21]. The nicotinic positive allosteric modulator NS9283, which potentiates cholinergic responses while maintaining fast endogenous kinetics, improves performance on attention tasks in wild-type rodents [102, 103].

Clinically, in individuals pre-diagnosed with elevated amyloid-β (Aβ) and none/mild baseline cognitive deficits, cholinergic inhibition with scopolamine unmasks otherwise undetectable cognitive deficits that correlate with Aβ load [104]. This supports that in pre-diagnosis or early AD, cholinergic signalling may be important in compensating for pathological decline and maintaining cognitive functions. This preclinical and clinical behavioral literature, coupled with the opto-physiological data in the present study, underscores the need for future work to examine the behavioral impact of nicotinic-targeted therapeutics such as NS9283 in models of AD and, particularly, its interactions with age and stage of disease.

Cholinergic signalling and synapses in AD

Previous molecular investigations into cholinergic neurons and synapses in AD emphasize a trajectory of cholinergic decline, with decreases in both pre- and post-synaptic markers resulting in eventual heterogenous loss of cholinergic neurons in advanced AD [32, 33, 105,106,107,108,109,110,111,112,113,114,115]. However, much of this characterization was performed later in disease progression [116, 117]. Molecular and functional investigations that have been carried out in early to mid-disease mostly consist of swiftly-progressing genetic models of AD that preclude the use of littermate controls [38,39,40,41,42,43,44]. To detect and systematically investigate mechanisms of compensatory plasticity, it is essential to use a well-charted model with appropriately matched non-transgenic controls. Furthermore, functional characterisation is vital for understanding cholinergic synaptic transmission.

Here, we found upregulation of prefrontal cholinergic signalling in layer 6 that emerges after disease onset, at early to mid-disease in two different preclinical models of AD. Both the TgCRND8/ChATChR2 AD mice and the TgF344 AD rats harbor human APP mutations [48, 57], resulting in amyloid-driven AD pathologies. Aβ interacts with nicotinic receptors [118,119,120,121,122,123,124,125], the consequences of which depend on cell type and nicotinic receptor configuration. Nicotinic receptors are regulated by many cellular elements, including lynx family proteins [73, 126] and protein kinase C by way of muscarinic receptor agonism [68], providing many potential avenues for signalling to be harnessed for compensation. Our use of models with non-transgenic littermate controls revealed an upregulation of nicotinic signalling in early to mid-AD that did not continue to increase in later-AD. Strengths of our electrophysiological and opto-physiological approaches include functional insight into cholinergic signalling upregulation and identification of this upregulation as specific to nicotinic receptors.

A caveat for our work is its limitation to layer 6 pyramidal neurons. While this neuronal population has prominent expression of nicotinic receptors and their regulatory lynx prototoxins [73] and plays a key role in attention [21, 24, 98], processes of cognitive reserve likely also require the involvement of neurons in other prefrontal layers. It will be important for future work to specifically target the impact of endogenous cholinergic responses on additional neurophysiological processes beyond those involved in attention.

Translational and clinical impact

Deficits in attention and executive function have consequences for other cognitive domains: if you cannot attend, you cannot encode [127]. It is therefore important to identify mechanisms through which we can improve attention and extend the maintenance of this cognitive domain as much as possible throughout AD progression. Nicotinic signalling has long been a target for enhancing cognition, including in AD [128, 129]. Direct stimulation of nicotinic receptors is pro-cognitive in AD [27], potentially protective against Aβ [130, 131] but complicated by desensitization [132,133,134]. Nicotinic positive allosteric modulators, such as NS9283 used here, present less risk of desensitization [135], and are pro-cognitive preclinically [102, 103]. Our results suggest that nicotinic positive allosteric modulation further enhances nicotinic signalling upregulation in AD.

Attention and cue-detection are mediated by cholinergic, and specifically nicotinic stimulation of the prefrontal cortex [19, 20, 93,94,95,96, 136] and depend on fast ionotropic receptor kinetics [21, 69]. Acetylcholinesterase inhibitor, a current and long-used AD treatment, enhances all cholinergic signaling: fast, ionotropic nicotinic signal and slower, longer-lasting metabotropic muscarinic signal shown above (Fig. 5) and previously [68, 69]. While acetylcholinesterase inhibitor imparts some increase in response amplitude, it profoundly slows response decay. Treatments that maintain the endogenous timing of responses, such as NS9283 that increases the pro-attentional rise kinetics, largely amplifies response magnitude, and does not alter decay, might better enhance time-sensitive cognitive functions.

Understanding neural compensation and neurological changes at different disease stages is important for understanding the implications of clinical interventions. Different levels of effectiveness of novel AD treatments may result from timing of intervention and the level of neurological changes already set in motion by AD. Adaptations that are pro-cognitive in the presence of AD may have altered outcomes if pathology is resolved. Therefore, it is important to take neurological changes into account when determining treatment strategies.

Conclusion

Overall, we uncover evidence for cholinergic compensation in two preclinical models of AD. In both models, functional upregulation in prefrontal cholinergic signalling occurs in early to mid-AD. Mechanistic investigation reveals increased nicotinic signalling, which is amenable to further upregulation, both by acetylcholinesterase inhibitor and by nicotinic positive allosteric modulation. While the scope of benefit across cognitive domains requires investigation, harnessing compensatory nicotinic upregulation may be an important treatment strategy to further enhance and preserve cognition in AD.

Availability of data and materials

The datasets generated during and/or analysed during the current study are not publicly available due to agency over intellectual property but are available from the corresponding author on reasonable request.

