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EARLY RECOGNITION OF COGNITIVE ABILITY AND NUTRITIONAL MARKERS FOR DEMENTIA IN PARKINSON’S DISEASE

 

L. Håglin1, L. Bäckman1, J. Linder2, L. Forsgren2, M. Domellöf2,3

 

1. Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, SE-901 87 Umeå, Sweden; 2. Department of Pharmacology and Clinical Neuroscience, Umeå University, SE-901 87 Umeå, Sweden; 3. Department of Psychology, Umeå University, SE-90187 Umeå Sweden

Corresponding Author: L Håglin, Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, SE-901 87 Umeå, Sweden, lena.haglin@umu.se

J Aging Res Clin Practice 2018;7:156-162
Published online November 19, 2018, http://dx.doi.org/10.14283/jarcp.2018.26

 


Abstract

Background: Cognitive decline and dementia are common non-motor problems in Parkinson’s disease (PD). The underlying aetiology is multifaceted and both chronic and reversible causes for cognitive decline are likely to be present. Malnutrition is frequent in the Parkinson population, both early and late in the disease, and nutritional deficiencies could play a role in some cognitive deficits. Objectives: The objective is to study the association between nutritional status with focus on iron intake and homeostasis, mild cognitive impairment (MCI), and PD dementia (PDD). Setting and Participants: This study included 73 out of 145 patients with PD participating in a population-based study in northern Sweden. Measurements: Registration of nutritional status by laboratory analyses of blood plasma and neuropsychological assessments at time of diagnosis were performed. MCI and PDD were assessed yearly up to ten years after diagnosis. Mini Nutritional Assessments (Full-MNA score) and plasma variables detecting iron homeostasis were compared between patients with MCI and patients with normal cognition (NC). Motor severity was measured using the Unified Parkinson´s disease rating scale III, (UPDRS III) and Hoehn and Yahr (H&Y) staging scale. Cox proportional Hazard model were performed to see if any variables that differed between MCI and NC could predict PDD at follow-up. Results: Patients with MCI at time of diagnosis had lower levels of plasma iron (P-Fe) and albumin (P-Albumin) as well as a lower score on Full-MNA score. Dietary intake of iron was higher in patients with MCI than in patients with NC (p = 0.012). In logistic regression models adjusted for age, sex, and UPDRS III, lower levels of P-Fe (p = 0.025) and P-Albumin (p = 0.011) and higher dietary iron intake (p = 0.019) were associated with MCI at baseline. A Cox regression model with dementia as endpoint revealed that lower levels of P-Fe increase the risk of dementia at follow-up with adjustments for age, sex, UPDRS III, and MCI at baseline (HR 95% CI = 0.87 (0.78-0.98), p = 0.021). Conclusions: Low P-Fe was associated with cognitive disturbance at baseline and predicted dementia up to ten years after diagnosis in patients with PD. Low P-Albumin and malnutrition assessed with Full-MNA score were associated with MCI at baseline but did not predict dementia at follow-up.

Key words: Cognition, dementia, iron deficiency, Parkinson’s disease.


 

 

Introduction

Parkinson’s disease is a complex multifaceted disease with great variations in prognosis. Predicting the path the illness will take is next to impossible. Therefore, it is important to find predictors for different disease outcomes.
Cognitive decline and dementia are common non-motor problems in PD and the incidence of dementia is two to six times higher than in the general population (1).
At diagnosis, 20-40% of the populations have Mild Cognitive Impairment (MCI) (2 – 5). MCI at diagnosis increases the risk of Parkinson’s disease dementia (PDD), but not all patients with MCI develop dementia (5). Different patterns of cognitive decline have been connected to PDD. For example, impairment of semantic fluency and pentagon copying has repeatedly been shown to predict PDD (5,6). Low education level, postural instability, UPDRS (7), impaired olfactory function (8,9), and male sex has been connected to higher rates of PDD (10).
Cognitive impairment has been reported among elderly with malnutrition and iron deficiency (11, 12). Solfrizzi et al. (2006) presented a review on the nutrient-dementia risk pattern and suggested that more studies were needed to support the role of metals in progression of cognitive decline (13). A high iron intake has frequently been reported to increase the risk of PD, but no convincing evidence exists for an association between PDD and intake of iron. Cheng et al. (2011) reported that PD risk increased by 18% (RR 1.18, 95 % CI 1.02-1.37) by every 10-mg/day increment in iron intake (14). Powers et al. (2003) reported that a high intake of iron, especially in combination with high manganese intake, may be related to an increased risk of PD (15). In addition, Powers et al. (2009) reported that high iron intake together with a low intake of cholesterol may be associated with an increased risk of PD (16). On the contrary, a higher intake of iron, magnesium, and zinc was independently associated with a reduced risk of PD (17). Follow-up of two large cohort studies, including accumulated information on nutrient intake, revealed a higher risk of PD with a high intake of non-heme iron in combination with low vitamin C intake, while not with intake of heme iron (18).
This study investigated the association between nutritional status with a focus on iron intake and homeostasis in PD patients at time of diagnosis and risk of MCI and PDD at follow-up.

 

Methods

Patients

This community-based prospective study focuses on idiopathic forms of Parkinsonism in a catchment area (parts of Västerbotten county in northern Sweden) with 142 000 inhabitants (19). All suspected cases with idiopathic Parkinsonism were referred to the neurological department that employed all the neurologists involved in this investigation. From January 2004 through April 2009, 185 cases with Parkinsonism were identified. In total 145 patients fulfilled diagnostic criteria for PD at the next follow-up (up to 10 years). Of these, 73 were included in the study (Table 1). Because the remaining 72 non-participating patients came to follow-up without fulfilling the three-day dietary registration, they were not included for a blood sample. Individuals not participating in the three-day dietary registration were older (mean 73.5 years vs mean 69.1 years, p=0.006) and scored higher on the UPDRS III (29.2 vs 24.7 p=0.016) compared to those participating. There were no significant differences between the groups with regard to proportions of men and woman, total MMSE and MNA score.
A few patients refused to participate and were classified as drop outs. All participants were extensively examined during repeated visits the first month following initial contact. Information about demographics and disease history was obtained. All cases with suspected idiopathic Parkinsonism underwent a standardized clinical examination by a neurologist specializing in movement disorders.
To confirm the presence of PD, another specialist in movement disorders (blinded to the assessment of the previous examiner) evaluated a videotape of the patient undergoing the UPDRS III examination investigating PD related motor functions speech, facial expression, rigidity, tremor, posture, gait and bradykinesia (20). Patients were included if both examiners judged that they had fulfilled the clinical criteria for PD according to the UK Parkinson ’s Disease Society Brain Bank (UK PDSBB) criteria. Motor severity was measured using the Unified Parkinson´s disease rating scale III, (UPDRS III) and Hoehn and Yahr (H&Y) staging scale.

Table 1 Baseline variables (mean±sd) for the total PD group and for patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). P-values as a result from comparing variables between MCI and NC

Table 1
Baseline variables (mean±sd) for the total PD group and for patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). P-values as a result from comparing variables between MCI and NC

Abbreviations: UPDRS = Unified Parkinson’s Disease Rating Scale; H&Y = Hoehn & Yahr stage, median; ADL = Activity of daily living; PIGD = Postural instability Gait Disorder; Ind = Indeterminate; TD = Tremor dominance:

 

The UPDRS scoring was performed with patients on their regular medication when started on dopaminergic treatment. The motor subtype was classified as tremor dominant (TD), postural instability and gait difficulty (PIGD) or indeterminate (Ind) according to Jancovic et al (21). The MMSE was used as a screening instrument for global cognition.
The study was approved by the Regional Medical Ethics Board in Umeå, Sweden. Written informed consent was obtained from all participants.

Medication for PD

The levodopa equivalent daily dose (LEDD) was calculated at baseline and at follow-ups by use of a conversion factor for each of the anti-Parkinson medications (22). Information about LEDD at baseline revealed that only two patients had started anti-Parkinson treatment at time of diagnosis. At first follow-up (six months), all but nine patients had started treatment and about 50% of the patients had a LEDD <200 and 8% had >300. Medication was introduced over the first weeks after diagnosis. The nutritional investigation, including the blood sampling, was performed in a non-standardized manner according to drug therapy during this time. Thirteen patients started anti-Parkinson medication before the blood sampling.

Nutritional assessments

The Full Mini-Nutritional Assessment (MNA score), an international validated screening tool, was used to assess nutritional status and performed by the dietician concomitantly with anthropometrical measurements. The screening consists of 18 questions regarding anthropometry, diet, and health (23). MNA total scores between 24 and 30 points indicate optimal nutritional status and scores between 17 and 23.5 points indicate at risk for malnutrition.
Dietary data were collected from a three-day dietary registration (3-day DR) performed by the patients three days before a scheduled visit to the Department of Neurology. The subjects recorded in a protocol what they ate and drank during those three days. To describe portion sizes, they had access to a booklet with photographs and drawings of various foods and dishes. Standard household measures or package sizes were used for food items not included. Energy and nutrient intake were calculated using the dietary software program Dietist XP (Kost och näringsdata, Stockholm, Sweden), which employs the National Food Administrations food database (NFA database 2.00, Uppsala, Sweden).

Biochemical analysis

Blood samples at baseline were collected at admittance between 8 am and 4 pm in a non-fasting condition on the day when the patients were admitted for assessments of nutritional status. Plasma samples were collected and stored at -70◦C until iron, ferritin, albumin, and transferrin were measured. Transferrin saturation was calculated S-Fe [µmol/L] x 100 / (S-Transferrin [g/L] x 25.1) (Trf %). Analysis was performed in clinical routine in the accredited laboratory at Umeå University Hospital. Plasma levels of albumin and transferrin were analysed by Vitros PHOS Slides, Vitros ALB Slides, and Vitros TRFRN reagent on an Ortho Vitros 5.1 FS analyser.

