Nonmotor Symptoms and Natural History of Parkinson's Disease: Evidence From Cognitive Dysfunction and Role of Noninvasive Interventions

ARTICLE IN PRESS

Nonmotor Symptoms and Natural History of Parkinson’s Disease: Evidence From Cognitive Dysfunction and Role of Noninvasive Interventions Roberta Biundo*, Eleonora Fiorenzato*,†, Angelo Antonini*,†,1 *Parkinson’s Disease and Movement Disorders Unit, San Camillo Hospital IRCCS, Venice-Lido, Italy † University of Padua, Padua, Italy 1 Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 1.1 Assessing the Contribution to Cognition to Disease Progression 2. Role of Nonpharmacological Interventions 2.1 Cognitive Rehabilitation 2.2 Physical Exercise 3. Telemedicine: The Future of Rehabilitation? 4. Discussion References Further Reading

2 4 7 7 10 13 14 15 23

Abstract Parkinson’s disease (PD) is a common neurodegenerative disorder, characterized by motor and nonmotor symptoms (NMS). Several subsequent studies substantiate the great functional burden related to NMS, their progression, and negative effect on quality of life in PD. Additional evidence indicates interesting relationships between striatal dopaminergic function and NMS. The basal ganglia are implicated in the modulation and integration of sensory information and pain, bladder function is under control of both inhibitory (D1) and facilitatory (D2) dopaminergic inputs, finally reduced dopaminergic activity in the mesocortical and mesolimbic pathways is involved in the development of several NMS including mood, motivational, and cognitive alterations. Some NMS fluctuate in response to dopaminergic treatment and are relieved by dopamine replacement therapy, other are insensitive to current therapeutic strategies. The relation among the overall disease complications, perhaps the most important for PD patients and family members’ well-being and functionality is dementia that affects most PD patients over the course of disease. Specific pharmacological treatment is lacking, International Review of Neurobiology ISSN 0074-7742 http://dx.doi.org/10.1016/bs.irn.2017.05.031

#

2017 Elsevier Inc. All rights reserved.

1

ARTICLE IN PRESS 2

Roberta Biundo et al.

and alternative approaches have been implemented to improve everyday functionality and quality of life. The state of the art suggests that cognitive rehabilitation in PD is possible and may either increase performance or preserve cognitive level over the time. However, it is also evident that cognitive abnormalities in PD are heterogeneous and we still do not have biomarkers to detect early patients at risk for dementia. Cognitive dysfunction is one the most prevalent NMS and is a clinically and functionally important disease milestone. Given the available clinical and imaging evidence it is possible to use cognition to model NMS progression and design nonpharmacological interventions. In this chapter we will address the use of cognitive rehabilitation and noninvasive brain stimulation techniques to modulate cognitive performance and rescue connectivity in affected brain circuitry.

1. INTRODUCTION Parkinson’s disease (PD) is a complex neurodegenerative disorder that affects up to 2% of population over age 65 (de Rijk et al., 1997) with an incidence of 14 per 100,000 individuals (Hirtz et al., 2007) and an estimated prevalence ranging between 8.7 and 9.3 million by 2030 (Dorsey et al., 2007). The motor cardinal symptoms of PD (bradykinesia, resting tremor, rigidity, gait impairment) are associated with Lewy bodies and loss of dopaminergic neurons in the substantia nigra pars compacta (Gibb & Lees, 1988). PD patients also present several nonmotor symptoms (NMS), often preceding motor signs by more than a decade (Abbott et al., 2007; Akaogi, Asahina, Yamanaka, Koyama, & Hattori, 2009; Braak, Ghebremedhin, Rub, Bratzke, & Del Tredici, 2004; Chaudhuri et al., 2006; Goldstein, 2006; Lim & Lang, 2010; Ponsen et al., 2004; Postuma et al., 2012). Although under recognized, NMS have also been found to be highly prevalent in PD. Some studies reported the presence of NMS in 100% of PD and in patients experiencing motor fluctuations (Kim et al., 2013; Krishnan, Sarma, Sarma, & Kishore, 2011). Although NMS also occur in healthy subjects (68%–88% of individuals experience at least one NMS), in PD they are more frequent and severe (Khoo et al., 2013; Krishnan et al., 2011; Witjas et al., 2002). It is now well recognized that NMS represent an important part of PD symptoms spectrum as well as significantly cause disability and, consequently, poor quality of life for PD patients (Duncan et al., 2014; Martinez-Martin, Rodriguez-Blazquez, Kurtis, Chaudhuri, & NMSS Validation Group, 2011) increasing caregiver burden and annual economic costs (estimated at around $14 billion in United States and also Europe) (Kowal, Dall, Chakrabarti, Storm, & Jain, 2013; Olesen et al., 2012).

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

3

NMS encompass sensory abnormalities (olfactory dysfunctions, problem with vision) behavioral changes (such as depression, anxiety, impulse control disorders and other psychiatric symptoms), psychosocial (punding and apathy) dysfunctions, cognitive impairment, rapid eyeball movement sleep behavior disorder, autonomic dysfunctions (constipation, orthostatic hypotension, dysphagia, gastroparesis, small intestinal bacterial overgrowth, bowel dysfunction, urinary symptoms, sexual and thermoregulation dysfunction), and some more difficult to categorize symptoms such as pain and fatigue (Kalia & Lang, 2015; Pfeiffer, 2016; Picillo et al., 2017; Polli et al., 2016). Although there is evidence that some NMS, particularly depression, may be responsive to dopaminergic therapy, most are not (Chaudhuri & Schapira, 2009; Kehagia, Barker, & Robbins, 2013; Seppi et al., 2011). Several studies have assessed NMS but only a few have followed prospectively large PD populations. The PRIAMO study was a prospective study designed to assess prevalence and incidence of NMS in a large cohort of PD patients at different disease stages selected from both academic and hospital based services over 24 months. The cross-sectional observation found that overall NMS number was higher in individuals with greater motor severity and duration. Unlike other studies PRIAMO used a questionnaire that did not undergo formal clinimetric validation but delivered consistent results with other cohort studies where NMS were evaluated using specific scales or questionnaire. The results of the prospective assessment indicated that NMS progression is variable and domain specific, which means that it often follows a different pattern compared to motor features. More specifically, although NMS increased in number only in patients showing clinical motor progression, there were domains becoming more and other less prevalent. Finally, only the development of NMS in specific domains contributed to worsening quality of life. These findings further highlight the relevance of NMS for PD, but also indicate that their assessment is complementary to motor evaluation if one wants to measure PD progression. The uneven development of discrete NMS domains in our PRIAMO cohort suggests a nonlinear progression that is relevant for planning future trials targeting specific NMS and possibly neuroprotection. The occurrence of NMS that are concomitantly increasing and decreasing in frequency in the same patient population confirms that making the treating neurologists aware of NMS presence they may have adjusted medications’ doses or regimens. Indeed several studies have indicated that NMS are often undeclared by patients unless a specific questionnaire is administered, while randomized studies indicate that NMS like sleep disturbances

ARTICLE IN PRESS 4

Roberta Biundo et al.

or depressive symptoms can be improved by dopamine agonists. This may be reflected particularly in the stable group where adjustment in dopaminergic therapy possibly contributed in stabilizing clinical motor conditions. The observation that NMS with remitter greater than incident number included cardiovascular symptoms (which included two symptoms lightheadedness/ dizziness during the postural changes, fall because of syncope) or psychiatric features (which incorporated 10 symptoms including anxiety, panic attacks, depression, and hallucinations) which may benefit from optimization of dopaminergic therapy would be consistent with this hypothesis. Unfortunately the PRIAMO study did not specifically record medication doses and therefore it was not possible to establish with certainty the presence of this relationship. Interestingly the presence or absence of symptoms in the cardiovascular and psychiatric domains had great impact on quality of life confirming their relevance for PD management. By contrast skin domain that in our study included two NMS hyperhidrosis and seborrhea showed the greatest progression in terms of new incident patients but had little impact on quality of life. One interesting observation from PRIAMO study regarded the assessment of mortality rate. Overall there was higher mortality in the PRIAMO cohort compared to the Italian population in the same age range and more importantly a similar death rate in male and female patients indicating the PD has greater impact on women life expectancy (which is higher than men in the control population). Interestingly the number of NMS in patients who died during follow-up was higher at baseline compared to other patients confirming that end stage PD is associated also with widespread degeneration in addition to motor disability.

1.1 Assessing the Contribution to Cognition to Disease Progression Cognitive dysfunction and dementia are the clinically most relevant NMS given their impact on quality of life and autonomy ( Johnson, Diener, Kaltenboeck, Birnbaum, & Siderowf, 2013; Ker€anen et al., 2003; Vossius, Larsen, Janvin, & Aarsland, 2011). The point prevalence of dementia in PD is about 30% (Aarsland & Kurz, 2010) and most PD patients will eventually experience dementia during the course of the disease (Aarsland, Andersen, Larsen, & Lolk, 2003; Buter et al., 2008; Hely, Reid, Adena, Halliday, & Morris, 2008). It has been observed that PD with mild cognitive impairment (PD-MCI) has a greater likelihood to develop dementia than those with normal cognition (Barone et al., 2011; Pedersen, Larsen,

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

5

Tysnes, & Alves, 2013). PD-MCI patients have an annual rate of dementia between 9% and 15% (Pedersen et al., 2013) with clinical and demographic variables affecting the incidence (Williams-Gray et al., 2013). Although cognitive difficulties clearly become more frequent and prominent as PD progresses, mild cognitive deficits can be detected in
15%–25% of newly diagnosed patients (Aarsland et al., 2009; Biundo et al., 2014) and could be present even before motor symptoms appear (Goldman, WilliamsGray, Barker, Duda, & Galvin, 2014; Pigott et al., 2015). The mechanisms underlying dementia development in PD remain poorly understood. Therapeutic strategies to prevent or delay dementia in PD are limited (Svenningsson, Westman, Ballard, & Aarsland, 2012) mainly because their insufficient knowledge on the identifying predictors of dementia and improving the understanding of how neurodegeneration develops are essential for implementing efficacious pharmacological and no pharmacological treatments. The presence of marked heterogeneity in neuropsychological deficits observed among PD patients makes it difficult to establish a comprehensive unique model for cognitive decline in PD (Pagonabarraga & Kulisevsky, 2012). In this regard, one of the major challenges is understanding nature and evolution of these cognitive alterations and the interplay between cognitive, anatomical, neurochemical, and neuropathological entities associated with these deficits. Indeed, intriguing overlaps in biochemical, clinical, and imaging findings question the concept of distinct entities and suggest a continuous spectrum in which individual patients express PD-typical patterns (α-synuclein pathology mainly in cortical and limbic structure) and AD-typical patterns (beta-amyloid deposition) to a variable degree. In this regards, interesting metabolic imaging studies support the notion of PDD and dementia with Lewy bodies (DLB) as overlapping disease entities, characterized by the presence of mixed neuropathology and only different by the time course (Granert et al., 2015). By contrast only few neuropathology studies are available in PD-MCI, but results are heterogeneous (Adler et al., 2010; Jellinger, 2013). Neuronal and synaptic dysfunction and neuronal loss are considered to be the structural basis of dementia in most neurodegenerative disorders (Wishart, Parson, & Gillingwater, 2006). Interestingly, some studies showed an earlier and more robust correlation between synaptic loss and cognitive decline in PD than with AD markers of pathology (Scheff, Price, Schmitt, DeKosky, & Mufson, 2007; Terry et al., 1991). Less clear is the role of

