Biomarkers of Nonmotor Symptoms in Parkinson's Disease

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Biomarkers of Nonmotor Symptoms in Parkinson’s Disease Takuya Konno, Rana Hanna AL-Shaikh, Angela B. Deutschl€ander, Ryan J. Uitti1 Mayo Clinic, Jacksonville, FL, United States 1 Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 2. Neuropsychiatric Symptoms 2.1 Cognitive Impairment 2.2 Depression 2.3 Apathy 3. Sleep Disorders 3.1 REM Sleep Behavior Disorder (RBD) 3.2 Excessive Daytime Sleepiness (EDS) 3.3 Restless Legs Syndrome (RLS) 4. Autonomic Symptoms 4.1 Constipation 4.2 Orthostatic Hypotension (OH) 5. Sensory Symptoms 5.1 Olfactory Dysfunction 6. Conclusion References

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Abstract Biomarkers are helpful for early diagnosis, assessment of disorder severity, prognosis, and prediction of response to therapy. Given that early therapeutic intervention may be useful in forestalling or slowing neurodegenerative conditions, employing reliable biomarkers to identify asymptomatic individuals who are destined to develop clinical Parkinson’s disease (PD) is critical. Two important observations have been repeatedly found in persons who eventually develop clinical PD: (1) significant neuronal loss occurs in the substantia nigra and (2) the presence of nonmotor symptoms (NMS). Each of these findings occurs prior to the development of motor signs and symptoms, often preceding the clinical diagnosis of PD by a decade or more. As such, NMS themselves, and factors associated with their development may be useful clinical biomarkers for predicting future development of motor PD. Recently, research criteria for prodromal

International Review of Neurobiology ISSN 0074-7742 http://dx.doi.org/10.1016/bs.irn.2017.05.020

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PD, defined as presence of motor and/or NMS, but not yet fulfilling the classic PD diagnosis, have been proposed by the International Parkinson and Movement Disorder Society Task Force. Although there are a small number of biomarkers associated with NMS of PD, in this chapter, discussion follows concerning the expanding literature associated with clinical, biochemical, imaging, and genetic biomarkers of NMS in patients with PD.

1. INTRODUCTION A biomarker is defined as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” (Biomarkers Definitions Working Group, 2001). Biomarkers are generally used for several purposes: diagnosis, evaluating condition severity and prognosis, and predicting responsiveness to a therapeutic intervention. Various factors can be considered as biomarkers, including clinical signs, biochemical specimens, imaging findings, and genetic data (Delenclos, Jones, McLean, & Uitti, 2016) (Table 1).

Table 1 Biomarkers

Clinical signs Motor symptoms Nonmotor symptoms Biochemical specimens Plasma/serum Urine CSF Biopsy (e.g., skin, mucosa) Imaging findings MRI/fMRI SPECT/PET Transcranial sonography Genetics

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Parkinson’s disease (PD) has historically been described and characterized as a “movement disorder.” In current diagnostic criteria, the diagnosis of PD is based on cardinal motor signs (Postuma et al., 2015). However, in patients with PD, pathological processes insidiously progress, probably more than a decade prior to the development of an initial motor symptom/sign. Given that more than 60% of neuronal cell loss has already occurred within the substantia nigra (SN) at the time of symptom onset (Fearnley & Lees, 1991), there is a significant period of time for potential therapeutic intervention aimed at forestalling or slowing the otherwise natural progression of the disorder in the hopes of conceivably maintaining a completely asymptomatic phase of PD. In the past decade, significant attention has focused on nonmotor symptoms (NMS) of PD which often precede motor signs and symptoms (Langston, 2006). Constipation, for example, is more frequently observed among those who went on to develop PD (than controls) even as early as 10 years prior to PD diagnosis (Schrag, Horsfall, Walters, Noyce, & Petersen, 2015). Increasing knowledge about NMS may provide the opportunity to redefine PD according to disease progression as follows: preclinical PD (presence of PD-specific pathology without any evidence of clinical signs/symptoms), prodromal PD (presence of motor and/or NMS but not yet fulfilling the classic PD diagnosis), and clinical PD (fulfilling the classic PD diagnosis based on cardinal motor signs and symptoms) (Berg et al., 2014; Stern, Lang, & Poewe, 2012). From a therapeutic standpoint, the earliest recognition of preclinical/prodromal states would be ideal. Consequently, NMS have an important role as clinical biomarkers in predicting future development of clinical PD and opportunity to influence such. Indeed, according to recently proposed diagnostic criteria for prodromal PD by the International Parkinson and Movement Disorder Society Task Force, NMS are essential for estimating probability of prodromal PD (Berg et al., 2015) (Fig. 1). This chapter will discuss the current body of evidence related to biomarkers of NMS in PD, with particular emphasis on neuropsychiatric symptoms and sleep disorders, due to their clinical significance and the availability of noteworthy findings.