Abbreviations

ACh:

Acetylcholine

AD:

Alzheimer’s disease

AT:

Atropine

ChAT:

Choline acetyl transferase

ChR2:

Channelrhodopsin

DHβE:

Dihydro-β-erythroidine

Gal:

Galantamine

Opto-ACh:

Optogenetic release of acetylcholine

References

  1. Stern Y. Cognitive reserve in ageing and Alzheimer’s disease. Lancet Neurol. 2012;11:1006–12.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Valenzuela MJ, Sachdev P. Brain reserve and dementia: a systematic review. Psychol Med. 2006;36:441–54.

    Article  PubMed  Google Scholar 

  3. Stern Y, Gurland B, Tatemichi TK, Tang MX, Wilder D, Mayeux R. Influence of education and occupation on the incidence of Alzheimer’s disease. JAMA. 1994;271:1004–10.

    Article  CAS  PubMed  Google Scholar 

  4. Scarmeas N, Levy G, Tang M-X, Manly J, Stern Y. Influence of leisure activity on the incidence of Alzheimer’s disease. Neurology. 2001;57:2236–42.

    Article  CAS  PubMed  Google Scholar 

  5. Stern Y, Alexander GE, Prohovnik I, Mayeux R. Inverse relationship between education and parietotemporal perfusion deficit in Alzheimer’s disease. Ann Neurol. 1992;32:371–5.

    Article  CAS  PubMed  Google Scholar 

  6. Stern Y, Alexander GE, Prohovnik I, Stricks L, Link B, Lennon MC, Mayeux R. Relationship between lifetime occupation and parietal flow: implications for a reserve against Alzheimer’s disease pathology. Neurology. 1995;45:55–60.

    Article  CAS  PubMed  Google Scholar 

  7. Scarmeas N, Zarahn E, Anderson KE, Habeck CG, Hilton J, Flynn J, et al. Association of life activities with cerebral blood flow in Alzheimer disease. Arch Neurol. 2003;60:359–65.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Alexander GE, Furey ML, Grady CL, Pietrini P, Brady DR, Mentis MJ, et al. Association of premorbid intellectual function with cerebral metabolism in Alzheimer’s disease: implications for the cognitive reserve hypothesis. Am J Psychiatry. 1997;154:165–72.

    Article  CAS  PubMed  Google Scholar 

  9. Perneczky R, Drzezga A, Diehl-Schmid J, Schmid G, Wohlschläger A, Kars S, et al. Schooling mediates brain reserve in Alzheimer’s disease: findings of fluoro-deoxy-glucose-positron emission tomography. J Neurol Neurosurg Psychiatry. 2006;77:1060–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Roe CM, Xiong C, Miller JP, Morris JC. Education and Alzheimer disease without dementia: support for the cognitive reserve hypothesis. Neurology. 2007;68:223–8.

    Article  PubMed  Google Scholar 

  11. Groot C, van Loenhoud AC, Barkhof F, van Berckel BNM, Koene T, Teunissen CC, et al. Differential effects of cognitive reserve and brain reserve on cognition in Alzheimer disease. Neurology. 2018;90:e149–56.

    Article  PubMed  Google Scholar 

  12. Morcom AM, Johnson W. Neural reorganization and compensation in aging. J Cogn Neurosci. 2015;27:1275–85.

    Article  PubMed  Google Scholar 

  13. Stern Y. What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc JINS. 2002;8:448–60.

    Article  PubMed  Google Scholar 

  14. Morrone CD, Lai AY, Bishay J, Hill ME, McLaurin J. Parvalbumin neuroplasticity compensates for somatostatin impairment, maintaining cognitive function in Alzheimer’s disease. Transl Neurodegener. 2022;11:26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bhembre N, Bonthron C, Opazo P. Synaptic compensatory plasticity in Alzheimer’s disease. J Neurosci. 2023;43:6833–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Dumas JA, Newhouse PA. The cholinergic hypothesis of cognitive aging revisited again: cholinergic functional compensation. Pharmacol Biochem Behav. 2011;99:254–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Berry AS, Harrison TM. New perspectives on the basal forebrain cholinergic system in Alzheimer’s disease. Neurosci Biobehav Rev. 2023;150:105192.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Dalley JW, Theobald DE, Bouger P, Chudasama Y, Cardinal RN, Robbins TW. Cortical cholinergic function and deficits in visual attentional performance in rats following 192 IgG-saporin-induced lesions of the medial prefrontal cortex. Cereb Cortex. 2004;14:922–32.

    Article  PubMed  Google Scholar 

  19. Gritton HJ, Howe WM, Mallory CS, Hetrick VL, Berke JD, Sarter M. Cortical cholinergic signaling controls the detection of cues. Proc Natl Acad Sci. 2016;113:E1089–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Howe WM, Gritton HJ, Lusk NA, Roberts EA, Hetrick VL, Berke JD, et al. Acetylcholine release in prefrontal cortex promotes gamma oscillations and theta–gamma coupling during cue detection. J Neurosci. 2017;37:3215–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bailey CDC, De Biasi M, Fletcher PJ, Lambe EK. The nicotinic acetylcholine receptor α5 subunit plays a key role in attention circuitry and accuracy. J Neurosci. 2010;30:9241–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Guo W, Robert B, Polley DB. The cholinergic basal forebrain links auditory stimuli with delayed reinforcement to support learning. Neuron. 2019;103:1164-1177.e6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Tu G, Halawa A, Yu X, Gillman S, Takehara-Nishiuchi K. Outcome-locked cholinergic signaling suppresses prefrontal encoding of stimulus associations. J Neurosci. 2022;42:4202–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Guillem K, Bloem B, Poorthuis RB, Loos M, Smit AB, Maskos U, et al. Nicotinic acetylcholine receptor β2 subunits in the medial prefrontal cortex control attention. Science. 2011;333:888–91.