ARTICLE IN PRESS 6

Roberta Biundo et al.

synaptic dysfunction in PDD–DLB (Aarsland, Perry, Brown, Larsen, & Ballard, 2005; Compta et al., 2011). Synaptic changes have been reported in PDD/DLB (Pienaar, Burn, Morris, & Dexter, 2012). A recent postmortem biochemical study showed that synaptic protein changes of Rab3A and neurogranin in the inferior parietal lobe (BA40) as well as SNAP25 in prefrontal cortex (BA9) best discriminated between the DLB/PDD/AD and nonneurologic controls (Bereczki et al., 2016). Interestingly the presence of these synaptic changes correlated positively with cognitive decline and neuropathological scores, highlighting their importance as a treatment target and its potential as future biomarkers of disease progression. Numerous genes increase the dementia risk such as ɑ-synuclein mutation (SNCA), the apolipoprotein ε4 (APOE4) allele, and the microtubuleassociated protein tau (MAPT) H1 haplotype), and similarly different neurotransmitters are involved in PD cognitive dysfunction (Halliday, Leverenz, Schneider, & Adler, 2014). In particular, the observation that levodopa treatment could restore only some cognitive functions (such as working memory, flexibility, capacity to switch in well-learned tasks rules) confirms that cognitive disturbances in PD are related both to nigrostriatal, mesolimbic, and mesocortical dopaminergic systems as well as nonstriatal and nondopaminergic origins. Indeed, a relationship between lesions of cholinergic (Bohnen et al., 2006; Sadeh, Braham, & Modan, 1982; Ziabreva et al., 2006) and noradrenergic (Cash et al., 1987; Delaville, Deurwaerdere, & Benazzouz, 2011; McMillan et al., 2011) systems and cognitive impairment in PD patients has been reported previously (Hanganu, Provost, & Monchi, 2015). In particular noradrenergic dysfunctions in PD probably underlies the attentional set shifting deficit, which is part of the dysexecutive syndrome (Kehagia et al., 2014; Weintraub et al., 2010) and both cholinergic and dopaminergic system changes possibly contribute independently to the cognitive deficits in nondemented PD (Bohnen et al., 2003; Meyer et al., 2009). These finding are also in line with evidence showing heterogeneity of cognitive deficits in PD. Indeed, together with the hypothesis of a frontostriatal syndrome, positing that cognitive deficits were executive in nature mainly affecting working memory, planning/sequencing, task-switching, response inhibition process, memory recall, verbal fluency, as well as many aspect of motor cognition (as psychomotor speed) (Goldman et al., 2014), today it is well documented that attention deficits (such as impaired vigilance with fluctuating level of alertness) (Ballard et al., 2002), language (Bocanegra, Gracia, Trujillo, Slachevsky, & Ibanez, 2015), visuospatial

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

7

(difficulties with the perception of extra personal space and in recognizing objects based on their form) (Kida, Tachibana, Takeda, Yoshikawa, & Okita, 2007; Montse, Pere, Carme, Francesc, & Eduardo, 2001), and memory deficits (with free recall retrieval more prominent at the earlier stage of the disease) (Costa et al., 2014) can also be found at various stage of the disease progression (Aarsland et al., 2017; Biundo, Weis, et al., 2013; Kehagia, Barker, & Robbins, 2010; Muslimovic, Post, Speelman, & Schmand, 2005).

2. ROLE OF NONPHARMACOLOGICAL INTERVENTIONS Among NMS several largely suboptimal pharmacological options have been tested for the treatment of cognitive impairment in PD, particularly for PDD. The positive effects of levodopa therapy could be either linked to alertness, mood, and arousal or more specific for some components of information processing, working memory, or internal control of attention (Pillon, Boller, Levy, & Dubois, 2001). These beneficial effects, however, may be complicated by adverse effects such as confusion and psychosis, more prominent in demented patients (Hietanen & Teravainen, 1988; Sacks, Marjorie, Kohl, Messeloff, & Schwartz, 1972). So far, rivastigmine is the only drug approved by the Food and Drug Administration (FDA) for PDD (Szeto & Lewis, 2016). Therefore, nonpharmacologic therapy may be considered as first-line treatment of dementia, and medications can be used when nonpharmacologic therapy fails (Delphin-Combe et al., 2013; Livingston et al., 2014).

2.1 Cognitive Rehabilitation Recently, a large meta-analysis by Norton and colleagues suggested that many dementia cases may be attributed to modifiable risk factors (e.g., vascular risk factors, depression, and cognitive inactivity), supporting justification for early intervention (Norton, Matthews, Barnes, Yaffe, & Brayne, 2014). Nonpharmacological interventions may be best effective in patients with mild or moderate cognitive dysfunction rather than in the presence of severe deficits. Cognitive training (CT) is particularly relevant and is based on the concept that repeated execution of cognitive tasks leads to improved cognitive functions. It can be performed with pen-andpencil exercises or computer-based using individually tailored “game-like” tasks, which frequently provide feedback and motivate subjects to play. CT has been useful in old healthy subjects (Lampit, Hallock, & Valenzuela, 2014) and in various pathological conditions such as traumatic brain injury

ARTICLE IN PRESS 8

Roberta Biundo et al.

(Chen, Thomas, Glueckauf, & Bracy, 2009), schizophrenia, Alzheimer’s disease, and dementia (Huntley, Gould, Liu, Smith, & Howard, 2015) and, more recently, MCI (non-PD) (Coyle, Traynor, & Solowij, 2015). Notably, evidence on these two groups (MCI and dementia) showed that broader-focused interventions rather than a specific domains training, measuring behavior and well-being outcomes, could be more efficient to stimulate cognition in patients with diffuse brain deficits (Huntley et al., 2015; Mowszowski, Batchelor, & Naismith, 2010; Woods, Spector, Prendergast, Orrell, & Woods, 2005). Several studies also have been performed to evaluate the efficacy of CT in PD. We will now review evidence on nonpharmacological RCTs in PD, discussing practical considerations that may help the development of high quality trials in PD. 2.1.1 Computerized and “Pen and Pencil” CT Studies In a small controlled study using neuroimaging together with CT, 10 PD (5 enrolled in the training group and 5 in controls) and 10 healthy subjects were assessed with functional magnetic resonance (fMRI) during cognitive testing using a modified Stroop test. The experimental group performed daily, easy-level Sudoku at home for 6 months, whereas the control group performed no specific activity. The trained PD group had faster reaction time (RT) on the Stroop task, performed Sudoku more quickly, and showed increased inhibition/set shifting and logical reasoning functions compared to untrained control group. Moreover, they showed brain activation during the Stroop task similar to that of control group. The authors suggested that CT induces cortical plasticity (Nombela et al., 2011) but small sample size, and lack of randomization (participants were voluntary) were significant study limits. In a controlled study, participants (35 PD vs 15 control group PD) performed 14 individually tailored computer based treatment (NEAR) sessions over 2 weeks and improved more than the waitlist control group on learning and memory retention. However, due to the complexity of the study, it is difficult to generalize data to the overall PD population (Naismith, Mowszowski, Diamond, & Lewis, 2013). A randomized, controlled study by Edwards et al. (2013) consisting of 3 months (three times a week, 1-h session) of a computerized, self-administered, home based, processing speed training intervention (SOPT program) on useful field of view (UFOV), self-rated cognition, and depressive symptoms. Both groups ameliorated in UFOV task but no significant changes were observed for other variables. It is worth to underlie that participants were cognitively intact PD with mild motor deficits. Comparing the effect of two different

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

9

treatments [cognition-specific computer-based CT program (N ¼ 19) vs a motion-controlled computer sports game: Nintendo Wii (N ¼ 20)] three times per week for 4 weeks, Zimmermann et al. (2014) found no benefit in enhancing cognition. Conversely, in a randomized control trial, Cerasa et al. (2014) observed greater efficacy of tailored computer-based attention-working memory tasks (by means of the RehaCOM) compared to simple visual-motor tapping tasks in a group of PD patients showing only focal attention–executive task. Interestingly, compared to controls (N ¼ 7), the experimental group (N ¼ 8) showed additionally overactivity of parietal– dorsolateral prefrontal cortex areas after treatment. Authors interpreted these finding as a “compensatory brain mechanisms” to achieve normal cognitive performance. Moreover, not like other studies, which generally employed nonspecific interventions and PD with heterogeneous cognitive deficits (Paris et al., 2011; Pena et al., 2014; Pompeu et al., 2012), this investigation stresses the importance to adopt tailored cognitive rehabilitation program in homogeneous cognitively impaired PD to obtain more effective results. Indeed, a recent randomized control study (Adamski, Adler, Opwis, & Penner, 2016) highlighted the suitability of a specific cognitive intervention to improve cognitive vulnerabilities in PD as well as in healthy older people. To our knowledge, only two RCTs studies (Petrelli et al., 2015; Reuter, Mehnert, Sammer, Oechsner, & Engelhardt, 2012) reported follow-up data of CT in PD. One, using a combined approach of CT and exercise training, found positive results 6 months after the end of treatment (Reuter et al., 2012). PD patients who participated in one of the 6-week CT programs (structured intervention by means of Neurovitalis and unstructured mental fit program), 12 sessions, 90-min each, maintained their overall cognitive functions 1 year after intervention and widely showed response to trainings compared to an inactive control group and had a reduced risk of developing MCI (structured trained group > unstructured trained group) (Petrelli et al., 2015). Indeed, a recent systematic review by Leung et al. (2015), including 7 RCTs and 272 PD patients, suggests that CT leads to measurable improvements in PD cognitive performance particularly in working memory, executive functioning, and processing speed, which are typically impaired in the disease. However, results demonstrated only a modest overall effect (g ¼ 0.23, 95% confidence interval 0.014–0.44, P ¼ 0.037) of CT on cognitive function in mild to moderate PD. Due to the observed mild efficacy of CT as repeated practice of specific cognitive tasks in mild dementia patients, new direction studies launch into the concept of cognitive rehabilitation (CR) as a more personally relevant goals strategies (Bahar-Fuchs,

ARTICLE IN PRESS 10

Roberta Biundo et al.

