Cognitive Pathology in Parkinson's Disease
van der Zee, Sygrid
DOI:
10.33612/diss.172837091
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Publication date: 2021
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van der Zee, S. (2021). Cognitive Pathology in Parkinson's Disease: a cholinergic perspective. University of Groningen. https://doi.org/10.33612/diss.172837091
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The aim of this thesis was to investigate the cholinergic pathology underlying cognitive impairment in Parkinson’s disease (PD). In the following paragraphs, we summarize the most important findings from each chapter, followed by an in-depth discussion on the role of the cholinergic system in cognitive functioning in PD, the clinical implications, general considerations and recommendations for future research.
Summary of main findings
Chapter 2 established the use of the presynaptic vesicular acetylcholine (VAChT) PET
tracer [18F]Fluoroethoxybenzovesamicol ([18F]FEOBV) as a reliable marker of cholinergic
innervation in PD. VAChT binding between 10 PD patients and 10 control subjects was compared, showing significantly lower binding in the occipital lobe and the posterior regions of the parietal and temporal lobes in PD patients. A subgroup of 5 PD patients and 5 control subjects underwent a second [18F]FEOBV PET scan within two weeks of
the first scan, to evaluate test-retest variability and reliability. For cortical regions and the thalamus, excellent test-retest reliability was demonstrated for both PD patients and control subjects. The striatal regions showed higher variability, but with good retest reliability in PD patients and excellent retest reliability in control subjects. These findings support the use of [18F]FEOBV PET imaging to evaluate regional cholinergic innervation
and its relationship with clinical symptomatology in PD.
In chapter 3 and chapter 4, the use of [18F]FEOBV as a measure of brain
cholinergic innervation was further explored in newly diagnosed, treatment naïve, PD patients as part of the DUtch PARkinson Cohort (DUPARC). Chapter 3 provides a detailed description of the DUPARC study; a longitudinal, observational, cohort study of de novo PD patients. The study aims to extensively characterize PD patients within three major non-motor domains, including cognition, gastrointestinal function and vision. Main objectives include the assessment of cognitive decline over time and the relationship with both dopaminergic and cholinergic denervation. In chapter 4 the first baseline results of the DUPARC study are presented, showing the pattern of cholinergic innervation in newly diagnosed, treatment naïve, PD patients. Subjects were grouped as either cognitively normal NC) or with mild cognitive impairment (PD-MCI), and compared to healthy control subjects on [18F]FEOBV PET imaging. 29.8% of
included patients were classified as PD-MCI, the majority presented with multi-domain cognitive impairment. The most frequently affected domains were memory and executive functioning. Bidirectional cholinergic innervation changes were found in PD patients compared to control subjects. Both PD-NC and PD-MCI showed limited but significant cortical cholinergic denervation compared to controls, primarily in the posterior and temporal cortical regions. However, at the same time voxel-based cholinergic analyses showed significant higher VAChT binding in PD-NC compared to HC in both cortical
and sub-cortical regions, including the cerebellum, cingulate cortex, putamen, gyrus rectus, hippocampus and amygdala. These results suggests a compensatory cholinergic mechanism in early PD and that a lack of cholinergic increase may play an important role in early, clinically evident, cognitive impairment in PD.
Chapter 5 and chapter 6 concentrate on PD patients with a more advanced
disease duration, recruited as part of a cross-sectional study at the University of Michigan. The studies present the evaluation of regional cholinergic correlates of cognitive functioning in more advanced PD patients from two distinctive perspectives: from a cognitive perspective by predefining cognitive domain scores and evaluating regional cholinergic correlates (chapter 5), and from a cholinergic perspective, primarily focusing on the identification of cholinergic covarying components using a data-driven approach (chapter 6). In chapter 5 cognitive performance of PD patients was assessed using a detailed neuropsychological assessment with a z score for each cognitive domain that reflects the degree of deviation from normal performance. Based on Movement Disorder Society (MDS) level II criteria, 45,3% of PD subjects were classified as PD-MCI. 92.3% of PD-MCI subjects presented with multidomain impairments, of which attention, executive functions and memory were the most frequently affected domains. Global cortical cholinergic innervation was significantly correlated with performance on the memory, executive function and attention domains. Evaluation of more detailed regional cholinergic correlates of cognitive performance with a voxel-based analysis demonstrated most robust correlates with the same cognitive domains. A shared cholinergic topography was found across cognitive domains, including both cortical and subcortical regions. An additional sensitivity analysis demonstrated both disease-specific as well as age-related cholinergic correlates of cognitive functioning. The PD-specific regional cholinergic topography related to cognitive functioning included the cingulum, bilateral insula and operculum, the hippocampal region and the visual thalamus. In chapter 6, the relationship between cognitive functioning and cholinergic innervations was evaluated from a cholinergic perspective using a principle component analysis as a data-driven approach to identify cholinergic covarying patterns. First, we identified seven main covarying principle components (PCs): (1) bilateral posterior cortical regions (2) bilateral subcortical regions, (3) bilateral centro-cingulate regions, (4) bilateral frontal regions, (5) right-sided fronto-temporal region, (6) cerebellum, and (7) predominantly left sided temporal region. Second, we demonstrated that three PCs, including the centro-cingulate region (PC3), the right-sided fronto-temporal regions (PC5) and the predominantly left-sided temporal region (PC5) were significant predictors for general and domain specific cognitive functioning in memory, attention, executive function and language domains. The centro-cingulate region, including cingulate cortices, pre-, para- and postcentral gyri and the superior frontal regions, was specific for PD subjects and most robustly correlated
with cognitive functioning. Our findings in this chapter suggest a cholinergic role in regional and large scale neural networks underlying cognitive changes in PD.