Cognition

A battery of neuropsychological tests was performed and used for MCI and PDD classification at baseline, one year, three years, five, eight, and ten years. For MCI classification, the MDS Task force guidelines were used (24). Since the battery of tests included a minimum of two tests in all domains except language, modified level II criteria were applied (25). For patients not performing the full neuropsychological testing, MCI classification was based on self-perceived cognitive decline and MMSE (cut-off ≤29) (26).  All but four patients with blood samples performed the neuropsychological evaluation at baseline. PDD was diagnosed according to published criteria by neurologists experienced in neurodegenerative disorders (27). In periods between the neuropsychological testing, PDD was diagnosed by decline in MMSE, decline in basic activities of daily living (ADL) (28) due to decreased cognition, and cognitive decline reported from patients and/or family member. In addition to MCI and PDD, composite scores for different cognitive domains (executive function, attention, language, visuospatial function, and episodic memory) were calculated based on means of the z scores for each individual test. Neuropsychological measures used for classification of Mild Cognitive Impairment and calculation of composite scores. Pentagon copying was not included in the calculation of composite scores.
Episodic memory: Free and Cued Selective Reminding Test (FCSRT) free recall, Brief Visuospatial Memory Test (BVMT) total, Brief Visuospatial Memory Test (BVMT) delayed.
Visuospatial function: Benton Judgement of Line Orientation (BJOLOT), pentagon copying from MMSE. Language function: Boston Naming Test. Working memory and attention: Digit span backwards, Trail Making Test part B. Executive function: Wisconsin Card Sorting Test (WCST) total errors, Wisconsin Card Sorting Test (WCST) preservative errors, Semantic fluency (animals in 60 seconds).

Data analyses

The results are presented as mean and standard deviation with min-max for each variable presented. Independent two-tailed tests were used to compare patients with MCI and NC. For non-normal distributed data and variables with skewed distribution, non-parametric tests were performed: the Mann-Whitney and the Wilcoxon Signed Ranks Test. Most variables were approximately normally distributed except for H&Y score, P-Ferritin, and dietary iron intake. Because of the non-normal distribution, P-Ferritin and dietary intake of iron were dichotomized by the median value (P-Ferritin median = 128.7 µg/L and dietary iron intake median = 9.77 mg/day).
To check whether the variables that significantly differed between MCI and NC independent of age, sex, and UPDRS III, logistic regression models adjusted for age, sex, and UPDRS III were performed. To investigate the specific cognitive domains (i.e., the association with the variables differing between patients with MCI and patients with NC), partial correlations was used with corrections for age, sex, and UPDRS III with the biochemical assessments and merged scores for the separate cognitive domains.
The Cox proportional hazards model was used to study the association between biochemical assessments at baseline and the development of PDD. Variables associated with MCI were included in Cox-regression models, first univariate, and then multivariate adjusted for age, gender, UPDRS III at baseline, and finally MCI at baseline was added.
The program Predictive Analytics Software (SPSS Statistics, version 24 SPSS Inc., Chicago IL, USA) was used for the analysis.

 

Results

Baseline data

Non-motor and motor functions assessed at baseline for patients with PD (n=73) and for patients with MCI (n=30) and NC (n=43) are presented in Table 1. At baseline, MCI was more prevalent in males than in females and was associated with older age, lower level of education, and higher UPDRS III score. Patients with MCI had higher daily intake of iron and lower MNA score, P-Albumin, and P-Fe before adjusting for age, sex, and UPDRS III (Table 2). After adjusting, the OR for having MCI was still significant for P-Albumin, P- Fe and daily intake of iron but not for MNA score (Exp B: 95% CI = 0.799 (0.672-0.950), p = 0.011), P-Fe (Exp B: 95% CI = 0.854 (0.744-0.980), p = 0.025), dietary iron intake (Exp B: 95% CI = 4.425 (1.54-18.9) p = 0.019), and MNA score (Exp B: 95% CI = 0.79 (0.984-1.125, p = 0,057, respectively) (Table 2). Biochemical and nutritional assessments for males and females, including variables for iron homeostasis, are presented in Table 3. Males had higher P-Ferritin and dietary iron intake than females. No other differences indicate sex dependent disturbed iron homeostasis and nutritional status.

 

Table 2 Baseline variables (mean±sd) used to assess iron status in PD patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). The level of significance from the logistic regression with adjustments for age, sex, and UPDRS III are presented in the right column

Table 2
Baseline variables (mean±sd) used to assess iron status in PD patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). The level of significance from the logistic regression with adjustments for age, sex, and UPDRS III are presented in the right column

* Plasma ferritin and dietary iron intake were dichotomized to over and under median value (median=128.7 μg/L and median = 9.77 mg/day respectively) As seen in table 3. Abbreviations: TrF % = S-Fe [µmol/L] x 100 / (S-Transferrin [g/L] x 25.1); MNA = Mini Nutritional Assessment.

 

Correlations between P-Albumin and neuropsychological tests

Composite scores of working memory correlated with P-Albumin levels (r = 0.452, p < 0.001) and P-Ferritin levels (r=270, p=0.025).   Both correlations were stronger for males than females: P-Albumin (male; r = 0.549, p < 0.001 and female r = 0.331, p = 0.069 (Figure 1), P-Ferritin (male; r = 0.413, p = 0.01 and female r = 0.212, p = 0.252)  Composite scores of episodic memory correlated with P-albumin (r = 0.253, p = 0.036). After adjusting for age, gender, and UPDRS III score in partial correlations, the positive association between composite score of working memory and P-Albumin (r = 0.346, p = 0.004) and P-Ferritin (r = 0.309, p = 0.012) remained significant.

Table 3 Baseline variables in mean±sd and for min-max used to assess iron status in patients with PD

Table 3
Baseline variables in mean±sd and for min-max used to assess iron status in patients with PD

* Plasma ferritin and dietary iron intake were dichotomized to over and under median value (median=128.7 µg/L and median = 9.77 mg/day respectively); Abbreviations: TrF % = S-Fe [µmol/L] x 100 / (S-Transferrin [g/L] x 25.1); MNA = Mini Nutritional Assessment.

 

Figure 1 P-Albumin levels correlated with composite score of working memory and were stronger for males than females (male: r = 0.549, p < 0.001 and female: r = 0.336, p = 0.064)

Figure 1
P-Albumin levels correlated with composite score of working memory and were stronger for males than females (male: r = 0.549, p < 0.001 and female: r = 0.336, p = 0.064)

 

Cox regressions in prediction of PDD

Results from Cox regression analysis are shown in Table 4. Lower baseline P-Fe (µmol/L) and P-Albumin (g/L) levels increased the risk of PDD at follow-up in univariate models. In models controlling for age, sex, and UPDRS III, lower levels of P-Fe significantly increased the risk of PDD (HR (95% CI) = 0.85(0.76-0.94), p = 0.002). Adding MCI to the model did not affect the higher risk of PDD with lower P-Fe levels (HR (95% CI) = 0.87(0.78-0.98), p = 0.02).

Table 4 Results from Cox regression (HR 95% CI) with Dementia as outcome variable and nutritional variables as explanatory included are presented with bivariate and multivariate calculations

Table 4
Results from Cox regression (HR 95% CI) with Dementia as outcome variable and nutritional variables as explanatory included are presented with bivariate and multivariate calculations

*Adjusted for age, sex, and UPDRS III. ** Adjusted for age, sex, UPDRS III, and MCI; Iron intake was dichotomized to over and under median value (9.77 mg/day); Abbreviations: MNA = Mini Nutritional Assessment.

 

Discussion

The main finding from our study is that low levels of P-Fe were associated with MCI at time of diagnosis and increased risk of dementia over 10 years, while neither intake of iron, MNA-score, nor P-Albumin predicted dementia at follow-up. In addition, significantly lower levels of P-Albumin and lower score on Full MNA, indicating risk of malnutrition, and higher dietary intake of iron were seen in patients with PD-MCI at time of diagnosis. With adjustments for age, sex, and UPDRS III, the difference was maintained only for P-Albumin and dietary intake of iron.

Lower levels of P-Albumin, P-Fe, and Full MNA score at diagnosis for patients with MCI indicate malnutrition, which may have had its origin years prior to diagnosis and first symptoms. An association between MNA score and MCI in older in-patients (29) and between MNA score and disease severity and progress of disability in patients with PD has been reported (30,31). Nutritional status may be affected by several of the disease-related measurements such as ADL, UPDRS, and medication.
Used at baseline to assess malnutrition, the MNA score was lower in patients with MCI compared to patients with NC, but it did not predict PDD at follow-up. Different components of nutritional status besides results from a screening test may have importance when focusing on risk of dementia progression (32). However, MNA score has been shown to correlate with P-Albumin and dietary intake of iron (33). Being malnourished and having MCI may also have contributed to low P-Fe levels and may be one of several components of nutritional status that can influence progress to PDD. Difficulties in eating abilities and cutting food, often reported in PD patients, can result in a low intake of nutrients and energy. Age, disease, and sex-related factors also contribute to the consequences of malnutrition. In addition to finding predictors for different disease outcomes at the time of diagnosis, we also need to focus on finding PDD predictors already in the prodromal phase of PD.
In the present study, P-Albumin was significantly lower in patients with MCI than in patients with intact cognition at baseline. Albumin has previously mostly been associated with mortality and aging (34,35,36), although a handful studies have found an association of low levels of P-Albumin with cognitive decline (37,38). The different P-Albumin levels between MCI and NC were still significant after controlling for age and disease severity, which indicates that P-Albumin has a specific connection to cognitive decline. Also, the correlation between P-Albumin and P-Ferritin within normal limits and working memory was stronger in men than in woman, which suggests a sex difference for the impact of P-Albumin and P-Ferritin levels on working memory. No studies have reported this association before. As several comparisons were performed, the results may be spurious. Had we applied Bonferroni correction, only P-Albumin would have been considered significantly different between MCI and NC. Frangos et al. (2016) concluded that both age and disease contribute to low albumin, which could explain low haemoglobin levels in malnourished associated anaemia in very old hospitalized elderly (39). The baseline levels of P-Albumin and MNA score indicate an early association with cognitive decline in patients with PD in our study population.
Haemoglobin analysis was not performed on the same occasion/visit with blood sampling and assessment of malnutrition, limiting the possibility to assess anaemia. However, iron deficiency may be important for cognitive function independent from anaemia. Yavuz et al. (2012) studied geriatric patients (mean 72 years of age) and concluded that iron levels and Trf % independently correlated with MMSE. In that study, patients with dementia had low Trf % and a low MMSE associated with iron deficiency (11). Mean levels for P-Transferrin increase to compensate for low P-Fe and increased need, but in our study mean levels for P-Transferrin decreased with malnutrition. P-Fe is transported with transferrin, and about 30-40% of this capacity is used dependent on age and sex and increases after the age of 70 years (40,41). Besides being an iron transporter, P-Transferrin is a marker for nutritional status (42,43). By a shorter half-life than albumin, transferrin may be a strong marker for protein energy malnutrition within days to weeks.
Iron deficiency may affect dopamine metabolism (44,45), and dysregulation of iron metabolism has been described as a risk factor for PD (46). Iron homeostasis is reported to be important for cognition (47). Cognitive impairment has been reported among elderly with iron deficiency and malnutrition (11,12).  Iron deficiency in adults and elderly indicates that age and sex may have contributed to hypo-metabolism that might have resulted in early dementia in Parkinson’s disease (48). In the present study, age was associated with both MCI at baseline and with increased risk for dementia over 10 years. The vicious circle with ageing, malnutrition, and cognitive decline may be even stronger in PD patients due to disease-related disturbances than in a non-PD elderly population. A low bioavailability of iron in the intestine (the main cause of iron deficiency, at least among elderly) could have generated the low P-Fe in the present population of patients, for example, due to gastrointestinal disturbances like gastro pares and achlorhydria (49). The level of P-Fe varies from day to day and low levels indicate either low intake or malabsorption. The risk of MCI, associated with either high intake of iron or low plasma Fe, indicate the importance of intestinal function for maintaining iron homeostasis. A high intake of iron may affect bioavailability of other minerals and thereby contribute to deficit cognition. To study influence from dietary intake, more information on nutrient density in general and individual energy intake are needed together with data on intestinal function and medication. Reporting dietary intake may also have been affected by the level of cognitive ability.