Clare, & Woods, 2013). The CORD-PD is an ongoing “goal-oriented cognitive rehabilitation” trial, similar to the multicenter single-blinded randomized controlled trial (GREAT) developed for people with AD or mixed dementia (Clare et al., 2013). These studies aim at obtaining definitive evidence on efficacy and cost-effectiveness of goal-oriented CR (Hindle et al., 2016b).

2.2 Physical Exercise Exercise is among the potential protective lifestyle factors identified in delaying progression of cognitive deficits (Lautenschlager, Cox, & Kurz, 2010). In a recent pilot study, balance and gait skills showed significant correlations with some cognitive features in Parkinsonian patients (Varalta et al., 2015). These findings put the basis for the implementation of combined treatments (such as rehabilitative cognitive and motor interventions) to boost efficacy on cognition. Picelli (2016), in a recent pilot, randomized, controlled trial, evaluated the effects of treadmill training on cognitive and motor performance in mild to moderate PD. They found significant improvements in cognitive performance (as measured by the FAB-it, the TMT) and motor performance (as measured by the 6MWT and the 10MWT) in the experimental PD group who underwent a training program consisting of 4 weeks of treadmill training without body weight support. Furthermore, they also showed significant mood and motor improvements (as measured by the BDI and the UPDRS). Aerobic training has been reported to improve cognition in healthy old adult, especially for executive control process (Colcombe et al., 2003). Exercise may also improve general cognitive functions in MCI and AD (Hernandez, Coelho, Gobbi, & Stella, 2010). A meta-analysis of RCTs (29 studies, 2049 participants) has indicated that healthy older adults reliably achieve modest improvements in attention and processing speed, executive function, and memory following aerobic training. Moreover aerobic exercise may be associated with greater memory improvements among adults with MCI relative to cognitively intact adults (Smith et al., 2010). A recent Cochrane systematic review (2015), based mostly on AD data, suggests that exercise may improve activities of daily living delaying the need of caregiver dependence and resulting in significant quality of life benefits for patients and caregivers, and possibly delaying the need for placement in long-term care institutions. No trials reported adverse events related to exercise programs (Forbes, Forbes, Blake, Thiessen, & Forbes, 2015), while the quality of the evidence was judged very low.

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

11

Aerobic and resistance exercises may improve cognition in PD but larger, well-controlled studies are warrented (Reynolds, Otto, Ellis, & Cronin-Golomb, 2016). Combined aerobic and anabolic exercise, conducted twice weekly for 12 weeks, resulted in selective improvement in frontal-based executive function in 15 PD compared to 13 nonexercising PD controls (Cruise et al., 2011). Likewise, 6 months of moderate-intensity aerobic exercise, conducted three times per week for 45–60 min, led to improved executive functioning for individuals with mild to moderate PD (mean age of approximately 65 in both studies), though only one of these studies used nonexercising PD control group (Uc et al., 2014). At the same time, recent evidence suggests that resistance exercise may also benefit cognition in PD. After 24 months of twice weekly progressive resistance exercise (60–90 min per session), adults with PD improved their performance on measures of working memory, inhibition, and attention (Digit Span, Stroop, Brief Test of Attention) (David et al., 2015). Further research is warranted to examine the underlying mechanisms driving these selective improvements (such as increased cerebral perfusion, release of growth factors, angiogenesis following aerobic exercise or increasing volume thickness in prefrontal regions) (Colcombe et al., 2006; Tabak, Aquije, & Fisher, 2013). Taken together, emerging research suggests that aerobic and resistance exercise may improve cognition in PD and particularly fronto-executive abilities. 2.2.1 Noninvasive Brain Stimulation Interventions Over the last 15 years, noninvasive brain stimulation (NIBS) techniques such as repetitive transcranial magnetic stimulation (rTMS) or direct current stimulation (tDCS) have been tested to boost the outcome of cognitive rehabilitation in patients with neurological disorders (Rossini et al., 2015). Recent research has highlighted the potential of tDCS, as a safer, painless, low-cost technique and more user-friendly than rTMS for neurological and NPSI rehabilitations, to complement and enhance neuroplasticity and learning in patients with neurological disorders and older individuals (de Aguiar et al., 2015; Floel, 2014; Liu, Fregni, Hummel, & Pascual-Leone, 2012). tDCS is a technique eliciting constant weak electric currents through the scalp via two electrodes (anode and cathode), which has been shown to modulate excitability in cortical and subcortical tissue and may therefore facilitate cell plasticity (for review, see Lefaucheur et al., 2017). Additionally, other mechanisms, such as dynamic modulation of synaptic efficacy, induction of the release of neurotransmitters (dopamine release in the caudate nucleus), resting membrane potentials modification

ARTICLE IN PRESS 12

Roberta Biundo et al.

(mediated by changes in N-methyl-D-aspartate-receptor activation and GABAergic inhibition), and modulation of functional connectivity of the corticostriatal and thalamocortical circuits in the human brain, may be also involved (Parasuraman & McKinley, 2014; Polania, Nitsche, & Paulus, 2011; Tanaka et al., 2013). Taken together, these findings lead to consider tDCS as tool to modulate dopaminergic transmission. So far, there are several published tDCS trials aimed at improving various clinical aspects in PD (Benninger & Hallett, 2015; Elsner, Kugler, Pohl, & Mehrholz, 2016). Only three sham-controlled repetitive t-DCS studies focusing on PD motor symptoms are present in literatures suggesting a potential impact of anodal tDCS of M1 on gait and motor symptoms in PD patients, but do not provide sufficient evidence for a recommendation (Benninger et al., 2010; CostaRibeiro et al., 2017; Valentino et al., 2014). Four studies investigated the effects of t-DCS on cognitive functions in nondemented PD (according to Level I criteria or clinically defined), and only two characterized the cognitive status of the patients (Biundo et al., 2016; Manenti et al., 2016). In a crossover study, Boggio et al. (2006) investigated t-DCS effects in 18 nondemented PD (mean age ¼ 61, ranging 45–71; mean MMSE ¼ 24.4) using a three-back working memory task. Patients performed the task during anodal tDCS on L-DLPFC, on motor cortex (M1) and sham. A single session of anodal tDCS of left DLPFC, but not of left M1, improved performance in a working memory task, only at the stimulation intensity of 2 mA. Using tDCS combined with fMRI, Pereira et al. (2013) in another crossover study (16 nondemented PD) showed that phonemic fluency performance increased significantly more after DLPFC tDCS than after temporal–parietal cortex (TPC) stimulation. fMRI data showed that tDCS over the DLPFC enhanced functional connectivity in areas associated with verbal fluency significantly more than when applied over the TPC. Doruk, Gray, Bravo, Pascual-Leone, and Fregni (2014) in a double-blinded randomized study reported the beneficial long-term effect (1 month) of 2 weeks tDCS over the DLPFC on executive function in no-demented PD. Evidence of the use of CT and/or tDCS as therapeutic tools for cognition amelioration in PD, together with the idea of potential increased efficacy when cognitive and physical activities are performed simultaneously (Varalta et al., 2015), stimulated researchers to test if combining different intervention tools could boost treatment effect. In a sham-controlled study of 20 PD patients with PD-MCI (according to Level I criteria), a protocol of 10 sessions of anodal tDCS delivered over the DLPFC contralateral to the most affected body side during a physical therapy program was found to increase cognitive

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

13

performance and verbal fluency only in the active arm group with a stable effect at 3-month follow-up but did not observe additional effects of tDCS on motor or mood performance (Manenti et al., 2016). In our previous study, using sham-controlled design with 16 PD performing 16 sessions of CT (20 min tDCS plus 30 min computer based CT over left DLPFC), we observed increased performance only in fronto-executive task at 3-month follow-up in PD-MCI patients (screened according to level II criteria) and no significant motor changes between groups at end of treatment and follow-up (Biundo et al., 2015). It is noteworthy that although the active group was trained on frontal and visuospatial tasks, they increased their performance only in executive abilities. Moreover, they decreased their performance in a language subitem of the RBANS during the stimulation period to return to baseline performance at the follow-up period. Overall, findings seem to corroborate enhanced executive/attention abilities of repetitive anodal tDCS over the DLPRC in PD patients, but results are highly heterogeneous and evidence, so far, did not reach recommendation level according to recent guidelines (Lefaucheur et al., 2017). As for studies adopting CT alone, tDCS evidence seems to underline the need of specific methodological approaches to obtain consistent results.

3. TELEMEDICINE: THE FUTURE OF REHABILITATION? In the attempt to overcome some challenges linked to healthcare access (uneven distribution of highly specialized clinicians), difficulty in traveling for disabled patients who, for example, would need to reach clinic quite often, if recruited for a rehabilitation treatments, delivering care remotely by telemedicine is becoming one of the most cost-effective and efficient phenomenon (Achey et al., 2014). Ongoing studies have been implemented. A RCT study offers patients the possibility to practice aerobic exercise and gaming at home, with the use of devices which allow individualized treatments and can be monitored by clinicians and patients by remote access and iPad (van der Kolk et al., 2015). Of interest it is also the possibility to monitor remotely the daily living functions of patients using wearable sensors, for example, smartphone apps can be used to monitor mood, effect of pharmacological treatment on cognitions and speech, insoles and wrists bracelets to monitor physical activities (gait), etc. (Arora et al., 2015; Cancela et al., 2016). Canada (the Ontario Telemedicine Network) and the Netherlands (ParkinsonNet approach) already use telemedicine successfully in daily

ARTICLE IN PRESS 14

Roberta Biundo et al.

practice (Arora et al., 2015; Bloem & Munneke, 2014). Validity of these findings remains an issue but ongoing technology advances will offer the opportunity for cognitive rehabilitation treatment implementation at home.

