Plasma Neurofilament Light and p-tau181 and Risk of Psychosis in Parkinson’s Disease

Abstract

Background:

Neuropsychiatric symptoms are common and important to people with Parkinson’s disease (PD), but their etiology is poorly understood. Plasma neurofilament light (NfL) and p-tau181 are biomarkers of neuro-axonal degeneration and tau pathology respectively, which have yet to be explored in association with the affective and psychotic symptoms in PD.

Objective:

To investigate the relationship between plasma NfL and p-tau181 with the affective and psychotic symptoms in PD.

Methods:

We assessed the baseline concentration of plasma NfL and p-tau181 in a cohort of 108 patients with PD and 38 healthy controls. A subgroup of patients (n = 63) were assessed annually with clinical measures for up to 7 years. Psychotic symptoms were assessed using the Non-Motor Symptom Scale and affective symptoms were measured in the Hospital Anxiety and Depression Scale.

Results:

Baseline plasma NfL was a significant predictor of psychotic symptoms longitudinally across the study adjusted for age, Hoehn and Yahr stage, duration of follow up, duration of disease, baseline levodopa and dopamine agonist medication, and baseline cognition: (OR 8.15 [95% CI 1.40–47.4], p = 0.020). There was no association between NfL concentration and the cumulative prevalence of affective symptoms. Plasma p-tau181 concentration was not associated with psychotic or affective symptoms.

Conclusion:

These findings suggest psychotic symptoms are associated with greater neurodegeneration in PD. Further studies are needed to explore NfL as a potential biomarker for psychosis in PD.

Keywords

Neurofilament light p-tau psychosis neuropsychiatric symptoms biomarker Parkinson’s disease

INTRODUCTION

Neuropsychiatric symptoms (NPS) such as anxiety, depression, psychosis, and apathy are common in Parkinson’s disease (PD) with almost all patients affected at some point during the disease course [1]. Of these NPS, affective and psychotic symptoms are two of the most important determinants of quality of life in PD [2, 3]. Affective and psychotic symptoms are a significant burden for people with PD, associated with earlier mortality [4], greater caregiver strain [5, 6], and earlier nursing home placement [7]. While these symptoms can co-exist in PD, with negative consequences for cognitive performance [8], factor analyses support their existence as separate subsyndromes [9]. Indeed, their respective clinical implications are differ considerably; the treatment of PD psychosis (PDP) is particularly challenging due to the limited treatment options and increased risk in mortality associated with the use of antipsychotics [10]. Furthermore, evidence suggests key differences in their mechanistic underpinnings with psychosocial determinants likely to contribute more significantly to affective symptoms [11].

Little is known about the biological mechanisms underlying the affective and psychotic symptoms in PD. Older age, cognitive impairment, and longer duration of disease have been identified as predictive factors for both emergent psychosis and depression in PD, but no objective biomarkers exist and the underlying neurobiology remains poorly understood [12]. However, both affective and psychotic symptoms can be seen in the prodromal phase of PD indicating that the neuropathological substrates of PD contribute to their etiology [13, 14]. Indeed, affective and psychotic symptoms have been linked with widespread neurodegeneration both inside and outside nigrostriatal dopaminergic pathways in PD [15 –18]. In PDP, Alzheimer’s disease (AD) pathology may also contribute, with postmortem studies finding increased neurofibrillary tangles and greater burden of hyperphosphorylated tau associated with psychotic symptoms [19 –21]. The earlier emergence of psychotic symptoms in Lewy body dementias relative to AD indicates alpha-synuclein may also be a key contributor to the risk of psychosis, but this has not yet been clearly demonstrated in studies [22]. However, accumulation of alpha-synuclein in the nucleus accumbens, ventral tegmental area, and substantia nigra has been associated with depression in PD [17, 23].

The differing etiologies of the affective and psychotic symptoms in PD are likely multifactorial but the relative importance of transmitter changes, neurodegeneration, neuropathology, and dopaminergic and other medications remains unclear [12 , 25]. Better characterization of the mechanisms behind these important symptoms is crucial to aid novel drug discovery; identifying biomarkers for these NPS would help to determine their biological correlates and, importantly, could offer prognostic value for at risk patients which would lead to more careful monitoring and earlier management [26, 27].

Neurofilament light (NfL) is a specific biomarker for neuro-axonal damage, irrespective of the underlying cause [28]. Plasma and CSF NfL concentrations correlate closely, adding to its promise as a potential candidate for use in clinical practice [29]. Growing consensus suggests that NfL may not be increased in the early stages of PD [30, 31], but higher NfL concentrations are associated with faster disease progression and greater motor and cognitive impairments [32, 33]. Coexistent AD pathology is a common feature of dementia in PD (PDD), seen in over 50% of cases postmortem [34]. Phosphorylated tau at threonine 181 (p-tau181) is a newly established plasma biomarker, specific for AD tau pathology and correlates closely with amyloid-β pathology [35]. Plasma p-tau181 has recently been shown to predict cognitive decline in patients with dementia with Lewy bodies [36].

However, to our knowledge no prior study has looked to investigate an association between plasma NfL or p-tau181 and the affective or psychotic symptoms (A/PS) in PD. Any increase in NfL in patients reporting A/PS would suggest neuro-axonal degeneration as a key factor in the etiology and could offer prognostic value, while an increase in p-tau would indicate a contribution of AD pathology to these symptoms. Here, the aim was to explore the relationship between NfL and p-tau181 concentration with the cumulative prevalence of A/PS over the duration of the study. Given NPS are known to fluctuate in neurodegenerative disease [37], the cumulative prevalence of these symptoms over time is more likely to reflect underlying neurobiological changes measured by plasma biomarkers. A preferential increase in p-tau181 was expected in patients with PDP reflecting the contribution of tau to the etiology suggested by post-mortem studies, and greater concentrations of NfL was anticipated for both A/PS reflecting the contribution of neurodegeneration to the neurobiology of these symptoms.

METHODS

Patient cohort

Plasma samples were taken at study entry between 2012 to 2015 from 108 patients with a diagnosis of probable idiopathic PD from the King’s College Hospital center of the Non-motor International Longitudinal Study (NILS) and 38 age- and sex-matched healthy controls (HC). NILS is a cohort study designed to assess outcomes from non-motor symptoms in PD over time, patients are assessed at baseline with clinical measures and plasma collection and a subgroup (n = 63, 58%) were followed up annually with clinical measures for up to 7 years after inclusion [38]. Follow up length was variable between patients with a median duration of follow up of 4 years. Inclusion required a diagnosis of PD made by a neurologist according to internationally recognized diagnostic criteria [39]. Exclusion criteria include insufficient plasma or clinical information, inability to give informed consent, clinical diagnosis of dementia at baseline or atypical parkinsonism. Plasma samples from HC were retrieved from the NIHR South London and Maudsley BioResource Centre. The NILS study was authorized by local ethics committees (NRES Southeast London REC, 10084, 10/H0808/141). All patients gave written consent prior to study procedures and all patient data were anonymized and coded.