 

Conclusion

Our results indicate that low P-Fe was associated with MCI at baseline and increases risk for dementia up to 10 years after diagnosis of PD. Low P-Albumin and disturbed cognition in PD may influence the progression to dementia and be a sign of protein energy malnutrition. High intake of iron increased the risk of MCI at baseline but did not show any effect on PDD risk. We suggest that low P-Fe in our sample might be related to a disturbed regulation, including intestinal absorption in iron metabolism as well as malnutrition.

 

Funding: This study was funded by The Swedish Parkinson Foundation (Svenska Parkinsonstiftelsen), Swedish Parkinson foundation, Neuro Sweden, The Swedish Parkinson Disease Association, The Swedish Medical Research Council and Västerbotten County Council (ALF).

Conflict of interest: The authors declared that they had no conflict of interests.

Ethical Standard: The study was approved by the Ethics Committee of the Faculty of Medicine at Umeå University. Written, informed consent was obtained from all participants.

 

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BODY COMPOSITION AND POSTURAL INSTABILITY IN PEOPLE WITH IDIOPATHIC PARKINSON’S DISEASE

 

A.S. Diab, L.A. Hale, M.A. Skinner, G. Hammond-Tooke, A.L. Ward, D.L. Waters

 

Centre for Health, Activity, and Rehabilitation Research, School of Physiotherapy, University of Otago, Dunedin, New Zealand. 

Corresponding Author: Professor Leigh A. Hale, Centre for Health, Activity, and Rehabilitation Research, School of Physiotherapy, University of Otago, PO Box 56, Dunedin 9054, New Zealand, Tel:+64 3 479 5425, Email: leigh.hale@otago.ac.nz 

          


Abstract: Objectives: Idopathic Parkinson’s disease (PD) is the second most common neurodegenerative disorder. Our objective was to investigate the relationship between body composition and postural instability in people with PD, and age- and sex-matched controls. Design: Cross-sectional study among PD sufferers and age- and sex-matched controls. Setting: University of Otago’s Balance Clinic, School of Physiotherapy. Participants: Forty-seven people with PD and 58 age- and sex-matched controls. Measurements: Postural stability was assessed with the Sensory Organization Test, Motor Control Test, Timed Up and Go Test, and Step Test. Body composition was measured by dual energy x-ray absorptiometry (DXA). Movement Disorders Society-Unified Parkinson’s Disease Rating Scale was applied to assess PD severity. Results: Mean group differences between PD and controls for the equilibrium composite score, Timed Up and Go Tests, and Step Test were statistically significant (p<0.05); strategy and latency composite scores and body composition variables were not (p>0.05). Three PD participants were sarcopenic; 15 PD and 24 controls were obese. In PD participants, total body lean mass and age predicted latency composite scores. Disease, age, and leg fat mass predicted the Timed Up and Go Test results (p<0.05). Sex and disease predicted the equilibrium composite score (p<0.01). Conclusion: The prevalence of obesity was high and sarcopenia low in the PD group, which is a novel finding. Not surprisingly, participants with PD had reduced postural stability compared to controls. Disease status, age and sex were influential factors in the weak relationships found between postural stability and body composition. These findings may have clinical relevance for the treatment of the physical symptoms of those suffering from PD.

 

Key words: Body composition, postural instability, Parkinson’s disease. 


 

Introduction 

Idiopathic Parkinson’s disease (PD) is a common neurodegenerative disorder, which presents with a variety of motor and non-motor manifestations (1). Postural instability is considered a cardinal sign of PD, impacting independence and increasing falls risk (2). Postural instability typically presents late in PD, (3) although mechanisms for this timing are not fully understood. A number of factors have been suggested which include deficits in anticipatory and reactive responses to perturbations (4), visual and vestibular systems (5), sensory-motor integration (6), muscle tone (7), cognition (8), and muscle power (9). A recent review identified six primary factors contributing to postural instability in PD, dysfunction in sensory reorganization, bradykinesia, abnormal postural response patterns, L-dopa induced dyskinesia, hypotension, and cognitive impairment (10).

Postural instability is also prevalent in older adults without PD, resulting in increased risk of falling (11), and the associated factors are numerous (12). One possible factor identified in older adults is abnormal body composition phenotype, which is associated with losses in lean body mass and bone mineral density, and increases in fat mass and a sarcopenic-obese phenotype (13, 14). The association between reduced physical function and the sarcopenic obese phenotype has been widely reported (15, 16).

Body composition in PD has been investigated (17-20), especially in those with advanced stages of the disease (18), and it has been reported that people with PD are disproportionately sarcopenic (21).  To our knowledge, no research has focused on the association between body composition phenotype and postural instability in PD. The aim of this study was to investigate this relationship. 

   

Methods

Study design

A cross-sectional case-matched study compared people with PD to an age- and sex-matched control group. The Lower South Regional Ethics Committee, New Zealand approved the study.  

Participant recruitment

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Participants with PD were recruited through the Dunedin Hospital Neurology Department, the Parkinson Society, and via community advertising. Control participants were recruited via community advertising. Volunteers were screened for eligibility by telephone using a standardised checklist. Those meeting eligibility requirements were sent a study information sheet and assigned an appointment time, at which time eligibility and consent was confirmed.  The diagnosis of PD was confirmed by the study neurologist. Inclusion criteria were age over 40 years, and the ability to perform the measurement tests independently with or without assistive mobility devices. Participants with other types of Parkinsonism, the inability to undergo the measurement tests safely due to cognitive or physical disability, or significant co-morbidity were excluded. Inclusion criteria for controls were age and sex-matched to the participants with PD, with no known neurological disorder, and self-reported to be sedentary. 

Study procedures

All participants attended two appointments. Degrees of PD severity were assessed with the Movement Disorders Society-Unified Parkinson’s Disease Rating Scale, and disease stage was defined by Hoehn and Yahr (22). 

Postural instability was tested using both computerised posturography and clinical measures. Computerised posturography included the Sensory Organization Test (SOT) and the Motor Control Test (MCT) performed on the NeuroCom® Smart EquiTest® version 8.4.0. The clinical measures were the Timed Up and Go Test used without (TUG B) and with (TUG H) a concomitant cognitive task, which was naming the days of the week backwards, and the Step Test. The retest and inter-rate reliability of the TUG among people with PD has been found to be high during both L-dopa “off” and “on” states. The Step Test is a simple, reliable test commonly used for investigating dynamic stability and postural responses in older adults (23) and reliability has been reported to be good for those with PD and comparison groups (24).

Dual-energy X-ray Absorptiometry (DXA; Lunar DPX-L scanner GE LUNAR Corp; Madison, WI) was used to measure whole body and regional body composition. Prior to testing the scanner was calibrated per manufacturer protocol. Height and weight were measured using a standardized protocol. The appendicular skeletal muscle (ASM) was calculated by summing lean mass in the arms and legs. Phenotypes were determined by validated criteria. The sarcopenic phenotype was defined as ASM Index (ASM/height2) of < 7.26 and <5.4 for males and females, respectively, and obese as an ASM Index of ≥ 27% and ≥38% for males and females, respectively (15). 

Data Analysis

Data were entered into the SPSS statistics computer programme. Data from the postural stability tests and body composition were described in terms of mean and 95% CIs. The Student’s T-test was used to compare the mean of the study and control groups for each test variable. Pearson’s correlation coefficients (r) tests were used to test the strength and direction of association between the postural stability and body composition variables for the stepwise regression analysis. The selection criterion for choosing variables for regression was based on the results of the correlation analysis and informed by variables used in previously published research (25). Eight predictor variables (sex, age, disease, total body lean, total body legs lean, total body fat, percent body fat, and total body legs fat) used in the stepwise regression model. 

 

Results 

Table 1 shows participant characteristics from 47 participants with PD (male 57%), and 58 control participants (male 34%). Twenty-seven participants were in a moderate state (stage II) of PD, seven were in an advanced state (stage III-IV), and thirteen were in a mild state (stage I). Forty-one PD participants were on anti-Parkinsonian medications. No participants with PD had received deep-brain stimulation prior to the study. Dyskinesia was reported in those in stage II, and one participant in stage III. Dyskinesia was slight to mild and was self-reported not to impact on activities of daily living. Participants with PD who were on medication were categorized as in a state of “on” drug therapy.