2. NEUROPSYCHIATRIC SYMPTOMS 2.1 Cognitive Impairment Cognitive impairment, depending upon definition, is almost inevitable in patients with PD. The Sydney Multicenter Study, followed patients with

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Fig. 1 The current concept of Parkinson’s disease. Pathological changes initially begin at the preclinical PD stage and insidiously progress. Clinical PD is the final phase that is defined by the presence of cardinal motor symptoms. Prodromal PD is located between the preclinical and clinical PD stages. Several NMS often appear prior to the onset of motor symptoms and provide opportunities to serve as informative biomarkers for PD (Berg et al., 2015). NMS, nonmotor symptoms; PD, Parkinson’s disease.

PD for 20 years, and reported that 83% of 20-year survivors had developed dementia (Hely, Reid, Adena, Halliday, & Morris, 2008). Mild cognitive impairment (MCI) can also be observed in PD (PD-MCI) even at an early stage (Aarsland et al., 2009; Muslimovic, Post, Speelman, & Schmand, 2005). Importantly, patients with PD-MCI are more likely to develop dementia upon follow-up when compared to cognitively normal patients (Janvin, Larsen, Aarsland, & Hugdahl, 2006; Pedersen, Larsen, Tysnes, & Alves, 2013), thus suggesting that MCI in PD predicts future development of dementia. Some NMS can act as predictors of cognitive impairment in PD patients. In a prospective 4-year follow-up study of PD patients without dementia at baseline, 48% of patients with polysomnogram-confirmed REM sleep behavior disorder (RBD) developed dementia, whereas none of those without RBD developed dementia (Postuma, Bertrand, et al., 2012). Combined

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with other studies showing a similar association (Anang et al., 2014; Erro et al., 2012; Kwon et al., 2014; Nomura, Inoue, Kagimura, & Nakashima, 2013), RBD can be confidently concluded as a solid predictor of dementia. Several cross-sectional studies showed a relationship between orthostatic hypotension (OH) and cognitive impairment (Allcock et al., 2006; Bae, Lim, & Cheon, 2014; Kim et al., 2012; Pilleri et al., 2013), which can be observed even in drug-naı¨ve patients with early PD (Kim et al., 2012). This relationship was supported by a prospective cohort study, suggesting that OH can be a clinical biomarker for predicting development of dementia (Anang et al., 2014). In addition to RBD and OH, a link between olfactory dysfunction and cognitive impairment was observed in several cross-sectional studies (Baba et al., 2011; Bohnen et al., 2010; Damholdt, Borghammer, Larsen, & Ostergaard, 2011; Morley et al., 2011; Postuma & Gagnon, 2010). A retrospective cohort study revealed that patients with the lowest quartile of baseline olfactory performance had a higher risk of future development of cognitive impairment than others (Stephenson et al., 2010). The role of olfactory perception decline as a predictor of dementia has been similarly verified in prospective studies (Baba et al., 2012; Kwon et al., 2014). A recent longitudinal study conducted as part of the Parkinson’s Progression Marker’s Initiative (PPMI), a large world-wide collaboration with the aim to identify progression among biomarkers of PD, demonstrated that worse olfactory function at baseline is associated with long-term cognitive decline (Fullard et al., 2016). This study also showed that cerebrospinal fluid (CSF) Aβ42 was significantly lower and CSF tau/Aβ42 was higher in those with worse olfactory function at baseline. Furthermore, it has been reported that other NMS features, including depression (Kwon et al., 2014), apathy (Dujardin, Sockeel, Delliaux, Destee, & Defebvre, 2009), vivid dreaming (Kwon et al., 2014), insomnia (Erro et al., 2012), and abnormal color vision (Anang et al., 2014) predict a higher risk for development of dementia in PD patients. A recent metaanalysis found that advanced age, male sex, high UPDRS III scores, visual hallucinations, RBD, smoking, and hypertension are positive predictors of PD with dementia (PDD) (Xu, Yang, & Shang, 2016). The role of CSF biomarkers in diagnosing Alzheimer’s disease (AD) has been thoroughly investigated, particularly concerning three core CSF biomarkers; Aβ42, total tau (t-tau), and phosphorylated tau (p-tau), that have been shown to be strongly associated with AD (Olsson et al., 2016). Given that AD-related pathology coexists in PDD and dementia with Lewy bodies (DLB) (Irwin et al., 2012; Tsuboi, Uchikado, & Dickson, 2007), these