4. DISCUSSION In PD, cognitive alterations are the most disabling NMS, as the 80% of patients will experience dementia after 10–15 years of pathology. The complex and heterogeneous nature of the cognitive phenotype in PD unfortunately made the search for “dementia potential risk patients” very challenging. This issue has slowed down the progress for new effective treatments and so far, quality of life and well-being of patients and caregiver is very poor. Implementation of protocols for cognitive rehabilitation in PD has focused mainly on executive-frontal abilities including working memory, planning/sequencing, task-switching, response inhibition process, and memory recall, which are the most vulnerable skills and represent important processes for everyday functioning and quality of life. Although dopaminergic treatment can ameliorate some frontal-functional based abilities, pharmacological therapy continues to be largely ineffective and the overall cognitive deficiencies remain undiagnosed and untreated. Over the past decade alternative approaches have been developed to enhance cognition in PD, including computer-based CT, physical therapy, and NIBS techniques. The state of art suggests that an intensive computerized CT program (3/4 times a week for 4 weeks) and anodal tDCS stimulation (2 mA) over the dorsolateral prefrontal cortex (applied by itself or as combined approaches) can be an useful tool in improving the most vulnerable (frontal-executive skills) abilities in PD patients. Although promising, high quality trial evidence is lacking. A generic critique is that long-term effectiveness of most treatments remains unknown because absence of homogeneous cognitive profile at baseline, adequate sample sizes, controlled untreated group, significant clinical effects reflecting changes in behavioral symptoms, quality of life, and well-being. Moreover, it is not clear if all domains are equally treatable, frontal-executive domains seems to modestly improve after rehabilitation; however, specific protocol for other domains is not implemented so far. In addition, further large sample studies need to explore the end of treatment and follow-up effect of combined treatments (particularly if the same network is simultaneously simulated) as potential temporary breakdown can occur as product of overstimulation. In addition, it is highly recommended

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

15

to use “ad-hoc protocol” if demented patients are included in the study. Finally, patient-tailored therapeutic application of brain stimulation techniques might be developed in the future, especially in the light of new findings, which show profound interindividual variability of cortical. The state of art suggests that rehabilitation in PD is potentially possible in term of either increased cognitive outcome or maintenance of cognitive level over the time particularly if it is adopted before dementia has established. The success of this challenging strategy depends on improved characterization of cognitive phenotype in PD, identification of the most sensitive clinical variables in term of quality of life and worldwide consensus about treatment guidelines for implementation of efficacy studies.

REFERENCES Aarsland, D., Andersen, K., Larsen, J. P., & Lolk, A. (2003). Prevalence and characteristics of dementia in Parkinson disease. Archives of Neurology, 60(3), 387. Aarsland, D., Bronnick, K., Larsen, J. P., Tysnes, O. B., Alves, G., & Norwegian ParkWest Study Group. (2009). Cognitive impairment in incident, untreated Parkinson disease: The Norwegian ParkWest study. Neurology, 72(13), 1121–1126. Aarsland, D., Creese, B., Politis, M., Chaudhuri, K. R., Ffytche, D. H., Weintraub, D., et al. (2017). Cognitive decline in Parkinson disease. Nature Reviews. Neurology, 13(4), 217–231. Aarsland, D., & Kurz, M. W. (2010). The epidemiology of dementia associated with Parkinson’s disease. Brain Pathology, 20(3), 633–639. Aarsland, D., Perry, R., Brown, A., Larsen, J. P., & Ballard, C. (2005). Neuropathology of dementia in Parkinson’s disease: A prospective, community-based study. Annals of Neurology, 58(5), 773–776. Abbott, R. D., Ross, G. W., Petrovitch, H., Tanner, C. M., Davis, D. G., Masaki, K. H., et al. (2007). Bowel movement frequency in late-life and incidental Lewy bodies. Movement Disorders, 22(11), 1581–1586. Achey, M., Aldred, J. L., Aljehani, N., Bloem, B. R., Biglan, K. M., Chan, P., et al. (2014). The past, present, and future of telemedicine for Parkinson’s disease. Movement Disorders, 29(7), 871–883. Adamski, N., Adler, M., Opwis, K., & Penner, I. K. (2016). A pilot study on the benefit of cognitive rehabilitation in Parkinson’s disease. Therapeutic Advances in Neurological Disorders, 9(3), 153–164. Adler, C. H., Caviness, J. N., Sabbagh, M. N., Shill, H. A., Connor, D. J., Sue, L., et al. (2010). Heterogeneous neuropathological findings in Parkinson’s disease with mild cognitive impairment. Acta Neuropathologica, 120(6), 827–828. Akaogi, Y., Asahina, M., Yamanaka, Y., Koyama, Y., & Hattori, T. (2009). Sudomotor, skin vasomotor, and cardiovascular reflexes in 3 clinical forms of Lewy body disease. Neurology, 73(1), 59–65. Arora, S., Venkataraman, V., Zhan, A., Donohue, S., Biglan, K. M., Dorsey, E. R., et al. (2015). Detecting and monitoring the symptoms of Parkinson’s disease using smartphones: A pilot study. Parkinsonism & Related Disorders, 21(6), 650–653. Bahar-Fuchs, A., Clare, L., & Woods, B. (2013). Cognitive training and cognitive rehabilitation for mild to moderate Alzheimer’s disease and vascular dementia. Cochrane Database of Systematic Reviews, 6, CD003260.

ARTICLE IN PRESS 16

Roberta Biundo et al.

Ballard, C. G., Aarsland, D., McKeith, I., O’Brien, J., Gray, A., Cormack, F., et al. (2002). Fluctuations in attention: PD dementia vs DLB with parkinsonism. Neurology, 59(11), 1714–1720. Barone, P., Aarsland, D., Burn, D., Emre, M., Kulisevsky, J., & Weintraub, D. (2011). Cognitive impairment in nondemented Parkinson’s disease. Movement Disorders, 26(14), 2483–2495. Benninger, D. H., & Hallett, M. (2015). Non-invasive brain stimulation for Parkinson’s disease: Current concepts and outlook 2015. NeuroRehabilitation, 37(1), 11–24. Benninger, D. H., Lomarev, M., Lopez, G., Wassermann, E. M., Li, X., Considine, E., et al. (2010). Transcranial direct current stimulation for the treatment of Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 81(10), 1105–1111. Bereczki, E., Francis, P. T., Howlett, D., Pereira, J. B., Hoglund, K., Bogstedt, A., et al. (2016). Synaptic proteins predict cognitive decline in Alzheimer’s disease and Lewy body dementia. Alzheimers & Dementia, 12(11), 1149–1158. Biundo, R., Weis, L., Facchini, S., Formento-Dojot, P., Vallelunga, A., Pilleri, M., et al. (2014). Cognitive profiling of Parkinson disease patients with mild cognitive impairment and dementia. Parkinsonism & Related Disorders, 20(4), 394–399. Biundo, R., Weis, L., Fiorenzato, E., Gentile, G., Giglio, M., Schifano, R., et al. (2015). Double-blind randomized trial of t-DCS versus sham in Parkinson patients with mild cognitive impairment receiving cognitive training. Brain Stimulation, 8(6), 1223–1225. Biundo, R., Weis, L., Fiorenzato, E., Gentile, G., Giglio, M., Schifano, R., et al. (2016). Erratum to “double-blind randomized trial of tDCS versus sham in Parkinson patients with mild cognitive impairment receiving cognitive training”. Brain Stimulation 8 (2015) 1223–1225. Brain Stimulation, 9(3), 474. Biundo, R., Weis, L., Pilleri, M., Facchini, S., Formento-Dojot, P., Vallelunga, A., et al. (2013b). Diagnostic and screening power of neuropsychological testing in detecting mild cognitive impairment in Parkinson’s disease. Journal of Neural Transmission, 120(4), 627–633. Bloem, B. R., & Munneke, M. (2014). Revolutionising management of chronic disease: The ParkinsonNet approach. BMJ, 348, g1838. Bocanegra, Y., Gracia, A., Trujillo, N., Slachevsky, A., & Ibanez, A. (2015). Syntax, action verbs, and nouns in Parkinson’s disease: Dissociability, progression and executive influences. Journal of the Neurological Sciences, 357, e270–e271. Boggio, P. S., Ferrucci, R., Rigonatti, S. P., Covre, P., Nitsche, M., Pascual-Leone, A., et al. (2006). Effects of transcranial direct current stimulation on working memory in patients with Parkinson’s disease. Journal of the Neurological Sciences, 249(1), 31–38. Bohnen, N. I., Kaufer, D. I., Hendrickson, R., Ivanco, L. S., Lopresti, B. J., Constantine, G. M., et al. (2006). Cognitive correlates of cortical cholinergic denervation in Parkinson’s disease and parkinsonian dementia. Journal of Neurology, 253(2), 242–247. Bohnen, N. I., Kaufer, D. I., Ivanco, L. S., Lopresti, B., Koeppe, R. A., Davis, J. G., et al. (2003). Cortical cholinergic function is more severely affected in parkinsonian dementia than in Alzheimer disease: An in vivo positron emission tomographic study. Archives of Neurology, 60(12), 1745–1748. Braak, H., Ghebremedhin, E., Rub, U., Bratzke, H., & Del Tredici, K. (2004). Stages in the development of Parkinson’s disease-related pathology. Cell and Tissue Research, 318(1), 121–134. Buter, T. C., van den Hout, A., Matthews, F. E., Larsen, J. P., Brayne, C., & Aarsland, D. (2008). Dementia and survival in Parkinson disease: A 12-year population study. Neurology, 70(13), 1017–1022. Cancela, J., Villanueva Mascato, S., Gatsios, D., Rigas, G., Marcante, A., Gentile, G., et al. (2016). Monitoring of motor and non-motor symptoms of Parkinson’s disease through a mHealth platform. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016, 663–666.