Clinical data

Data extracted for PD patients included sex, age, duration of disease (years), education (years), follow up (FU) duration, dopaminergic medication history including baseline use of levodopa or dopamine agonists, and, where available, the levodopa equivalent daily dose (LEDD), Hoehn and Yahr stage (H&Y) [40], Scales for Outcomes in Parkinson’s Disease (SCOPA-motor) [41], Non-Motor Symptom Scale (NMSS) [42], Hospital Anxiety and Depression Scale (HADS) [43], and Mini-Mental State Examination (MMSE) score [44].

The NMSS is a clinician-rated scale used in PD to assess the severity (0–3) and frequency (1–4) of non-motor symptoms including illusions, hallucinations, and delusions. Severity and frequency are multiplied to give the total score for each item and a binary classification of psychosis was applied for patients scoring ≥1 in either hallucinations or delusions. The HADS is self-administered with patients meeting criteria for affective symptoms if they scored ≥7 on the anxiety or depression items [45]. Anxiety and depression were grouped together as affective symptoms due to the commonality in their underlying etiology. Cognitive impairment was clinician rated using the MMSE.

Plasma NfL concentration

Plasma NfL concentration was measured using the Simoa NF-Light Advantage kit on an HD-X assay platform in n= 143 samples (PD n= 105, HC n= 38) at the UK Dementia Research Institute, University College London, UK. All plasma samples collected during the course of the longitudinal cohort study were stored at –80°C until assayed, NfL is known to be a stable protein resistant to long freezing and multiple freeze thaws [46]. Testers were blinded to samples and 91% (n= 130) were measured in duplicate (insufficient sample available for n= 13). Intra-assay coefficient of variation was 4.55% and inter-assay coefficient of variation were 8.53% and 2.35% respectively for high and low controls. The limit of detection (LOD) was 0.038 pg/mL and the lower limit of quantification (LLOQ) was 0.174 pg/mL.

Plasma p-tau181 concentration

Plasma p-tau was measured for 104 PD samples at King’s College London using the commercially available Simoa^® pTau-181 V2 Advantage Kit (Quanterix; 103714). Plasma was diluted 1 : 4 and read on the HD-1 analyzer. Data acquisition spanned 5 analytical runs, the LLOQ for this assay was 0.127 pg/mL and the coefficient variation (CV) for inter- and intra-assay variability was 7.51% and 7.69% respectively. While plasma p-tau has only been measured in plasma over the last few years, it is known to be stable in CSF [47].

Statistical analysis

PD patients were grouped by A/PS at baseline and by cumulative prevalence of A/PS over the duration of the study. For the longitudinal analysis, cases without FU were excluded as it could not be determined if they developed A/PS in the unstudied period. Cumulative prevalence includes cases with A/PS at baseline or emergent A/PS in FU. Cumulative prevalence was used as the primary outcome given fluctuations in NPS are common in neurodegenerative disease and so point prevalence would likely lead to underestimates of symptomology [37]. ‘New cases’ describe those followed longitudinally who developed emergent A/PS in FU.

Across groups continuous variables were compared using the independent t-tests or Mann-Whitney U-tests, distribution dependent. Categorical data were analyzed with the Chi squared tests. The relationship of plasma NfL to age and gender was compared across PD and HC groups.

Within PD patients, correlations between NfL, p-tau181, and baseline clinical outcomes were assessed with Spearman’s rank correlation and linear regression. NfL and p-tau181 concentration were log-transformed to achieve a normal distribution with the assumption of normality assessed with Shapiro-Wilk tests. The log10 transformed data were used in all analysis. To assess the predictive power of plasma NfL and p-tau181 concentration for A/PS, the cumulative prevalence of A/PS was used in logistic regression as the primary outcome. Logistic regression analyses were adjusted for age, baseline MMSE, H&Y stage, baseline levodopa use (Yes/No), baseline dopamine agonist use (Yes/No), duration of disease, and duration of follow up as these are well-established correlates and predictors of A/PS in PD. LEDD was not available for all cases with longitudinal follow up and so treatment with levodopa or dopamine agonists were used as covariates for the main analysis, although we also explored the influence of LEDD on the findings. Secondary logistic regression was performed for incident psychosis during FU and for hallucinations and delusions separately.

Significance threshold was set to p< 0.05, where applicable values are given for two-tailed tests. Statistical tests were carried out with Stata version 16.0.

RESULTS

Demographic and clinical data

108 PD patients (26F; mean age 63.1±12.4 years) were included with 38 age- and sex-matched HC (12F, 63.2±12.4). Sixty-three (58%) PD patients (16F; mean age 62.6±12.0) were followed longitudinally for mean 3.69±1.76 years. At baseline, mean MMSE was 28.6±2.59, mean H&Y was 2.33±0.76, and mean duration disease was 6.61±5.92 years.

At baseline, 55 (51%) participants reported at least one A/PS, 23 (22%) with psychotic symptoms (hallucinations n = 21, delusions n = 9) and 50 (46%) with affective symptoms (depression n = 32, anxiety n = 35) (Table 1). In the cohort with longitudinal follow up, 50 (74%) cases reported A/PS, in 27 cases persistent from baseline, 19 new onset during the follow up period and 4 with symptoms at baseline which resolved during the follow up period. In patients with follow up, 29 had psychotic symptoms (hallucinations n = 27, delusions n = 17), 14 persistent from the baseline assessment, and 15 new onset during the follow up period. Forty-eight (76%) reported affective symptoms (depression n = 37, anxiety n = 43), 23 persistent from baseline, 21 emergent in the follow up period, and 4 for whom affective symptoms at baseline were no longer present during follow up. The evolution of neuropsychiatric symptoms during the course of the study is illustrated in Table 1.

