Muscarinic Receptors Expression in the Peripheral Blood Cells Differentiate Dementia with Lewy Bodies from Alzheimer’s Disease

Abstract

Background:

Central nervous system disruption of cholinergic (ACh) signaling, which plays a major role in cognitive processes, is well documented in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). The expression of muscarinic ACh receptors type 1 and 4 (CHRM1 and CHRM4) has been reported to be altered in the brain of DLB patients.

Objective:

We aim to assess the peripheral gene expression of CHRM1 and 4 in DLB as a possible marker as compared to AD and healthy control (HC) subjects.

Methods:

Peripheral blood mononuclear cells were collected from 21 DLB, 13 AD, and 8 HC matched subjects. RT-PCR was performed to estimate gene expression of CHRM1 and CHRM4.

Results:

Peripheral CHRM1 expression was higher and CHRM4 was lower in DLB and AD compared to HC, whereas both CHRM1 and CHRM4 levels were higher in AD compared to DLB patients. Receiver operating characteristics curves, with logistic regression analysis, showed that combining peripheral CHRM1 and CHRM4 levels, DLB and AD subjects were classified with an accuracy of 76.0%.

Conclusion:

Alterations of peripheral CHRM1 and CHRM4 was found in both AD and DLB patients as compared to HC. CHRM1 and CHRM4 gene expression resulted to be lower in DLB patients compared to AD. In the future, peripheral CHRM expression could be studied as a possible marker of neurodegenerative conditions associated with cholinergic deficit and a possible marker of response to acetylcholinesterase inhibitors.

Keywords

Alzheimer’s disease cholinergic imbalance dementia with Lewy bodies muscarinic receptors real time-polymerase chain reaction

INTRODUCTION

Dementia with Lewy bodies (DLB) is a common form of dementia in older age, where marked cholinergic dysfunction including reduced choline acetyltransferase is a key neurochemical feature and major contributor to the cognitive, sleep and psychiatric symptoms [1].

In DLB and Alzheimer’s disease (AD), cortical cholinergic neurotransmission is compromised, and this is thought to contribute to cognitive decline and the neuropsychiatric symptoms experienced by these patients [2 –4]. In AD, cholinergic innervation from the nucleus basalis of Meynert is disrupted, and there are reductions in cholinergic parameters (including choline acetyltransferase (ChAT)) in cortical areas [5, 6]. The greatest cortical deficits in acetylcholine occur in those brain areas concerned with memory and cognition, the hippocampus and temporal, frontal, and parietal cortices [7, 8]. There is a strong correlation between cortical cholinergic deficits (especially in temporal and parietal lobe) and dementia scores [8 –10]. Relatively greater losses of ChAT in DLB compared to AD occur in temporal and parietal neocortex and some thalamic nuclei [4, 8] and are relevant to psychosis and hallucinations since levels are lower in hallucinating than in non-hallucinating DLB cases [11]. ChAT is also moderately reduced in DLB in striatum [12]. In addition to hallucinations other non-cognitive symptoms, for example apathy, delusions and agitation, may also have a cholinergic component, since these have been reported to improve following cholinergic therapy [13 –15].

Acetylcholine (ACh) neurotransmission is facilitated by both muscarinic and nicotinic receptors. Of the former, there are five muscarinic subtypes (CHRM1–CHRM5), which are widely distributed throughout the central nervous system (CNS) and brain and are considered to play an important role in learning and memory with CHRM1 implicated, in particular, in regulating cognition [16, 17].

The distribution of various muscarinic subtypes (CHRM1-CHRM4) has been examined in several brain regions in DLB. M1 expression has been found to be decreased in temporal, hippocampal, and parietal areas relative to healthy controls (HC) [4 , 18–20], and in the striatum compared to AD and HC [21]. A decreased CHRM4 in temporal cortex [18] has also been observed in DLB relative to HC. In addition, increased binding levels of CHRM1/M4 receptors have been found within the insula, cingulate, and claustrum in DLB compared to HC. All these findings represent the basis of the effective symptomatic response to acetylcholinesterase inhibitors (AChEI) in DLB [1].