Integration of findings
Cholinergic imaging in PDPrior studies on in vivo imaging of brain cholinergic systems in PD have largely relied on PET acetylcholinesterase (AChE) substrate tracers1–4, which are an indirect marker of
cholinergic terminal integrity. The relatively novel cholinergic PET marker [18F]FEOBV
provides the opportunity for a selective presynaptic assessment of the cholinergic system.5
Unlike previously used AChE-based PET ligands, it allows for detailed assessment of not only low level cortical cholinergic innervation, but also higher binding areas, including the striatal region and cerebellum.5,6 We evaluated the use of [18F]FEOBV in PD patients by
comparing regional VAChT binding between PD patients and control subjects (chapter 2), which was not previously assessed using this novel tracer. Both whole-brain voxel-based analysis as well as a volume-of-interest analysis supported previous findings of cholinergic innervation patterns in PD2,4, suggesting that [18F]FEOBV can reliably be used
to evaluate cholinergic system integrity in PD. These findings support the use of [18F]
FEOBV as cholinergic marker in PD, as applied in the subsequent chapters 4, 5 and 6. In addition, our assessment of test-retest variability in both PD patients and healthy control subjects (chapter 2) demonstrated good to excellent retest reliability in both subject groups in cortical as well as subcortical regions. These findings are of importance for future longitudinal research on cholinergic denervation over time in PD, which is one of the main objectives described in the DUPARC study (chapter 3).
Regional cholinergic system vulnerability
[18F]FEOBV PET imaging provides the opportunity to evaluate the regional role of
cholinergic innervation in cognitive functioning on a cortical and subcortical level, in contrast to previous AChE studies. Our findings expand upon previous studies by demonstrating regional cortical and subcortical cholinergic correlates of domain-specific cognitive functioning in PD. Chapter 5 showed a PD disease domain-specific cholinergic topographic innervation pattern related to cognitive functioning including the cingulate cortex, insula and operculum, hippocampal regions and visual thalamus. Partly in line with these findings, chapter 6 showed primarily the centro-cingulate region related with cognitive functioning, together with bilateral fronto-temporal regions.
The contribution of these cholinergic regions to cognitive functioning in PD is an important finding, as most studies have focused on the relationship with more global cortical cholinergic innervation. The overlapping anatomic regions suggest a pattern of vulnerability of cholinergic projections underlying multi-domain cognitive impairment.
Primarily, vulnerability of basal forebrain cholinergic projections can be identified, in particular from the Ch4 group, the nucleus basalis of Meynert (NbM).7 This vulnerability
is not surprising, as NbM degeneration and the relationship with cognitive impairment in PD has repeatedly been demonstrated.8–10 However, our findings also demonstrate
that the cholinergic vulnerability related to cognitive impairment is not limited to basal forebrain projections, but striatal cholinergic interneurons and brainstem cholinergic projections may also be involved.11,12 This expands upon previous findings and emphasize
the necessity of cholinergic assessment on a detailed regional level beyond global cortical assessment, in order to better understand the contribution to cognitive functioning in PD.
Interestingly, the cholinergic topography of impaired cognitive functioning as demonstrated in chapter 5 and chapter 6, which is characterized by more centrally located frontal and temporal regions, differs from the posterior cholinergic denervation pattern as demonstrated in previous studies1,2,4 and in chapter 2 and chapter 4. However, these latter
findings are based on group comparisons between PD patients categorized at different levels of cognitive impairment, and control subjects, rather than a direct correlational assessment of regional correlates on a continuum of cognitive functioning. We postulate that although posterior regions show more pronounced cholinergic denervation in PD when compared to controls, this posterior vulnerability does not necessarily cause clinical evident cognitive impairment directly. Alternatively, the posterior cholinergic loss may be a prerequisite for cognitive impairment, but it is the degree of more anterior and centrally located regions that determine the degree of cognitive impairment. Longitudinal assessment of the posterior and anterior cholinergic projections and cognitive decline need further exploring to better understand the specific contributions.
Neural correlates of cognitive impairment – a cholinergic network perspective
Previous studies demonstrated a key role of cholinergic denervation in overall cognitive decline across multiple cognitive domains, but primarily associated with cognitive tasks in the attention, memory and executive function domains.13,14 Our results (chapter 5
and chapter 6) are in line with these findings, demonstrating most robust correlations between cholinergic innervation and cognitive functioning on memory, attention and executive function tasks. Interestingly, a considerable overlap in topography was found across these cognitive domains, suggesting a shared processing function underlying multiple cognitive domains.