 

Table 1 Descriptive characteristics of the PD and Control groups

*MDS-UPDRS: Movement Disorders Society –Unified Parkinson’s Disease Rating Scale results; **Hoehn and Yahr; † «On” /“Off»: state of medical therapy

 

Table 2 shows the mean and 95% confidence intervals for the postural stability tests and the body composition variables. To maintain balance both groups were primarily using the ankle strategy (79%) and without a delay, as the differences were non-significant for the strategy composite and latency composite scores. The mean Body Mass Index (BMI) was not significantly different between the PD and control groups. 

 

Table 2 Results for postural stability tests and body composition

*Control; **Not significant; †millisecond; ‡seconds; §number of steps in 15 seconds; ||TUG B: Timed Up and Go Basic test; TUG H: ¶Timed-Up and Go High cognition test

 

There were no significant differences in the body composition variables. Males in the PD group had slightly less total fat mass than control males. The mean total fat mass in the PD female group was higher than the control females; however, these differences were not significant (Table 2). The number of females with obesity in both the PD and the control group were nearly double that of the males (9%, 26%, respectively).

The three participants with PD in the sarcopenic phenotype were of relatively advanced age (≥75.6 years) but varied in disease stage and severity of symptoms. Neither group presented as the sarcopenic obese phenotype. In fact, most presented as obese. There was a small positive relationship between total leg fat mass and the TUG B and TUG H scores. Disease, sex, and age were each found to be predictive of body composition in relation to postural stability. Disease predicted the equilibrium composite score, the TUG B and the TUG H scores, and age predicted the latency composite score and the TUG B and TUG H. 

Of the many variables considered for the prediction equation, only a small subset of variables was selected to obtain good predictive results to fit the model. Results revealed a very low to moderate level of multicollinearity between the predictors. The equilibrium composite variable was not significantly correlated in either the PD or the control groups, but was deemed necessary to keep in the regression model, as it is widely used clinically to assess postural stability (25). Table 3 summarises the results of the stepwise regression. In the group with PD, total body lean mass, leg fat mass, sex, age, and disease stage significantly predicted postural instability. 

Table 3 Summary of the stepwise regression results

*SOT: Sensory Organization Test, †=p<0.01, ‡= p<0.001

  

Discussion

We found a significant difference in postural stability between those with PD and an age- and sex-matched control group as measured by the SOT equilibrium composite score, the MCT, the TUG Tests and the Step Test. The SOT strategy composite score and the MCT latency composite scores were not significantly different. There was a significant difference between groups for both the TUG B (p<.001) and the high cognition TUG H (p<.001) tests. 

We established a tenuous association between postural stability and two body composition variables (total lean body mass and leg fat mass); postural stability was similarly associated with sex, age and disease status. Of the body composition variables, total body lean mass, appendicular lean mass and leg fat mass most strongly predicted variations in postural stability. For the posturography measures of postural stability, only the latency composite score showed a relationship with body composition variables, which was a positive association with the total body lean mass variable.

Female sex was a negative predictor for the equilibrium composite score. This agrees with previous studies showing female gender to be a significant contributor to variance in balance control in PD (26, 27). Age and disease were found to be positive predictive factors for postural stability as reported by previous studies (11). There were no significant differences in BMI, body composition variables or body composition phenotype, which is not consistent with previous studies. For example, in a meta-analysis of seven studies (28), people with PD had a significantly lower BMI than the comparison group, correlated with disease staging. Also, DXA results in the present study showed no participants with sarcopenic obesity, which is consistent with the findings of Toth et al (29), but inconsistent with other studies reporting the presence of sarcopenic obesity in those with PD (18-21). 

Notably, only three of our participants with PD were sarcopenic. This is an unusual finding, as PD is often linked with sarcopenia (18-21). Obesity is not a body composition phenotype normally associated with PD, yet one-third of our participants with PD were found to be obese.  Revilla et al showed total fat and percentage of fat were higher, and the total lean mass was lower, in males with PD when compared with male controls, suggesting a sarcopenic phenotype; females with PD and female controls had similar values (19). Thus, our findings with regard to obesity in individuals with PD are unique and may reflect rising levels of obesity in the general older adult population (15).

Potential study limitations include the cross sectional design, the fact that participants with PD were primarily in a mild to moderate staging of their disease, which may account for some differences in our results and those of previous studies, and the criteria used to define the body composition phenotypes. Although there are now several published operational criteria, in the current study we used criteria recommended by Baumgartner et al (15) and not the criteria set which includes muscle function/strength, as this is still widely debated in the literature. The main study strengths were the relatively large sample size, and case matching to a control group. 

Although postural instability is a frequent manifestation of PD, the reasons are not fully understood and most likely a complex interplay of numerous factors is responsible. Our study investigated body composition as one such contributing factor, and a small association was identified. While the group with PD were significantly different with regard to measures of postural stability, body composition variables were not significantly different. Unexpected findings were that only three participants were found to be sarcopenic, and a large number of participants with PD were obese, in contrast with findings in the current literature. The findings of the current study could have significant implications for the clinical treatment of the physical symptoms of those suffering from PD.

 

Funding: This work was supported by a grant from The Physiotherapy New Zealand Scholarship Trust Fund. The first author received financial assistance from The Iraqi Ministry of Higher Education and Scientific Research/Mission Office and the School of Physiotherapy, College of Health and Medical Technology, Baghdad, Iraq. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

Conflict of interest: There are no conflicts of interest.

Ethical Standards: Ethical approval was granted by the Lower South Regional Ethics Committee, New Zealand (Ref: LRS/10/10/047).

 

References

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2. Ashburn A, Stack E, Pickering RM, Ward CD. A community-dwelling sample of people with Parkinson’s disease: characteristics of fallers and non-fallers. Age Ageing 2001; 30:47-52.

3. Beuter A, Hernández R, Rigal R, Modolo J, Blanchet PJ. Postural sway and effect of levodopa in early Parkinson’s disease. Can J Neurol Sci 2008;35:65-68.

4. Bleuse S, Cassim F, Blatt J-L, et al. Anticipatory postural adjustments associated with arm movement in Parkinson’s disease: a biomechanical analysis. J Neurol Neurosurg Psychiatry 2008;79:881-887.

5. Rossi M, Soto A, Santos S, Sesar A, Labella T. A prospective study of alterations in balance among patients with Parkinson’s Disease. Protocol of the postural evaluation. Eur Neurol 2009;61:171-176.

6. Brown LA, Cooper SA, Doan J.B, et al. Parkinsonian deficits in sensory integration for postural control: temporal response to changes in visual input. Parkinsonism Relat Disord 2006;12) 376-381.

7. Bartolic A, Pirtosek Z, Rozman J, Ribaric S. Postural stability of Parkinson’s disease patients is improved by decreasing rigidity. Eur J Neurol 2005;12:156-159.

8. Morris, ME. Movement disorders in people with Parkinson disease: a model for physical therapy. Phys Ther 2005;80:578-597.

9. Paul SS, Sherrington C, Fung VS, Canning CG. Motor and cognitive impairments in Parkinson disease: relationships with specific balance and mobility tasks. Neurorehabil Neural Repair 2013;27:63-71.

10. Diab KS, Hale LA, Waters DL, Skinner MA. Factors contributing to postural instability in patients with idiopathic Parkinson’s disease. Physical Therapy Reviews 2014;19:302-327.

11. Bosek M, Grzegorzewski B, Kowalczyk A, Lubinski I. Degradation of postural control system as a consequence of Parkinson’s disease and ageing. Neurosci Lett 2005;376:215-220.

12. Ambrose AF, Paul G, Hausdorff JM. Risk factors for falls among older adults: a review of the literature. Maturitas 2013;75:51-61.

13. Waters DL, Hale LA, Grant AM, Herbison P, Goulding A. Osteoporosis and gait and balance disturbances in older sarcopenic obese New Zealanders. Osteoporos Int 2010;21:351-357.

14. Prado CM, Siervo M, Mire E, et al. A population-based approach to define body-composition phenotypes. Am J Clin Nutr 2014;99:1369-1377.

15. Baumgartner RN, Wayne SJ, Waters DL, Janssen I, Gallagher D, Morley JE. Sarcopenic obesity predicts instrumental activities of daily living disability in the elderly. Obes Res 2004;12:1995-2004.

16. Bouchard DR, Dionne IJ, Brochu M. Sarcopenic/obesity and physical capacity in older men and women: data from the Nutrition as a Determinant of Successful Aging (NuAge)-the Quebec longitudinal Study. Obesity (Silver Spring) 2009;17:2082-2088.

17. Poehlman ET, Toth MJ, Fishman PS, et al. Sarcopenia in aging humans: the impact of menopause and disease. J Gerontol A Biol Sci Med Sci 1995;50:73-77.

18. Revilla M, Jiménez-Jiménez FJ, Villa LF, et al. Body composition in Parkinson’s disease: a study with dual-energy X-ray absorptiometry. Parkinsonism Relat Disord 1998;4:137-142.

19. Petroni ML, Albani G, Bicchiega V, et al. Body composition in advanced-stage Parkinson’s disease. Acta Diabetol 2003;40:S187-190. 

20. Doherty J, Farid S, Avalos G, Ryan M, Rooney B, Hickey P. Falls and disability in a study of sarcopenia and bone health in parkinson’s disease. Osteoporos International 2011;22:S352-S353.

21. Lorefat B, Ganowiak W, Wissing U, Granerus AK,  Unosson M. Food habits and intake of nutrients in elderly patients with Parkinson’s disease. Gerontology 2006;52:160-168.

22. Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. Neurology 1967;17:427-442.

23. Hill KD, Bernhardt J, McGann AM, Maltese D, Berkovis D. A New Test of Dynamic Standing Balance for Stroke Patients: Reliability, Validity and Comparison with Healthy Elderly. Physiother Canada 1996;48:257-262.

24. Smithson F, Morris ME, Iansek R. Performance on clinical tests of balance in Parkinson’s disease. Phys Ther 1998;78:577-592.

25. Toole T, Park S, Hirsch MA, Lehman DA, Maitland CG. The multicomponent nature of equilibrium in persons with parkinsonism: a regression approach. J Neural Transm 1996;103: 561-580.