Immune cells present a complete cholinergic system consisting of ACh, muscarinic and nicotinic receptors, choline acetyl-transferase and acetyl-cholinesterase [22, 23], and respond to neurotransmitters, specific agonists, and antagonists, playing a pivotal role in the neuroimmune communication.

The identification, in human peripheral blood mononuclear cells (PBMCs), of various subtypes of nicotinic cholinergic receptors and all five muscarinic receptor [24, 25], may reflect to some extent the status of homologous brain sites [22, 26].

Derangement of these leukocyte receptors has been previously observed in AD and Parkinson’s disease with dementia [23 , 27–30]; however, evidence in DLB patients are still lacking. Given the greater extent of CNS cholinergic dysfunction in DLB [31], we hypothesize that, as happens in the brain, the expression of CHRM1 and CHRM4 could be differentially affected in DLB as compared to AD and HC.

If this hypothesis will be confirmed, peripheral expression of CHRM could serve as a peripheral supportive diagnostic biomarker for DLB, and possibly a predictor of pharmaceutical response to cholinesterase inhibitors.

In the present pilot study, we therefore measured the expression of CHRM1 and CHRM4 receptors in the PBMCs of a cohort of DLB patients in comparison with AD patients and HC.

MATERIALS AND METHODS

Patients

Twenty-one patients diagnosed with Probable DLB according to clinical criteria [32] and thirteen patients with AD [33] frequency matched for gender, age, education, disease duration, and cognitive level, naïve to AChEI treatment, were consecutively recruited from the outpatient clinic of the Neurology Unit, “G. d’Annunzio” University of Chieti-Pescara. Eight HC, frequency matched for age and gender, were recruited among the patients’ spouses.

The presence of fluctuating cognition (CF) was assessed by the Clinician Assessment of Fluctuations (CAF) questionnaire [34], the presence of REM sleep behavior disorder (RBD) with the Mayo Questionnaire [35], parkinsonism was assessed by the Unified Parkinson’s Disease Rating Scale (UPDRS) motor score [36], the presence of visual hallucinations (VH) by the Neuropsychiatric Inventory (NPI) [37], and cognitive impairment was evaluated by Mini-Mental Statement Examination (MMSE) [38].

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Chieti-Pescara (Protocol code 2098. 11/6/2020. Protocol “Neurodem” 26/7/2018, emend 2/8/2018). All the participants or their caregivers signed an informed consent to participate to the study.

Blood samples collection and PBMC purification

Peripheral venous blood samples (3–5 mL) were collected in the morning between 08 : 00 and 10 : 00 in vacutainer tubes containing EDTA, according to the routine puncture method. Blood was collected by blood centrifugation at 1600 rpm for 10 min and frozen at –80°C within 30 min, until assayed. 10 mL of blood/saline (1 : 2 v/v) was layered over 5 mL of Ficoll-Paque (GE Healthcare, Sigma-Aldrich, Darmstadt, Germany) and centrifuged at 1600 rpm for 30 min at room temperature [39, 40]. Cells were harvested from the interface, washed twice with Phosphate buffered saline (PBS) and resuspended in RPMI 1640 medium (Sigma-Aldrich, Darmstadt, Germany) supplemented with 10%fetal bovine serum (FBS) (Euroclone, MI, Italy), 4 mM L-glutamine, 50 U/ml penicillin, and 50 mg/L streptomycin (all purchased by Sigma-Aldrich, Darmstadt, Germany). PBMCs (3x106 in 1 mL of medium) were placed in 5 mL polypropylene culture tubes (BD Falcon™, Two Oak Park Bedford, MA, USA) and incubated at 37°C in 5%CO₂ in cell culture incubator for 24 h. After this time, tubes were centrifuged to collect separately cell pellet and supernatant that were stored at –80°C for later analysis of muscarinic receptor gene expression.