    Article  CAS  PubMed  Google Scholar 

  25. Dong H, Csernansky CA, Martin MV, Bertchume A, Vallera D, Csernansky JG. Acetylcholinesterase inhibitors ameliorate behavioral deficits in the Tg2576 mouse model of Alzheimer’s disease. Psychopharmacology. 2005;181:145–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Nagakura A, Shitaka Y, Yarimizu J, Matsuoka N. Characterization of cognitive deficits in a transgenic mouse model of Alzheimer’s disease and effects of donepezil and memantine. Eur J Pharmacol. 2013;703:53–61.

    Article  CAS  PubMed  Google Scholar 

  27. Nie H, Wang Z, Zhao W, Lu J, Zhang C, Lok K, et al. New nicotinic analogue ZY-1 enhances cognitive functions in a transgenic mice model of Alzheimer’s disease. Neurosci Lett. 2013;537:29–34.

    Article  CAS  PubMed  Google Scholar 

  28. Salloway S, Ferris S, Kluger A, Goldman R, Griesing T, Kumar D, et al. Efficacy of donepezil in mild cognitive impairment: a randomized placebo-controlled trial. Neurology. 2004;63:651–7.

    Article  CAS  PubMed  Google Scholar 

  29. Doody RS, Ferris SH, Salloway S, Sun Y, Goldman R, Watkins WE, et al. Donepezil treatment of patients with MCI: a 48-week randomized, placebo-controlled trial. Neurology. 2009;72:1555–61.

    Article  CAS  PubMed  Google Scholar 

  30. Geula C, Mesulam MM. Cholinesterases and the pathology of Alzheimer disease. Alzheimer Dis Assoc Disord. 1995;9:23–8.

    Article  PubMed  Google Scholar 

  31. Tan CC, Yu JT, Wang HF, Tan MS, Meng XF, Wang C, et al. Efficacy and safety of donepezil, galantamine, rivastigmine, and memantine for the treatment of Alzheimer’s disease: a systematic review and meta-analysis. J Alzheimers Dis. 2014;41:615–31.

    Article  CAS  PubMed  Google Scholar 

  32. Teipel SJ, Dyrba M, Ballarini T, Brosseron F, Bruno D, Buerger K, et al. Association of cholinergic basal forebrain volume and functional connectivity with markers of inflammatory response in the Alzheimer’s disease spectrum. J Alzheimers Dis. 2022;85:1267–82.

    Article  CAS  PubMed  Google Scholar 

  33. Aghourian M, Legault-Denis C, Soucy J-P, Rosa-Neto P, Gauthier S, Kostikov A, et al. Quantification of brain cholinergic denervation in Alzheimer’s disease using PET imaging with [18F]-FEOBV. Mol Psychiatry. 2017;22:1531–8.

    Article  CAS  PubMed  Google Scholar 

  34. Burghaus L, Schütz U, Krempel U, de Vos RA, Jansen Steur EN, Wevers A, et al. Quantitative assessment of nicotinic acetylcholine receptor proteins in the cerebral cortex of Alzheimer patients. Brain Res Mol Brain Res. 2000;76:385–8.

    Article  CAS  PubMed  Google Scholar 

  35. Xhima K, Markham-Coultes K, Nedev H, Heinen S, Saragovi HU, Hynynen K, et al. Focused ultrasound delivery of a selective TrkA agonist rescues cholinergic function in a mouse model of Alzheimer’s disease. Sci Adv. 2020;6:eaax6646.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Liu W, Li J, Yang M, Ke X, Dai Y, Lin H, et al. Chemical genetic activation of the cholinergic basal forebrain hippocampal circuit rescues memory loss in Alzheimer’s disease. Alzheimers Res Ther. 2022;14:53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. McKeever PM, Kim T, Hesketh AR, MacNair L, Miletic D, Favrin G, et al. Cholinergic neuron gene expression differences captured by translational profiling in a mouse model of Alzheimer’s disease. Neurobiol Aging. 2017;57:104–19.

    Article  CAS  PubMed  Google Scholar 

  38. Choi H-J, Park J-H, Jeong YJ, Hwang J-W, Lee S, Lee H, et al. Donepezil ameliorates Aβ pathology but not tau pathology in 5xFAD mice. Mol Brain. 2022;15:63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Na D, Zhang J, Beaulac HJ, Piekna-Przybylska D, Nicklas PR, Kiernan AE, et al. Increased central auditory gain in 5xFAD Alzheimer’s disease mice as an early biomarker candidate for Alzheimer’s disease diagnosis. Front Neurosci. 2023;17:1106570.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Oddo S, Caccamo A, Shepherd JD, Murphy MP, Golde TE, Kayed R, et al. Triple-transgenic model of Alzheimer’s disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron. 2003;39:409–21.