Table 1

Cases by neuropsychiatric symptom across study duration. A/PS: affective or psychotic symptom

	Baseline (n = 108)		Follow up (n = 63)
	Cases	Evolution of symptoms from baseline	New cases	Total cases
Any A/PS	55 (51%)	27 persistent	19 (31%)	50 (80%)
		4 resolved
		24 no FU
Psychosis (hallucination or delusion)	23 (22%)	14 persistent	15 (24%)	29 (46%)
		9 no FU
Hallucination	21 (20%)	9 persistent	13 (21%)	27 (43%)
		5 resolved
		7 no FU
Delusion	9 (8%)	5 persistent	12 (19%)	17 (27%)
		4 no FU
Illusion or perceptual problem	13 (12%)	8 persistent	10 (16%)	19 (29%)
		1 resolved
		3 no FU
Affective symptoms	50 (46%)	23 persistent	21 (41%)	48 (76%)
		4 resolved
		23 no FU
Depression	32 (30%)	15 persistent	20 (33%)	37 (59%)
		2 resolved
		15 no FU
Anxiety	35 (32%)	15 persistent	25 (39%)	43 (69%)
		3 resolved
		17 no FU

Clinical characteristics of patients with psychotic and affective symptoms cumulatively across the study

Demographic and clinical outcomes for PD patients followed longitudinally with and without psychosis cumulative throughout the study are presented in Table 2. Patients with psychotic symptoms displayed more significant motor impairments (SCOPA-motor: U = –2.69, p = 0.007) and reported a higher burden of affective symptoms (HADS: U = –2.55, p = 0.01) without evidence of more advanced stage of disease (H&Y stage U = –0.40, p = 0.69). Baseline MMSE was equivalent across those with or without psychosis but patients with psychosis had significantly greater annual decline in MMSE (U = –2.23, p = 0.03). Duration of follow up was similar in those with or without psychosis but patients with psychosis trended towards greater duration of disease (U = –1.88, p = 0.06).

Table 2

Demographic and clinical data stratified by the cumulative prevalence of psychotic and affective symptoms in longitudinal follow up. B/l, baseline; H&Y, Hoehn and Yahr stage; LEDD, levodopa equivalent daily dose. ^*n = 53

	Psychosis+ (n = 29)	Psychosis-(n = 34)	Test statistic	p	Affective+ (n = 48)	Affective-(n = 15)	Test statistic	p
Age mean (SD)	63.7 (12.1)	61.7 (12.0)	t(61) = –0.66	0.51	61.9 (12.8)	64.9 (8.89)	t(61) = 0.84	0.41
Female % (n)	31% (9)	21% (7)	χ² = 0.90	0.34	25% (12)	27% (4)	χ² = 0.02	0.90
Education, y mean (SD)	15.4 (4.84)	15.8 (4.44)	U = 0.17	0.87	15.9 (4.64)	14.8 (4.51)	U = –0.75	0.45
Duration of disease, y mean (SD)	6.10 (3.40)	4.63 (4.19)	U = –1.88	0.06	5.27 (3.83)	5.41 (4.19)	U = 0.05	0.96
B/l MMSE mean (SD)	28.3 (3.27)	29.3 (1.48)	U = 1.59	0.11	28.6 (2.78)	29.4 (1.12)	U = 0.85	0.39
B/l HADS mean (SD)	11.9 (7.73)	7.62 (5.38)	U = –2.69	0.007	11.3 (6.97)	4.07 (1.58)	U = –4.46	<0.001
B/l H&Y stage mean (SD)	2.38 (0.73)	2.32 (0.77)	U = –0.40	0.69	2.35 (0.73)	2.33 (0.82)	U = –0.13	0.90
B/l SCOPA-motor mean (SD)	19.1 (6.50)	14.6 (9.34)	U = –2.50	0.01	18.4 (8.26)	10.9 (6.11)	U = –3.24	0.001
LEDD^* mg mean (SD)	984 (721)	472 (439)	U = –3.16	0.002	753 (663)	508 (472)	U = –1.10	0.27
B/l levodopa use % (n)	83% (24)	53% (18)	χ² = 6.26	0.01	68% (32)	73% (11)	χ² = 0.15	0.70
B/l dopamine agonist use % (n)	69% (20)	70% (23)	χ² = 0.003	0.95	71% (34)	53% (8)	χ² = 1.58	0.21
Duration of follow up, y mean (SD)	3.72 (1.78)	3.67 (1.78)	U = 0	1.00	3.72 (1.79)	3.40 (1.71)	U = –0.37	0.71
Annual MMSE decline mean (SD)	0.88 (1.51)	0.37 (0.88)	U = –2.23	0.03	0.65 (1.26)	0.48 (1.17)	U = –1.08	0.28

The majority of PD patients (76%) met criteria for anxiety or depression at some point in the duration of the study. Demographic and clinical outcomes for affective symptoms are included in Table 2. There was no difference in cognition or disease stage in patients with or without affective symptoms but those with affective symptoms showed significantly greater degree of motor impairment (SCOPA-motor: U = –2.88, p = 0.001).

Medication use and psychosis

In the full cohort at baseline, 93% (n = 100) were treated with dopamine replacement therapy (DRT); 77% (n = 84) were treated with levodopa, 61% (n = 65) were treated with dopamine agonists, and 46% (n = 50) were treated with combined therapy. There was no difference in LEDD across patients with or without psychosis at baseline (psychosis+ 756.5 mg versus psychosis– 688.6 mg, U = –0.71, p = 0.48).

For participants with longitudinal follow up, 87% (n = 55) were treated with DRT at baseline with 48% (n = 30) on combined levodopa and dopaminergic agonists. A quarter (n = 2) of the 8 medication naïve patients at baseline reported psychotic symptoms. A greater proportion of participants with psychosis received combined treatment than those without psychosis but the difference did not meet significance (59% versus 33%, χ² = 2.28, p = 0.13). Significantly more patients with psychosis were prescribed levodopa (psychosis+ 83% versus psychosis– 53%, χ² = 6.26, p = 0.01) but there was no difference in treatment with dopamine agonists (Table 2). LEDD was significantly higher in those with psychotic symptoms than those without (984 mg versus 472 mg, U = –3.16, p = 0.002) but this data was not available for all participants. There was no difference in DRT across participants with or without affective symptoms.

Plasma NfL concentration and A/PS

There was no significant difference in NfL levels between HC (mean 23.5 pg/mL ± 20.2) and PD samples (mean 26.2 pg/mL ± 16.3), (logNfL t(139) = –1.86, p = 0.06). In linear regression increased age was predictive of greater plasma NfL levels (R² = 0.17, p < 0.001). No gender differences were seen in NfL concentrations (logNfL t(139) = –0.62, p = 0.54).