RNA extraction and real-time polymerase chain reaction

Total RNA was extracted from PBMCs using QIAzol reagent (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. The RNA concentration was determined by measuring the samples’ absorbance at 260 nm by NanoDrop 2000 UV-Vis Spectrophotometer (Thermo Scientific, Waltham, MA, USA) and its purity was assessed by the absorbance ratio 260/280 nm and 260/230 nm [41]. For each sample, 1μg of RNA was reverse transcribed into complementary DNA (cDNA) using QuantiTect Reverse Transcription Kit (Qiagen, Hilden, Germany). Subsequently, Real-Time Polymerase Chain Reaction (RT- PCR) was performed using the GoTaq® qPCR Master Mix (Promega, Madison, WI, USA), to evaluate the gene expression of CHRM1, CHRM4 and Ribosomal Protein S18 (RPS18). Specific primer pairs were used to evaluate the gene expression of CHRM1 (FW: 5-CAATCACTGGCTGTGCCTCTT-3, RW: 5-GGTGATCCCAATGAAGGCCA-3), CHRM4 (FW:5-ATCGCTATGAGACGGTGGAA-3, RW:5-GTTGGACAGGAACTGGATGA-3) and the housekeeping gene RPS18 (FW 5^′-CTTTGCCATCACTGCCATTAAG-3’, RW 5^′-TCCATCCTTTACATCCTTCTGTC-3^′) was used as a reference gene. All RT-PCR reactions were performed in triplicates in the CFX RT-PCR Detection Systems (Bio-Rad, Hercules, CA, USA), with the following conditions: initially, 2 min incubation at 95°C followed by 40 cycles consisting in 30 s 95°C, then 60°C for 1 min and 30 s at 68°C. The gene expression analysis was done according to 2-ΔΔCt method [42].

Statistical analysis

The sample size required for the ROC analysis on gene expression of CHRM1 and 4 in DLB compared to AD and HC subjects was estimated in 30 subjects hypothesizing a AUC of 0.80, with 80%power, alpha = 0.05 and an equal number of cases and controls [43]. Mean and standard deviation (SD) and absolute frequency (percentage) were used as descriptive statistics. Normality distribution was tested by Jarque-Bera test. Mann-Whitney U test was used to detect differences between two independent groups in demographic and clinical characteristics. Kruskal–Wallis H test was used to detect differences between more than two independent groups. Pearson’s Chi-squared test (for cell frequency n≥5), and Fisher’s exact test (for cell frequency n < 5). Diagnostic accuracy and efficiency were analyzed by receiver operating characteristics (ROC) curve analysis using MedCalc (MedCalc software, USA). Sensitivity and specificity for CHRM1 and CHMR4 were calculated. Areas under the curves (AUCs) and p-value were calculated, assuming a nonparametric distribution. An AUC greater than 0.9 indicated excellent diagnostic efficacy. An AUC between 0.7 and 0.9 indicated good diagnostic efficacy. An AUC between 0.5 and 0.7 indicated poor diagnostic efficacy. AUC of no more than 0.5 indicated the lack of a diagnostic value of the marker using the method suggested by DeLong et al. [43]. Logistic regression was used as classifier considering CHRM1 and CHMR4 simultaneously. Relations between CHRM1 or CHMR4 levels and demographic and clinical characteristics were assessed by Spearman correlation coefficient for quantitative parameters. All statistical tests were 2-sided, with a significance level set at p < 0.05. Analyses were performed using the R software environment for statistical computing and graphics (version 3.5.3; http://www.r-project.org/).

RESULTS

Demographic and clinical characteristics are reported in Table 1. No significant differences were detected between the groups of patients for gender, age, education, disease duration, and cognitive level, as per inclusion criteria. No differences were detected between each group of patients versus HC for age and gender. As expected, prevalence of VH, CF, RBD, and parkinsonism was higher in DLB group.

Table 1

Demographic and clinical data of the cohort

	DLB (n = 21)	AD (n = 13)	HC (n = 8)	Chi-square p
Gender –n female (%)	13 (61.9)	9 (69.2)	7 (87.5%)	0.411
Age –mean (±SD)	78.9 (±6.1)	77.2 (±7.8)	73.6 (±5.6)	0.166^a
Years of education –mean (±SD)	8.10 (±5.2)	7.0 (±4.8)	11.3 (±4)	0.151^a
Disease duration, y –mean (±SD)	4.4 (±3.1)	6.4 (±3.9)	–	0.238 ^a
Fluctuating cognition –n (%)	13 (61.9)	2 (15.4)	–	0.008
Recurrent VH –n (%)	15 (71.4)	3 (23.1)	–	0.006
REM sleep behavior disorder –n (%)	16 (76.2)	4 (30.8)	–	0.009
Parkinsonism –n (%)	18 (85.7)	3 (23.1)	–	< 0.001
UPDRS-III score –mean (±SD)	24.5 (±16.0)	4.7 (±7.4)	–	< 0.001^a
MMSE score –mean (±SD)	17.45 (±7.1)	14.7 (±6.6)^*	28.6 (±0.9)^*	< 0.001^a