    Article  CAS  PubMed  Google Scholar 

  41. Oakley H, Cole SL, Logan S, Maus E, Shao P, Craft J, et al. Intraneuronal β-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J Neurosci. 2006;26:10129–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Chen C, Wei J, Ma X, Xia B, Shakir N, Zhang JK, et al. Disrupted maturation of prefrontal layer 5 neuronal circuits in an Alzheimer’s mouse model of amyloid deposition. Neurosci Bull. 2022;39:881–892.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Chakroborty S, Kim J, Schneider C, Jacobson C, Molgó J, Stutzmann GE. Early presynaptic and postsynaptic calcium signaling abnormalities mask underlying synaptic depression in presymptomatic Alzheimer’s disease mice. J Neurosci. 2012;32:8341–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Stutzmann GE, Smith I, Caccamo A, Oddo S, Laferla FM, Parker I. Enhanced ryanodine receptor recruitment contributes to Ca2+ disruptions in young, adult, and aged Alzheimer’s disease mice. J Neurosci. 2006;26:5180–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Falangola MF, Nie X, Ward R, Dhiman S, Voltin J, Nietert PJ, et al. Diffusion MRI detects basal forebrain cholinergic abnormalities in the 3xTg-AD mouse model of Alzheimer’s disease. Magn Reson Imaging. 2021;83:1–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. McNerney MW, Heath A, Narayanan SK, Yesavage J. Repetitive transcranial magnetic stimulation improves brain-derived neurotrophic factor and cholinergic signaling in the 3xTgAD mouse model of Alzheimer’s disease. J Alzheimers Dis. 2022;86:499–507.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Perez SE, He B, Muhammad N, Oh K-J, Fahnestock M, Ikonomovic MD, et al. Cholinotrophic basal forebrain system alterations in 3xTg-AD transgenic mice. Neurobiol Dis. 2011;41:338–52.

    Article  CAS  PubMed  Google Scholar 

  48. Chishti MA, Yang DS, Janus C, Phinney AL, Horne P, Pearson J, et al. Early-onset amyloid deposition and cognitive deficits in transgenic mice expressing a double mutant form of amyloid precursor protein 695. J Biol Chem. 2001;276:21562–70.

    Article  CAS  PubMed  Google Scholar 

  49. Zhao S, Ting JT, Atallah HE, Qiu L, Tan J, Gloss B, et al. Cell-type specific optogenetic mice for dissecting neural circuitry function. Nat Methods. 2011;8:745–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Sparks DW, Tian MK, Sargin D, Venkatesan S, Intson K, Lambe EK. Opposing cholinergic and serotonergic modulation of layer 6 in prefrontal cortex. Front Neural Circuits. 2017;11:107.

    Article  PubMed  Google Scholar 

  51. Nasirova N, Quina LA, Agosto-Marlin IM, Ramirez J-M, Lambe EK, Turner EE. Dual recombinase fate mapping reveals a transient cholinergic phenotype in multiple populations of developing glutamatergic neurons. J Comp Neurol. 2020;528:283–307.

    Article  CAS  PubMed  Google Scholar 

  52. Romberg C, Horner AE, Bussey TJ, Saksida LM. A touch screen-automated cognitive test battery reveals impaired attention, memory abnormalities, and increased response inhibition in the TgCRND8 mouse model of Alzheimer’s disease. Neurobiol Aging. 2013;34:731–44.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Walker JM, Fowler SW, Miller DK, Sun AY, Weisman GA, Wood WG, et al. Spatial learning and memory impairment and increased locomotion in a transgenic amyloid precursor protein mouse model of Alzheimer’s disease. Behav Brain Res. 2011;222:169–75.

    Article  CAS  PubMed  Google Scholar 

  54. Steele JW, Brautigam H, Short JA, Sowa A, Shi M, Yadav A, et al. Early fear memory defects are associated with altered synaptic plasticity and molecular architecture in the TgCRND8 Alzheimer’s disease mouse model. J Comp Neurol. 2014;522:2319–35.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Hanna A, Iremonger K, Das P, Dickson D, Golde T, Janus C. Age-related increase in amyloid plaque burden is associated with impairment in conditioned fear memory in CRND8 mouse model of amyloidosis. Alzheimers Res Ther. 2012;4:21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ambrée O, Touma C, Görtz N, Keyvani K, Paulus W, Palme R, et al. Activity changes and marked stereotypic behavior precede Aβ pathology in TgCRND8 Alzheimer mice. Neurobiol Aging. 2006;27:955–64.

    Article  PubMed  Google Scholar 

  57. Cohen RM, Rezai-Zadeh K, Weitz TM, Rentsendorj A, Gate D, Spivak I, et al. A transgenic Alzheimer rat with plaques, tau pathology, behavioral impairment, oligomeric aβ, and frank neuronal loss. J Neurosci. 2013;33:6245–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Saré RM, Cooke SK, Krych L, Zerfas PM, Cohen RM, Smith CB. Behavioral phenotype in the TgF344-AD rat model of Alzheimer’s disease. Front Neurosci. 2020;14:601.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Pentkowski NS, Berkowitz LE, Thompson SM, Drake EN, Olguin CR, Clark BJ. Anxiety-like behavior as an early endophenotype in the TgF344-AD rat model of Alzheimer’s disease. Neurobiol Aging. 2018;61:169–76.

    Article  CAS  PubMed  Google Scholar 

  60. Joo IL, Lai AY, Bazzigaluppi P, Koletar MM, Dorr A, Brown ME, et al. Early neurovascular dysfunction in a transgenic rat model of Alzheimer’s disease. Sci Rep. 2017;7.

  61. Morrone CD, Bazzigaluppi P, Beckett TL, Hill ME, Koletar MM, Stefanovic B, et al. Regional differences in Alzheimer’s disease pathology confound behavioural rescue after amyloid-β attenuation. Brain. 2020;143:359–73.