There was no association between psychosis at baseline and NfL concentration (OR 1.71 [0.72–4.10], p = 0.23). However, in those with longitudinal follow up, higher NfL concentration was a significant predictor of cumulative prevalence of psychosis in logistic regression adjusted for age, baseline MMSE, H&Y stage, use of levodopa, use of dopamine agonist, duration of disease, and duration of follow up (OR 8.15 [95% CI 1.40–47.4], p = 0.020) (Table 3). Where SCOPA-motor was introduced as a covariate rather than duration of disease and H&Y stage, both of which it was highly correlated with (r = 0.36, p < 0.005 and r = 0.60, p < 0.005 respectively), NfL remained a significant predictor of the cumulative prevalence of psychosis (OR 6.12 [1.03–36.5], p = 0.047). Higher baseline NfL was also associated with greater odds of new onset incident psychosis in the follow up period in logistic regression adjusted for age, baseline cognition, H&Y, baseline levodopa and dopamine agonist medication, duration of disease, and duration of follow up (OR 8.82 [95% CI 1.02–76.6], p = 0.048). There was trend association between baseline NfL and cumulative prevalence of hallucinations in similarly adjusted logistic regression (OR 5.42 [95% CI 0.96–30.47], p = 0.055) but no association between NfL and delusions [OR 2.26 [95% CI 0.41–12.3], p = 0.35). However, if LEDD (rather than proportion treated) is added as a covariate for the reduced number of participants for whom it is available (n = 53), NfL is no longer a significant predictor of the cumulative prevalence of psychosis in the study (OR 2.96 [0.52–16.7], p = 0.21).

Table 3

Baseline plasma NfL and p-tau181 concentration stratified by neuropsychiatric symptoms in logistic regression models adjusted for age, baseline MMSE, duration of follow up, duration of disease, baseline levodopa and dopamine agonist use and H&Y stage

	Mean plasma NfL concentration (pg/mL) mean (SD), n = 61				Mean plasma p-tau concentration (pg/mL) mean (SD), n = 61
	Symptom present	Symptom absent	OR [95% CI]	p	Symptom present	Symptom absent	OR [95% CI]	p
Affective symptoms	23.9 (12.4)	21.4 (8.99)	3.87 [0.66–22.9]	0.14	2.11 (1.12)	2.64 (1.97)	0.25 [0.01–4.64]	0.35
Depression	23.9 (12.0)	22.5 (11.2)	3.85 [0.77–19.3]	0.10	2.14 (1.18)	2.40 (1.65)	0.37 [0.03–5.35]	0.47
Anxiety	24.5 (12.7)	20.6 (8.53)	4.08 [0.73–22.7]	0.11	2.18 (1.13)	2.36 (1.80)	0.80 [0.06–10.8]	0.87
Psychosis (hallucinations+/–delusions)	26.1 (11.4)	20.9 (11.5)	8.15 [1.40–47.4]	0.020	2.43 (1.10)	2.07 (1.54)	3.63 [0.22–59.3]	0.37
Hallucination	26.2 (11.7)	21.1 (11.2)	5.42 [0.96–30.47]	0.055	2.43 (1.12)	2.08 (1.52)	3.00 [0.20–45.5]	0.43
Delusion	24.4 (9.84)	22.9 (12.3)	2.26 [0.41–12.3]	0.35	2.28 (1.00)	2.22 (1.48)	0.45 [0.02–12.5]	0.64
Illusions and perceptual difficulties	23.2 (11.3)	23.3 (11.9)	1.68 [0.31–9.06]	0.55	2.16 (1.24)	2.27 (1.42)	1.15 [0.09–14.7]	0.91

There was no correlation between plasma NfL and HADS scores at baseline (rho = 0.04, p = 0.68). Cumulative affective symptoms across the duration of study was not associated with higher baseline plasma NfL in logistic regression adjusted for age, baseline cognition, H&Y stage, levodopa and dopamine agonist medication, duration of disease, and duration of follow up (OR 3.87 [95% CI 0.66–22.9], p = 0.14) (Table 3).

In PD patients, NfL concentration was correlated with the duration with PD (r(105) = 0.27, p = 0.01). Increased plasma NfL was correlated with lower baseline MMSE score (r(105) = –0.30, p = 0.002).

Plasma NfL was positively correlated with scores on SCOPA-motor (r(81) = 0.28, p = 0.012). In linear regression adjusted for age, NfL was a significant predictor of SCOPA motor scores (adjusted R² = 0.23, p = 0.01). NfL was also positively correlated with H&Y (r(85) = 0.27, p = 0.01). NfL concentration was higher in participants lost to follow up but the difference was not significant (logNfL t(103) = 1.72, p = 0.09).

Plasma p-tau181 concentration

There was trend association between increasing age and greater plasma p-tau181 in linear regression (Pearson corr 0.19; adjusted R² = 0.02, p= 0.05). No sex differences in p-tau181 were seen across patients with PD (logp-tau t(104)=1.12, p= 0.26). Plasma p-tau was also higher in participants lost to follow up but the difference was not significant (logp-tau t(102)=1.31, p= 0.19).

Psychosis at baseline was not associated with plasma p-tau181 concentration (OR 3.08 [0.43–21.9], p= 0.26). In logistic regression adjusted for age, H&Y, duration of disease, duration of FU, levodopa and dopamine agonist medication and baseline MMSE, plasma p-tau181 also showed no association with cumulative prevalence of psychosis (OR 3.63 [95% CI 0.22–59.3], p= 0.37) (Table 3). There was no correlation between baseline HADS score and plasma p-tau181 (r(102)=–0.05, p= 0.59) and there was no association between p-tau181 concentration and cumulative affective symptoms across the course of the study in adjusted logistic regression (OR 0.25 [95% CI 0.01–4.64]], p= 0.35).

DISCUSSION

In the first longitudinal study to explore the relationship between plasma NfL and p-tau181 with the affective and psychotic symptoms in PD, increased NfL concentration was associated with both greater longitudinal risk of PDP and greater odds of incident psychosis. Plasma NfL concentration was not associated with the cumulative prevalence of affective symptoms, and we did not see any association between p-tau181 concentration and psychotic or affective symptoms in PD.