26. Schenkman M, Morey M, Kuchibhatla M. Spinal flexibility and balance control among community-dwelling adults with and without Parkinson’s disease. J Gerontol A Biol Sci Med Sci 2000;55:M441-445.

27. Roland KP, Jakobi JM, Powell C, Jones GR. Factors related to functional independence in females with Parkinson’s disease: a systematic review. Maturitas 2011;69:304-311.

28. Morales-Briceno H, Cervantes-Arriaga A, Rodríguez-Violante M, Calleja-Castill J,  Corona T. Overweight is more prevalent in patients with Parkinson’s disease. Arq Neuropsiquiatr 2012;70:843-846.

29. Toth MJ, Fishman PS, Poehlman ET. Free-living daily energy expenditure in patients with Parkinson’s disease. Neurology 1997;48:88-91.

REVIEW OF NATURAL PRODUCTS ON PARKINSON’S DISEASE PATHOLOGY

M.M. Essa1,2, N. Braidy3, W. Bridge4, S. Subash1,2, T. Manivasagam5, R.K. Vijayan1, S. Al-Adawi2,6, G.J. Guillemin7

 

1. Department of Food Science and Nutrition, College of Agriculture and Marine, Sciences, Sultan Qaboos University, Oman; 2. Ageing and Dementia Research Group, Sultan Qaboos Unviersity, Oman; 3. Centre for Healthy Ageing, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia; 4 School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, Australia; 5. Department of Biochemistry and Biotechnology, Faculty of Science, Annamalai University, Tamil Nadu, India; 6. Department of Behavioural Medicine, College of Medicine and Health Sciences, Sultan Qaboos University, Oman; 7. Neuropharmacology group, MND and Neurodegenerative diseases Research Centre, Macquarie University, NSW, Australia

Corresponding Author: G.J. Guillemin, Neuroinflammation group MND and Neurodegenerative diseases Research Group, Australian School of Advanced Medicine (ASAM), Macquarie University, NSW, 2109 Australia. Tel.: +61 02 9850 2727; fax: +61 02 9850 2701. E-mail address: gilles.guillemin@mq.edu.au

 


Abstract

This review examines evidence of plant-derived natural products and their constituents that have been shown to slow down or reverse the underlying neuronal degeneration observed in Parkinson’s disease (PD), with a focus on their effect on the modulation of dopaminergic neurotransission levels and motor function. During the last decade, there have been over 140 studies published that have investigated the anti-PD therapeutic potential of herbs, fruits, vegetables and spices, ornamental and parasitic plants, and fungi. Empirical evidence implicates phytochemicals may play a role in the prevention and mitigation of some of the intractable signs and symptoms of PD. The anti-PD effects exhibited by these natural products are considered to be due to their ability to modulate; reactive oxygen species production, neuroinflammation, dopamine production, excitotoxicity, metal homeostasis, mitochondrial function, and cellular signaling pathways, which are all disrupted in the PD brain. However, the precise neuroprotective mechanism of action of natural products for PD remains unclear. Research is necessary to further elucidate the mechanisms by which these compounds are efficacious in attenuating PD or controlling PD-related symptoms.

Key words: Polyphenols, Parkinson’s disease, oxidative stress, mitochondrial dysfunction, neurodegeneration.


 

Introduction

Parkinson’s disease (PD) is the world’s second most common neurodegenerative disorder, which can significantly impair the quality of life, create dependency and trigger premature mortality of affected individuals (1). The prevalence rate of PD is 0.5-1% among people aged 65-69 years and 1-3% among those aged 80 and above (2). Clinical manifestations include bradykinesia, tremors, rigidity, and postural instability (3). Spectrums of non-motor symptoms are also common, including cognitive impairment, and emotional and behavioral dysfunction (4).

As yet, no definite etiological factors have been identified to contribute to the development and progression of PD, although many factors have been previously proposed (5). Pathologically, PD is characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta region of the brain (7, 8). Intracytoplasmic proteinaceous inclusions termed Lewy bodies (LBs) and dystrophic neurites (Lewy neurites) are present in surviving neurons of PD patients (8). Genetic factors such as mutations to the α-synuclein or the parkin gene, and environmental factors such as neurotoxic pollutants have also been proposed to contribute to the onset of PD (9-11).

The neurochemical events associated with the pathology of PD include increased levels of free radicals, oxidative stress, inflammation, mitochondrial dysfunction, and α-synuclein aggregation. Additionally, increased concentration of redox active metals such as iron and copper, reduced glutathione levels, and increased lipid peroxidation have also been reported in PD (12, 13). Currently available pharmacological interventions provide only limited symptomatic relief for patients with PD and have little efficacy in reversing the underlying neuropathological changes associated with the disease. Therefore there is a clinical need to identify therapeutic agents that can ameliorate, or slow down the deleterious processes associated with PD. One such paradigm is to explore the possible contribution of natural products that might interfere with PD pathology (14). Natural products have been increasing found to have specific molecular or pharmacological effects that are likely to contribute to the development of neuroprotective agents against PD (15).

Bioactive derivatives of plants such as flavonoids, stilbenoids and alkaloids possess potent anti-oxidative and anti-inflammatory properties that are of considerable interest for the treatment of PD. These naturally occurring phytochemicals can also promote mitochondrial function and serve as important cognitive enhancers (15). Moreover, these compounds act as inhibitors for α- synuclein aggregation, c-Ju N-terminal kinase (JNK) activation, and monoamine oxidase production, and are agonists for dopaminergic neurons (16, 17). Considering the socioeconomic burden and undesirable side effects of synthetic drugs, natural remedies are promising avenues in the treatment of PD.

However, the claims that many natural products available to the general population are therapeutically beneficial for PD are based solely on empirical or preliminary data. Therefore, the purposes of this review are to highlight available evidence on the role of specific bioactive molecules present in a wide range of natural flora, and to present information on the potential mechanism of action of these natural products, and their relationship to neuropathological events associated with PD.

 

Summary of the literature cited

There are over 140 studies published in the last 10 years associated with the beneficial effects of plant- derived natural products and PD. This review included electronic searches of the PubMed, Medline, Scopus, EMBASE, CINAHL, AMED, PsycInfo, CNKI, 7 Korean Medical Databases, J-East and Web of Science with the search terms as follows: “Parkinson’s disease therapy”, “natural products parkinson’s disease”, “phytochemicals”, “antioxidants” and “plant extracts” in various combinations. The “Dopamine and PD” section is provided since the etiology of PD is thought to be due to an imbalance in brain dopamine levels. This review presents a summary of literature on the relationship between dopamine (DA) levels and motor function in PD, and the beneficial effects of natural products which demonstrate potential anti-PD properties. This also review summarizes recent progress in determining the potential mechanism of action on PD.

 

Dopamine Levels and Parkinson’s Disease

DA is a neurotransmitter produced from the dietary amino acid tyrosine and plays significant roles in a variety of motor, cognitive, motivational, and neuroendocrine functions (18). The rate-limiting enzyme responsible for DA synthesis is tyrosine hydroxylase (TyrH), which catalyzes the hydroxylation of tyrosine to DA. The biosynthetic pathway leads to the production of a number of different catechol monoamines, such as epinephrine and norepinephrine. These products play significant roles in many brain functions, including attention, memory, and cognition. Therefore, deficits in catecholamine synthesis can lead to several deleterious processes, such as hypertension, depression, and dystonias (reviewed in 19). As TyrH is the slowest enzyme in this pathway, its mechanisms of regulation are of considerable interest to neuroscientisits.

The activity of TyrH is regulated by protein-protein interactions with other enzymes in the DA synthesis pathway or the tetrahydrobiopterin pathway , an important cofactor in several redox reactions and acts as a chaperone for the maintenance of normal neuronal oxidative status (19). TyrH is also regulated by protein which transfer DA into synaptic vesicles. Recent studies have shown that TyrH is localized in close proximity to effector proteins near neuronal vesicles and mitochondria, along with protein phosphatases, and aromatic amino acid decarboxylase (AADC), and the vesicular monoamine transporter-2 (VMAT). These vesicles contain the enzyme dopamine beta-hydroxylase, thus ensuring that DA is stored in secretory vesicles rather than freely located in the cytosol (19). TyrH activity is inhibited by reversible glutathionylation during chronic oxidative stress, and the effect may be attenuated by natural phytochemicals which exhibit potent antioxidant potential (20).

DA is unstable and cannot cross the blood brain barrier (BBB). It is formed in the brain by conversion of its precursor L-DOPA. In PD, L-DOPA (Levodopa) can be administered in conjunction with a DA agonist, or the decarboxylase inhibitor carbidopa, which increases plasma concentration of L-DOPA by blockage of peripheral degradation of L-DOPA to DA. This allows more L-DOPA to BBB (21). L-DOPA is naturally found in beans, especially Mucuna spp, which has been proven experimentally to enhance DA levels in the brain (22).

DA receptor agonists (e.g. bromocriptine, cabergoline, pergolide, rotigotine, apomorphine, ropinirole and pamipexole) are the main class of drugs used to treat PD symptoms. Parkinson’s symptoms occur in response to reduced levels of the chemical messenger DA, due to the progressive loss of neuronal cells in the brain that synthesize it. These drugs activate DA receptors by bypassing the presynaptic synthesis of DA. Like DA, these DA agonists serve as endogenous free-radical scavengers, regulating DA synthesis and ameliorating excitotoxicity by suppressing subthalamic nucleus overactivity and exerting anti-apoptotic effects (23-25). Additionally, DA receptors can regulate adenylyl cyclase activity and cAMP synthesis (26, 27), and are involved in modulating voltage dependent Ca2+ and K+ channels (28). Compared to levodopa, DA agonists provide modest symptomatic relief but are associated with higher incidence of adverse effects including hallucinations, edema, sudden sleep attacks, and impulse control disorders (ICD). Interestingly, motor fluctuations such as dyskinesias are less frequent following administration with DA agonists. Naturally occurring protoalkaloids and ergot alkaloids are phytochemicals that exert dopaminergic or DA receptor activity. For example, apomorphine derived from opium alkaloids is used as a DA agonist (29).