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

17

Cash, R., Dennis, T., L’Heureux, R., Raisman, R., Javoy-Agid, F., & Scatton, B. (1987). Parkinson’s disease and dementia: Norepinephrine and dopamine in locus ceruleus. Neurology, 37(1), 42. Cerasa, A., Gioia, M. C., Salsone, M., Donzuso, G., Chiriaco, C., Realmuto, S., et al. (2014). Neurofunctional correlates of attention rehabilitation in Parkinson’s disease: An explorative study. Neurological Sciences, 35(8), 1173–1180. Chaudhuri, K. R., Martinez-Martin, P., Schapira, A. H., Stocchi, F., Sethi, K., Odin, P., et al. (2006). International multicenter pilot study of the first comprehensive selfcompleted nonmotor symptoms questionnaire for Parkinson’s disease: The NMSQuest study. Movement Disorders, 21(7), 916–923. Chaudhuri, K. R., & Schapira, A. H. V. (2009). Non-motor symptoms of Parkinson’s disease: Dopaminergic pathophysiology and treatment. The Lancet Neurology, 8(5), 464–474. Chen, S. H. A., Thomas, J. D., Glueckauf, R. L., & Bracy, O. L. (2009). The effectiveness of computer-assisted cognitive rehabilitation for persons with traumatic brain injury. Brain Injury, 11(3), 197–210. Clare, L., Bayer, A., Burns, A., Corbett, A., Jones, R., Knapp, M., et al. (2013). Goaloriented cognitive rehabilitation in early-stage dementia: Study protocol for a multicentre single-blind randomised controlled trial (GREAT). Trials, 14, 152. Colcombe, S. J., Erickson, K. I., Raz, N., Webb, A. G., Cohen, N. J., McAuley, E., et al. (2003). Aerobic fitness reduces brain tissue loss in aging humans. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 58(2), M176–M180. Colcombe, S. J., Erickson, K. I., Scalf, P. E., Kim, J. S., Prakash, R., McAuley, E., et al. (2006). Aerobic exercise training increases brain volume in aging humans. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 61(11), 1166–1170. Compta, Y., Parkkinen, L., O’Sullivan, S. S., Vandrovcova, J., Holton, J. L., Collins, C., et al. (2011). Lewy- and Alzheimer-type pathologies in Parkinson’s disease dementia: Which is more important? Brain, 134(Pt. 5), 1493–1505. Costa, A., Monaco, M., Zabberoni, S., Peppe, A., Perri, R., Fadda, L., et al. (2014). Free and cued recall memory in Parkinson’s disease associated with amnestic mild cognitive impairment. PLoS One, 9(1), e86233. Costa-Ribeiro, A., Maux, A., Bosford, T., Aoki, Y., Castro, R., Baltar, A., et al. (2017). Transcranial direct current stimulation associated with gait training in Parkinson’s disease: A pilot randomized clinical trial. Developmental Neurorehabilitation, 20(3), 121–128. Coyle, H., Traynor, V., & Solowij, N. (2015). Computerized and virtual reality cognitive training for individuals at high risk of cognitive decline: Systematic review of the literature. The American Journal of Geriatric Psychiatry, 23(4), 335–359. Cruise, K. E., Bucks, R. S., Loftus, A. M., Newton, R. U., Pegoraro, R., & Thomas, M. G. (2011). Exercise and Parkinson’s: Benefits for cognition and quality of life. Acta Neurologica Scandinavica, 123(1), 13–19. David, F. J., Robichaud, J. A., Leurgans, S. E., Poon, C., Kohrt, W. M., Goldman, J. G., et al. (2015). Exercise improves cognition in Parkinson’s disease: The PRET-PD randomized, clinical trial. Movement Disorders, 30(12), 1657–1663. de Aguiar, V., Bastiaanse, R., Capasso, R., Gandolfi, M., Smania, N., Rossi, G., et al. (2015). Can tDCS enhance item-specific effects and generalization after linguistically motivated aphasia therapy for verbs? Frontiers in Behavioral Neuroscience, 9, 190. de Rijk, M. C., Tzourio, C., Breteler, M. M., Dartigues, J. F., Amaducci, L., Lopez-Pousa, S., et al. (1997). Prevalence of parkinsonism and Parkinson’s disease in Europe: The EUROPARKINSON Collaborative Study. European Community Concerted Action on the Epidemiology of Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 62(1), 10–15. Delaville, C., Deurwaerdere, P. D., & Benazzouz, A. (2011). Noradrenaline and Parkinson’s disease. Frontiers in Systems Neuroscience, 5, 31.

ARTICLE IN PRESS 18

Roberta Biundo et al.

Delphin-Combe, F., Martin-Gaujard, G., Roubaud, C., Fortin, M. E., Husson, F., Rouch, I., et al. (2013). Experience of a care pathway for psychological and behavioral symptoms of dementia. Geriatrie et Psychologie Neuropsychiatrie du Vieillissement, 11(4), 416–422. Dorsey, E. R., Constantinescu, R., Thompson, J. P., Biglan, K. M., Holloway, R. G., Kieburtz, K., et al. (2007). Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology, 68(5), 384–386. Doruk, D., Gray, Z., Bravo, G. L., Pascual-Leone, A., & Fregni, F. (2014). Effects of tDCS on executive function in Parkinson’s disease. Neuroscience Letters, 582, 27–31. Duncan, G. W., Khoo, T. K., Yarnall, A. J., O’Brien, J. T., Coleman, S. Y., Brooks, D. J., et al. (2014). Health-related quality of life in early Parkinson’s disease: The impact of nonmotor symptoms. Movement Disorders, 29(2), 195–202. Edwards, J. D., Hauser, R. A., O’Connor, M. L., Valdes, E. G., Zesiewicz, T. A., & Uc, E. Y. (2013). Randomized trial of cognitive speed of processing training in Parkinson disease. Neurology, 81(15), 1284–1290. Elsner, B., Kugler, J., Pohl, M., & Mehrholz, J. (2016). Transcranial direct current stimulation (tDCS) for idiopathic Parkinson’s disease. Cochrane Database of Systematic Reviews, 7, CD010916. Floel, A. (2014). tDCS-enhanced motor and cognitive function in neurological diseases. NeuroImage, 85(Pt. 3), 934–947. Forbes, D., Forbes, S. C., Blake, C. M., Thiessen, E. J., & Forbes, S. (2015). Exercise programs for people with dementia. Cochrane Database of Systematic Reviews, 4, CD006489. Gibb, W. R., & Lees, A. J. (1988). The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 51(6), 745–752. Goldman, J. G., Williams-Gray, C., Barker, R. A., Duda, J. E., & Galvin, J. E. (2014). The spectrum of cognitive impairment in Lewy body diseases. Movement Disorders, 29(5), 608–621. Goldstein, D. S. (2006). Orthostatic hypotension as an early finding in Parkinson’s disease. Clinical Autonomic Research, 16(1), 46–54. Granert, O., Drzezga, A. E., Boecker, H., Perneczky, R., Kurz, A., Gotz, J., et al. (2015). Metabolic topology of neurodegenerative disorders: Influence of cognitive and motor deficits. Journal of Nuclear Medicine, 56(12), 1916–1921. Halliday, G. M., Leverenz, J. B., Schneider, J. S., & Adler, C. H. (2014). The neurobiological basis of cognitive impairment in Parkinson’s disease. Movement Disorders, 29(5), 634–650. Hanganu, A., Provost, J. S., & Monchi, O. (2015). Neuroimaging studies of striatum in cognition part II: Parkinson’s disease. Frontiers in Systems Neuroscience, 9, 138. Hely, M. A., Reid, W. G., Adena, M. A., Halliday, G. M., & Morris, J. G. (2008). The Sydney multicenter study of Parkinson’s disease: The inevitability of dementia at 20 years. Movement Disorders, 23(6), 837–844. Hernandez, S. S., Coelho, F. G., Gobbi, S., & Stella, F. (2010). Effects of physical activity on cognitive functions, balance and risk of falls in elderly patients with Alzheimer’s dementia. Brazilian Journal of Physical Therapy, 14(1), 68–74. Hietanen, M., & Teravainen, H. (1988). Dementia and treatment with L-dopa in Parkinson’s disease. Movement Disorders, 3(3), 263–270. Hindle, J. V., Watermeyer, T. J., Roberts, J., Martyr, A., Lloyd-Williams, H., Brand, A., et al. (2016b). Cognitive rehabiliation for Parkinson’s disease demantia: A study protocol for a pilot randomised controlled trial. Trials, 17, 152. Hirtz, D., Thurman, D. J., Gwinn-Hardy, K., Mohamed, M., Chaudhuri, A. R., & Zalutsky, R. (2007). How common are the “common” neurologic disorders? Neurology, 68(5), 326–337.

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

19

Huntley, J. D., Gould, R. L., Liu, K., Smith, M., & Howard, R. J. (2015). Do cognitive interventions improve general cognition in dementia? A meta-analysis and metaregression. BMJ Open, 5(4), e005247. Jellinger, K. A. (2013). Mild cognitive impairment in Parkinson disease: Heterogenous mechanisms. Journal of Neural Transmission, 120(1), 157–167. Johnson, S. J., Diener, M. D., Kaltenboeck, A., Birnbaum, H. G., & Siderowf, A. D. (2013). An economic model of Parkinson’s disease: Implications for slowing progression in the United States. Movement Disorders, 28(3), 319–326. Kalia, L. V., & Lang, A. E. (2015). Parkinson’s disease. The Lancet, 386(9996), 896–912. Kehagia, A. A., Barker, R. A., & Robbins, T. W. (2010). Neuropsychological and clinical heterogeneity of cognitive impairment and dementia in patients with Parkinson’s disease. The Lancet Neurology, 9(12), 1200–1213. Kehagia, A. A., Barker, R. A., & Robbins, T. W. (2013). Cognitive impairment in Parkinson’s disease: The dual syndrome hypothesis. Neurodegenerative Diseases, 11(2), 79–92. Kehagia, A. A., Housden, C. R., Regenthal, R., Barker, R. A., Muller, U., Rowe, J., et al. (2014). Targeting impulsivity in Parkinson’s disease using atomoxetine. Brain, 137(Pt. 7), 1986–1997. Ker€anen, T., Kaakkola, S., Sotaniemi, K., Laulumaa, V., Haapaniemi, T., Jolma, T., et al. (2003). Economic burden and quality of life impairment increase with severity of PD. Parkinsonism & Related Disorders, 9(3), 163–168. Khoo, T. K., Yarnall, A. J., Duncan, G. W., Coleman, S., O’Brien, J. T., Brooks, D. J., et al. (2013). The spectrum of nonmotor symptoms in early Parkinson disease. Neurology, 80(3), 276–281. Kida, Y., Tachibana, H., Takeda, M., Yoshikawa, H., & Okita, T. (2007). Recognition memory for unfamiliar faces in Parkinson’s disease: Behavioral and electrophysiologic measures. Parkinsonism & Related Disorders, 13(3), 157–164. Kim, H. S., Cheon, S. M., Seo, J. W., Ryu, H. J., Park, K. W., & Kim, J. W. (2013). Nonmotor symptoms more closely related to Parkinson’s disease: Comparison with normal elderly. Journal of the Neurological Sciences, 324(1–2), 70–73. Kowal, S. L., Dall, T. M., Chakrabarti, R., Storm, M. V., & Jain, A. (2013). The current and projected economic burden of Parkinson’s disease in the United States. Movement Disorders, 28(3), 311–318. Krishnan, S., Sarma, G., Sarma, S., & Kishore, A. (2011). Do nonmotor symptoms in Parkinson’s disease differ from normal aging? Movement Disorders, 26(11), 2110–2113. Lampit, A., Hallock, H., & Valenzuela, M. (2014). Computerized cognitive training in cognitively healthy older adults: a systematic review and meta-analysis of effect modifiers. PLoS Medicine, 11(11), e1001756. Lautenschlager, N. T., Cox, K., & Kurz, A. F. (2010). Physical activity and mild cognitive impairment and Alzheimer’s disease. Current Neurology and Neuroscience Reports, 10(5), 352–358. Lefaucheur, J. P., Antal, A., Ayache, S. S., Benninger, D. H., Brunelin, J., Cogiamanian, F., et al. (2017). Evidence-based guidelines on the therapeutic use of transcranial direct current stimulation (tDCS). Clinical Neurophysiology, 128(1), 56–92. Leung, I. H., Walton, C. C., Hallock, H., Lewis, S. J., Valenzuela, M., & Lampit, A. (2015). Cognitive training in Parkinson disease: A systematic review and meta-analysis. Neurology, 85(21), 1843–1851. Lim, S. Y., & Lang, A. E. (2010). The nonmotor symptoms of Parkinson’s disease—An overview. Movement Disorders, 25(Suppl. 1), S123–S130. Liu, A., Fregni, F., Hummel, F., & Pascual-Leone, A. (2012). Therapeutic applications of transcranial magnetic stimulation/transcranial direct current stimulation in Neurology. In: Transcranial brain stimulation (pp. 359–412). Boca Raton: CRC Press.