A possible explanation for this might be that cholinergic innervation contributes to more domain-general processes instead of a cholinergic domain-specific role. Processes that may play a role are awareness, conflict monitoring and information processing speed/pace. The latter can for example be of importance as the majority of included
neuropsychological tests in the domains of memory, attention and executive functioning contain a timed element and mental slowness has previously been demonstrated in PD.15
In addition, and conceivably in line with the suggested domain-general processes, the key regions in the overlapping topography (chapter 5 and chapter 6) may reflect important hubs of a shared cholinergic network function. The insula, anterior cingulate cortex and dorsolateral prefrontal cortex have previously been described as part of a salience network which may play a key role in directing saliency processing and brain network switching functions.16 The detection of salient cues is important for optimal
attentional performance. Christopher et al. (2015) found dopaminergic differences in the insula and associated regions of the salience network to be related to executive dysfunction and memory impairment in PD.17 Our observations suggest an additional
role of the cholinergic system in the salience network as previously suggested by Picard et al.(2013).18 Furthermore, our findings of involvement of the posterior cingulate cortex
and medial prefrontal cortex, two of the key hubs of the default mode network (DMN), suggest that the cholinergic system may be an important contributor to the integrity of the DMN in PD.19 As a central region in the DMN, the posterior cingulate cortex is a highly
connected region and is associated with cognitive performance in non-demented PD patients, across multiple cognitive domains including memory, attention and visuospatial abilities.20–22 A decline in functional connectivity of the DMN is correlated with impaired
verbal and visual memory performance in PD.23 Our observations are in line with the
recent notion that the posterior cingulate cortex is a heterogeneous structure that plays an important multi-hub function.24 Finally, our findings involve key hubs of the
cingulo-opercular network, given the involvement of operculum, insula, anterior cingulate cortex, medial superior frontal cortex and the thalamus.25 The cingulo-opercular network is
considered a major component of the cingulo-opercular task control network (COTC), together with the salience network.26 The COTC may play a key role in domain-general
cognitive task performance, including task set maintenance, salience detection of stimuli and alertness.25,27–30
Overall, our findings of chapter 5 and chapter 6 suggest a cholinergic role in central and frontal/temporal regions in multidomain cognitive functioning, which may reflect involvement of hubs of distributed neural networks, both on a large scale and more local circuits. To get a better understanding of the possible role of cholinergic system in brain network functioning underlying cognitive functioning in PD, future research is needed. For example combining regional cholinergic imaging and functional MRI imaging, related to cognitive performance on a detailed cognitive domain level or generic cognitive task performance. In addition, it would be of interest to evaluate the role of domain-general cognitive tasks in relation to cholinergic network functioning. The DUPARC study (chapter 3) provides the opportunity for both suggestions and may aid the understanding of cholinergic neural network functioning.
The cholinergic compensatory hypothesis
The cholinergic denervation pattern demonstrated in PD is primarily based on studies in more advanced PD patients.1,31 Elucidation of the cholinergic role early in the disease
(chapter 4), and the relationship with cognitive impairment has provided new insights on the pathology underlying cognitive functioning and in particular the role of cholinergic innervation across stages of disease severity.
Initially recognized in prodromal Alzheimer’s disease patients, an increase of hippocampal choline acetyltransferase activity was found postmortem in the brains of subjects with MCI, compared to either cognitive unimpaired subjects and subjects with Alzheimer’s disease. They suggested a possible compensatory cholinergic upregulation involved in early cognitive changes.32 This cholinergic upregulation has also been suggested
in early PD, by studies representing possible prodromal PD, such as subjects with idiopathic REM sleep behavior disorder33 and LRRK2 gene mutation carriers.34 However,
chapter 4 describes the first study that evaluates cholinergic innervation in actual newly diagnosed PD patients. In line with the previous prodromal findings, we demonstrated a higher than normal cholinergic binding in de novo PD patients. The topography of the higher binding regions was found in the cerebellum, frontal and subcortical regions, including the thalamic complex, hippocampus and parahippocampal region, putamen, caudate nucleus, amygdala, cingulate cortex and gyrus rectus. These findings indicate a possible cholinergic role in early cognitive functioning of not only basal forebrain cholinergic projections, but also striatal cholinergic interneurons and pedunculopontine-laterodorsal tegmental complex pathways.11,12,35
Interestingly, this higher binding was most prominently visible in cognitively normal PD patients, and less prominent in PD patients considered as PD-MCI, although both had a similar disease duration. This seems to imply that PD-MCI starts if compensatory mechanisms fail. In addition, both groups showed comparable patterns of posterior denervation, suggesting that early cognitive impairment may be the result of a failing cholinergic compensation, rather than cholinergic denervation per se. However, future longitudinal research is needed to substantiate this finding.
Dual syndrome hypothesis revisited
Our findings are relevant to the current prevailing paradigm of cognitive impairment in PD, the dual-syndrome hypothesis.36,37 This hypothesis distinguishes between early
executive dysfunction driven primarily by dopaminergic modulation of the fronto-striatal system, and the more subsequent posterior cortical dysfunction, including memory and visuospatial impairments, related to non-dopaminergic pathology, including cholinergic denervation.
In de novo PD patients we found comparable cholinergic denervation patterns in
4). These findings can be explained in line with the dual syndrome hypothesis that early cognitive deficits in PD are more related to fronto-striatal dopaminergic changes and non-dopaminergic, including cholinergic, changes are more relevant in subsequent cognitive decline. However, we did not evaluate dopaminergic denervation in this group, therefore the dopaminergic role in de novo PD can not be confirmed. Furthermore, the cognitive deficits in this group were not limited to executive dysfunction, as is suggested in the dual syndrome hypothesis.