    Article  PubMed  Google Scholar 

  62. Brannigan G, LeBard DN, Hénin J, Eckenhoff RG, Klein ML. Multiple binding sites for the general anesthetic isoflurane identified in the nicotinic acetylcholine receptor transmembrane domain. Proc Natl Acad Sci. 2010;107:14122–7.

  63. Coates KM, Flood P. Ketamine and its preservative, benzethonium chloride, both inhibit human recombinant α7 and α4β2 neuronal nicotinic acetylcholine receptors in Xenopus oocytes. Br J Pharmacol. 2001;134:871–9.

  64. Downie DL, Franks NP, Lieb WR. Effects of thiopental and its optical isomers on nicotinic acetylcholine receptors. Anesthesiology. 2000;93:774–83.

  65. Kamiya Y, Andoh T, Watanabe I, Higashi T, Itoh H. Inhibitory effects of barbiturates on nicotinic acetylcholine receptors in rat central nervous system neurons. Anesthesiology. 2001;94:694–704.

  66. Scheller M, Bufler J, Schneck H, Kochs E, Franke C. Isoflurane and sevoflurane interact with the nicotinic acetylcholine receptor channels in micromolar concentrations. Anesthesiology. 1997;86:118–27.

  67. Scheller M, Bufler J, Hertle I, Schneck HJ, Franke C, Kochs E. Ketamine blocks currents through mammalian nicotinic acetylcholine receptor channels by interaction with both the open and the closed state. Anesth Analg. 1996;83:830–6.

  68. Power SK, Venkatesan S, Lambe EK. Xanomeline restores endogenous nicotinic acetylcholine receptor signaling in mouse prefrontal cortex. Neuropsychopharmacology. 2023;48:671–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Venkatesan S, Lambe EK. Chrna5 is essential for a rapid and protected response to optogenetic release of endogenous acetylcholine in prefrontal cortex. J Neurosci. 2020;40:7255–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Laszlovszky T, Schlingloff D, Hegedüs P, Freund TF, Gulyás A, Kepecs A, et al. Distinct synchronization, cortical coupling and behavioral function of two basal forebrain cholinergic neuron types. Nat Neurosci. 2020;23:992–1003.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Unal CT, Golowasch JP, Zaborszky L. Adult mouse basal forebrain harbors two distinct cholinergic populations defined by their electrophysiology. Front Behav Neurosci. 2012;6:21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Lee MG, Hassani OK, Alonso A, Jones BE. Cholinergic basal forebrain neurons burst with theta during waking and paradoxical sleep. J Neurosci. 2005;25:4365–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Venkatesan S, Chen T, Liu Y, Turner EE, Tripathy SJ, Lambe EK. Chrna5 and lynx prototoxins identify acetylcholine super-responder subplate neurons. iScience. 2023;26:105992.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Venkatesan S, Jeoung H-S, Chen T, Power SK, Liu Y, Lambe EK. Endogenous acetylcholine and its modulation of cortical microcircuits to enhance cognition. Curr Top Behav Neurosci. 2020;45:47–69.

    Article  CAS  PubMed  Google Scholar 

  75. Poorthuis RB, Bloem B, Schak B, Wester J, de Kock CPJ, Mansvelder HD. Layer-specific modulation of the prefrontal cortex by nicotinic acetylcholine receptors. Cereb Cortex. 2013;23:148–61.

    Article  PubMed  Google Scholar 

  76. Cabeza R, Anderson ND, Locantore JK, McIntosh AR. Aging gracefully: compensatory brain activity in high-performing older adults. Neuroimage. 2002;17:1394–402.

    Article  PubMed  Google Scholar 

  77. Cabeza R. Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychol Aging. 2002;17:85–100.

    Article  PubMed  Google Scholar 

  78. Morbelli S, Perneczky R, Drzezga A, Frisoni GB, Caroli A, van Berckel BNM, et al. Metabolic networks underlying cognitive reserve in prodromal Alzheimer disease: a European Alzheimer disease consortium project. J Nucl Med. 2013;54:894–902.

    Article  CAS  PubMed  Google Scholar 

  79. Menardi A, Pascual-Leone A, Fried PJ, Santarnecchi E. The role of cognitive reserve in Alzheimer’s disease and aging: a multi-modal imaging review. J Alzheimers Dis. 2018;66:1341–62.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Arenaza-Urquijo EM, Vemuri P. Resistance vs resilience to Alzheimer disease. Neurology. 2018;90:695–703.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Mathys H, Peng Z, Boix CA, Victor MB, Leary N, Babu S, et al. Single-cell atlas reveals correlates of high cognitive function, dementia, and resilience to Alzheimer’s disease pathology. Cell. 2023;186:4365-4385.e27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Alonso-Nanclares L, Merino-Serrais P, Gonzalez S, DeFelipe J. Synaptic changes in the dentate gyrus of APP/PS1 transgenic mice revealed by electron microscopy. J Neuropathol Exp Neurol. 2013;72:386–95.

    Article  CAS  PubMed  Google Scholar 

  83. Androuin A, Potier B, Nägerl UV, Cattaert D, Danglot L, Thierry M, et al. Evidence for altered dendritic spine compartmentalization in Alzheimer’s disease and functional effects in a mouse model. Acta Neuropathol (Berl). 2018;135:839–54.

    Article  CAS  PubMed  Google Scholar 

  84. da Silva SV, Haberl MG, Zhang P, Bethge P, Lemos C, Gonçalves N, et al. Early synaptic deficits in the APP/PS1 mouse model of Alzheimer’s disease involve neuronal adenosine A2A receptors. Nat Commun. 2016;7:11915.