DLB, dementia with Lewy bodies; AD, Alzheimer’s disease; HC, healthy controls; SD, standard deviation; VH, visual hallucinations; UPDRS-III, Unified Parkinson’s Disease Rating Scale (third section); MMSE, Mini-Mental State Examination. ^ap-value derived by Mann-Whitney U test or Kruskal–Wallis H test when appropriate. ^*p < 0.05 post-hoc analysis versus HC group.

Comparisons between every group showed that CHRM1 mRNA levels in PBMCs of DLB and AD patients were significantly higher than those in HC, respectively 4.2-fold (p < 0.001) in DLB and 2.1-fold (p < 0.001) in AD. While, as compared to HC, CHRM4 gene expression in DLB was 0.4-fold (p = 0.001) lower than in HC and in AD was lower 0.1-fold (p = 0.002) than in HC. Comparing CHRM1 and CHRM4 expression in DLB and AD, expression of CHRM1 and CHRM4 was 0.2-fold lower in DLB than in AD (p = 0.022 and p = 0.013, respectively).

ROC curves, showing the diagnostic performances of each receptor gene expression in discriminating each patient group from HC and DLB from AD patients, are depicted in Fig. 1. As illustrated in Fig. 1a (diagnostic performance in discriminating AD from HC), the most accurate cut-off for CHRM1 was ≤15.60 (AUC = 0.875), which revealed good accuracy. For CHRM4 (Fig. 1b), the best cut-off was > 14.45 (AUC = 0.587), thus showing a diagnostic accuracy not significantly lower than CHRM1. As illustrated in Fig. 1c (diagnostic performance in discriminating DLB from HC), the most accurate cut-off for CHRM1 was of ≤15.55 (AUC = 0.827), which revealed good accuracy. For CHRM4 (Fig. 1d), the best cut-off was > 14.57 (AUC = 0.720), thus showing a good diagnostic accuracy as well.

Fig. 1

ROC curves: Areas under the curves (AUC)±Standard error and associate p-value, Sensitivity, Specificity, and best cut-off for CHRM1 and CHRM4. Gray dotted lines indicate the 95%confidence interval. a, b) Represents the comparison between AD and HC for CHRM1 and CHRM4 expression. c, d) Depicts the same gene expressions in discriminating DLB from HC. e, f) Represents the comparison between DLB and AD patients for CHRM1 and CHRM4. DLB, dementia with Lewy bodies; AD, Alzheimer’s disease; HC, healthy controls.

As illustrated in Fig. 1e and 1f, which reports diagnostic performance of CHRM1 and CHRM4 in the differential diagnosis between DLB and AD, the most accurate cut-off for CHRM1 was of > 13.13 (AUC = 0.676), revealed moderate accuracy (Fig. 1e). For CHRM4 (Fig.1f), the best cut-off was > 15.94 (AUC = 0.586), thus showing a diagnostic accuracy not significantly lower than CHRM1.

CHRM1 showed the highest sensitivity (82.0%), whereas CHRM4 showed the highest specificity (61.0%) in differentiating the two diseases. Finally, with combined use of CHRM1 and CHRM4 and logistic regression as classifier, diagnostic accuracy improved (76.0%). We report the confusion matrices of the classifier as Table 2.

Table 2

Confusion matrices of the classifier

	AD	DLB
AD	7	2
DLB	6	19
Percent of cases correctly classified: 76.00%
	AD	HC
AD	12	1
HC	1	7
Percent of cases correctly classified: 90.41%
	DLB	HC
DLB	19	2
HC	2	6
Percent of cases correctly classified: 86.21%

AD, Alzheimer’s disease; DLB, dementia with Lewy bodies; HC, healthy controls.