In further apparent disagreement with the dual-syndrome hypothesis we did not find a significant relationship between cognitive functioning and VAChT uptake in the occipital and posterior parietal regions (chapter 5 and chapter 6). In contrast, cholinergic regions that correlated with cognitive performance in non-demented PD patients, including the memory, attention and executive functions domain, were more centrally located, and frontal and temporal regions. These findings indicate that the proposed dopaminergic denervation of the fronto-striatal system in the dual-syndrome hypothesis alone may not be sufficient for the development of early cognitive impairment and that there is a significant role of the cholinergic system across domains. In addition, we demonstrated early involvement of frontal and subcortical cholinergic innervation in PD, related to cognitive impairment (chapter 4), providing further support that early cognitive dysfunction is not only driven by dopaminergic losses.
Based on our findings, we suggest a more complex interplay between dopaminergic and cholinergic innervation underlying cognitive functioning in PD, already present in early stages of the disease. For one, early cognitive impairment is not limited to executive dysfunction and fronto-striatal dopaminergic changes, but there is already a substantial cholinergic role in multi-domain cognitive functioning which is not limited to the posterior cortical regions (chapter 4, chapter 5 and chapter 6). Furthermore, there may be a complex interplay of dopaminergic and cholinergic neurotransmitter systems involved in the above suggested cholinergic compensatory mechanism, in line with previously found interactive effects of both systems.38 It is conceivable that loss in
cholinergic compensatory upregulation may worsen cognitive functioning (chapter 4), including fronto-striatal dysfunction.
However, our findings are solely based on the assessment of cholinergic innervation, without dopaminergic assessment. Longitudinal evaluation of cognitive status and both cholinergic and dopaminergic innervation may further elucidate this relationship. For example dual-PET assessment of both the dopaminergic and cholinergic systems of de
novo PD patients over time, in particular comparing patients that convert to PD-MCI or PDD, to those that remain cognitively stable. The DUPARC-study, as described in chapter 3, provides this opportunity.
General considerations and future directions
This thesis presents new insights in the role of the cholinergic system in PD, in particular for cognitive functioning. However, there are multiple aspects to take into consideration when interpreting the findings. In the following paragraphs of this thesis some overarching principles and considerations will be provided, followed by recommendations for future research.
Methodology of cognitive assessment
The assessment of cognitive functioning in PD is still a subject of debate. Different criteria and different definitions of PD-MCI have been used previously, precluding comparisons between studies. The MDS task force therefore proposed diagnostic criteria for PD-MCI to provide a more uniform method to characterize PD-MCI.39 However, even
with the proposed criteria, the assessment remains a subject of debate. For example, there is no consensus yet on which cognitive tasks should preferably be included in the neuropsychological assessment battery and which subscores of neuropsychological tests should be included for the classification.40 Furthermore, MDS criteria propose an
impairment at the cut-off of 1.5-2 SD below mean, but there is no consensus whether 1.5 or 2 SD below mean is the better cut-off.41–43
Furthermore, the arbitrary process of grouping patients as PD-MCI may limit interpretation, as the spectrum of cognitive impairment occurs along a continuum. Correlation analysis as performed in chapter 5 may provide more information on the relationship between cognitive functioning on the continuous spectrum and cholinergic innervation patterns. In addition, as described above, it would be of interest to look at more domain-general cognitive tasks, without the clustering of cognitive tasks in domains.
Finally, the MDS PD-MCI criteria and the majority of studies on the cognitive profile of PD cover five main cognitive domains: memory, attention, executive function, language and visuospatial functioning. The assessment of social cognition is not included in these criteria, even though the newest edition of the Diagnostic and Statistical Manual of Mental Disorder (DSM-5) includes social cognition as one of the core functional domains.44
Social cognition is a term used to describe cognitive processes that are critical in the communication and interpretation of social information, including empathy, theory of mind and social perception.45 Previous research has repeatedly demonstrated impairments in
social cognition in PD in both advanced as well as early stage PD patients.46–48 Further
research on the additional value of social cognition assessment in the PD-MCI criteria is therefore of interest.
Longitudinal assessment
Our findings and the majority of previous studies on the cholinergic role in cognitive functioning in PD are of cross-sectional nature. To correctly interpret these results in the context of the neurodegenerative character of PD, longitudinal research is crucial. As previously mentioned there are a number of longitudinal cohort studies on cognitive functioning in PD, including the ICICLE, CAMPAIGN, ParkWEST, Personalized Parkinson Project and PPMI studies.49–53 These studies add to the understanding of the cognitive
pathology in PD and each provides the unique opportunity for biomarker discovery. However, none of these studies correlate cognition to cholinergic imaging markers. The DUPARC study as described in chapter 3 may add to this by providing longitudinal data on cholinergic innervation in PD patients over time and how this relates to cognitive decline, starting assessment at time of diagnosis with drug-naïve patients. Longitudinal assessment of this relationship may also provide a better understanding of the suggested cholinergic compensatory mechanism (chapter 4). Furthermore, in line with the previously discussed dual-syndrome hypothesis, combining cholinergic and dopaminergic imaging will allow for better assessment of multisystem degeneration underlying cognitive impairment in PD. It will not only elucidate the interplay between both neurotransmitter systems, but longitudinal dual-tracer assessment may also provide pivotal information on the cognitive pathology over time.