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markers may have predictive value of cognitive impairment in PD. In early cross-sectional studies, lower levels of CSF Aβ42 were observed in PDD patients (Compta et al., 2009; Mollenhauer et al., 2006). The association was further validated by several prospective cohort studies (Alves et al., 2014; Backstrom et al., 2015; Compta et al., 2013; Siderowf et al., 2010; Terrelonge, Marder, Weintraub, & Alcalay, 2016), suggesting that reduced Aβ42 in CSF predicts future development of dementia. In contrast, the predictive value of CSF t-tau and p-tau for cognitive impairment is less apparent. While levels of CSF t-tau and p-tau have been reported as elevated in PDD compared to PD without dementia in cross-sectional studies (Compta et al., 2009; Mollenhauer et al., 2006; Vranova et al., 2014), most prospective longitudinal studies fail to show any clear associations between CSF t-tau, p-tau level, and cognitive decline (Alves et al., 2014; Backstrom et al., 2015; Hall et al., 2015; Siderowf et al., 2010; Terrelonge et al., 2016). A recent CSF analysis from a large PD cohort, DATATOP (deprenyl and tocopherol antioxidative therapy of Parkinsonism), revealed that higher p-tau and p-tau/Aβ42 predicted subsequent cognitive decline (Liu et al., 2015). Also, a prospective 2-year follow-up study showed that more rapid increase of CSF p-tau is related to faster progression of cognitive decline (Hall et al., 2016). In addition to the three core CSF biomarkers, total α-synuclein and oligomeric α-synuclein in CSF have been investigated. High levels of both types of α-synuclein in CSF are associated with cognitive impairment in PD (Compta et al., 2015; Hall et al., 2015; Hansson et al., 2014; Stewart et al., 2014). Backstrom et al. reported that the combined CSF biomarkers at baseline (low Aβ42, high neurofilament light chain protein [NFL], and high heart fatty acid-binding protein) can predict future PDD (Backstrom et al., 2015), whereas the association between baseline NFL level and subsequent cognitive decline was not replicated in another study (Hall et al., 2015). Recently, it has been shown that an increasing CSF level of YKL-40, expressed in microglia, astrocytes, and associated with inflammation, is correlated with cognitive decline in PD (Hall et al., 2016). Interestingly, YKL-40 was also reported as a potential predictive marker for AD (Craig-Schapiro et al., 2010). A number of biochemical specimens other than CSF have been investigated. Low plasma and urine uric acid is related to cognitive decline in PD (Annanmaki, Pessala-Driver, Hokkanen, & Murros, 2008). It has been reported that low levels of plasma/serum epidermal growth factor and serum insulin-like growth factor-1 can be potential predictors for subsequent cognitive decline (Chen-Plotkin et al., 2011; Pellecchia et al., 2013, 2014).

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Another study showed that increased levels of plasma soluble tumor necrosis factor receptor-1 and -2 are associated with poor cognitive performance and higher soluble tumor necrosis factor receptor-1 may predict poorer executive function in PD (Rocha et al., 2014). In addition, increased levels of several species of ceramide and monohexosylceramide in plasma, and lower expression of EFTUD2 and PTBP1 mRNA in peripheral blood have been associated with cognitive impairment in PD (Mielke et al., 2013; Santiago & Potashkin, 2015). However, further investigation would be warranted to verify the significance of these biochemical biomarkers. There have been a wide variety of imaging studies pertaining to cognitive impairment in PD. Using spatial covariance analysis of metabolic imaging data acquired with 18F-FDG PET, a “PD cognition-related pattern” was identified. Expression values of this pattern have been found to correlate with cognitive impairment in PD patients (Mattis, Tang, Ma, Dhawan, & Eidelberg, 2011; Niethammer & Eidelberg, 2012). Using this approach, metabolic reductions were seen in prefrontal (premotor cortex and medial prefrontal cortex) and parietal sites, while elevations were detected in cerebellar sites (dentate nucleus and vermis) (Niethammer & Eidelberg, 2012). After the administration of levodopa, the expression of this pattern was found to be reduced, as executive functions began to improve in PD patients (Mattis et al., 2011). It is assumed that cognitive impairment in PD is caused by changes in both the dopaminergic and cholinergic systems. Dopaminergic transmitter changes occur mainly in the striatum and frontolimbic system, while cholinergic changes are thought to be more widespread and involve posterior cortical regions (Bohnen et al., 2003, 2011; Calabresi, Picconi, Parnetti, & Di Filippo, 2006; Christopher et al., 2014; DelgadoAlvarado, Gago, Navalpotro-Gomez, Jimenez-Urbieta, & RodriguezOroz, 2016; Klein et al., 2010). In addition to neurotransmitter changes and pathologic protein depositions, other factors like neuroinflammation may also contribute to cognitive impairment in PD; neuroinflammation may appear before the onset of dementia (Fan et al., 2015). Combining several biomarkers may yield higher predictive value than a single marker. The PPMI study showed that combining five variables, including older age, hyposmia, RBD, lower CSF Aβ42, and lower caudate uptake on dopamine transporter (DAT) imaging, can predict cognitive decline at 2 years with high accuracy (Schrag, Siddiqui, Anastasiou, Weintraub, & Schott, 2017). Several studies are available on the genetic associations with cognitive impairment in PD. SNCA mutations, including missense mutations and triplications, cause early-onset dementia (Farrer et al., 2004; Puschmann