ARTICLE IN PRESS 20

Roberta Biundo et al.

Livingston, G., Kelly, L., Lewis-Holmes, E., Baio, G., Morris, S., Patel, N., et al. (2014). A systematic review of the clinical effectiveness and cost-effectiveness of sensory, psychological and behavioural interventions for managing agitation in older adults with dementia. Health Technology Assessment, 18(39), 1–226. v–vi. Manenti, R., Brambilla, M., Benussi, A., Rosini, S., Cobelli, C., Ferrari, C., et al. (2016). Mild cognitive impairment in Parkinson’s disease is improved by transcranial direct current stimulation combined with physical therapy. Movement Disorders, 31(5), 715–724. Martinez-Martin, P., Rodriguez-Blazquez, C., Kurtis, M. M., Chaudhuri, K. R., & NMSS Validation Group. (2011). The impact of non-motor symptoms on healthrelated quality of life of patients with Parkinson’s disease. Movement Disorders, 26(3), 399–406. McMillan, P. J., White, S. S., Franklin, A., Greenup, J. L., Leverenz, J. B., Raskind, M. A., et al. (2011). Differential response of the central noradrenergic nervous system to the loss of locus coeruleus neurons in Parkinson’s disease and Alzheimer’s disease. Brain Research, 1373, 240–252. Meyer, P. M., Strecker, K., Kendziorra, K., Becker, G., Hesse, S., Woelpl, D., et al. (2009). Reduced alpha4beta2*-nicotinic acetylcholine receptor binding and its relationship to mild cognitive and depressive symptoms in Parkinson disease. Archives of General Psychiatry, 66(8), 866–877. Montse, A., Pere, V., Carme, J., Francesc, V., & Eduardo, T. (2001). Visuospatial deficits in Parkinson’s disease assessed by judgment of line orientation test: Error analyses and practice effects. Journal of Clinical and Experimental Neuropsychology, 23(5), 592–598. Mowszowski, L., Batchelor, J., & Naismith, S. L. (2010). Early intervention for cognitive decline: Can cognitive training be used as a selective prevention technique? International Psychogeriatrics, 22(4), 537–548. Muslimovic, D., Post, B., Speelman, J. D., & Schmand, B. (2005). Cognitive profile of patients with newly diagnosed Parkinson disease. Neurology, 65(8), 1239–1245. Naismith, S. L., Mowszowski, L., Diamond, K., & Lewis, S. J. (2013). Improving memory in Parkinson’s disease: A healthy brain ageing cognitive training program. Movement Disorders, 28(8), 1097–1103. Nombela, C., Bustillo, P. J., Castell, P. F., Sanchez, L., Medina, V., & Herrero, M. T. (2011). Cognitive rehabilitation in Parkinson’s disease: Evidence from neuroimaging. Frontiers in Neurology, 2, 82. Norton, S., Matthews, F. E., Barnes, D. E., Yaffe, K., & Brayne, C. (2014). Potential for primary prevention of Alzheimer’s disease: An analysis of population-based data. The Lancet Neurology, 13(8), 788–794. Olesen, J., Gustavsson, A., Svensson, M., Wittchen, H. U., Jonsson, B., CDBE2010 Study Group, et al. (2012). The economic cost of brain disorders in Europe. European Journal of Neurology, 19(1), 155–162. Pagonabarraga, J., & Kulisevsky, J. (2012). Cognitive impairment and dementia in Parkinson’s disease. Neurobiology of Disease, 46(3), 590–596. Parasuraman, R., & McKinley, R. A. (2014). Using noninvasive brain stimulation to accelerate learning and enhance human performance. Human Factors, 56(5), 816–824. Paris, A. P., Saleta, H. G., de la Cruz Crespo Maraver, M., Silvestre, E., Freixa, M. G., Torrellas, C. P., et al. (2011). Blind randomized controlled study of the efficacy of cognitive training in Parkinson’s disease. Movement Disorders, 26(7), 1251–1258. Pedersen, K. F., Larsen, J. P., Tysnes, O. B., & Alves, G. (2013). Prognosis of mild cognitive impairment in early Parkinson disease: The Norwegian ParkWest study. JAMA Neurology, 70(5), 580–586. Pena, J., Ibarretxe-Bilbao, N., Garcia-Gorostiaga, I., Gomez-Beldarrain, M. A., DiezCirarda, M., & Ojeda, N. (2014). Improving functional disability and cognition in Parkinson disease: Randomized controlled trial. Neurology, 83(23), 2167–2174.

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

21

Pereira, J. B., Junque, C., Bartres-Faz, D., Marti, M. J., Sala-Llonch, R., Compta, Y., et al. (2013). Modulation of verbal fluency networks by transcranial direct current stimulation (tDCS) in Parkinson’s disease. Brain Stimulation, 6(1), 16–24. Petrelli, A., Kaesberg, S., Barbe, M. T., Timmermann, L., Rosen, J. B., Fink, G. R., et al. (2015). Cognitive training in Parkinson’s disease reduces cognitive decline in the long term. European Journal of Neurology, 22(4), 640–647. Pfeiffer, R. F. (2016). Non-motor symptoms in Parkinson’s disease. Parkinsonism & Related Disorders, 22(Suppl. 1), S119–S122. Picelli, A. (2016). Effects of treadmill training on cognitive and motor features of patients with mild to moderate Parkinson’s disease: A pilot, single-blind, randomized controlled trial. Functional Neurology, 31(1), 25–31. Picillo, M., Palladino, R., Barone, P., Erro, R., Colosimo, C., Marconi, R., et al. (2017). The PRIAMO study: Urinary dysfunction as a marker of disease progression in early Parkinson’s disease. European Journal of Neurology, 24(6), 788–795. Pienaar, I. S., Burn, D., Morris, C., & Dexter, D. (2012). Synaptic protein alterations in Parkinson’s disease. Molecular Neurobiology, 45(1), 126–143. Pigott, K., Rick, J., Xie, S. X., Hurtig, H., Chen-Plotkin, A., Duda, J. E., et al. (2015). Longitudinal study of normal cognition in Parkinson disease. Neurology, 85(15), 1276–1282. Pillon, B., Boller, F., Levy, R., & Dubois, B. (2001). Cognitive deficits and dementia in Parkinson’s disease. In F. Boller & S. Cappa (Eds.), Handbook of neuropsychology (2nd ed., pp. 311–371). Amsterdam: Elsevier Science. Polania, R., Nitsche, M. A., & Paulus, W. (2011). Modulating functional connectivity patterns and topological functional organization of the human brain with transcranial direct current stimulation. Human Brain Mapping, 32(8), 1236–1249. Polli, A., Weis, L., Biundo, R., Thacker, M., Turolla, A., Koutsikos, K., et al. (2016). Anatomical and functional correlates of persistent pain in Parkinson’s disease. Movement Disorders, 31(12), 1854–1864. Pompeu, J. E., Mendes, F. A., Silva, K. G., Lobo, A. M., Oliveira Tde, P., Zomignani, A. P., et al. (2012). Effect of Nintendo Wii-based motor and cognitive training on activities of daily living in patients with Parkinson’s disease: A randomised clinical trial. Physiotherapy, 98(3), 196–204. Ponsen, M. M., Stoffers, D., Booij, J., van Eck-Smit, B. L., Wolters, E., & Berendse, H. W. (2004). Idiopathic hyposmia as a preclinical sign of Parkinson’s disease. Annals of Neurology, 56(2), 173–181. Postuma, R. B., Aarsland, D., Barone, P., Burn, D. J., Hawkes, C. H., Oertel, W., et al. (2012). Identifying prodromal Parkinson’s disease: Pre-motor disorders in Parkinson’s disease. Movement Disorders, 27(5), 617–626. Reuter, I., Mehnert, S., Sammer, G., Oechsner, M., & Engelhardt, M. (2012). Efficacy of a multimodal cognitive rehabilitation including psychomotor and endurance training in Parkinson’s disease. Journal of Aging Research, 2012, 235765. Reynolds, G. O., Otto, M. W., Ellis, T. D., & Cronin-Golomb, A. (2016). The therapeutic potential of exercise to improve mood, cognition, and sleep in Parkinson’s disease. Movement Disorders, 31(1), 23–38. Rossini, P. M., Burke, D., Chen, R., Cohen, L. G., Daskalakis, Z., Di Iorio, R., et al. (2015). Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application. An updated report from an I.F.C.N. Committee. Clinical Neurophysiology, 126(6), 1071–1107. Sacks, O. W., Marjorie, B. C., Kohl, S., Messeloff, C. R., & Schwartz, W. F. (1972). Effects of levodopa in parkinsonian patients with dementia. Neurology, 22(5), 516. Sadeh, M., Braham, J., & Modan, M. (1982). Effects of anticholinergic drugs on memory in Parkinson’s disease. Archives of Neurology, 39(10), 666–667.

ARTICLE IN PRESS 22

Roberta Biundo et al.