NfL is a well-established cross-disease biomarker of axonal degeneration [28]. The higher concentration of NfL in PDP suggests a potential role for neurodegeneration in the etiology of psychosis and may also have translational relevance to other psychotic disorders given susceptibility to psychosis is increasingly viewed trans-diagnostically [48]. The association between increased NfL and greater odds of incident psychosis suggests NfL may have also potential as a biomarker to indicate patients at increased risk of future PDP, who may benefit from more frequent monitoring and earlier intervention, but this finding requires replication in a larger cohort. Neither hallucinations or delusions were associated with NfL concentration individually, but the trend association observed between hallucinations and NfL suggests this negative finding may reflect the smaller numbers with positive symptomology, with the current study underpowered to detect a difference. Future studies should aim to explore the relationship between NfL and hallucinations and delusions separately in a larger cohort. This relationship between NfL and the cumulative prevalence of psychosis perhaps unsurprising given PDP is associated with extensive neurodegeneration of limbic, paralimbic, and neocortical gray matter [18] and has recently been associated with increased density of Lewy bodies and greater neuronal loss and gliosis both inside and outside the substantia nigra [20, 49]. Furthermore, in patients with mild cognitive impairment, emergent mild behavioral impairment has also been associated with increases in NfL suggesting that neurodegeneration may drive these clinical symptoms at an early stage [50].

However, where LEDD was introduced as a covariate, albeit for a reduced number of participants, the association between NfL and PDP was no longer significant. While this be could interpreted to suggest that LEDD accounts for the variance in psychosis, we believe this is unlikely to be the full explanation given that no correlation is seen between LEDD and NfL (r= 0.14, p= 0.32). Therefore, while LEDD may be an important contributor to PDP, given it is not itself associated with NfL, it is unlikely to account for the difference in NfL concentration across the groups with and without psychosis. LEDD is closely correlated with a number of other covariates such as H&Y (p< 0.05) and duration of disease (p< 0.005) and so it may be that multicollinearity between the variables is a contributing factor to the reduction in significance. Furthermore, LEDD was not available for 13% (n= 8) of participants and so the regression analyses may be underpowered to detect an association between NfL and the cumulative prevalence of psychosis for this reduced number of cases. For those participants where LEDD was available, it related to baseline, not time of psychosis onset, and it is possible the NfL difference would remain significant using a more temporally relevant LEDD value. Where binary classifications for the use of levodopa and dopamine agonist medication (which are available for the full cohort) are used as proxies to adjust for medication effects, cumulative prevalence of psychosis is significantly associated with higher NfL concentration. Indeed, despite the known association between medication exposure and PDP, previous studies have found that dosage and duration of dopaminergic medication do not clearly correlate with psychosis and incident psychosis does not appear to be related to medication onset or dose increases [25]. Thus it seems likely that PDP likely represents a complex intersection of exogenous and endogenous factors with both dopaminergic medication and neurodegeneration important factors in their etiology.

Previous postmortem studies have suggested AD pathology may also contribute to PDP with hallucinations associated with a widespread increase in amyloid-β plaque and tangle densities in later stage PD [20]. Our results did not reflect these postmortem findings, which perhaps reflects the earlier stage of PD of the patients included in the study, typically PDP at the mild cognitive impairment stage has Lewy bodies mainly restricted to the amygdala with limited AD pathology [51]. Further studies with larger sample sizes, more advanced PD and more comprehensive follow up are needed to explore the role of p-tau181 as a marker of psychosis in PD.

No increase in NfL or p-tau181 was seen in patients with affective symptoms in the study. However, only a minority of patients (n= 15, 24%) did not report affective symptoms at some point during the study and so it could be that the study is underpowered to detect differences for the cumulative prevalence of affective symptoms. An increase in NfL might be expected for patients with depression given the development of affective symptoms is particularly associated with neuronal loss and gliosis in the locus coeruleus and substantia nigra [16 , 49]. However, while in some cases affective symptoms likely develop due to pathological changes inherent to PD, in other cases depression may be incidental or intrinsic to the comorbidity of a chronic condition with greater psychosocial influences rather than specifically related to neurodegenerative processes in PD [52]. Where the etiology of depression differs, the underlying neurobiology may also differ which could cause variation in the degree of neurodegeneration and subsequent NfL increases in PD patients with depression.

Limitations

While the longitudinal nature of this study is one of its major strengths, the attrition rate and variation in the length of follow up could affect the estimates of patient numbers developing A/PS. To calculate the cumulative frequency of A/PS, patients without follow up were excluded reducing the number of participants included. Subsequently, our sample size was small and limited further by missing data for some key variables such as LEDD. This may underlie some of the negative findings in the study and future studies should aim to include larger cohorts to address this. Furthermore, NfL and p-tau181 concentrations were only measured at baseline and so we were not able to monitor changes in these biomarkers in patients who developed A/PS during the study, this would have been particularly interesting given associations with NfL were seen with cumulative prevalence rather than at baseline. Future studies should aim to investigate whether emergence of A/PS over time are associated with further increases in NfL.

A/PS were assessed in this study using the NMSS for psychotic symptoms and HADS for affective symptoms. While the NMSS allows for the assessment of severity and frequency of hallucinations and delusions and correlates closely with similar items on the Neuropsychiatric Inventory, the perceptual and hallucinatory domains have lower internal consistency [53]. Furthermore, the NMSS lacks the breadth of NPS assessed in the Neuropsychiatric Inventory and does not include a number of symptoms known to be common to PD such as apathy and impulse control disorders [54]. We were therefore unable to adjust for the overall NPS burden or other potentially overlapping symptoms such as agitation or apathy in our analysis. Other scales such as the MDS-NMS also offer greater phenomenological detail than the NMSS assessing illusions, passage, and presence hallucinations in addition to modality of hallucination [55]. In our study, the HADS was used to supplement the NMSS due to the greater diagnostic detail it offers for symptoms of depression and anxiety. The HADS is validated for use in PD [56] and was closely correlated with the mood domain of the NMSS (r = 0.7) in our study but our use of differing scales for the affective and psychotic symptoms means they were not assessed uniformly and may have led to relative overestimates of affective symptoms. Future studies should aim to use additional measures of NPS which are validated in PD and include fine-grained assessment of A/PS.

This longitudinal cohort study was designed with MMSE rather than the Montreal Cognitive Assessment which is known to be more sensitive in PD in the pre-dementia stage [57]. However, while the Montreal Cognitive Assessment shows greater variability in PD, MMSE has been shown to be a suitable scale to measure cognitive abilities in PD and given cognition was not the primary end point of this study, use of this scale should not affect the validity of our results [57].

Conclusions

NfL may have potential as a predictive marker for the cumulative prevalence of psychotic symptoms in PD, but further studies are needed to delineate this relationship and the role of LEDD. The rise in NfL in participants with psychosis across the study suggests axonal neurodegeneration may be an important etiological factor in the development of psychosis and suggests NfL may have future promise as a prognostic marker for these common and hard to treat symptoms. Further studies are needed to explore the longitudinal characterization of A/PS with a wide array of biomarkers, both new and existing.