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et al., 2009; Seidel et al., 2010; Somme et al., 2011). Initially it was reported that cognitive impairment is usually absent in patients with SNCA duplications (Chartier-Harlin et al., 2004); however, there have been multiple reports describing clinical variability (Elia et al., 2013; Fuchs et al., 2007; Kasten & Klein, 2013; Nishioka et al., 2006). Indeed, all autopsied patients with SNCA duplications who had dementia showed diffuse neocortical type of dementia with Lewy bodies (Konno, Ross, Puschmann, Dickson, & Wszolek, 2016). The relationship between the SNCA-Rep1 variant (SNCA intron4) and dementia in PD is controversial (De Marco et al., 2008; Markopoulou et al., 2014; Mata et al., 2014). On the other hand, LRRK2 mutation carriers demonstrate better performance on cognitive tests (Srivatsal et al., 2015). Future longitudinal studies on cognitive function in LRRK2 mutation carriers are awaited. Several studies found an association of GBA mutations and cognitive decline in PD patients. The p.Leu444Pro mutation was associated with cognitive impairment compared to the p.Asn370Ser mutation in two recent studies with large sample size (Cilia et al., 2016; Liu et al., 2016). GBA mutations were associated with a distinct pattern of cognitive impairment, which included predominant impairment of executive functions, working memory, and visuospatial functions (Mata et al., 2016, 2014). Dementia is reported to be present in about 50% of GBA-associated PD cases, even though a younger age of motor onset is typically reported (Neumann et al., 2009). The p.Glu326Lys mutation was particularly found to be associated with dementia, as it was found in DLB and PDD (Gamez-Valero et al., 2016). MAPT H1/H1 genotype is also considered as a risk for cognitive decline (Nombela et al., 2014; Seto-Salvia et al., 2011; Williams-Gray, Evans, et al., 2009; Williams-Gray et al., 2013). However, two large studies did not replicate this finding (Mata et al., 2014; Morley et al., 2012). The magnitude of the effect of the H1/H1 genotype on the risk to develop dementia in PD seems to lessen with disease duration (Williams-Gray et al., 2013), which may explain the discrepancies of the findings of these studies. The Apo ε4 allele is a strong risk factor for AD. An association between the ε4 allele and risk of cognitive impairment in PD has also been repeatedly described (Mata et al., 2014; Morley et al., 2012). However, this association has not been universally found (Federoff, Jimenez-Rolando, Nalls, & Singleton, 2012; Kurz et al., 2009; Williams-Gray, Goris, et al., 2009). While several studies indicated that MAPT H1/H1 genotype and Apo ε4 allele may be associated with visual hallucinations in PD (de la Fuente-Fernandez, Nunez, & Lopez, 1999; Papapetropoulos et al., 2007), others have not replicated these

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associations (Camicioli et al., 2005; Factor et al., 2011; Goetz et al., 2001). Influences of disease stages may account for some of the discrepancies. While MAPT may have its greatest impact on cognition in early disease stages, ApoE may have its largest effect in later stages. It is also possible that the influence of ApoE status may be in part due to the development of AD pathology in the aging brain (Monsell et al., 2014; Tsuang et al., 2013).

2.2 Depression While PD patients frequently have depression as a comorbidity, depression itself can also precede PD. A large, population-based study in Netherlands in which 105,416 people were enrolled showed that 9.2% of the patients with PD had a history of depression at the time of their diagnosis compared to 4.0% of the controls (Leentjens, Van den Akker, Metsemakers, Lousberg, & Verhey, 2003). A nested case–control study, including 140,688 cases with depression at baseline, revealed a clear relationship between depression and subsequent occurrence of PD. This association decreased over time but remained significant during the 25-year follow-up period (Gustafsson, Nordstrom, & Nordstrom, 2015). These findings indicate that depression can be a clinical biomarker for predicting future development of PD. Serotonergic dysfunction may play a role in the mood of PD patients (Fox, Chuang, & Brotchie, 2009). An early study showed that the CSF metabolite of serotonin (5-HT), 5-hydroxyindoleacetic acid (5-HIAA), was reduced in PD patients with depression (Mayeux, Stern, Cote, & Williams, 1984). Olivola et al. found CSF levels of both 5-HT and 5-HIAA were significantly reduced in PD patients compared to AD patients and controls; however, there was no relationship between depression and low levels of CSF 5-HT and 5-HIAA (Olivola et al., 2014). On the other hand, decreased levels of plasma 5-HT and 5-HIAA were correlated with severity of depression (Tong et al., 2015). A link between low levels of serum uric acid and progression of depression has also been reported (Moccia et al., 2015). Further studies are required to clarify whether or not these can be used as biochemical markers for depression in PD. Although the pathophysiological background of depression in PD remains to be elucidated, not only dopamine but also other neurotransmitter systems, including noradrenaline and serotonin, may be involved. 123I-FPCIT SPECT studies yielded controversial results: both increased and reduced DAT binding were observed in the striatum of depressed PD