    Article  Google Scholar 

  85. Neuman KM, Molina-Campos E, Musial TF, Price AL, Oh K-J, Wolke ML, et al. Evidence for Alzheimer’s disease-linked synapse loss and compensation in mouse and human hippocampal CA1 pyramidal neurons. Brain Struct Funct. 2015;220:3143–65.

    Article  CAS  PubMed  Google Scholar 

  86. Heiss JK, Barrett J, Yu Z, Haas LT, Kostylev MA, Strittmatter SM. Early activation of experience-independent dendritic spine turnover in a mouse model of Alzheimer’s disease. Cereb Cortex. 2017;27:3660–74.

    PubMed  Google Scholar 

  87. Tosh JL, Rickman M, Rhymes E, Norona FE, Clayton E, Mucke L, et al. The integration site of the APP transgene in the J20 mouse model of Alzheimer’s disease. Wellcome Open Res. 2018;2:84.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Stephen T-L, Tamagnini F, Piegsa J, Sung K, Harvey J, Oliver-Evans A, et al. Imbalance in the response of pre- and post-synaptic components to amyloidopathy. Sci Rep. 2019;9:14837.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Jackson JS, Witton J, Johnson JD, Ahmed Z, Ward M, Randall AD, et al. Altered synapse stability in the early stages of tauopathy. Cell Rep. 2017;18:3063–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Palop JJ, Chin J, Roberson ED, Wang J, Thwin MT, Bien-Ly N, et al. Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer’s disease. Neuron. 2007;55:697–711.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Iwakiri M, Mizukami K, Ikonomovic MD, Ishikawa M, Hidaka S, Abrahamson EE, et al. Changes in hippocampal GABABR1 subunit expression in Alzheimer’s patients: association with Braak staging. Acta Neuropathol (Berl). 2005;109:467–74.

    Article  CAS  PubMed  Google Scholar 

  92. Allard S, Shuler MGH. Cholinergic reinforcement signaling is impaired by amyloidosis prior to its synaptic loss. J Neurosci. 2023;43:6988–7005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Parikh V, Kozak R, Martinez V, Sarter M. Prefrontal acetylcholine release controls cue detection on multiple time scales. Neuron. 2007;56:141–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Hahn B, Shoaib M, Stolerman IP. Nicotine-induced enhancement of attention in the five-choice serial reaction time task: the influence of task demands. Psychopharmacology. 2002;162:129–37.

    Article  CAS  PubMed  Google Scholar 

  95. Hahn B, Shoaib M, Stolerman IP. Involvement of the prefrontal cortex but not the dorsal hippocampus in the attention-enhancing effects of nicotine in rats. Psychopharmacology. 2003;168:271–9.

    Article  CAS  PubMed  Google Scholar 

  96. Hahn B. Cross-species evidence that nicotine widens the attentional window. Psychopharmacology. 2021;238:3559–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Lambe EK, Olausson P, Horst NK, Taylor JR, Aghajanian GK. Hypocretin and nicotine excite the same thalamocortical synapses in prefrontal cortex: correlation with improved attention in rat. J Neurosci. 2005;25:5225–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Howe WM, Brooks JL, Tierney PL, Pang J, Rossi A, Young D, et al. α5 nAChR modulation of the prefrontal cortex makes attention resilient. Brain Struct Funct. 2018;223:1035–47.

    Article  CAS  PubMed  Google Scholar 

  99. Sarter M, Lustig C. Cholinergic double duty: cue detection and attentional control. Curr Opin Psychol. 2019;29:102–7.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Paolone G, Lee TM, Sarter M. Time to pay attention: attentional performance time-stamped prefrontal cholinergic activation, diurnality, and performance. J Neurosci. 2012;32:12115–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Meck WH. Neuropharmacology of timing and time perception. Brain Res Cogn Brain Res. 1996;3:227–42.

    Article  CAS  PubMed  Google Scholar 

  102. Grupe M, Grunnet M, Laursen B, Bastlund JF. Neuropharmacological modulation of the P3-like event-related potential in a rat two-tone auditory discrimination task with modafinil and NS9283, a positive allosteric modulator of α4β2 nAChRs. Neuropharmacology. 2014;79:444–55.

    Article  CAS  PubMed  Google Scholar 

  103. Timmermann D, Sandager-Nielsen K, Dyhring T, Smith M, Jacobsen A-M, Nielsen E, et al. Augmentation of cognitive function by NS9283, a stoichiometry-dependent positive allosteric modulator of α2- and α4-containing nicotinic acetylcholine receptors. Br J Pharmacol. 2012;167:164–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Lim YY, Maruff P, Schindler R, Ott BR, Salloway S, Yoo DC, et al. Disruption of cholinergic neurotransmission exacerbates Aβ-related cognitive impairment in preclinical Alzheimer’s disease. Neurobiol Aging. 2015;36:2709–15.

    Article  CAS  PubMed  Google Scholar 

  105. Bowen DM, Smith CB, White P, Davison AN. Neurotransmitter-related enzymes and indices of hypoxia in senile dementia and other abiotrophies. Brain J Neurol. 1976;99:459–96.

    Article  CAS  Google Scholar 

  106. Davies P, Maloney AJ. Selective loss of central cholinergic neurons in Alzheimer’s disease. Lancet Lond Engl. 1976;2:1403.

    Article  CAS  Google Scholar 

  107. Nordberg A, Alafuzoff I, Winblad B. Nicotinic and muscarinic subtypes in the human brain: changes with aging and dementia. J Neurosci Res. 1992;31:103–11.