Ageing
Another important aspect to discuss is the effect of ageing on cholinergic innervation. The degeneration of the nigrostrtial system in PD has shown to be a combination of PD- and age-related losses.54 Albin et al (2018) demonstrated age-related decrease in VAChT
binding in normal control subjects.55 In chapter 5 we have included a sensitivity analysis
using a mask, based on PD versus controls, on VAChT binding, differentiating between PD-specific and age-related denervation patterns. We demonstrated that both components contribute to the cholinergic pattern related to cognitive impairment. Evaluation of the cholinergic innervation patterns in PD should therefore always be interpreted in the context of ageing. A more detailed assessment of the effect of ageing on the cholinergic system in a longitudinal setting is recommended. A better understanding of age-associated cholinergic denervation will also help to better understand the previously suggested compensatory mechanism found in early PD.
Comorbid pathologies
The pathophysiology of cognitive impairment in PD is multifactorial and includes numerous neuropathological substrates, including Lewy body pathology, Alzheimer disease pathology (tau and amyloid-β aggregation), neuroinflammation and neurotransmitter changes.56,57
underlying pathology of cognitive impairment, in addition to the cholinergic perspective of this thesis. Above, we already proposed longitudinal dual-PET assessment combining dopaminergic and cholinergic imaging to better understand the interplay underlying cognitive impairment. In addition, it would be of interest to take the cumulative and interactive effects of the noradrenergic and serotonergic neurotransmitter systems into consideration. Both neurotransmitter systems have previously been associated with PDD and for noradrenaline a possible compensatory upregulation mechanism for the loss of striatal dopamine has even been proposed.58–60
Genetics
In addition, one of the factors that can be of influence on the clinical symptomatology of PD patients is the genetic vulnerability. The most common genetic risk factors for PD include mutations of the GBA1 gene.61 PD subjects who carry GBA mutations putatively
comprise a distinct clinical subtype, with a younger age of onset and faster progression. It is associated with more severe cognitive impairment, mood disorders, PIGD symptoms, and hyposmia.62,63 This phenotype bears resemblance to cholinergic system degeneration
related symptomatology64–66, suggesting a distinct role of the cholinergic system in
GBA mutation carriers. Future studies on the PD subgroup carrying GBA mutations is therefore of great interest and may provide important additional information on the role of the cholinergic system in PD.
Clinical implications
Our results provide new insights on the cholinergic role in cognitive impairment in PD, across different stages of the disease. These findings have potential clinical implications, in particular related to the management of cognitive impairment.
The quantification of the VAChT binding PET ligand [18F]FEOBV provides new
possibilities for in vivo assessment of cholinergic innervation in PD. In contrast to previously used PET ligands, [18F]FEOBV allows for detailed regional assessment of cholinergic
innervation in both lower binding cortical regions as well as higher binding subcortical regions and cerebellum. Cholinergic assessment using [18F]FEOBV therefore will become
of interest for clinical practice.
Clinical application of cholinergic PET imaging is of particular interest for the management of clinically relevant cognitive symptoms. The current main treatment for PDD is administration of cholinesterase inhibitors. However, early cholinesterase inhibitors prescription in PD-MCI patients has proven to be not effective, at least in particular subpopulations and in combination with the endpoint used.67,68 In this thesis
we have demonstrated that cholinergic innervation underlying cognitive impairment
showed that the posterior cholinergic denervation not directly correlates with cognitive performance (chapter 5 and chapter 6), and that early cognitive impairment may be more related to a failing or lacking compensation instead of cholinergic denervation (chapter 4). Clinical application of cholinergic PET imaging, identifying normal range cholinergic innervation, and therefore providing means to identify cholinergic denervation patterns as well as upregulation, may help distinguish failing cholinergic compensation from cholinergic degeneration and aid the correct stratification for cholinergic treatment in non-demented PD patients.
Conclusion
Cognitive impairment is a common and debilitating symptom in PD. This dissertation broadened our knowledge on the cognitive pathology in PD, from a cholinergic perspective. We evaluated reliability of in vivo assessment of presynaptic cholinergic PET imaging, cholinergic innervation of de novo PD patients and the regional cholinergic correlates of cognitive functioning in more advanced disease stages. Overall, we can confirm our hypotheses. [18F]FEOBV PET imaging allows for reliable and detailed
assessment of the cholinergic system. In addition, we demonstrated the early, bidirectional involvement of the cholinergic system in PD and the regional cholinergic vulnerability related to cognitive domain functioning in more advanced PD. These findings provide new directions for clinical practice and future studies on the cholinergic pathology of cognitive impairment in PD.
References
1. Klein JC, Eggers C, Kalbe E, et al. Neurotransmitter changes in dementia with Lewy bodies and Parkinson disease dementia in vivo. Neurology. 2010;74(11):885-892. doi:10.1212/WNL.0b013e3181d55f61 2. Shimada H, Hirano S, Shinotoh H, et al. Mapping of brain acetylcholinesterase alterations in Lewy body
disease by PET. Neurology. 2009;73(4):273-278. doi:10.1212/WNL.0b013e3181ab2b58
3. Bohnen NI, Müller MLTM, Kotagal V, et al. Heterogeneity of cholinergic denervation in Parkinson’s disease without dementia. J Cereb Blood Flow Metab. 2012;32(8):1609-1617. doi:10.1038/jcbfm.2012.60
4. Hilker R, Thomas A V., Klein JC, et al. Dementia in Parkinson disease: Functional imaging of cholinergic and dopaminergic pathways. Neurology. 2005;65(11):1716-1722. doi:10.1212/01.wnl.0000191154.78131.f6 5. Petrou M, Frey K a, Kilbourn MR, et al. In Vivo Imaging of Human Cholinergic Nerve Terminals with
(-)-5-18F-Fluoroethoxybenzovesamicol: Biodistribution, Dosimetry, and Tracer Kinetic Analyses. J Nucl
Med. 2014;55(3):396-404. doi:10.2967/jnumed.113.124792
6. Nejad-Davarani S, Koeppe RA, Albin RL, Frey KA, Müller MLTM, Bohnen NI. Quantification of brain cholinergic denervation in dementia with Lewy bodies using PET imaging with [18F]-FEOBV. Mol Psychiatry.