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patients (Wen, Chan, Tan, & Tan, 2016). Divergence in sample size, severity of depression, PD stage, and concomitant dopaminergic therapy in each study may influence these results (Ceravolo et al., 2013). A study using 11CRTI-32 PET, a marker of both dopamine and noradrenaline transporters, showed that depression in PD is associated with a reduction of 11C-RTI32 binding in the locus coeruleus and in the limbic system including the anterior cingulate cortex, thalamus, amygdala, and ventral striatum (Remy, Doder, Lees, Turjanski, & Brooks, 2005). 11C-DASB PET, a marker of 5-HT transporter, demonstrated that increased 5-HT binding in the orbitofrontal cortex, raphe nuclei, and limbic structures including amygdala, hypothalamus, and posterior cingulate cortex, correlates with depression (Boileau et al., 2008; Politis et al., 2010). This finding is supported by another PET study using 18F-MPPF, a marker of 5-HT1A receptors, showing the dysregulation of serotonergic transmission within the limbic system (Ballanger et al., 2012). In addition, alteration of the serotonergic system in the raphe nuclei in depressed patients has been suggested by a study using transcranial sonography (Walter et al., 2007). This study also suggests that depressed patients with SN hyperechogenicity and reduced raphe echogenicity are at increased risk of developing PD. However, a recent study with a large sample size (345 patients with early drug-naı¨ve PD from the PPMI cohort) revealed no association between depression and raphe 5-HT transporter availability (Qamhawi et al., 2015). At the same time, MRI studies using voxel-based morphometry showed gray matter and white matter loss in cingulate and orbitofrontal regions (Feldmann et al., 2008; Kostic et al., 2010). Although several studies have attempted to clarify the genetic predisposition of depression in PD, results remain equivocal. Early studies suggested that the polymorphism in the promotor of the serotonin transporter gene has an association with depression in PD (Menza, Palermo, DiPaola, Sage, & Ricketts, 1999; Mossner et al., 2001), whereas this was not supported by subsequent studies with larger cohorts (Burn, Tiangyou, Allcock, Davison, & Chinnery, 2006; Dissanayaka, Silburn, O’Sullivan, & Mellick, 2009; Zhang, Yang, & Chan, 2009). Effects of LRRK2 and Parkin genes are similarly inconclusive. Some studies showed that frequency and severity of depression was higher among mutation carriers compared with noncarriers (Belarbi et al., 2010; Goldwurm et al., 2006; Marras et al., 2011), but others did not detect such an association (Ben Sassi et al., 2012; Gaig et al., 2014; Pankratz et al., 2008). These discrepancies may be due to the relatively

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small sample sizes and differences in populations. GBA mutations are more likely related to depression (Beavan et al., 2015; Brockmann et al., 2011; Dan et al., 2016; Swan et al., 2016). Although there are few studies pertaining to each gene, a possible link between depression in PD and the polymorphism of genes including CNR1, Tef, SNCA-Rep1, BDNF, SLC6A15, and TPH2 has been reported (Barrero et al., 2005; Cagni et al., 2017; Dan et al., 2016; Hua et al., 2012; Zheng et al., 2017). Further investigation is required to verify genetic roles in developing depression in PD.

2.3 Apathy Apathy, whose core feature is loss of or diminished motivation (Robert et al., 2009), is commonly observed in PD patients, and frequently coexists with depression and cognitive impairment. However, apathy also occurs independently (Kirsch-Darrow, Fernandez, Marsiske, Okun, & Bowers, 2006; Pedersen, Larsen, Alves, & Aarsland, 2009). A recent systematic review and metaanalysis revealed the prevalence of apathy in PD was 39.8% and half of the study population had apathy without depression or cognitive impairment (den Brok et al., 2015). A prospective study, with an 18-month follow-up period, showed that apathy can be a predictor of cognitive impairment in PD (Dujardin et al., 2009). Meanwhile, in another prospective study with a 4-year follow-up period, dementia at baseline and more rapid motor deterioration (especially in speech and axial impairment) were independent predictors of apathy (Pedersen, Alves, Aarsland, & Larsen, 2009). Furthermore, a correlation between apathy and olfactory dysfunction has been observed in a cross-sectional study (Cramer, Friedman, & Amick, 2010). There is a little evidence of biochemical biomarkers of apathy in PD patients. Picillo et al. followed nondemented, nondepressed, early (within 2 years from symptom onset), drug-naı¨ve patients with PD for 2 years, and identified that lower serum uric acid levels are associated with greater apathy at both baseline and 2-year follow-up (Picillo et al., 2016). SPECT or PET studies, using several radioligands, have been conducted in PD patients with apathy. DAT imaging demonstrated that the decreased DAT levels in the striatum are associated with apathy (Remy et al., 2005; Santangelo et al., 2015), whereas a 18F-FP-CIT PET study with larger numbers of patients failed to replicate this association (Chung, Lee, Ham, Lee, & Sohn, 2016). Recently, serotonergic alteration in the ventral striatum,