Footnotes

ACKNOWLEDGMENTS

We thank NIHR BioResource volunteers for their participation, and gratefully acknowledge NIHR BioResource centers, NHS Trusts and staff for their contribution. We thank the National Institute for Health Research, NHS Blood and Transplant, and Health Data Research UK as part of the Digital Innovation Hub Programme. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. This represents independent research partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. This work was also supported by a grant from King’s Health Partners.

HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712), Swedish State Support for Clinical Research (#ALFGBG-720931), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C and #ADSF-21-831377-C), the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2019-0228), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), European Union Joint Program for Neurodegenerative Disorders (JPND2021-00694), and the UK Dementia Research Institute at UCL.

TAP was supported in a clinical lectureship by the National Institute for Health Research (NIHR). LLG is funded by NIHR Academic Clinical Fellowship and an Alzheimer’s Society fellowship.

CONFLICT OF INTEREST

HZ has served at scientific advisory boards and/or as a consultant for Abbvie, Alector, Annexon, Artery Therapeutics, AZTherapies, CogRx, Denali, Eisai, Nervgen, Pinteon Therapeutics, Red Abbey Labs, Passage Bio, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure, Biogen, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work).

DA has received research support and/or honoraria from Astra-Zeneca, H. Lundbeck, Novartis Pharmaceuticals, Evonik, and GE Health and has served as paid consultant for H. Lundbeck, Eisai, Heptares, Mentis Cura, Eli Lilly, and Biogen.

KRC is in the advisory board of AbbVie, UCB, GKC, Bial, Cynapsus, Lobsor, Stada, Medtronic, Zambon, Profile, Sunovion, Roche, Therevance, Scion, Britannia, Acadia and 4D, has received honoraria for lectures from AbbVie, Britannia, UCB, Zambon, Novartis, Boeringer Ingelheim and Bial, and reports grants for investigator-initiated studies from Britania Pharmaceuticals, AbbVie, UCB, GKC and Bial as well as academic grants from EU, IMI EU, Horizon 2020, Parkinson’s UK, NIHR, PDNMG, Kirby Laing Foundation, NPF, MRC, and Wellcome Trust.

References

Kim

, Shin

, Park

, Kim

, Jeon

(2020) Longitudinal evolution of non-motor symptoms according to age at onset in early Parkinson’s disease. J Neurol Sci 418, 117157.

Schrag

(2006) Quality of life and depression in Parkinson’s disease. J Neurol Sci 248, 151–157.

Fredericks

, Norton

, Atchison

, Schoenhaus

, Pill

(2017) Parkinson’s disease and Parkinson’s disease psychosis: A perspective on the challenges, treatments, and economic burden. Am J Manag Care 23, S83–S92.

de Lau

, Verbaan

, van Rooden

, Marinus

, van Hilten

(2014) Relation of clinical subtypes in Parkinson’s disease with survival. Mov Disord 29, 150–151.

Lee

, McKeith

, Mosimann

, Ghosh-Nodyal

, Thomas

(2013) Examining carer stress in dementia: The role of subtype diagnosis and neuropsychiatric symptoms. Int J Geriatr Psychiatry 28, 135–141.

Schrag

, Hovris

, Morley

, Quinn

, Jahanshahi

(2006) Caregiver-burden in parkinson’s disease is closely associated with psychiatric symptoms, falls, and disability. Parkinsonism Relat Disord 12, 35–41.

Aarsland

, Larsen

, Tandberg

, Laake

(2000) Predictors of nursing home placement in Parkinson’s disease: A population-based, prospective study. J Am Geriatr Soc 48, 938–942.

Liew

(2019) Symptom clusters of neuropsychiatric symptoms in mild cognitive impairment and their comparative risks of dementia: A cohort study of 8530 older persons. J Am Med Dir Assoc 20, 1054.e1–1054.e9.

Aalten

, Verhey

, Boziki

, Bullock

, Byrne

, Camus

, Caputo

, Collins

, De Deyn

, Elina

, Frisoni

, Girtler

, Holmes

, Hurt

, Marriott

, Mecocci

, Nobili

, Ousset

, Reynish

, Salmon

, Tsolaki

, Vellas

, Robert

(2007) Neuropsychiatric syndromes in dementia. Results from the European Alzheimer Disease Consortium: Part I. Dement Geriatr Cogn Disord 24, 457–463.

10.

Schneider

, Dagerman

, Insel

(2005) Risk of death with atypical antipsychotic drug treatment for dementia: Meta-analysis of randomized placebo-controlled trials. JAMA 294, 1934–1943.

11.

Rod

, Bordelon

, Thompson

, Marcotte

, Ritz

(2013) Major life events and development of major depression in Parkinson’s disease patients. Eur J Neurol 20, 663–670.

12.

Factor

, Steenland

, Higgins

, Molho

, Kay

, Montimurro

, Rosen

, Zabetian

, Payami

(2011) Disease-related and genetic correlates of psychotic symptoms in Parkinson’s disease. Mov Disord 26, 2190–2195.

13.

Schrag

, Horsfall

, Walters

, Noyce

, Petersen

(2015) Prediagnostic presentations of Parkinson’s disease in primary care: A case-control study. Lancet Neurol 14, 57–64.

14.

Pagonabarraga

, Martinez-Horta

, Fernandez de Bobadilla

, Perez

, Ribosa-Nogue

, Marin

, Pascual-Sedano

, Garcia

, Gironell

, Kulisevsky

(2016) Minor hallucinations occur in drug-naive Parkinson’s disease patients, even from the premotor phase. Mov Disord 31, 45–52.

15.

Ffytche

, Creese

, Politis

, Chaudhuri

, Weintraub

, Ballard

, Aarsland

(2017) The psychosis spectrum in Parkinson disease. Nat Rev Neurol 13, 81–95.

16.

Frisina

, Haroutunian

, Libow

(2009) The neuropathological basis for depression in Parkinson’s disease. Parkinsonism Relat Disord 15, 144–148.

17.

Saari

, Heiskanen

, Gardberg

, Kaasinen

(2021) Depression and nigral neuron density in Lewy body spectrum diseases. Ann Neurol 89, 1046–1050.

18.

Barrett

, Blair

, Sperling

, Smolkin

, Druzgal

(2018) Baseline symptoms and basal forebrain volume predict future psychosis in early Parkinson disease. Neurology 90,e1618–e1626.

19.

Ehrenberg

, Suemoto

, Franca Resende

, Petersen

, Leite

REP

, Rodriguez

, Ferretti-Rebustini

REL

, You

, Oh

, Nitrini

, Pasqualucci

, Jacob-Filho

, Kramer

, Gatchel

, Grinberg

(2018) Neuropathologic correlates of psychiatric symptoms in Alzheimer’s disease. J Alzheimers Dis 66, 115–126.