2019;24(3):322-327. doi:10.1038/s41380-018-0130-5
7. Liu AKL, Chang RCC, Pearce RKB, Gentleman SM. Nucleus basalis of Meynert revisited: anatomy, history and differential involvement in Alzheimer’s and Parkinson’s disease. Acta Neuropathol. 2015;129(4):527-540. doi:10.1007/s00401-015-1392-5
8. Schulz J, Pagano G, Fernández Bonfante JA, Wilson H, Politis M. Nucleus basalis of Meynert degeneration precedes and predicts cognitive impairment in Parkinson’s disease. Brain. 2018;141(5):1501-1516. doi:10.1093/brain/awy072
9. Lee JE, Cho KH, Song SK, et al. Exploratory analysis of neuropsychological and neuroanatomical correlates of progressive mild cognitive impairment in Parkinson’s disease. J Neurol Neurosurg Psychiatry. 2014;85(1):7-16. doi:10.1136/jnnp-2013-305062
10. Zarow C, Lyness SA, Mortimer JA, Chui HC. Neuronal Loss Is Greater in the Locus Coeruleus Than Nucleus Basalis and Substantia Nigra in Alzheimer and Parkinson Diseases. 2017;60:337-341.
11. Ballinger EC, Ananth M, Talmage DA, Role LW. Basal Forebrain Cholinergic Circuits and Signaling in Cognition and Cognitive Decline. Neuron. 2016;91(6):1199-1218. doi:10.1016/j.neuron.2016.09.006 12. Selden NR, Gitelman DR, Salamon-Murayama N, Parrish TB, Mesulam MM. Trajectories of cholinergic
pathways within the cerebral hemispheres of the human brain. Brain. 1998;121 ( Pt 1:2249-2257. http:// www.ncbi.nlm.nih.gov/pubmed/9874478.
13. Bohnen NI, Kaufer DI, Hendrickson R, et al. Cognitive correlates of cortical cholinergic denervation in Parkinson’s disease and parkinsonian dementia. J Neurol. 2006;253(2):242-247. doi:10.1007/s00415-005-0971-0
14. Bohnen NI, Mu MLTM, Kotagal V, et al. Heterogeneity of cholinergic denervation in Parkinson ’ s disease without dementia. 2012:1609-1617. doi:10.1038/jcbfm.2012.60
15. Vlagsma TT, Koerts J, Tucha O, et al. Mental slowness in patients with Parkinson’s disease: Associations with cognitive functions? J Clin Exp Neuropsychol. 2016;3395(May):1-9. doi:10.1080/13803395.2016.11678 40
16. Seeley WW, Menon V, Schatzberg AF, et al. Segmental kidney volumes measured by dynamic contrast- enhanced magnetic resonance imaging and their association with CKD in older people. Am J Kidney Dis. 2009;27(9):2349-2356. doi:10.1523/JNEUROSCI.5587-06.2007.Dissociable
17. Christopher L, Duff-Canning S, Koshimori Y, et al. Salience network and parahippocampal dopamine dysfunction in memory-impaired Parkinson disease. Ann Neurol. 2015;77(2):269-280. doi:10.1002/ ana.24323
18. Picard F, Sadaghiani S, Leroy C, Courvoisier DS, Maroy R, Bottlaender M. High density of nicotinic receptors in the cingulo-insular network. Neuroimage. 2013;79:42-51. doi:10.1016/j.neuroimage.2013.04.074 19. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain
function. Proc Natl Acad Sci U S A. 2001;98(2):676-682. doi:10.1073/pnas.98.2.676
20. Tessitore A, Esposito F, Vitale C, et al. Default-mode network connectivity in cognitively unimpaired patients with Parkinson disease. Neurology. 2012;79(23):2226-2232. doi:10.1212/WNL.0b013e31827689d6 21. Lee Y, Ham JH, Cha J, et al. The cholinergic contribution to the resting-state functional network in
non-demented Parkinson’s disease. Sci Rep. 2018;8(1):1-10. doi:10.1038/s41598-018-26075-3
22. Karunanayaka PR, Lee E-Y, Lewis MM, et al. Default mode network differences between rigidity- and tremor-predominant Parkinson’s disease. Cortex. 2016;81:239-250. doi:10.1016/j.cortex.2016.04.021 23. Lucas-Jiménez O, Ojeda N, Peña J, et al. Altered functional connectivity in the default mode network
is associated with cognitive impairment and brain anatomical changes in Parkinson’s disease. Park Relat
Disord. 2016;33:58-64. doi:10.1016/j.parkreldis.2016.09.012
24. Leech R, Sharp DJ. The role of the posterior cingulate cortex in cognition and disease. Brain. 2014;137(1):12-32. doi:10.1093/brain/awt162