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anterior cingulate, caudate, and orbitofrontal cortex was observed in drugnaı¨ve PD patients with apathy using 11C-DASB PET (Maillet et al., 2016). This study also showed that serotonergic disruption is associated with both depression and anxiety. Based on MRI studies, morphological changes were detected in several brain regions including the cingulate gyrus, inferior frontal gyrus, left nucleus accumbens, and the caudate head (Carriere et al., 2014; Reijnders et al., 2010). A functional MRI study indicated that apathy in PD patients is associated with reduced functional connectivity in the left-sided circuits involving limbic striatal and frontal territories (Baggio et al., 2015). Taken together with the imaging findings of depressed patients with PD, not only nigrostriatal but also extra-nigrostriatal pathways (particularly in the frontal connecting areas) and multiple neurotransmitters seem to be implicated in these neuropsychiatric symptoms in PD (Wen et al., 2016). There is little evidence of genetic associations with apathy in PD. One study showed that PD patients with GBA mutations presented with increased severity of apathy compared to sporadic PD without GBA mutations (Brockmann et al., 2011).

3. SLEEP DISORDERS 3.1 REM Sleep Behavior Disorder (RBD) RBD is characterized by the loss of muscle atonia during REM sleep. As a result, affected subjects tend to act out their vivid dreams or nightmares (Chaudhuri & Schapira, 2009). RBD occurs frequently between the ages of 50–70, is more common among men and can portend a PD risk of upto 65% within 10 years (Ponsen, Stoffers, Twisk, Wolters, & Berendse, 2009; Postuma, Gagnon, & Montplaisir, 2012). It has been also reported that RBD is prevalent among 58% of PD patients (Gagnon, Postuma, Mazza, Doyon, & Montplaisir, 2006). RBD has been found to predate PD by 12–14 years (Chaudhuri & Schapira, 2009). This long latency period provides a particularly robust opportunity for therapeutic intervention in order to prevent phenoconversion to PD (Arnaldi, Antelmi, St Louis, Postuma, & Arnulf, 2016). RBD has a high specificity to PD when compared to other NMS (Postuma, Aarsland, et al., 2012). Postuma et al. reported that olfactory dysfunction, abnormal color vision, significant systolic blood pressure decline, and other autonomic symptoms including constipation, erectile dysfunction, and urinary dysfunction were

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more frequently observed in patients with RBD than controls. Interestingly, systolic blood pressure decline and color vision are significantly worse in PD patients with RBD than those without RBD (Postuma, Gagnon, Vendette, & Montplaisir, 2009). In a prospective cohort of 91 RBD patients in whom 32 developed α-synucleinopathy during the average of a 3.3-year follow-up period, autonomic dysfunction (systolic blood pressure decline, constipation, erectile dysfunction, and urinary dysfunction) were clearly observed prior to the development of parkinsonism. The prodromal interval was estimated to be 10–20 years (Postuma, Gagnon, Pelletier, & Montplaisir, 2013). Another study showed that olfactory dysfunction can occur up to 8 years prior to PD onset in some populations with RBD (Goldman & Postuma, 2014). As for biochemical biomarkers in RBD, a recent study revealed that α-synuclein oligomer was elevated in the CSF and serum of PD patients with RBD. The level of α-synuclein oligomer in CSF was enhanced along with an increase in the inflammatory factors: nitric oxide, interleukin-1β, and tumor necrosis factor-α in CSF (Hu et al., 2015). In addition, the RBD screening questionnaire score showed a positive correlation with the levels of α-synuclein oligomer, nitric oxide, and interleukin-1β in CSF, and prostaglandin E2 in the serum of PD patients, suggesting that brain inflammation may play a role in the pathogenesis of RBD in PD (Hu et al., 2015). A study using a 3 T MRI showed that cortical thinning was present in the lingual and fusiform gyri, paracingulate gyri, and dorsolateral frontal cortex. This was also seen in patients with olfactory dysfunction (Rahayel et al., 2015). Midbrain hyperechogenicity has been frequently observed on transcranial sonography among RBD patients (Stockner et al., 2009). An MRI study using susceptibility-weighted imaging revealed that loss of dorsolateral nigral hyperintensity was detected in almost two-thirds of idiopathic RBD patients (a rate similar to PD patients), suggesting these findings can be used as imaging markers of prodromal PD (De Marzi et al., 2016). There are limited studies of genetic association with RBD. No relationship between RBD and LRRK2 mutations (p.Atg1441Cys/Gly/His and p. Gly2019Ser) has been identified (Fernandez-Santiago et al., 2016; PontSunyer et al., 2015). Among PD-associated single-nucleotide polymorphisms, those in the SCARB2 and MAPT regions were associated with RBD (Fernandez-Santiago et al., 2017; Gan-Or, Girard, et al., 2015), whereas no association was found in SNCA (Fernandez-Santiago et al., 2017).