    Article  CAS  PubMed  Google Scholar 

  108. Schröder H, Giacobini E, Struble RG, Zilles K, Maelicke A. Nicotinic cholinoceptive neurons of the frontal cortex are reduced in Alzheimer’s disease. Neurobiol Aging. 1991;12:259–62.

    Article  PubMed  Google Scholar 

  109. Court J, Martin-Ruiz C, Piggott M, Spurden D, Griffiths M, Perry E. Nicotinic receptor abnormalities in Alzheimer’s disease. Biol Psychiatry. 2001;49:175–84.

    Article  CAS  PubMed  Google Scholar 

  110. Teipel SJ, Cavedo E, Hampel H, Grothe MJ. Alzheimer’s Disease Neuroimaging Initiative, Alzheimer Precision Medicine Initiative (APMI). Basal forebrain volume, but not hippocampal volume, is a predictor of global cognitive decline in patients with Alzheimer’s disease treated with cholinesterase inhibitors. Front Neurol. 2018;9:642.

    Article  PubMed  PubMed Central  Google Scholar 

  111. Sassin I, Schultz C, Thal DR, Rüb U, Arai K, Braak E, et al. Evolution of Alzheimer’s disease-related cytoskeletal changes in the basal nucleus of Meynert. Acta Neuropathol (Berl). 2000;100:259–69.

    Article  CAS  PubMed  Google Scholar 

  112. Araujo DM, Lapchak PA, Robitaille Y, Gauthier S, Quirion R. Differential alteration of various cholinergic markers in cortical and subcortical regions of human brain in Alzheimer’s disease. J Neurochem. 1988;50:1914–23.

    Article  CAS  PubMed  Google Scholar 

  113. Cowburn RF, Wiehager B, Ravid R, Winblad B. Acetylcholine muscarinic M2 receptor stimulated [35S]GTP gamma S binding shows regional selective changes in Alzheimer’s disease postmortem brain. Neurodegeneration. 1996;5:19–26.

    Article  CAS  PubMed  Google Scholar 

  114. Nizari S, Carare RO, Romero IA, Hawkes CA. 3D reconstruction of the neurovascular unit reveals differential loss of cholinergic innervation in the cortex and hippocampus of the adult mouse brain. Front Aging Neurosci. 2019;11:172.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Nizari S, Wells JA, Carare RO, Romero IA, Hawkes CA. Loss of cholinergic innervation differentially affects eNOS-mediated blood flow, drainage of Aβ and cerebral amyloid angiopathy in the cortex and hippocampus of adult mice. Acta Neuropathol Commun. 2021;9:12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Tiraboschi P, Hansen LA, Alford M, Masliah E, Thal LJ, Corey-Bloom J. The decline in synapses and cholinergic activity is asynchronous in Alzheimer’s disease. Neurology. 2000;55:1278–83.

    Article  CAS  PubMed  Google Scholar 

  117. Davis KL, Mohs RC, Marin D, Purohit DP, Perl DP, Lantz M, et al. Cholinergic markers in elderly patients with early signs of Alzheimer disease. JAMA. 1999;281:1401–6.

    Article  CAS  PubMed  Google Scholar 

  118. Dineley KT. Beta-amyloid peptide–nicotinic acetylcholine receptor interaction: the two faces of health and disease. Front Biosci J Virtual Libr. 2007;12:5030–8.

    Article  CAS  Google Scholar 

  119. Arora K, Belcaid M, Lantz MJ, Taketa R, Nichols RA. Transcriptome profile of nicotinic receptor-linked sensitization of beta amyloid neurotoxicity. Sci Rep. 2020;10:5696.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Lamb PW, Melton MA, Yakel JL. Inhibition of neuronal nicotinic acetylcholine receptor channels expressed in Xenopus oocytes by beta-amyloid1-42 peptide. J Mol Neurosci MN. 2005;27:13–21.

    Article  CAS  PubMed  Google Scholar 

  121. Pandya A, Yakel JL. Allosteric modulator Desformylflustrabromine relieves the inhibition of α2β2 and α4β2 nicotinic acetylcholine receptors by β-amyloid(1–42) peptide. J Mol Neurosci MN. 2011;45:42–7.

    Article  CAS  PubMed  Google Scholar 

  122. Jürgensen S, Ferreira ST. Nicotinic receptors, amyloid-β, and synaptic failure in Alzheimer’s disease. J Mol Neurosci. 2010;40:221–9.

    Article  PubMed  Google Scholar 

  123. Magdesian MH, Nery AA, Martins AHB, Juliano MA, Juliano L, Ulrich H, et al. Peptide blockers of the inhibition of neuronal nicotinic acetylcholine receptors by amyloid beta. J Biol Chem. 2005;280:31085–90.

    Article  CAS  PubMed  Google Scholar 

  124. Rybnicek J, Chen Y, Milic M, Tio ES, McLaurin J, Hohman TJ, et al. CHRNA5 links chandelier cells to severity of amyloid pathology in aging and Alzheimer’s disease. Transl Psychiatry. 2024;14:83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Oz M, Lorke DE, Yang K-HS, Petroianu G. On the interaction of β-amyloid peptides and α7-nicotinic acetylcholine receptors in Alzheimer’s disease. Curr Alzheimer Res. 2013;10:618–30.