Scheff, S. W., Price, D. A., Schmitt, F. A., DeKosky, S. T., & Mufson, E. J. (2007). Synaptic alterations in CA1 in mild Alzheimer disease and mild cognitive impairment. Neurology, 68(18), 1501–1508. Seppi, K., Weintraub, D., Coelho, M., Perez-Lloret, S., Fox, S. H., Katzenschlager, R., et al. (2011). The movement disorder society evidence-based Medicine review update: Treatments for the non-motor symptoms of Parkinson’s disease. Movement Disorders, 26(Suppl. 3), S42–S80. Smith, P. J., Blumenthal, J. A., Hoffman, B. M., Cooper, H., Strauman, T. A., WelshBohmer, K., et al. (2010). Aerobic exercise and neurocognitive performance: A metaanalytic review of randomized controlled trials. Psychosomatic Medicine, 72(3), 239–252. Svenningsson, P., Westman, E., Ballard, C., & Aarsland, D. (2012). Cognitive impairment in patients with Parkinson’s disease: Diagnosis, biomarkers, and treatment. The Lancet Neurology, 11(8), 697–707. Szeto, J., & Lewis, S. (2016). Current treatment options for Alzheimer’s disease and Parkinson’s disease dementia. Current Neuropharmacology, 14(4), 326–338. Tabak, R., Aquije, G., & Fisher, B. E. (2013). Aerobic exercise to improve executive function in Parkinson disease: A case series. Journal of Neurologic Physical Therapy, 37(2), 58–64. Tanaka, T., Takano, Y., Tanaka, S., Hironaka, N., Kobayashi, K., Hanakawa, T., et al. (2013). Transcranial direct-current stimulation increases extracellular dopamine levels in the rat striatum. Frontiers in Systems Neuroscience, 7, 6. Terry, R. D., Masliah, E., Salmon, D. P., Butters, N., DeTeresa, R., Hill, R., et al. (1991). Physical basis of cognitive alterations in Alzheimer’s disease: Synapse loss is the major correlate of cognitive impairment. Annals of Neurology, 30(4), 572–580. Uc, E. Y., Doerschug, K. C., Magnotta, V., Dawson, J. D., Thomsen, T. R., Kline, J. N., et al. (2014). Phase I/II randomized trial of aerobic exercise in Parkinson disease in a community setting. Neurology, 83(5), 413–425. Valentino, F., Cosentino, G., Brighina, F., Pozzi, N. G., Sandrini, G., Fierro, B., et al. (2014). Transcranial direct current stimulation for treatment of freezing of gait: A cross-over study. Movement Disorders, 29(8), 1064–1069. van der Kolk, N. M., Overeem, S., de Vries, N. M., Kessels, R. P., Donders, R., Brouwer, M., et al. (2015). Design of the Park-in-Shape study: A phase II double blind randomized controlled trial evaluating the effects of exercise on motor and non-motor symptoms in Parkinson’s disease. BMC Neurology, 15, 56. Varalta, V., Picelli, A., Fonte, C., Amato, S., Melotti, C., Zatezalo, V., et al. (2015). Relationship between cognitive performance and motor dysfunction in patients with Parkinson’s disease: A pilot cross-sectional study. BioMed Research International, 2015, 365959. Vossius, C., Larsen, J. P., Janvin, C., & Aarsland, D. (2011). The economic impact of cognitive impairment in Parkinson’s disease. Movement Disorders, 26(8), 1541–1544. Weintraub, D., Koester, J., Potenza, M. N., Siderowf, A. D., Stacy, M., Voon, V., et al. (2010). Impulse control disorders in Parkinson disease: A cross-sectional study of 3090 patients. Archives of Neurology, 67(5), 589–595. Williams-Gray, C. H., Mason, S. L., Evans, J. R., Foltynie, T., Brayne, C., Robbins, T. W., et al. (2013). The CamPaIGN study of Parkinson’s disease: 10-Year outlook in an incident population-based cohort. Journal of Neurology, Neurosurgery, and Psychiatry, 84(11), 1258–1264. Wishart, T. M., Parson, S. H., & Gillingwater, T. H. (2006). Synaptic vulnerability in neurodegenerative disease. Journal of Neuropathology and Experimental Neurology, 65(8), 733–739. Witjas, T., Kaphan, E., Azulay, J. P., Blin, O., Ceccaldi, M., Pouget, J., et al. (2002). Nonmotor fluctuations in Parkinson’s disease: Frequent and disabling. Neurology, 59(3), 408–413.

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

23

Woods, B., Spector, A. E., Prendergast, L., Orrell, M., & Woods, B. (2005). Cognitive stimulation to improve cognitive functioning in people with dementia. Cochrane Database of Systematic Reviews, 4, CD005562. Ziabreva, I., Ballard, C. G., Aarsland, D., Larsen, J. P., McKeith, I. G., Perry, R. H., et al. (2006). Lewy body disease: Thalamic cholinergic activity related to dementia and parkinsonism. Neurobiology of Aging, 27(3), 433–438. Zimmermann, R., Gschwandtner, U., Benz, N., Hatz, F., Schindler, C., Taub, E., et al. (2014). Cognitive training in Parkinson disease: Cognition-specific vs nonspecific computer training. Neurology, 82(14), 1219–1226.

FURTHER READING Aarsland, D., Bronnick, K., Williams-Gray, C., Weintraub, D., Marder, K., Kulisevsky, J., et al. (2010). Mild cognitive impairment in Parkinson disease: A multicenter pooled analysis. Neurology, 75(12), 1062–1069. Agid, Y., Javoy-Agid, F., & Ruberg, M. (1987). Biochemistry of neurotransmitters in Parkinson’s disease. In C. D. Marsden & S. Fahn (Eds.), Vol. 2. Movement disorders (pp. 166–230). London, England: Butterworth. Agosta, F., Canu, E., Stefanova, E., Sarro, L., Tomic, A., Spica, V., et al. (2014). Mild cognitive impairment in Parkinson’s disease is associated with a distributed pattern of brain white matter damage. Human Brain Mapping, 35(5), 1921–1929. Baggio, H. C., Segura, B., Sala-Llonch, R., Marti, M. J., Valldeoriola, F., Compta, Y., et al. (2015). Cognitive impairment and resting-state network connectivity in Parkinson’s disease. Human Brain Mapping, 36(1), 199–212. Besser, L. M., Litvan, I., Monsell, S. E., Mock, C., Weintraub, S., Zhou, X. H., et al. (2016). Mild cognitive impairment in Parkinson’s disease versus Alzheimer’s disease. Parkinsonism & Related Disorders, 27, 54–60. Biundo, R., Calabrese, M., Weis, L., Facchini, S., Ricchieri, G., Gallo, P., et al. (2013a). Anatomical correlates of cognitive functions in early Parkinson’s disease patients. PLoS One, 8(5), e64222. Bronnick, K., Ehrt, U., Emre, M., De Deyn, P. P., Wesnes, K., Tekin, S., et al. (2006). Attentional deficits affect activities of daily living in dementia-associated with Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 77(10), 1136–1142. Brunoni, A. R., Ferrucci, R., Bortolomasi, M., Scelzo, E., Boggio, P. S., Fregni, F., et al. (2013). Interactions between transcranial direct current stimulation (tDCS) and pharmacological interventions in the major depressive episode: Findings from a naturalistic study. European Psychiatry, 28(6), 356–361. Brunoni, A. R., Shiozawa, P., Truong, D., Javitt, D. C., Elkis, H., Fregni, F., et al. (2014). Understanding tDCS effects in schizophrenia: A systematic review of clinical data and an integrated computation modeling analysis. Expert Review of Medical Devices, 11(4), 383–394. Carlesimo, G. A., Piras, F., Assogna, F., Pontieri, F. E., Caltagirone, C., & Spalletta, G. (2012). Hippocampal abnormalities and memory deficits in Parkinson disease: A multimodal imaging study. Neurology, 78(24), 1939–1945. Chapman, S. B., Aslan, S., Spence, J. S., Hart, J. J., Jr., Bartz, E. K., Didehbani, N., et al. (2015). Neural mechanisms of brain plasticity with complex cognitive training in healthy seniors. Cerebral Cortex, 25(2), 396–405. Colosimo, C. (2003). Lewy body cortical involvement may not always predict dementia in Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 74(7), 852–856. Copeland, J. N., Lieberman, A., Oravivattanakul, S., & Troster, A. I. (2016). Accuracy of patient and care partner identification of cognitive impairments in Parkinson’s disease-mild cognitive impairment. Movement Disorders, 31(5), 693–698.

ARTICLE IN PRESS 24

Roberta Biundo et al.

Datta, A., Truong, D., Minhas, P., Parra, L. C., & Bikson, M. (2012). Inter-individual variation during transcranial direct current stimulation and normalization of dose using MRI-derived computational models. Frontiers in Psychiatry, 3, 91. Deane, K. H., Flaherty, H., Daley, D. J., Pascoe, R., Penhale, B., Clarke, C. E., et al. (2014). Priority setting partnership to identify the top 10 research priorities for the management of Parkinson’s disease. BMJ Open, 4(12), e006434. Domellof, M. E., Ekman, U., Forsgren, L., & Elgh, E. (2015). Cognitive function in the early phase of Parkinson’s disease, a five-year follow-up. Acta Neurologica Scandinavica, 132(2), 79–88. Duncan, G. W., Firbank, M. J., Yarnall, A. J., Khoo, T. K., Brooks, D. J., Barker, R. A., et al. (2016). Gray and white matter imaging: A biomarker for cognitive impairment in early Parkinson’s disease? Movement Disorders, 31(1), 103–110. Engvig, A., Fjell, A. M., Westlye, L. T., Moberget, T., Sundseth, O., Larsen, V. A., et al. (2010). Effects of memory training on cortical thickness in the elderly. NeuroImage, 52(4), 1667–1676. Engvig, A., Fjell, A. M., Westlye, L. T., Moberget, T., Sundseth, O., Larsen, V. A., et al. (2012). Memory training impacts short-term changes in aging white matter: A longitudinal diffusion tensor imaging study. Human Brain Mapping, 33(10), 2390–2406. Factor, S. A., Feustel, P. J., Friedman, J. H., Comella, C. L., Goetz, C. G., Kurlan, R., et al. (2003). Longitudinal outcome of Parkinson’s disease patients with psychosis. Neurology, 60(11), 1756–1761. Foltynie, T., Brayne, C. E., Robbins, T. W., & Barker, R. A. (2004). The cognitive ability of an incident cohort of Parkinson’s patients in the UK. The CamPaIGN study. Brain, 127(Pt. 3), 550–560. Galletta, E. E., Cancelli, A., Cottone, C., Simonelli, I., Tecchio, F., Bikson, M., et al. (2015). Use of computational modeling to inform tDCS electrode montages for the promotion of language recovery in post-stroke aphasia. Brain Stimulation, 8(6), 1108–1115. Galvin, J. E., Pollack, J., & Morris, J. C. (2006). Clinical phenotype of Parkinson disease dementia. Neurology, 67(9), 1605–1611. Gorges, M., Muller, H. P., Lule, D., Consortium, L., Pinkhardt, E. H., Ludolph, A. C., et al. (2015). To rise and to fall: Functional connectivity in cognitively normal and cognitively impaired patients with Parkinson’s disease. Neurobiology of Aging, 36(4), 1727–1735. Hindle, J. V. (2010). Ageing, neurodegeneration and Parkinson’s disease. Age and Ageing, 39(2), 156–161. Hindle, J. V., Hurt, C. S., Burn, D. J., Brown, R. G., Samuel, M., Wilson, K. C., et al. (2016a). The effects of cognitive reserve and lifestyle on cognition and dementia in Parkinson’s disease—A longitudinal cohort study. International Journal of Geriatric Psychiatry, 31(1), 13–23. Hindle, J. V., Martyr, A., & Clare, L. (2014). Cognitive reserve in Parkinson’s disease: A systematic review and meta-analysis. Parkinsonism & Related Disorders, 20(1), 1–7. Ho, K. A., Bai, S., Martin, D., Alonzo, A., Dokos, S., Puras, P., et al. (2014). A pilot study of alternative transcranial direct current stimulation electrode montages for the treatment of major depression. Journal of Affective Disorders, 167, 251–258. Howlett, D. R., Whitfield, D., Johnson, M., Attems, J., O’Brien, J. T., Aarsland, D., et al. (2015). Regional multiple pathology scores are associated with cognitive decline in Lewy body dementias. Brain Pathology, 25(4), 401–408. Irwin, D. J., White, M. T., Toledo, J. B., Xie, S. X., Robinson, J. L., Van Deerlin, V., et al. (2012). Neuropathologic substrates of Parkinson disease dementia. Annals of Neurology, 72(4), 587–598. Jellinger, K. A. (1999). Neuropathological correlates of mental dysfunction in Parkinson’s disease: An update. In E. C. Wolters, P. Scheltens, & H. W. Berendse (Eds.), Mental dysfunction in Parkinson’s disease: II (pp. 82–105). Utrecht: Academic Pharmaceutical Productions.