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Recently, a strong association between GBA mutations and RBD was suggested in cohorts of idiopathic RBD and PD patients screened for RBD (Gan-Or, Mirelman, et al., 2015).

3.2 Excessive Daytime Sleepiness (EDS) EDS, somnolence, and insomnia are commonly encountered in PD. The presence of EDS increases the likelihood of developing PD more than threefold (Abbott et al., 2005). It was implicated that hypocretin/orexin levels can be altered in patients with PD and may lead to an increase in somnolence; 19 patients with late-stage PD underwent ventricular CSF analysis to determine orexin-A/hypocretin-1 concentrations. The cross-sectional study concluded that CSF orexin-A levels are negatively correlated with disease progression (Drouot et al., 2003). Increased levels of sleepiness were also reported among PD patients suggesting that decreases in orexin may be associated with an increase in EDS (Drouot et al., 2003). A case–control cohort study showed that PD patients suffer from various sleep abnormalities including increased sleep latency, reduced sleep efficiency, and reduced REM sleep (Breen et al., 2014). This study showed that PD patients possessed higher cortisol and lower melatonin levels in serum compared to controls. Circadian rhythm analysis was also conducted to investigate circadian clock gene expression among PD patients; a loss of time-dependent variation of gene expression was observed in Bmal1 (Breen et al., 2014).

3.3 Restless Legs Syndrome (RLS) RLS has been classified as one of the nonmotor findings of PD. The prevalence of RLS was 7.9%–11.9% of PD patients compared to 0.8%–2.9% in controls (Bhalsing, Suresh, Muthane, & Pal, 2013; Krishnan, Bhatia, & Behari, 2003). A prospective 8-year follow-up study showed that the presence of RLS at baseline was associated with a higher risk of PD development. This association was only significant in the first 4-year follow-up but was not observed at the 8-year follow-up period, suggesting that RLS is an early feature of symptomatic PD rather than a risk factor (Wong, Li, Schwarzschild, Ascherio, & Gao, 2014). A recent genetic study revealed no association between PD and RLS-related genetic risk markers including MEIS1, BTBD9, PTPRD, and MAP2KS/SKOR1 (Gan-Or, Alcalay, et al., 2015).

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4. AUTONOMIC SYMPTOMS 4.1 Constipation Another common NMS is constipation. Many studies have shown that constipation predates the onset of PD. For example, the Honolulu-Asia Aging study, a large prospective cohort of 6790 men without PD at the time of enrollment who were followed for a period of 24 years, showed that participants with less frequent bowel movements were more prone to developing PD (Abbott et al., 2001). A recent systematic review and metaanalysis found that individuals with constipation had a 2.27 higher risk of developing PD compared to those without (Adams-Carr et al., 2016). Although controversial, α-synuclein pathology in gastrointestinal mucosae may serve as a viable biomarker for developing PD (Ruffmann & Parkkinen, 2016; Visanji, Marras, Hazrati, Liu, & Lang, 2014). A study showing the presence of α-synuclein in colon mucosae from PD patients obtained 2–5 years before PD onset suggests this possibility (Shannon, Keshavarzian, Dodiya, Jakate, & Kordower, 2012). However, recent studies yielded no clear differences between PD and controls (Antunes et al., 2016; Visanji et al., 2015). A study using colonoscopy biopsied specimens demonstrated that the presence of Lewy neurites within the enteric nervous system is positively associated with constipation (Lebouvier et al., 2010). While the presence of α-synuclein within the gastrointestinal mucosa has not been clearly elucidated as a true link to constipation, further studies are warranted in order to investigate this matter further.