20.

Jacobson

, Morshed

, Dugger

, Beach

, Hentz

, Adler

, Shill

, Sabbagh

, Belden

, Sue

, Caviness

, Hu

,Arizona Parkinson’s Disease Consortium (2014) Plaques and tangles as well as Lewy-type alpha synucleinopathy are associated with formed visual hallucinations. Parkinsonism Relat Disord 20, 1009–1014.

21.

Murray

, Kirkwood

, Gray

, Fish

, Ikonomovic

, Hamilton

, Kofler

, Klunk

, Lopez

, Sweet

(2014) Hyperphosphorylated tau is elevated in Alzheimer’s disease with psychosis. J Alzheimers Dis 39, 759–773.

22.

Ismail

, Creese

, Aarsland

, Kales

, Lyketsos

, Sweet

, Ballard

(2022) Psychosis in Alzheimer disease - mechanisms, genetics and therapeutic opportunities. Nat Rev Neurol 18, 131–144.

23.

Patterson

, Rushton

, Attems

, Thomas

, Morris

(2019) Degeneration of dopaminergic circuitry influences depressive symptoms in Lewy body disorders. Brain Pathol 29, 544–557.

24.

Aarsland

, Marsh

, Schrag

(2009) Neuropsychiatric symptoms in Parkinson’s disease. Mov Disord 24, 2175–2186.

25.

Dave

, Weintraub

, Aarsland

, Ffytche

(2020) Drug and disease effects in Parkinson’s psychosis: Revisiting the role of dopamine. Mov Disord Clin Pract 7, 32–36.

26.

Fischer

, Ismail

, Youakim

, Creese

, Kumar

, Nunez

, Ryan Darby

, Di Vita

, D’Antonio

, de Lena

, McGeown

, Ramit

, Rasmussen

, Bell

, Wang

, Bruneau

, Panegyres

, Lanctot

, Aguera-Ortiz

, Lyketsos

, Cummings

, Jeste

, Sano

, Devanand

, Sweet

, Ballard

(2020) Revisiting criteria for psychosis in Alzheimer’s disease and related dementias: Toward better phenotypic classification and biomarker research. J Alzheimers Dis 73, 1143–1156.

27.

Cummings

, Pinto

, Cruz

, Fischer

, Gerritsen

, Grossberg

, Hwang

, Ismail

, Jeste

, Koopmans

, Lanctot

, Mateos

, Peschin

, Sampaio

, Tsuang

, Wang

, Zhong

, Bain

, Sano

(2020) Criteria for psychosis in major and mild neurocognitive disorders: International Psychogeriatric Association (IPA) Consensus Clinical and Research Definition. Am J Geriatr Psychiatry 28, 1256–1269.

28.

Ashton

, Janelidze

, Al Khleifat

, Leuzy

, van der Ende

, Karikari

, Benedet

, Pascoal

, Lleo

, Parnetti

, Galimberti

, Bonanni

, Pilotto

, Padovani

, Lycke

, Novakova

, Axelsson

, Velayudhan

, Rabinovici

, Miller

, Pariante

, Nikkheslat

, Resnick

, Thambisetty

, Scholl

, Fernandez-Eulate

, Gil-Bea

, Lopez de Munain

, Al-Chalabi

, Rosa-Neto

, Strydom

, Svenningsson

, Stomrud

, Santillo

, Aarsland

, van Swieten

, Palmqvist

, Zetterberg

, Blennow

, Hye

, Hansson

(2021) A multicentre validation study of the diagnostic value of plasma neurofilament light. Nat Commun 12, 3400.

29.

Zetterberg

, Blennow

(2018) From cerebrospinal fluid to blood: The third wave of fluid biomarkers for Alzheimer’s disease. J Alzheimers Dis 64, S271–S279.

30.

Zetterberg

(2020) Is there a value of neurofilament light as a biomarker for neurodegeneration in Parkinson’s disease? Mov Disord 35, 1111–1112.

31.

Marques

, van Rumund

, Oeckl

, Kuiperij

, Esselink

RAJ

, Bloem

, Otto

, Verbeek

(2019) Serum NFL discriminates Parkinson disease from atypical parkinsonisms. Neurology 92, e1479–e1486.

32.

Lerche

, Wurster

, Roben

, Zimmermann

, Machetanz

, Wiethoff

, Dehnert

, Rietschel

, Riebenbauer

, Deuschle

, Stransky

, Lieplt-Scarfone

, Gasser

, Brockmann

(2020) CSF NFL in a longitudinally assessed PD cohort: Age effects and cognitive trajectories. Mov Disord 35, 1138–1144.

33.

Pilotto

, Imarisio

, Conforti

, Scalvini

, Masciocchi

, Nocivelli

, Turrone

, Gipponi

, Cottini

, Borroni

, Rizzetti

, Pizzi

, Bonanni

, Sturchio

, Espay

, Zetterberg

, Ashton

, Hye

, Padovani

(2021) Plasma NfL, clinical subtypes and motor progression in Parkinson’s disease. Parkinsonism Relat Disord 87, 41–47.

34.

Smith

, Malek

, Grosset

, Cullen

, Gentleman

, Grosset

(2019) Neuropathology of dementia in patients with Parkinson’s disease: A systematic review of autopsy studies. J Neurol Neurosurg Psychiatry 90, 1234–1243.

35.

Skillback

, Farahmand

, Rosen

, Mattsson

, Nagga

, Kilander

, Religa

, Wimo

, Winblad

, Schott

, Blennow

, Eriksdotter

, Zetterberg

(2015) Cerebrospinal fluid tau and amyloid-beta1-42 in patients with dementia. Brain 138, 2716–2731.

36.

Gonzalez

, Ashton

, Gomes

, Tovar-Rios

, Blanc

, Karikari

, Mollenhauer

, Pilotto

, Lemstra

, Paquet

, Abdelnour

, Kramberger

, Bonanni

, Vandenberghe

, Hye

, Blennow

, Zetterberg

, Aarsland

, European–Dementia With Lewy Bodies (E-DLB) Consortium (2021) Association of Plasma p-tau181 and p-tau231 concentrations with cognitive decline in patients with probable dementia with Lewy bodies. JAMA Neurol 79, 32–37.

37.

Vik-Mo

, Giil

, Borda

, Ballard

, Aarsland

(2020) The individual course of neuropsychiatric symptoms in people with Alzheimer’s and Lewy body dementia: 12-year longitudinal cohort study. Br J Psychiatry 216, 43–48.