Monoamine inhibitor (MAOI) activity of plant derived alkaloids is another therapeutic target for PD. Monoamine oxidases (MAO A & MAO B) are flavin- containing enzymes in the central and peripheral nervous systems that catalyze the conversion of neurotransmitters to hydrogen peroxide (H2O2), aldehydes, and ammonia. In the PD brain, MAOI regulates the breakdown of DA to its metabolites (30, 31). Therefore, MAOIs can be used therapeutically to maintain optimum DA levels (32).

 

Herb Derived Anti-parkinsonian Compounds

The neuroprotective potential of natural products derived from herbs, fruits, vegetables, and spices against PD relies on the presence of flavonoids, steroidal lactones, ginsenosides, alkaloids, caffeine, stilbenoids, ginkgolides, bilobalides , xanthones, saponins, oligosaccharide esters, glycosides isoflavonoids, polymethoxyflavones, catechins, anthocyanins, S- Allylcysteine, lycopene, thymoquinone, sesaminoids,curcuminoids, zingerone, eugenol, and chrysotoxine. enoids, catechols and glycosides. Flavonoids, the major polyphenol group, consist of aromatic rings possessing a phenolic hydroxyl group and a 3-OH group offering potent antioxidant and iron chelating properties (33-35). Based on their alkylation, glycation, and hydroxylation patterns, flavonoids are classified into flavones, flavanones, flavanonols, flavanols, anthocyanidins, and isoflavones (36). Apart from their antioxidative properties, the potential mechanism of action of flavonoids is their interaction with neuronal signaling cascades such as PI3K/Akt, protein kinase C, and MAPK which leads to decreased apoptosis and enhanced neuronal survival (37). Additionally, flavonoids induce angiogenesis and neurogenesis and act directly to counteract neurotoxic and proinflammatory agents (38). Moreover, flavonoids exert antioxidant effects by scavenging free radicals and reactive oxygen species (ROS) (39, 40). As oxidative stress is thought to be the leading cause of dopaminergic neuronal loss in the substantia nigra, neuroprotective molecules that ameliorate oxidative stress and excitotoxicity are of primary importance (41-43).

Camelia sinesis (Green tea) is a shrub native to Asia. Green tea is widely consumed as a beverage in Japan, China, and other Asian nations. Tea flavonoids exert antioxidant, anti-inflammatory and neuroregenerative effects (44, 45). Epicatechin-3-gallate (EGCG) is the tea’s most abundant polyphenol which offers antioxidant and neurogenerative effects (46-48). Epidemiological studies showing the alleviation of PD risk in tea drinking populations and its low prevalence in Chinese populations provides additional support for its neuroprotective effects in PD (49-51). In vivo studies in MPTP-induced parkinsonian mice have shown that green tea extract can attenuate DA depletion and dopaminergic neuronal survival in the substantia nigra region of the brain (51). The catechol-like structure of EGCG exerts an inhibitory effect on DA uptake by blocking uptake of the neurotoxin MPP+ (1-methyl-4-phenylpyridinium) and protecting dopaminergic neurons against MPP+ injury (52). Moreover, EGCG regulates extracellular signaling kinases (ERK1/2 and mitogen activated protein kinases), the major impediment to neuronal damage and oxidative stress (53). Additionally, the metal chelating ability of green tea flavonoids can attenuate iron dyshomeostasis observed in PD (54). Supplementation with green tea extract also mitigates NF-kB immunoreactivity and oxidative stress induced in SHSY-5Y cells (55).

Withania somnifera (Ws) is an Indian Ayurvedic traditional medicinal herb grown in India, Africa, and the Mediterranean region. The root extract is rich in steroidal lactones including withanone, withaferin, withanolides, withasomidienone, and withanolide (56). These compounds have been reported to inhibit metastasis and quinone reductase activity, .and preferentially affect the cholinergic signal transduction cascade of the cortical and basal forebrain, and thus may be beneficial for the treatment of PD. One study recently showed that withanolides are potent suppressors of NF-κB activation mediated by a number of inflammatory agents, and that this suppression occurs through inhibition of IκBα kinase (IKK) complex consisting of IKK-α, IKK-β, IKK-γ (also called NEMO), IKK-associated protein 1, FIP-3 (type 2 adenovirus E3-14.7-kDa interacting protein), heat shock protein 90, and glutamic acid, leucine, lysine, and serine–abundant protein. Experimental studies have also shown that MPTP-administered parkinsonian mice showed improvement in neuronal survival and locomotion after administration of Withania somnifera (Ws) root extract. Importantly, there was a significant increase in catacholamines such as DA, glutathione (GSH), and glutathione (GSH) peroxidase enzyme in Ws ingested PD mice compared to control. Also, there was a remarkable increase in the level of DA metabolites, 3,4- dihydroxy-phenylacetic acid (DOPAC) and homovanillic acid (HVA) (57). Further evidence supporting the antioxidative effect of Ws root extract against PD mice is notable. Treatment with Ws root extract (100mg/kg) for a period of 7 days correlated with a significant reduction in aggravated levels of malondialdehyde, superoxide, and catalase in the brains of PD mice (58). The ability of Ws to alleviate gait disorders, inflammation, and brain aging and its potential to upregulate p13 kinase and enhance neuronal growth has also been numerously reported (59, 60).

Ginseng is an adaptogen that resists adverse effects of harmful substances, restoring homeostasis and acting as a psychic energizer (61, 62). Scientific evidence has substantiated the neuroprotective potential of ginseng extract G115 against dopaminergic neuronal loss and gait disturbance in PD mice models (63). Ginsenosides are triterpinoid saponins unique to Panax ginseng species distributed throughout China, North and South Korea, and Russia. These compounds elicit a pleotrophic mechanism of action. The DA uptake inhibiting activity of that ginsenosides have the potential to act as NMDA antagonists and protect neurons from mitochondrial dysfunction and glutamate elevation and excitotoxicity caused by MPTP (64, 65). The potential of ginsenosides to reduce calcium influx and free radical generation and oxidative stress may also play a role in ginseng’s disease modifying effects (66, 67).

Caffeine is an Adenosine 2A receptor antagonist present in coffee beans from the Coffea arabica and Coffea canephora plants, which are widely distributed in Asia and Africa. Caffeine exerts neuroprotective effects against dopaminergic neuronal loss in MPTP-induced PD mice (68-70). Furthermore, caffeine causes reversal of motor deficit in PD mice models (71). Caffeine’s behavioral and neurobiochemical effects have been shown to cause a reduction in apomorphine-induce rotation and enhanced motor function. In experimentally depletion of dopaminergic neurotransmssion using neurotoxic, 6-hydroxydopamine (6-OHDA), the level of DA and its metabolites have also been shown to recover following caffeine administration (72).

Ginkgolides and bilobalides are unique phytochemicals present only in the Ginkgo biloba tree (73). EGb761, a well-defined mixture of active compounds extracted from its leaves, exerts a protective effect against oxidative stress induced by MPTP in C57BL/6J mice. Mice receiving EGb761 recovered striatal DA levels and tyrosine hydroxylase in the striatum and substantia nigra pars compacta. The neuroprotective effect of EGb761 against MPTP neurotoxicity is associated with its free radical scavenging activity, blockade of lipid peroxidation, and reduction of superoxide radical production (74). Furthermore, G. biloba extract exhibits inhibitory effects on MAO activity on rat mitochondria (75), suggesting that its neuroprotective effects on dopaminergic neurons may be due to its inhibitory action on MAO.

Polygala root extract (PRE) consists of xanthones, saponins, and oligosaccharide esters (76) and is reported to have as neuroprotective effect on dopaminergic neuron in 6-OHDA induced neurotoxicity in both in vitro and in vivo PD models. The possible mechanism of action is due to reduced ROS and nitric oxide (NO) production and altered caspase-3 activity (77). Moreover, oligosaccharide derivatives of PRE act against clinical depression by binding to norepinephrine transporter proteins (78). Furthermore, the 3,4,5-trimethoxycinnamic acid (TMCA) present in PRE exerts anti-stress effects through suppression of norepinephrine (79).

Baicalein and baicalin are flavonoids found in large concentrations in the Scutellaria baicalensis and Bupleurum scorzonerifolfium (S/B) herbs (80). These compounds have been shown to attenuate iron-induced lipid peroxidation and DA depletion in the substantia nigra. They can also augment GSH levels, hinder α- synuclein aggregation, and reduce iron-induced mitochondrial stress and apoptosis. The 3-OH group attached to the benzene ring of the molecular target baicalein is responsible for α-synuclein disaggregation. A significant reduction in nitric oxide synthase and inflammatory markers was also observed in the substantia nigra of neurotoxic rat brain treated with S/B remedies. Furthermore, baicalein ameliorated 6-OHDA induced toxicity by decreasing phosphor-JNK and caspase activity in SHSY-5Y cells (81). Baicalein pretreatment improved behavior in MPTP induced PD mice. The potential mechanism of action may rely on increased DA and melatonin (5-HT) in the striatum (82).

Pueraria thomsonii Benth is a herbal medicine enriched with isoflavonoids such as puerarin, daidzin, daidzein, and genistein (83). The neuroprotective effect of genistein in dopaminergic neurons has been reported, where in 6- OHDA induced nerve growth factor (NF) differentiated pc12 cells, genistein and daidzin showed an inhibitory effect on caspase 3 and caspase 8 activation, thereby preventing apoptosis (84).

Uncaria rhynchophylla is used as a traditional medicine to treat convulsive disorders, tremors, and hypertension (85). The major alkaloids are rhynchophylline, corynoxeine, corynantheine, and hirsutine and the major flavonoids are catechin and epicatechin. All have been shown to have a cytoprotective effect (86). In animal with depleted DA activity using 6- OHDA Uncaria rhynchophylla extract (URE) ameliorated dopaminergic neuronal loss and apomorphine induced rotation. Meanwhile, a significant reduction was observed in ROS generation and caspase 3 activity and a remarkable maintenance of cell viability and GSH levels was observed in neurotoxic PC12 cells.

Polygonum cuspidatum is a perennial herb used primarily in Traditional Chinese Medicine and other Asian cultures. Recent studies have shown the neuroprotective potential of P. cuspidatum-derived resveratrol (RES) in 6-OHDA induced mice. The protective effect is exerted by its antioxidant reducing and antiapoptotic abilities (87). In another study, male Wistar rats pretreated with RES escaped dopaminergic neuronal loss and neurobehavioral defects following 6- OHD injection. This affect is likely due to upregulation of antioxidant enzyme status and mitigation of DA deprivation (88).