4.2 Orthostatic Hypotension (OH) The presence of OH among PD patients has been a subject of investigation for several years. The prevalence is estimated to be 30% of PD (Velseboer, de Haan, Wieling, Goldstein, & de Bie, 2011). A combination of cardiac, extracardiac noradrenergic denervation, and arterial baroreflex dysfunction may be involved in OH in PD (Jain & Goldstein, 2012). OH has been frequently associated with RBD and can predate the onset of PD as early as 20 years (Postuma et al., 2013). A case–control study showed an increase in the systolic pressure drop in patients with RBD and PD compared to PD alone (Postuma et al., 2009). OH was found in 40% of drug-naı¨ve PD patients in a case–control study. In this study, urinary incontinence was more frequently observed among patients with OH compared to

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patients without OH (Bae, Cheon, & Kim, 2011). Kaiserova et al. assessed for chromogranin A, which is associated with a decrease in noradrenergic cells that can lead to a reduction of sympathoexcitatory responses. They found the CSF levels of chromogranin A were reduced in patients within the early stage of PD compared to controls (Kaiserova et al., 2015). Recently, CSF biomarkers of angiogenesis were investigated in 100 PD patients (Janelidze et al., 2015). This study showed elevated CSF levels of vascular endothelial growth factor and placental growth factor in PD patients with orthostatic diastolic hypotension compared to patients without orthostatic diastolic hypotension. The PD patients who had higher levels of vascular endothelial growth factor and placental growth factor exhibited more severe white matter lesions on brain MRI, suggesting a link between OH and brain hypoxia ( Janelidze et al., 2015). 123I-metaiodobenzylguanidine (MIBG) scintigraphy is a useful tool to detect cardiac sympathetic denervation. A reduced myocardial MIBG uptake has been evident in PD patients (Orimo, Suzuki, Inaba, & Mizusawa, 2012). Some studies claim that a reduced MIBG uptake is related to autonomic symptoms including OH (Guidez et al., 2014; Manabe et al., 2011), whereas others argue against this relationship (Berganzo et al., 2012; Haensch, Lerch, Jorg, & Isenmann, 2009). The association between PD patients with LRRK2 mutations (p.Gly2019Ser and p.Arg1441Gly) and autonomic dysfunction was assessed in a study with 25 PD patients, 12 of which carried the mutation. The study demonstrated that autonomic dysfunction including OH, was less prevalent among mutation carriers than in noncarriers (Tijero et al., 2013).

5. SENSORY SYMPTOMS 5.1 Olfactory Dysfunction Olfactory dysfunction occurs frequently among patients with PD. It is one of the most common NMS of PD. A multicenter study including 400 PD patients who underwent olfactory testing showed that more than 95% of the patients reported reduction of smell (Haehner et al., 2009). A prospective cohort study revealed a link between lower olfactory performance and likelihood of developing PD within a 5-year period among first degree relatives of PD patients (Ponsen et al., 2009). In a prospective cohort of RBD, olfactory dysfunction was detectable at least 5 years before developing

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symptoms suggestive of neurodegenerative diseases (Postuma, Gagnon, Vendette, Desjardins, & Montplaisir, 2011). Although the study sample size was small, a correlation between olfactory dysfunction and reduced glutathione levels in plasma and increased urinary neopterin levels was observed, fueling speculation that decreased antioxidant capacity may underlie olfactory dysfunction (Campolo et al., 2016). Loss of striatal DAT has been observed in patients with olfactory dysfunction without PD, supporting the idea that olfactory dysfunction precedes motor symptoms (Berendse et al., 2001; Sommer et al., 2004). Based on MRI studies, several brain regions were considered to be involved in patients with olfactory dysfunction: olfactory bulb, olfactory tract, piriform cortex, and amygdala (Brodoehl et al., 2012; Rolheiser et al., 2011; Scherfler et al., 2006; Wattendorf et al., 2009). Diffusion tensor imaging showed an association between olfactory dysfunction and fractional anisotropy reduction in the white matter adjacent to gyrus rectus and primary olfactory cortex in PD patients (Ibarretxe-Bilbao et al., 2010). Functional imaging studies using PET suggested that dopaminergic and cholinergic denervation in limbic area is associated with olfactory dysfunction (Bohnen, Gedela, Herath, Constantine, & Moore, 2008; Bohnen et al., 2010).

6. CONCLUSION The role of NMS as a diagnostic marker of PD is currently being established and expanded (Berg et al., 2015). Purported roles of biomarkers for NMS, as prognostic and therapeutic markers remain fertile ground for investigation. Nevertheless, there are biochemical, imaging, and genetic features that may prove to be valuable biomarkers of NMS and PD. Given that NMS does not always precede motor symptoms/signs and sometimes appears at a more advanced stage (e.g., cognitive impairment and impulse control disorders), investigation to differentiate association and pathogeneses are required. Additionally, given the syndromic nature of PD, as a disorder with potentially many causes/pathogeneses, characterization of NMS will require similar scientific discipline to delineate the true nature of NMS in PD. Nevertheless, the opportunity to influence progression of PD through engagement with NMS biomarker understanding represents a topic of tremendous importance for PD patients and researchers.

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