No relation was found between CHRM1 or CHRM4 levels and demographic characteristics or the clinical symptoms. More specifically no association was found with presence/absence of CF, RBD, VH, parkinsonism, or cognitive impairment. Furthermore, no relation was found with UPDRS motor score and with MMSE score.

DISCUSSION

Cholinergic receptors are the key elements of the cholinergic system, and in lymphocyte these neurotransmitter receptors may reflect the status of homologous brain sites [44]. The expression of muscarinic receptors in PBMCs has been known since early 1970s, based on the various functional and biochemical changes elicited by ACh, agonists and antagonists in these cells [22]. Therefore, a possible tool for exploring in vivo cholinergic function is probably given by peripheral blood lymphocytes.

These cells contain acetylcholine, express acetylcholine synthesizing and degrading enzymes, as well as muscarinic and nicotinic cholinergic receptors [25 , 45–48]. Lymphocyte muscarinic receptors were assayed in neurological disorders with cognitive impairment such as AD [27 –29] and Parkinson’s disease with cognitive impariment [30]. Previous studies reported a decrease of muscarinic cholinergic receptor binding in peripheral lymphocytes associated with cognitive dysfunction [27 –30].

Former studies have suggested the occurrence of cholinergic receptor impairment in peripheral lymphocytes in aging, AD, or other neurodegenerative disorders [49, 50], but these investigations did not analyze cholinergic receptor impairment in DLB.

Cholinergic dysfunction is a major feature of DLB and makes a significant contribution to the cognitive impairment and other challenging symptoms seen in this condition [51]. Thus, manipulation of the cholinergic system can offer significant therapeutic opportunities for treating DLB, as highlighted by the use of AChEI as one of the best treatments in this condition.

In the present study we observed a lower expression of CHRM1 and 4 in PBMCs of DLB as compared to AD patients. These data seem to be in agreement with previous observations which showed greater reduction of brain ACh activity in DLB than AD [31]. In our patient groups, no significant correlations were found between the expression of CHRM1 and CHRM4 genes and either cognitive/neuropsychiatric variables or disease duration. But we cannot exclude that such a lack of correlation can be explained by the small sample size, other than the incomplete pattern of CHRM subtypes evaluation.

It will be interesting to assess the correlations between CHRM1 and CHRM4 changes in PBMCs of DLB patients with the in vivo assessment of cholinergic neurotransmission markers using PET scan and single photon emission tomography (SPECT) to suggest that peripheral CHRM expression could serve as a possible peripheral diagnostic biomarker of DLB. It could also be interesting to test CHRM peripheral expression as a marker of disease severity and progression. Finally, peripheral CHRM expression could serve as a marker of response to AChEI therapy.

Footnotes

ACKNOWLEDGMENTS

This research was funded by 2019 MIUR funds.

Authors’ disclosures available online ().

References

Aarsland

, Litvan

, Salmon

, Galasko

, Wentzel-Larsen

, Larsen

(2003) Performance on the dementia rating scale in Parkinson’s disease with dementia and dementia with Lewy bodies: Comparison with progressive supranuclear palsy and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 74, 1215–1220.

Perry

, Tomlinson

, Blessed

, Bergmann

, Gibson

, Perry

(1978) Correlation of cholinergic abnormalities with senile plaques and mental test scores in senile dementia. Br Med J 2, 1457–1459.

Perry

, Marshall

, Perry

, Irving

, Smith

, Blessed

, Fairbairn

(1990) Cholinergic and dopaminergic activities in senile dementia of Lewy body type. Alzheimer Dis Assoc Disord 4, 87–95.

Ballard

, Piggott

, Johnson

, Cairns

, Perry

, McKeith

, Jaros

, O’Brien

, Holmes

, Perry

(2000) Delusions associated with elevated muscarinic binding in dementia with Lewy bodies. Ann Neurol 48, 868–76.

Mesulam

M-M

, Geula

(1988) Nucleus basalis (Ch4) and cortical cholinergic innervation in the human brain: Observations based on the distribution of acetylcholinesterase and choline acetyltransferase. J Comp Neurol 275, 216–240.