25. Dosenbach NUF, Visscher KM, Palmer ED, et al. A core system for the implementation of task sets.
Neuron. 2006;50(5):799-812. doi:10.1016/j.neuron.2006.04.031
26. Power JD, Cohen AL, Nelson SM, et al. Functional network organization of the human brain. Neuron. 2011;72(4):665-678. doi:10.1016/j.neuron.2011.09.006
27. Dosenbach NUF, Fair DA, Miezin FM, et al. Distinct brain networks for adaptive and stable task control in humans. Proc Natl Acad Sci. 2007;104(26):11073-11078. doi:10.1073/pnas.0704320104
28. Dosenbach NUF, Fair DA, Cohen AL, Schlaggar BL, Petersen SE. A dual-networks architecture of top-down control. Trends Cogn Sci. 2008;12(3):99-105. doi:10.1016/j.tics.2008.01.001
29. Sadaghiani S, D’Esposito M. Functional Characterization of the Cingulo-Opercular Network in the Maintenance of Tonic Alertness. Cereb Cortex. 2015;25(9):2763-2773. doi:10.1093/cercor/bhu072 30. Coste CP, Kleinschmidt A. Cingulo-opercular network activity maintains alertness. Neuroimage.
2016;128:264-272. doi:10.1016/j.neuroimage.2016.01.026
31. Hilker R, Thomas a. V., Klein JC, et al. Dementia in Parkinson disease: Functional imaging of cholinergic and dopaminergic pathways. Neurology. 2005;65(11):1716-1722. doi:10.1212/01.wnl.0000191154.78131.f6 32. DeKosky ST, Ikonomovic MD, Styren SD, et al. Upregulation of choline acetyltransferase activity in
hippocampus and frontal cortex of elderly subjects with mild cognitive impairment. Ann Neurol. 2002;51(2):145-155. doi:10.1002/ana.10069
33. Bedard M-A, Aghourian M, Legault-Denis C, et al. Brain cholinergic alterations in idiopathic REM sleep behaviour disorder: a PET imaging study with (18)F-FEOBV. Sleep Med. 2019;58:35-41. doi:10.1016/j. sleep.2018.12.020
34. Liu S-Y, Wile DJ, Fu JF, et al. The effect of LRRK2 mutations on the cholinergic system in manifest and premanifest stages of Parkinson’s disease: a cross-sectional PET study. Lancet Neurol. 2018;17(4):309-316. doi:10.1016/S1474-4422(18)30032-2
35. Zhang C, Zhou P, Yuan T. The cholinergic system in the cerebellum: from structure to function. Rev
Neurosci. 2016;27(8):769-776. doi:10.1515/revneuro-2016-0008
36. Kehagia AA, Barker RA, Robbins TW. Cognitive impairment in Parkinson’s disease: The dual syndrome hypothesis. Neurodegener Dis. 2012;11(2):79-92. doi:10.1159/000341998
37. Williams-Gray CH, Evans JR, Goris A, et al. The distinct cognitive syndromes of Parkinson’s disease: 5 year follow-up of the CamPaIGN cohort. Brain. 2009;132(11):2958-2969. doi:10.1093/brain/awp245 38. Bohnen NI, Albin RL, Müller MLTM, et al. Frequency of Cholinergic and Caudate Nucleus Dopaminergic
Deficits Across the Predemented Cognitive Spectrum of Parkinson Disease and Evidence of Interaction Effects. JAMA Neurol. 2015;72(2):194-200. doi:10.1001/jamaneurol.2014.2757
39. Litvan I, Goldman JG, Tröster AI, et al. Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines. Mov Disord. 2012;27(3):349-356. doi:10.1002/ mds.24893
40. Hoogland J, van Wanrooij LL, Boel JA, et al. Detecting Mild Cognitive Deficits in Parkinson’s Disease: Comparison of Neuropsychological Tests. Mov Disord. 2018;33(11):1750-1759. doi:10.1002/mds.110 41. Goldman JG, Holden S, Bernard B, Ouyang B, Goetz CG, Stebbins GT. Defining optimal cutoff scores for
cognitive impairment using Movement Disorder Society Task Force criteria for mild cognitive impairment in Parkinson’s disease. Mov Disord. 2013. doi:10.1002/mds.25655; 10.1002/mds.25655
42. Marras C, Armstrong MJ, Meaney C a., et al. Measuring mild cognitive impairment in patients with Parkinson’s disease. Mov Disord. 2013;28(5):626-633. doi:10.1002/mds.25426
43. Szeto JYY, Mowszowski L, Gilat M, Walton CC, Naismith SL, Lewis SJG. Assessing the utility of the Movement Disorder Society Task Force Level 1 diagnostic criteria for mild cognitive impairment in Parkinson’s disease. Parkinsonism Relat Disord. 2015;21(1):31-35. doi:10.1016/j.parkreldis.2014.10.020 44. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, (5th Ed.).; 2013. 45. Henry JD, von Hippel W, Molenberghs P, Lee T, Sachdev PS. Clinical assessment of social cognitive function
in neurological disorders. Nat Rev Neurol. 2016;12(1):28-39. doi:10.1038/nrneurol.2015.229
46. Chen H-B, Wu D-D, He J, Li S-H, Su W. Emotion Recognition in Patients With Parkinson Disease. Cogn