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

25

Kang, G. A., & Bronstein, J. M. (2004). Psychosis in nursing home patients with Parkinson’s disease. Journal of the American Medical Directors Association, 5(3), 167–173. Kempster, P. A., O’Sullivan, S. S., Holton, J. L., Revesz, T., & Lees, A. J. (2010). Relationships between age and late progression of Parkinson’s disease: A clinico-pathological study. Brain, 133(Pt. 6), 1755–1762. Klepac, N., Trkulja, V., Relja, M., & Babic, T. (2008). Is quality of life in non-demented Parkinson’s disease patients related to cognitive performance? A clinic-based crosssectional study. European Journal of Neurology, 15(2), 128–133. Kotzbauer, P. T., Cairns, N. J., Campbell, M. C., Willis, A. W., Racette, B. A., Tabbal, S. D., et al. (2012). Pathologic accumulation of alpha-synuclein and Abeta in Parkinson disease patients with dementia. Archives of Neurology, 69(10), 1326–1331. Kudlicka, A., Clare, L., & Hindle, J. V. (2014). Quality of life, health status and caregiver burden in Parkinson’s disease: Relationship to executive functioning. International Journal of Geriatric Psychiatry, 29(1), 68–76. Lawson, R. A., Yarnall, A. J., Duncan, G. W., Khoo, T. K., Breen, D. P., Barker, R. A., et al. (2014). Severity of mild cognitive impairment in early Parkinson’s disease contributes to poorer quality of life. Parkinsonism & Related Disorders, 20(10), 1071–1075. Lee, J. E., Cho, K. H., Song, S. K., Kim, H. J., Lee, H. S., Sohn, Y. H., et al. (2014). Exploratory analysis of neuropsychological and neuroanatomical correlates of progressive mild cognitive impairment in Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 85(1), 7–16. Lee, A. H., & Weintraub, D. (2012). Psychosis in Parkinson’s disease without dementia: Common and comorbid with other non-motor symptoms. Movement Disorders, 27(7), 858–863. Leroi, I., McDonald, K., Pantula, H., & Harbishettar, V. (2012). Cognitive impairment in Parkinson disease: Impact on quality of life, disability, and caregiver burden. Journal of Geriatric Psychiatry and Neurology, 25(4), 208–214. Litvan, I., Goldman, J. G., Troster, A. I., Schmand, B. A., Weintraub, D., Petersen, R. C., et al. (2012). Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines. Movement Disorders, 27(3), 349–356. Lohmann, E., Thobois, S., Lesage, S., Broussolle, E., du Montcel, S. T., Ribeiro, M. J., et al. (2009). A multidisciplinary study of patients with early-onset PD with and without parkin mutations. Neurology, 72(2), 110–116. Lopez-Alonso, V., Cheeran, B., Rio-Rodriguez, D., & Fernandez-Del-Olmo, M. (2014). Inter-individual variability in response to non-invasive brain stimulation paradigms. Brain Stimulation, 7(3), 372–380. Lopez-Alonso, V., Fernandez-Del-Olmo, M., Costantini, A., Gonzalez-Henriquez, J. J., & Cheeran, B. (2015). Intra-individual variability in the response to anodal transcranial direct current stimulation. Clinical Neurophysiology, 126(12), 2342–2347. Lucero, C., Campbell, M. C., Flores, H., Maiti, B., Perlmutter, J. S., & Foster, E. R. (2015). Cognitive reserve and beta-amyloid pathology in Parkinson disease. Parkinsonism & Related Disorders, 21(8), 899–904. McDowell, K., & Chesselet, M. F. (2012). Animal models of the non-motor features of Parkinson’s disease. Neurobiology of Disease, 46(3), 597–606. Moussaud, S., Jones, D. R., Moussaud-Lamodiere, E. L., Delenclos, M., Ross, O. A., & McLean, P. J. (2014). Alpha-synuclein and tau: Teammates in neurodegeneration? Molecular Neurodegeneration, 9, 43. Noyce, A. J., Bestwick, J. P., Silveira-Moriyama, L., Hawkes, C. H., Giovannoni, G., Lees, A. J., et al. (2012). Meta-analysis of early nonmotor features and risk factors for Parkinson disease. Annals of Neurology, 72(6), 893–901.

ARTICLE IN PRESS 26

Roberta Biundo et al.

Pagonabarraga, J., Corcuera-Solano, I., Vives-Gilabert, Y., Llebaria, G., Garcia-Sanchez, C., Pascual-Sedano, B., et al. (2013). Pattern of regional cortical thinning associated with cognitive deterioration in Parkinson’s disease. PLoS One, 8(1), e54980. Parazzini, M., Fiocchi, S., & Ravazzani, P. (2012). Electric field and current density distribution in an anatomical head model during transcranial direct current stimulation for tinnitus treatment. Bioelectromagnetics, 33(6), 476–487. Peng, S., Eidelberg, D., & Ma, Y. (2014). Brain network markers of abnormal cerebral glucose metabolism and blood flow in Parkinson’s disease. Neuroscience Bulletin, 30(5), 823–837. Plewnia, C., Zwissler, B., Langst, I., Maurer, B., Giel, K., & Kruger, R. (2013). Effects of transcranial direct current stimulation (tDCS) on executive functions: Influence of COMT Val/met polymorphism. Cortex, 49(7), 1801–1807. Priori, A. (2003). Brain polarization in humans: A reappraisal of an old tool for prolonged non-invasive modulation of brain excitability. Clinical Neurophysiology, 114(4), 589–595. Reginold, W., Duff-Canning, S., Meaney, C., Armstrong, M. J., Fox, S., Rothberg, B., et al. (2013). Impact of mild cognitive impairment on health-related quality of life in Parkinson’s disease. Dementia and Geriatric Cognitive Disorders, 36(1–2), 67–75. Ruberg, M., & Agid, Y. (1988). Dementia in Parkinson’s disease. In L. L. Iversen, S. D. Iversen, & S. H. Snyder (Eds.), Handbook of psychopharmacology (pp. 157–206). New York, NY: Springer. Schrag, A., Ben-Shlomo, Y., Brown, R., Marsden, C. D., & Quinn, N. (1998). Young-onset Parkinson’s disease revisited—Clinical features, natural history, and mortality. Movement Disorders, 13(6), 885–894. Schrag, A., Hovris, A., Morley, D., Quinn, N., & Jahanshahi, M. (2006). Caregiver-burden in parkinson’s disease is closely associated with psychiatric symptoms, falls, and disability. Parkinsonism & Related Disorders, 12(1), 35–41. Senco, N. M., Huang, Y., D’Urso, G., Parra, L. C., Bikson, M., Mantovani, A., et al. (2015). Transcranial direct current stimulation in obsessive-compulsive disorder: Emerging clinical evidence and considerations for optimal montage of electrodes. Expert Review of Medical Devices, 12(4), 381–391. Stella, F., Banzato, C. E., Quagliato, E. M., Viana, M. A., & Christofoletti, G. (2009). Psychopathological features in patients with Parkinson’s disease and related caregivers’ burden. International Journal of Geriatric Psychiatry, 24(10), 1158–1165. Stern, Y. (2009). Cognitive reserve and aging. Neuropsychologia, 47(10), 2015–2028. Strube, W., Bunse, T., Malchow, B., & Hasan, A. (2015). Efficacy and interindividual variability in motor-cortex plasticity following anodal tDCS and paired-associative stimulation. Neural Plasticity, 2015, 530423. Tessitore, A., Esposito, F., Vitale, C., Santangelo, G., Amboni, M., Russo, A., et al. (2012). Default-mode network connectivity in cognitively unimpaired patients with Parkinson disease. Neurology, 79(23), 2226–2232. Troster, A. I. (2008). Neuropsychological characteristics of dementia with Lewy bodies and Parkinson’s disease with dementia: Differentiation, early detection, and implications for “mild cognitive impairment” and biomarkers. Neuropsychology Review, 18(1), 103–119. Troster, A. I. (2011). A precis of recent advances in the neuropsychology of mild cognitive impairment(s) in Parkinson’s disease and a proposal of preliminary research criteria. Journal of the International Neuropsychological Society, 17(3), 393–406. Tucker, A. M., & Stern, Y. (2011). Cognitive reserve in aging. Current Alzheimer Research, 999(999), 1–7. Valenzuela, M. J., & Sachdev, P. (2006). Brain reserve and cognitive decline: A nonparametric systematic review. Psychological Medicine, 36(8), 1065–1073.

ARTICLE IN PRESS Nonmotor Symptoms and Natural History of Parkinson’s Disease

27

Vela, L., Martinez Castrillo, J. C., Garcia Ruiz, P., Gasca-Salas, C., Macias Macias, Y., Perez Fernandez, E., et al. (2016). The high prevalence of impulse control behaviors in patients with early-onset Parkinson’s disease: A cross-sectional multicenter study. Journal of the Neurological Sciences, 368, 150–154. Walton, C. C., Naismith, S. L., Lampit, A., Mowszowski, L., & Lewis, S. J. (2017). Cognitive training in Parkinson’s disease. Neurorehabilitation and Neural Repair, 31(3), 207–216. Weintraub, D., & Burn, D. J. (2011). Parkinson’s disease: The quintessential neuropsychiatric disorder. Movement Disorders, 26(6), 1022–1031. Wiethoff, S., Hamada, M., & Rothwell, J. C. (2014). Variability in response to transcranial direct current stimulation of the motor cortex. Brain Stimulation, 7(3), 468–475. Yarnall, A. J., Rochester, L., & Burn, D. J. (2013). Mild cognitive impairment in Parkinson’s disease. Age and Ageing, 42(5), 567–576. Zheng, Z., Shemmassian, S., Wijekoon, C., Kim, W., Bookheimer, S. Y., & Pouratian, N. (2014). DTI correlates of distinct cognitive impairments in Parkinson’s disease. Human Brain Mapping, 35(4), 1325–1333.