Bierer

, Haroutunian

, Gabriel

, Knott

, Carlin

, Purohit

, Perl

, Schmeidler

, Kanof

, Davis

(1995) Neurochemical correlates of dementia severity in Alzheimer’s disease: Relative importance of the cholinergic deficits. J Neurochem 64, 749–760.

Geula

, Mesulam

M-M

(1996) Systematic regional variations in the loss of cortical cholinergic fibers in Alzheimer’s disease. Cereb Cortex 6, 165–177.

Perry

(1998) Cholinergic mechanisms and cognitive decline. Eur J Anaesthesiol 15, 768–773.

Dournaud

, Delaere

, Hauw

, Epelbaum

(1995) Differential correlation between Neurochemical deficits, neuropathology, and cognitive status in Alzheimer’s disease. Neurobiol Aging 16, 817–823.

10.

Colloby

, McKeith

, Burn

, Wyper

, O’Brien

, Taylor

J-P

(2016) Cholinergic and perfusion brain networks in Parkinson disease dementia. Neurology 87, 178–185.

11.

Perry

, Perry

(1995) Acetylcholine and hallucinations: Disease-related compared to drug-induced alterations in human consciousness. Brain Cogn 28, 240–258.

12.

Piggott

, Marshall

(1996) Neurochemical correlates of pathological and iatrogenic extrapyramidal symptoms. In Dementia with Lewy Bodies: Clinical, Pathological, and Treatment Issues, Perry RH, McKeith IG, Perry EK, eds. Cambridge University Press, Cambridge, pp. 449–467.

13.

Shea

, MacKnight

, Rockwood

(1998) Donepezil for treatment of dementia with Lewy bodies: A case series of nine patients. Int Psychogeriatr 10, 229–238.

14.

Francis

, Palmer

, Snape

, Wilcock

(1999) The cholinergic hypothesis of Alzheimer’s disease: A review of progress. J Neurol Neurosurg Psychiatry 66, 137–147.

15.

McKeith

, Ferman

, Thomas

, Blanc

, Boeve

, Fujishiro

, Kantarci

, Muscio

, O’Brien

, Postuma

, Aarsland

, Ballard

, Bonanni

, Donaghy

, Emre

, Galvin

, Galasko

, Goldman

, Gomperts

, Honig

, Ikeda

, Leverenz

, Lewis

SJG

, Marder

, Masellis

, Salmon

, Taylor

, Tsuang

, Walker

, Tiraboschi

(2020) Research criteria for the diagnosis of prodromal dementia with Lewy bodies. Neurology 94, 743–755.

16.

Anagnostaras

, Murphy

, Hamilton

, Mitchell

, Rahnama

, Nathanson

, Silva

(2003) Selective cognitive dysfunction in acetylcholine M1 muscarinic receptor mutant mice. Nat Neurosci 6, 51–58.

17.

Erskine

, Taylor

, Thomas

, Collerton

, McKeith

, Khundakar

, Attems

, Morris

(2019) Pathological changes to the subcortical visual system and its relationship to visual hallucinations in dementia with Lewy bodies. Neurosci Bull 35, 295–300.

18.

Shiozaki

, Iseki

, Uchiyama

, Watanabe

, Haga

, Kameyama

, Ikeda

, Yamamoto

, Kosaka

(1999) Alterations of muscarinic acetylcholine receptor subtypes in diffuse Lewy body disease: Relation to Alzheimer’s disease. , 209 LP –. J Neurol Neurosurg Psychiatry 67, 209LP–213.

19.

Shiozaki

, Iseki

, Hino

, Kosaka

(2001) Distribution of M1 muscarinic acetylcholine receptors in the hippocampus of patients with Alzheimer’s disease and dementia with Lewy bodies-an immunohistochemical study. J Neurol Sci 193, 23–28.

20.

Colloby

, Nathan

, McKeith

, Bakker

, O’Brien

, Taylor

J-P

(2020) Cholinergic muscarinic M(1)/M(4) receptor networks in dementia with Lewy bodies. Brain Commun 2, fcaa098.

21.