38.

van Wamelen

, Sauerbier

, Leta

, Rodriguez-Blazquez

, Falup-Pecurariu

, Rodriguez-Violante

, Rizos

, Tsuboi

, Metta

, Bhidayasiri

, Bhattacharya

, Borgohain

, Prashanth

, Rosales

, Lewis

, Fung

, Behari

, Goyal

, Kishore

, Lloret

, Martinez-Martin

, Chaudhuri

(2021) Cross-sectional analysis of the Parkinson’s disease Non-motor International Longitudinal Study baseline non-motor characteristics, geographical distribution and impact on quality of life. Sci Rep 11, 9611.

39.

Lees

, Hardy

, Revesz

(2009) Parkinson’s disease. Lancet 373, 2055–2066.

40.

Hoehn

, Yahr

(1967) Parkinsonism: Onset, progression and mortality. Neurology 17, 427–442.

41.

Martinez-Martin

, Benito-Leon

, Burguera

, Castro

, Linazasoro

, Martinez-Castrillo

, Valldeoriola

, Vazquez

, Vivancos

, del Val

, van Blercom

, Frades

(2005) The SCOPA-Motor Scale for assessment of Parkinson’s disease is a consistent and valid measure. J Clin Epidemiol 58, 674–679.

42.

Chaudhuri

, Martinez-Martin

, Brown

, Sethi

, Stocchi

, Odin

, Ondo

, Abe

, Macphee

, Macmahon

, Barone

, Rabey

, Forbes

, Breen

, Tluk

, Naidu

, Olanow

, Williams

, Thomas

, Rye

, Tsuboi

, Hand

, Schapira

(2007) The metric properties of a novel non-motor symptoms scale for Parkinson’s disease: Results from an international pilot study. Mov Disord 22, 1901–1911.

43.

Zigmond

, Snaith

(1983) The hospital anxiety and depression scale. Acta Psychiatr Scand 67, 361–370.

44.

Folstein

, Robins

, Helzer

(1983) The Mini-Mental State Examination. Arch Gen Psychiatry 40, 812.

45.

, Levis

, Sun

, He

, Krishnan

, Neupane

, Bhandari

, Negeri

, Benedetti

, Thombs

, DEPRESsion Screening Data (DEPRESSD) HADS Group (2021) Accuracy of the Hospital Anxiety and Depression Scale Depression subscale (HADS-D) to screen for major depression: Systematic review and individual participant data meta-analysis. BMJ 373, n972.

46.

Kuhle

, Plavina

, Barro

, Disanto

, Sangurdekar

, Singh

, de Moor

, Engle

, Kieseier

, Fisher

, Kappos

, Rudick

, Goyal

(2020) Neurofilament light levels are associated with long-term outcomes in multiple sclerosis. Mult Scler 26, 1691–1699.

47.

Schipke

, Jessen

, Teipel

, Luckhaus

, Wiltfang

, Esselmann

, Frolich

, Maier

, Ruther

, Heppner

, Prokop

, Heuser

, Peters

(2011) Long-term stability of Alzheimer’s disease biomarker proteins in cerebrospinal fluid. J Alzheimers Dis 26, 255–262.

48.

Creese

, Vassos

, Bergh

, Athanasiu

, Johar

, Rongve

, Medboen

, Vasconcelos Da Silva

, Aakhus

, Andersen

, Bettella

, Braekhus

, Djurovic

, Paroni

, Proitsi

, Saltvedt

, Seripa

, Stordal

, Fladby

, Aarsland

, Andreassen

, Ballard

, Selbaek

, AddNeuroMed consortium and the Alzheimer’s Disease Neuroimaging Initiative (2019) Examining the association between genetic liability for schizophrenia and psychotic symptoms in Alzheimer’s disease. Transl Psychiatry 9, 273.

49.

Fischer

, Hinkle

, Perepezko

, Bakker

, Morris

, Broen

MPG

, Butala

, Dawson

, Leentjens

AFG

, Mari

, Marvel

, Mills

, Rosenthal

, Shepard

, Pantelyat

, Bakker

, Pletnikova

, Troncoso

, Wang

, Pontone

(2021) Brainstem pathologies correlate with depression and psychosis in Parkinson’s disease. Am J Geriatr Psychiatry 29, 958–968.

50.

Naude

, Gill

, Hu

, McGirr

, Forkert

, Monchi

, Stys

, Smith

, Ismail

, Alzheimer’s Disease Neuroimaging Initiative (2020) Plasma neurofilament light: A marker of neurodegeneration in mild behavioral impairment. J Alzheimers Dis 76, 1017–1027.

51.

Kalaitzakis

, Christian

, Moran

, Graeber

, Pearce

, Gentleman

(2009) Dementia and visual hallucinations associated with limbic pathology in Parkinson’s disease. Parkinsonism Relat Disord 15, 196–204.

52.

Even

, Weintraub

(2012) Is depression in Parkinson’s disease (PD) a specific entity? . J Affect Disord 139, 103–112.

53.

van Wamelen

, Martinez-Martin

, Weintraub

, Schrag

, Antonini

, Falup-Pecurariu

, Odin

, Ray Chaudhuri

, International Parkinson and Movement Disorder Society Parkinson’s Disease Non-Motor Study Group (2021) The Non-Motor Symptoms Scale in Parkinson’s disease: Validation and use. Acta Neurol Scand 143, 3–12.

54.

Aarsland

, Kramberger

(2015) Neuropsychiatric symptoms in Parkinson’s disease. J Parkinsons Dis 5, 659–667.

55.

Martinez-Martin

, Schrag

, Weintraub

, Rizos

, Rodriguez-Blazquez

, Chaudhuri

, Group INMPS (2019) Pilot study of the International Parkinson and Movement Disorder Society-sponsored Non-motor Rating Scale (MDS-NMS). Mov Disord Clin Pract 6, 227–234.

56.

Rodriguez-Blazquez

, Frades-Payo

, Forjaz

, de Pedro-Cuesta

, Martinez-Martin

, Longitudinal Parkinson’s Disease Patient Study Group (2009) Psychometric attributes of the Hospital Anxiety and Depression Scale in Parkinson’s disease. Mov Disord 24, 519–525.

57.

Biundo

, Weis

, Bostantjopoulou

, Stefanova

, Falup-Pecurariu

, Kramberger

, Geurtsen

, Antonini

, Weintraub

, Aarsland

(2016) MMSE and MoCA in Parkinson’s disease and dementia with Lewy bodies: A multicenter 1-year follow-up study. J Neural Transm (Vienna) 123, 431–438.