Behav Neurol Off J Soc Behav Cogn Neurol. 2019;32(4):247-255. doi:10.1097/WNN.0000000000000209 47. McIntosh LG, Mannava S, Camalier CR, et al. Emotion recognition in early Parkinson’s disease patients
undergoing deep brain stimulation or dopaminergic therapy: a comparison to healthy participants. Front
Aging Neurosci. 2014;6:349. doi:10.3389/fnagi.2014.00349
48. Enrici I, Adenzato M, Ardito RB, et al. Emotion processing in Parkinson’s disease: a three-level study on recognition, representation, and regulation. PLoS One. 2015;10(6):e0131470. doi:10.1371/journal. pone.0131470
49. Yarnall AJ, Breen DP, Duncan GW, et al. Characterizing mild cognitive impairment in incident Parkinson disease : The ICICLE-PD Study. Neurology. 2014;82(4):308-316. doi:10.1212/WNL.0000000000000066 50. Pedersen KF, Larsen JP, Tysnes OB, Alves G. Prognosis of mild cognitive impairment in early
Parkinson disease: the Norwegian ParkWest study. JAMA Neurol. 2013;70(5):580-586. doi:10.1001/ jamaneurol.2013.2110; 10.1001/jamaneurol.2013.2110
51. Williams-Gray CH, Mason SL, Evans JR, et al. The CamPaIGN study of Parkinson’s disease: 10-year outlook in an incident population-based cohort. J Neurol Neurosurg Psychiatry. 2013;84(11):1258-1264. doi:10.1136/ jnnp-2013-305277
52. The Parkinson Progression Marker Initiative (PPMI). Prog Neurobiol. 2011;95(4):629-635. doi:10.1016/j. pneurobio.2011.09.005
53. Bloem BR, Marks WJJ, Silva de Lima AL, et al. The Personalized Parkinson Project: examining disease progression through broad biomarkers in early Parkinson’s disease. BMC Neurol. 2019;19(1):160. doi:10.1186/s12883-019-1394-3
54. Bohnen NI, Albin RL, Koeppe RA, et al. Positron emission tomography of monoaminergic vesicular binding in aging and Parkinson disease. J Cereb blood flow Metab Off J Int Soc Cereb Blood Flow Metab. 2006;26(9):1198-1212. doi:10.1038/sj.jcbfm.9600276
55. Albin RL, Bohnen NI, Muller MLTM, et al. Regional vesicular acetylcholine transporter distribution in human brain: A [(18) F]fluoroethoxybenzovesamicol positron emission tomography study. J Comp Neurol. 2018;526(17):2884-2897. doi:10.1002/cne.24541
56. Kalia L V, Lang AE. Parkinson’s disease. Lancet (London, England). 2015;386(9996):896-912. doi:10.1016/ S0140-6736(14)61393-3
57. Aarsland D, Creese B, Politis M, et al. Cognitive decline in Parkinson disease. Nat Rev Neurol. 2017;13(4):217-231. doi:10.1038/nrneurol.2017.27
58. Halliday GM, Leverenz JB, Schneider JS, Adler CH. The neurobiological basis of cognitive impairment in Parkinson’s disease. Mov Disord. 2014;29(5):634-650. doi:10.1002/mds.25857 [doi]
59. Del Tredici K, Braak H. Dysfunction of the locus coeruleus-norepinephrine system and related circuitry in Parkinson’s disease-related dementia. J Neurol Neurosurg Psychiatry. 2013;84(7):774-783. doi:10.1136/ jnnp-2011-301817; 10.1136/jnnp-2011-301817
60. Isaias IU, Marotta G, Pezzoli G, et al. Enhanced catecholamine transporter binding in the locus coeruleus of patients with early Parkinson disease. BMC Neurol. 2011;11:88. doi:10.1186/1471-2377-11-88
61. Sidransky E, Nalls MA, Aasly JO, et al. Multicenter analysis of glucocerebrosidase mutations in Parkinson’s disease. N Engl J Med. 2009;361(17):1651-1661. doi:10.1056/NEJMoa0901281
62. Davis MY, Johnson CO, Leverenz JB, et al. Association of GBA Mutations and the E326K Polymorphism With Motor and Cognitive Progression in Parkinson Disease. JAMA Neurol. 2016;73(10):1217-1224. doi:10.1001/jamaneurol.2016.2245
63. Thaler A, Bregman N, Gurevich T, et al. Parkinson’s disease phenotype is influenced by the severity of the mutations in the GBA gene. Parkinsonism Relat Disord. 2018;55:45-49. doi:10.1016/j.parkreldis.2018.05.009 64. Bohnen N, Albin R. The Cholinergic System in Parkinson’s Disease. Behav Brain Res. 2011;221(2):564-573.
doi:10.1016/j.bbr.2009.12.048.The
65. Bohnen NI, Kanel P, Zhou Z, et al. Cholinergic system changes of falls and freezing of gait in Parkinson’s disease. Ann Neurol. 2019;85(4):538-549. doi:10.1002/ana.25430
66. Müller MLTM, Bohnen NI. Cholinergic dysfunction in parkinson’s disease. Curr Neurol Neurosci Rep. 2013;13(9). doi:10.1007/s11910-013-0377-9
67. Grace J, Amick MM, Friedman JH. A double-blind comparison of galantamine hydrobromide ER and placebo in Parkinson disease. J Neurol Neurosurg Psychiatry. 2009;80(1):18-23. doi:10.1136/jnnp.2008.144048 68. Mamikonyan E, Xie SX, Melvin E, Weintraub D. Rivastigmine for mild cognitive impairment in Parkinson