Piggott

, Owens

, O’Brien

, Colloby

, Fenwick

, Wyper

, Jaros

, Johnson

, Perry

(2003) Muscarinic receptors in basal ganglia in dementia with Lewy bodies, Parkinson’s disease and Alzheimer’s disease. J Chem Neuroanat 25, 161–173.

22.

Fujii

, Kawashima

(2000) YM905, a novel M3 antagonist, inhibits Ca2+signaling and c-fos gene expression mediated via muscarinic receptors in human T cells. Gen Pharmacol 35, 71–75.

23.

Tayebati

, Amenta

, Amici

, El-Assouad

, Gallai

, Ricci

, Parnetti

(2001) Peripheral blood lymphocytes muscarinic cholinergic receptor subtypes in Alzheimer’s disease: A marker of cholinergic dysfunction? J Neuroimmunol 121, 126–131.

24.

Sato

, Fujii

, Watanabe

, Yamada

, Ando

, Kazuko

, Kawashima

(1999) Diversity of mRNA expression for muscarinic acetylcholine receptor subtypes and neuronal nicotinic acetylcholine receptor subunits in human mononuclear leukocytes and leukemic cell lines. Neurosci Lett 266, 17–20.

25.

Tayebati

, Piergentili

, Natale

, Amenta

(1999) Evaluation of an agonist index: Affinity ratio for compounds active on muscarinic cholinergic M2 receptors. J Auton Pharmacol 19, 77–84.

26.

Costa

, Auger

, Traver

, Costa

(1995) Identification of m3, m4 and m5 subtypes of muscarinic receptor mRNA in human blood mononuclear cells. J Neuroimmunol 60, 45–51.

27.

Ferrero

, Rocca

, Eva

, Benna

, Rebaudengo

, Ravizza

, Genazzani

, Bergamasco

(1991) An analysis of lymphocyte 3H-N-methil-scopolamine binding in neurological patients: Evidence of altered binding in Alzheimer’s disease. Brain 114, 1759–1770.

28.

Eva

, Ferrero

, Rocca

, Funaro

, Bergamasco

, Ravizza

, Genazzani

(1989) [3H]N-methylscopolamine binding to muscarinic receptors in human peripheral blood lymphocytes: Characterization, localization on T-lymphocyte subsets and age-dependent changes. Neuropharmacology 28, 719–726.

29.

Adem

, Nordberg

, Bucht

, Winblad

(1986) Extraneural cholinergic markers in Alzheimer’s and Parkinson’s disease. Prog Neuropsychopharmacol Biol Psychiatry 10, 247–257.

30.

Rabey

, Grynberg

, Graff

(1991) Changes of muscarinic cholinergic binding by lymphocytes in parkinson’s disease with and without dementia. Ann Neurol 30, 847–850.

31.

Tiraboschi

, Hansen

, Alford

, Merdes

, Masliah

, Thal

, Corey-Bloom

(2002) Early and widespread cholinergic losses differentiate dementia with Lewy bodies from Alzheimer disease. Arch Gen Psychiatry 59, 946–951.

32.

McKeith

, Boeve

, Dickson

, Halliday

, Taylor

J-P

, Weintraub

, Aarsland

, Galvin

, Attems

, Ballard

, Bayston

, Beach

, Blanc

, Bohnen

, Bonanni

, Bras

, Brundin

, Burn

, Chen-Plotkin

, Duda

, El-Agnaf

, Feldman

, Ferman

, Ffytche

, Fujishiro

, Galasko

, Goldman

, Gomperts

, Graff-Radford

, Honig

, Iranzo

, Kantarci

, Kaufer

, Kukull

, Lee

VMY

, Leverenz

, Lewis

, Lippa

, Lunde

, Masellis

, Masliah

, McLean

, Mollenhauer

, Montine

, Moreno

, Mori

, Murray

, O’Brien

, Orimo

, Postuma

, Ramaswamy

, Ross

, Salmon

, Singleton

, Taylor

, Thomas

, Tiraboschi

, Toledo

, Trojanowski

, Tsuang

, Walker

, Yamada

, Kosaka

(2017) Diagnosis and management of dementia with Lewy bodies. Neurology 89, 88–100.

33.