    Article  CAS  PubMed  Google Scholar 

  126. Tekinay AB, Nong Y, Miwa JM, Lieberam I, Ibanez-Tallon I, Greengard P, et al. A role for LYNX2 in anxiety-related behavior. Proc Natl Acad Sci U S A. 2009;106:4477–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Romberg C, Bussey TJ, Saksida LM. Paying more attention to attention: towards more comprehensive cognitive translation using mouse models of Alzheimer’s disease. Brain Res Bull. 2013;92:49–55.

    Article  PubMed  Google Scholar 

  128. Levin ED, McClernon FJ, Rezvani AH. Nicotinic effects on cognitive function: behavioral characterization, pharmacological specification, and anatomic localization. Psychopharmacology. 2006;184:523–39.

    Article  CAS  PubMed  Google Scholar 

  129. Haydar SN, Dunlop J. Neuronal nicotinic acetylcholine receptors - targets for the development of drugs to treat cognitive impairment associated with schizophrenia and Alzheimer’s disease. Curr Top Med Chem. 2010;10:144–52.

    Article  CAS  PubMed  Google Scholar 

  130. Kihara T, Shimohama S, Sawada H, Kimura J, Kume T, Kochiyama H, et al. Nicotinic receptor stimulation protects neurons against β-amyloid toxicity. Ann Neurol. 1997;42:159–63.

    Article  CAS  PubMed  Google Scholar 

  131. Stevens TR, Krueger SR, Fitzsimonds RM, Picciotto MR. Neuroprotection by nicotine in mouse primary cortical cultures involves activation of calcineurin and L-type calcium channel inactivation. J Neurosci. 2003;23:10093–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Wang H, Sun X. Desensitized nicotinic receptors in brain. Brain Res Brain Res Rev. 2005;48:420–37.

    Article  CAS  PubMed  Google Scholar 

  133. Picciotto MR, Addy NA, Mineur YS, Brunzell DH. It’s not “either/or”: activation and desensitization of nicotinic acetylcholine receptors both contribute to behaviors related to nicotine addiction and mood. Prog Neurobiol. 2008;84:329–42.

    Article  CAS  PubMed  Google Scholar 

  134. Henderson BJ, Lester HA. Inside-out neuropharmacology of nicotinic drugs. Neuropharmacology. 2015;96:178–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Williams DK, Wang J, Papke RL. Positive allosteric modulators as an approach to nicotinic acetylcholine receptor- targeted therapeutics: advantages and limitations. Biochem Pharmacol. 2011;82:915–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Himmelheber AM, Sarter M, Bruno JP. Increases in cortical acetylcholine release during sustained attention performance in rats. Brain Res Cogn Brain Res. 2000;9:313–25.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank Janice McNabb and Yao-Fang Tan for expert technical assistance, and Madeleine Ridgeway for optimizing analysis of a related dataset.

Funding

This work was funded by research grants from the Canadian Institutes of Health (CIHR): MOP 89825, EKL; PRJ153101, EKL and JM. We also acknowledge the support of a CIHR Banting and Best Canada Graduate Scholarship and an Ontario Graduate Scholarship, SKP.

Author information

Authors and Affiliations

  1. Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5S 1A8, Canada

    Saige K. Power, Sridevi Venkatesan, Sarah Qu & Evelyn K. Lambe

  2. Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5S 1A8, Canada

    JoAnne McLaurin

  3. Biological Sciences, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, M4N 3M5, Canada

    JoAnne McLaurin

  4. Department of Obstetrics and Gynaecology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5G 1E2, Canada

    Evelyn K. Lambe

  5. Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5T 1R8, Canada

    Evelyn K. Lambe

Authors
  1. Saige K. Power
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Sridevi Venkatesan
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Sarah Qu
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. JoAnne McLaurin
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Evelyn K. Lambe
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Conceptualization, SKP, JM, EKL; Methodology, SKP, SV, EKL; Data acquisition SKP, SV; Analysis, SKP, SQ; Writing, SKP EKL; Review & editing, SKP, SV, JM, EKL; Funding, SKP, JM, EKL; Supervision, JM, EKL. All authors have critically reviewed and approved of the paper.

Corresponding author

Correspondence to Evelyn K. Lambe.

Ethics declarations

Ethical approval

This manuscript contains animal research that was approved by the Faculty of Medicine Animal Care Committee at the University of Toronto in accordance with the guidelines of the Canadian Council on Animal Care (protocols #20011621, #20011658, #20011796). This work was conducted under the appropriate Material Transfer Authorizations.

Competing interests

The authors have no conflicts or competing interests to declare.

Supplementary Information

Additional file 1

: Table S1 Neuronal intrinsic properties of layer 6 pyramidal neurons by genotype in mice. Table S2 Neuronal intrinsic properties of layer 6 pyramidal neurons by genotype in rats. Figure S1 There are no significant differences in intrinsic excitability between nTg and TgCRND8 layer 6 pyramidal neurons in mouse.  Figure S2 Decrease in intrinsic excitability between F344 and TgF344 layer 6 pyramidal neurons in mid disease.  Figure S3 Cholinergic treatments are consistently effective in prefrontal layer 6 pyramidal neurons of TgCRND8 AD and nTg controls. Figure S4 Cholinergic treatments are consistently effective at early to mid-AD and late-AD in layer 6 pyramidal neurons of prefrontal cortex

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Power, S.K., Venkatesan, S., Qu, S. et al. Enhanced prefrontal nicotinic signaling as evidence of active compensation in Alzheimer’s disease models. Transl Neurodegener 13, 58 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40035-024-00452-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40035-024-00452-7

Keywords

Translational Neurodegeneration

ISSN: 2047-9158

Contact us