Bacopa monniera is a traditional medicinal plant used extensively to treat anxiety, epilepsy, and memory deficits (89). It has been substantiated that Bacopa moniera extract (BME) exerts a dose dependent protective effect in 6-OHDA-lesioned PD rat models as determined by significant improvements behavioral activity and restoration of GSH, SOD, and catalase activity levels and reduced lipid peroxidation (90). The potential mechanism of action of BME is attributed to its antioxidant, free radical scavenging properties, and DA-enhancing effects (91).

Cassia obtusifolia L. is an annual plant commonly consumed as roasted tea and is widely distributed in Korea and China. Cassiae semen (sicklepod) seed extract (CSE) has been shown to protect against dopaminergic neuronal degeneration in the substantia nigra and striatum of MPTP-induced PD mice models and dopaminergic neurons in vitro. In 6-OHDA induced pc12 cells, CSE supplementation has been demonstrated to mitigate cell damage and attenuate ROS generation and mitochondrial membrane depolarization. MPP+, the neurotoxic metabolite of MPTP, induces dopaminergic neuronal loss by inhibiting the activity of respiratory complex 1 in the mitochondria of dopaminergic neurons (92).

 

Fruit, Vegetable and Spice derived Nutraceuticals for PD

Levodopa (L-DOPA) was first isolated from the seeds of the leguminous plant Mucuna pruriens, which is native to India and other parts of the tropics including Central and South America (93, 94) and Mucuna spp are considered to be richest natural sources of L-DOPA hotels of the world bay of many coves resort, luxury logdes of new zealand . (95). The administration of 30 grams of Mucuna seed powder has been reported to have antiparkinsonian effects in PD patients, with a more rapid onset of action, shorter latency, and enhanced improvement compared to the standard combination of levodopa (200 mg) and carbidopa (50mg) treatments (96). Vicia faba (broad bean) is an edible bean found in the Mediterranean region and is rich in L-DOPA (97). The ingestion of broad beans in PD patients has been shown to elevate L-DOPA plasma levels which have correlated with cognitive improvement in the same magnitude as levodopa/carbidopa administration (98, 99). Another study suggested that 2,4- epibrassinolide (24-Epi), a natural Brassinosteroid found in V. faba, offers antioxidative and antiapoptotic effect on MPTP induced PC12 cells. The mechanism underpinning the effect was considered to be due to modulation of antioxidant enzymes, Bax/Bcl-2 protein ratio, and cleaved caspase-3.

Chaenomeles speciosa is an East Asian native shrub that is known for its nutritionally edible fruit; the common flowering quince (FQ). FQ is used traditionally to treat neuralgia, migraine, depression, tremors, and dyskinesia (100, 101). Scientific evidence has proven FQ to be a potent DA transport (DAT) inhibitor that can be used as a therapeutic target for PD. In vitro studies have shown that FQ administration attenuates DA uptake by DATs in Chinese hamster ovary (CHO) cells expressing DAT (D8 cells). Additionally, FQ maintains cell viability, tyrosine hydroxylase (TH) activity, and behavioral performance in MPTP induced neurotoxic models of PD.

The rhizome of the perennial Cyperus rotundus is used as a functional food and medicine in Korea. Reports have suggested that cyperi rhizome extract (CRE) exerts protective effect on 6-OHDA induced PD models. CRE mitigates ROS and NO production and intensifies cell viability and caspase 3 activity. It also modulates mitochondrial membrane potential and dopaminergic neuronal loss in neurotoxic cell cultures (102).

Extracts of the edible fruit of the deciduous Morus alba L. (mulberry) have been demonstrated to have neuroprotective efficacy in in vitro and in vivo PD models, with the efficacy attributed to its content of polyphenols, anthocyanin, rutin, quercetin and α and γ tocopherol (103). In 6-OHDA mediated neurotoxic cell lines, the mulberry extract (ME) elicits antioxidant and antiapoptotic effects. Biochemical assays have shown that ME can stabilize the mitochondrial membrane, and regulate the expression of Bcl-2, Bax, and caspase 3 proteins involved in apoptosisAdministration of ME can also alleviate bradykinesia and dopaminergic neuronal damage in the substantia nigra in vivo (104, 105). Citrus is a family of flowering plants ranging from herbs, shrubs, and trees, including Citrus sinensis (orange), C. lemon (lemon), and C. paradisi (grape fruit). Citrus flavonoids are composed of flavonones, flavone glycosides and polymethoxyflavones (106). It has been reported that polymethoxyflavones present in orange and lemon peel can mitigate the loss of dopaminergic neurons and tyrosine hydroxylase in the substantia nigra of the 6- OHD rat model (107). Similar effects exerted by the flavonoid, naringenin, which is highly present in citrus, in PD models have also been noted (108). Naringenin and another citrus flavonoid, hesperidin attenuates LPS/IFNγ-induced TNF-α production in glial cells and naringenin also represses LPS/IFN-γ induced iNOS expression, p38 mitogen-activated protein kinase (MAPK) phosphorylation, and transcription-1 (STAT-1) which are associated with microglial and astrocyte-mediated inflammatory response (109).

Vitis vinifera (grape) is one of the world’s largest fruit crops and is enriched with catechins, epicatechins, anthocyanins, and resveratrol. Grape juice (GJ) administration has been correlated with a decrease in behavioral deficits in 6-OHDA induced mice (110). Resveratrol has been demonstrated to protect against MPTP induced apoptosis in neuronal cells, with the underpinning mechanism considered to involve the modulation of the expression of pro-apoptotic Bcl-2 gene and antiapoptotic Bax gene. Resveratrol administration has been shown to attenuate MPTP induced mitochondrial release of cytochrome c and caspase 3 activation, and facilitate membrane stabilization and neuronal survival (111). Interestingly, oxyresveratrol, a stilbinoide, contains one extra OH group and is more effective than resveratrol against 6-OHDA toxicity in SHSY-5Y cells. This is probably due to a greater antioxidant potential, more potent inhibition of the JNK pathway and an increase in activity of the nuclear sirtuin enzyme (SIRT1) which is associated with longevity (112).

Allium sativum (garlic), the edible bulb of the Liliacea family, possesses innumerable health benefits. S- allylcysteine (SAC), its most abundant organic sulfur containing compound, possesses radical scavenging activity (113) which when administered to MPTP induced neurotoxic mice improved locomotor function which correlated with increased dopamine production, alleviated lipid peroxidation and superoxide production, and enhanced superoxide dismutase (SOD) activity (114).

Morin (3,5,7,20,40-pentahydroxyflavone) is a bioflavonoid found in Prunus dulcis (almond), Maclura pomifera (osage orange), Maclura tinctoria (old fustic), and in leaves of Psidium guajava (guava) (115). The health benefits of morin have been investigated in in vitro and in vivo PD models. In PC12 cells, morin supplementation at 5-50μmol/L significantly viability losses, apoptosis, and ROS generation following MPTP treatment. In MPTP-induced PD mice models morin administration attenuated behavioral deficits and DA deprivation (116).

Lycopersicon esculentum L. (tomato) is rich in lycopene and well-known for its edible fruit. Pretreatment with a diet containing lyophilized tomato powder correlated with a decreased DA loss in a MPTP- induced PD model (117).

Black cumin (Nigella sativa)seeds are commonly used in culinary preparations. Thymoquinone, its main bioactive component, has been shown to protect against dopaminergic neuronal deprivation in MPP+ and rotenone induced neurotoxic PD models. In primary dopaminergic neuronal cell lines, long term and short term toxicity were reversed by thymoquinone treatment (118).

Sesame indicum is a flowering plant native to Africa, with high production in India and China. Sesame seed and its oil contain the bioactive molecules sesamin, sesamol, and sesaminol. Sesamin is a lipophilic lignin offering moderate antioxidant and immunomodulatory effects (119, 120). Sesamin has been demonstrated to have a DA enhancing effect in rotenone-induced loss of dopaminergic neurons in mice. Interestingly, MPP+ treated neuronal PC12 cells exhibit a significant decrease in ROS generation and oxidative stress following sesamin treatment. Sesamin modulates the expression of tyrosine hydroxylase (TH), SOD, and catalase, impedes inducible NO synthase (iNOS) protein expression in neuronal cells, and lowers mRNA levels of the potent pro-inflammatory cytokine interleukin-6 (IL-6) in microglial cells (121).

Curcuma longa is a rhizome grown throughout India and is extensively used in food additives and medicines (122). Its diverse cytoprotective action is offered by polyphenolic curcuminoids, consisting of curcumin, demethoxy curcumin (DMC), and bis-demethoxy curcumin (BDMC). In vitro and in vivo models of PD have shown that curcumin demonstrates a disease modifying effect by protecting dopaminergic neurons against LPS and α-synuclein induced neurotoxicity, mitigating DA loss, which allieviates oxidative stress and limits mitochondrial dysfunction (123, 124). The MPTP- mediated depletion of DA and TH immunoreactivity in dopaminergic neurons was reverted following the addition of curcuminoids. The administration of curcuminoids suppressed over-expression of iNOS, reduced pro-inflammatory cytokines, and total nitrite generation in the striatum of MPTP-intoxicated mice (125, 126). Another study has shown that curcumin protects against dopaminergic neurotoxicity induced by MPTP or MPP+ in C57BL/6 N mice and SHSY-5Y cells by inhibiting the JNK pathway (127).

Zingiber officinale (ginger) is a major spice that exhibits neuroprotective effects. Zingerone and 6 shogaol compounds isolated from ginger, impede 6-OHD induced DA loss in mouse striatum (128) and prevent apoptotic neural cell death (129). The DA replacement effect is possibly through up-regulation of the superoxide scavenging activity (SOSA) of SOD. The lipid peroxidation lowering effect of zingerone is also considered to contribute to its cytoprotective effect (130).