McKhann

, Knopman

, Chertkow

, Hyman

, Jack

CRJ

, Kawas

, Klunk

, Koroshetz

, Manly

, Mayeux

, Mohs

, Morris

, Rossor

, Scheltens

, Carrillo

, Thies

, Weintraub

, Phelps

(2011) The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7, 263–269.

34.

Walker

, Ayre

, Cummings

, Wesnes

, McKeith

, O’Brien

, Ballard

(2000) Quantifying fluctuation in dementia with Lewy bodies, Alzheimer’s disease, and vascular dementia. Neurology 54, 1616–1625.

35.

Boeve

, Molano

, Ferman

, Lin

S-C

, Bieniek

, Tippmann-Peikert

, Boot

, St Louis

, Knopman

, Petersen

, Silber

(2013) Validation of the Mayo Sleep Questionnaire to screen for REM sleep behavior disorder in a community-based sample. J Clin Sleep Med 9, 475–480.

36.

Goetz

, Tilley

, Shaftman

, Stebbins

, Fahn

, Martinez-Martin

, Poewe

, Sampaio

, Stern

, Dodel

, Dubois

, Holloway

, Jankovic

, Kulisevsky

, Lang

, Lees

, Leurgans

, LeWitt

, Nyenhuis

, Olanow

, Rascol

, Schrag

, Teresi

, van Hilten

, LaPelle

(2008) Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results. Mov Disord 23, 2129–2170.

37.

Cummings

(1997) The Neuropsychiatric Inventory: Assessing psychopathology in dementia patients. Neurology 48 (5 Suppl 6), S10–16.

38.

Folstein

, Folstein

, McHugh

(1975) Mini-mental state”. Apractical method for grading the cognitive state of patients for theclinician. J Psychiatr Res 12, 189–198.

39.

Böyum

(1968) Isolation of mononuclear cells and granulocytes from human blood. Isolation of monuclear cells by one centrifugation, and of granulocytes by combining centrifugation and sedimentation at 1 g. Scand J Clin Lab Invest Suppl 97, 77–89.

40.

Marteau

J-B

, Mohr

, Pfister

, Visvikis-Siest

(2005) Collection and storage of human blood cells for mRNA expression profiling: A 15-month stability study. Clin Chem 51, 1250–1252.

41.

Fleige

, Pfaffl

(2006) RNA integrity and the effect on the real-time qRT-PCR performance. Mol Aspects Med 27, 126–139.

42.

Livak

, Schmittgen

(2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25, 402–408.

43.

DeLong

, DeLong

, Clarke-Pearson

(1988) Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. Biometrics 44, 837–845.

44.

Maśliński

(1989) Cholinergic receptors of lymphocytes. Brain Behav Immun 3, 1–14.

45.

Toyabe

, Iiai

, Fukuda

, Kawamura

, Suzuki

, Uchiyama

, Abo

(1997) Identification of nicotinic acetylcholine receptors on lymphocytes in the periphery as well as thymus in mice. Immunology 92, 201–205.

46.

Bany

, Ryżewski

, Maśliński

(1999) Relative amountsof mRNA encoding four subtypes of muscarinic receptors(m2–m5) in human peripheral blood mononuclear cells. JNeuroimmunol 97, 191–195.

47.

Fitzgerald

, Costa

(1993) Modulation of muscarinic receptors and acetylcholinesterase activity in lymphocytes and in brain areas following repeated organophosphate exposure in rats. Toxicol Sci 20, 210–216.

48.

Kawashima

, Fujii

, Watanabe

, Misawa

(1998) Acetylcholine synthesis and muscarinic receptor subtype mRNA expression in T-lymphocytes. Life Sci 62, 1701–1705.

49.

Reale

, Costantini

(2021) Cholinergic modulation of the immune system in neuroinflammatory diseases. Diseases 9, 29.

50.

Adem

(1990) Lymphocyte cholinergic receptor changes in Alzheimer’s disease. In Neuropsychopharmacology, Bunney WE, Hippius H, Laakmann G, Schmauss M, eds. Springer, Berlin, Heidelberg, pp. 134–141.

51.

Taylor

J-P

, Firbank

, O’Brien

(2016) Visual cortical excitability in dementia with Lewy bodies. Br J Psychiatry 208, 497–498.