 

Neuroprotective Effects of Ornamental Plants

Paeoniae lactiflora is an ornamental flowering plant known for its dried root. Paeoniflorin (PF), a monoterpene glucoside, is abioactive molecule produced by Paeoniae alba Radix (131) and is reported to have a neuroprotective effect on dopaminergic neurons in an MPTP mouse model for PD. Dose dependent subcutaneous administration of PF restored TH positive cells, dopaminergic neuronal paucity, and ameliorated bradykinesia. The mechanism of action is due to PF acting as an agonist for the adenosine A1 receptor, which down regulates microglial and astrocytic activation and neuroinflammation (132).

Dendrobium nobile Lindl. is an ornamental medicinal plant in the Orchidacea family, which is rich in the bioactive benzyl compound chrysotoxine (133).

Chrysotoxine is reported to protect SHSY-5Y cells against 6-OHDA toxicity through mitochondrial protection and NF-κB modulation. Chrysotoxine pretreatment exerts beneficial effects including attenuation of 6-OHDA- induced intracellular generation of ROS, and activation of p38 MAPK and ERK1/2. Mitochondrial dysfunction is reverted through multiple mechanisms including the decrease of membrane potential, increase of intracellular free Ca2+, release of cytochrome c, imbalance of Bax/Bcl- 2 ratio and decrease in activation of caspase-3. An anti- inflammatory for response is exerted by suppression of NF- κB activation by blocking its translocation to the nucleus, thereby preventing up-regulation of iNOS and intracellular NO release (134).

Rosmarinus officinalis (rosemary) is an aromatic ornamental plant rich in cytoprotective biomolecules. R. officinalis extracts have been shown to offer neuroprotective potential in a model for H2O2-induced apoptosis of human dopaminergic cells correlating with suppression of of the expression of Bax, caspase-3 and -9 and Bcl-2 genes (135). Rosmaric acid (RA) has been demonstrated to have traiter l’anxiete, pour la sedation avant et apres l’anesthesie effect in a 6- OHDA-lesioned rat model of PD. RA exerts its effect by decreasing iron levels in the substantia nigra and regulating the ratio of Bcl-2/Bax gene expression (136). Carnosol, another major rosemary component has been shown to offer protection against rotenone-induced neurotoxicity by promoting cell viability and down regulating caspase 3 action, withincreased TH, Nurr1, and extracellular signal-regulated kinase 1/2 also likely to be involved (137).

 

Bioactive molecules Derived from Parasitic Plants and Fungi

Cistanche salsa is a parasitic plant used as a Chinese traditional medicine containing acteoside, echinacoside, and tubuloside as its major phenylethanoid glycosides (PHGs). C. salsa extracts containing these bioactive molecules have been shown to restore behavioral deficit and dopamine depletion in strata of MPTP induced C57 mice (138). They has also been demonstrated to protect dopaminergic neurons in the substantia nigra of PD model mice, which correlated with neurobehavior improvements (climbing test) and TH positive neuronal levels (139).

Gastrodia elata (GE) blume is a saprophytic perennial herb used traditionally as a medicine due to its wide range of therapeutic benefits. Protective effects of GE extract against MPP+-induced cytotoxicity in human dopaminergic SHSY-5Y cells demonstrated that GE extract dose dependently improved cell viability maintenance, attenuated oxidative damage, modulated expression of Bcl-2 and Bax, caspase-3, and limited poly(ADP-ribose) polymerase proteolysis (140). Recently, MPP+ induced MN9D dopaminergic cells were shown to exhibit antiapoptotic effects following GE extract treatment. The v anillyl alcohol present in GE was considered to act by attenuating the MPP+ induced elevation of ROS levels and decreasing the Bax/Bcl-2 ratio and poly (ADP-ribose) polymerase (141).

Ganoderma lucidum (GI) is a woody mushroom widely used as an alternative medicine. One study has identified that the neuromodulatory potential of GL on dopaminergic neurons to protect against inflammatory damage induced by microglial activation following exposure to MPP+ and LPS. The mechanism of action is purportedly the ability of GL to protect against the production of the microglia-derived toxic factors NO, TNF-α, IL-1ß, and superoxide (142).

 

Current and Future Developments

Current pharmacotherapies for PD do not provide the much desired permanent curative benefits to patients. Scientists in the field of nutrition have identified natural products as potential adjuvant treatments to conventional drug therapy to attenuate the PD symptoms and reduce the dose of anti-Parkinson drugs and the incidence of associated adverse events. There is a high rate of dyskinesia and relapse of Parkinsonian symptoms following long-term treatment with levodopa (143). Combination therapy with natural herbal products has demonstrated substantial benefits in lowering levodopa- related complications (144). However, the long term effect of combination therapy has not been investigated, and potential interactions with drugs that are currently used in the PD treatment remain unclear. The dosage regimen for anti-parkinson’s drug is of major clinical importance of anti-parkinson’s drug due to its lifelong requirement. Adjunct therapy with natural products may ultimately prove useful for reducing the dose of levodopa for managing PD symptoms.

While many natural products appear promising for the treatment of PD and management of dyskinesia, a global initiative to standardize compositions for pharmacological applications is essential to ensure good quality and efficacy. The efficacy of natural formulations are limited due to several problems related to the original species of individual herbs, chemical compositions and indexes, preparations and indications for herbal products (145). Chinese formulas currently available on the market are composed of a variety of natural products and there exists wide heterogeneity between the natural products described in this review. Standardization of single and combinations of natural products in human clinical trials will be a major factor for translating preclinical data to the clinical setting.

Future clinical trials using natural products for the treatment of PD need to be improved methodologically to ensure good reproducibility, to improve clinical benefit, and to reduce the potential to cause harm. Double blinded studies and the inclusion of placebos should be employed in the study design. Protocols need to be defined prior to commencement of clinical trials to guarantee the transparency of the study finding(s) and prevent publication bias (146).

 

Conclusion

Prior to the onset of modern medicine, societies all over the world have employed various natural products as ‘food for medicine’. With hegemony of biomedical sciences with its reductionism approach, the usage of natural products for the cause of prevention and amelioration of illness was deemed a relic of the past. The idea encapsulating ‘food for medicine’ was often portrayed as Grandmother’s medicine. However, despite decades of the reductionism approach in health and medicine, some of the emerging prevalent conditions such as PD appear to be inaccessible to modern medical interventions. In the age of paradigm shift, interests towards natural product have been rekindled. Rather than being limited to grandmother’s empiricism, development of science has rendered the possibility of scrutinizing mechanisms of natural project with lances of modern scientific approach. The evidence suggesting the heuristic value of some of the natural products is abundant. This paper has specifically explored the role of herbs, fruit, vegetable and spice, ornamental plants and parasitic plants and fungi in the trajectory of PD. The evidence appears to be tenderized with notion that the wisdom of Grandmother’s medicine is not a relic of the past; the natural product is once again live and kicking. If science would progress on such a quest, natural products may address the underlying pathological processes associated with the development and progression of neurodegenerative diseases, and PD in particular.

 

Acknowledgements: The project was supported by Sultan Qaboos University; Oman in the form of internal grant is gratefully acknowledged (IG/AGR/FOOD/14/01) and also supported by the Research Council; Oman (Grant # RC/AGR/FOOD/11/01). Nady Braidy is the recipient of an Alzheimer’s Australia Viertel Foundation and National Health and Medical Research Council Early Career Postdoctoral Research Fellow at the University of New South Wales.

Conflict of interest: Author has no conflict of interest with this paper.

 

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MALNUTRITION RISK IN PARKINSON’S DISEASE

 

S. Lindskov1,2,3, K. Sjöberg4, A. Westergren1, P. Hagell1

 

1. The PRO-CARE group, School of Health and Society, Kristianstad University, Kristianstad, Sweden; 2. Department of Geriatrics and Neurology, Central Hospital Kristianstad, Northeast Skåne Health Care District, Kristianstad, Sweden; 3. Department of Clinical Sciences, Lund University, Lund, Sweden; 4. Department of Clinical Sciences, Lund University, Division of Gastroenterology and Nutrition, Skåne University Hospital, Malmö, Sweden.

Corresponding Author: Susanne Lindskov, School of Health and Society, Kristianstad University, SE-291 88 Kristianstad, Sweden, Tel: +46 44 20 85 63, E-mail: Susanne.Lindskov@hkr.se

 


Abstract

Background: Unintentional weight loss and undernutrition have been found common in Parkinson’s disease but its relation to other disease aspects is unclear. Objectives: To explore nutritional status in relation to disease duration in Parkinson’s disease, as well as associations between nutritional status and motor and autonomic features. Design: Cross-sectional. Setting: South-Swedish outpatient Parkinson-clinic. Participants: Home-dwelling people with Parkinson’s disease (n=71), without significant cognitive impairment (mean age, 67.3 years; 56% men; mean disease duration, 6.3 years). Measurements: Parkinsonian motor symptoms, mobility, activity level, disability, dyskinesias, dysautonomia, under- and malnutrition risk screening (using MEONF II and MUST for undernutrition and SCREEN II for malnutrition) and anthropometric measures (BMI, handgrip strength, triceps skin-fold, mid-arm circumference and mid-upper arm muscle circumference) were recorded. The sample was divided into those with longer (n=34) and shorter disease duration (n=37) according to the median (5 years). Results: Longer disease duration was associated with more, disability, dyskinesias and dysautonomia than shorter duration (P≤0.04). Mean (SD) body weight and BMI were 80.3 (16.3) kg and 28.1 (4.8) kg/m2, respectively, and did not differ between duration groups (body weight, 80.9 vs. 79.6 kg; BMI, 28.0 vs. 28.3 kg/m2; P≥0.738). There were no differences in other anthropometric measures between duration groups (P≥0.300). BMI identified 4% and 62% as under- and overweight, respectively, and 4% exhibited undernutrition risk, whereas 87% were at risk for malnutrition. Nutritional and motor/dysautonomic variables showed relatively weak correlations (rs, ≤ 0.33), but people with orthostatic hypotension had lower BMI (26.7 vs 29.2 kg/m2; P=0.026) and lower handgrip strength (33.2 vs 41.6 kg; P=0.025) than those without orthostatic hypotension. Conclusion: Motor and autonomic features showed expected relationships with disease duration. In contrast to these observations, and to most previous reports on nutrition in PD, frequencies of underweight and undernutrition were low. However, malnutrition risk was high, emphasizing the need for regular clinical monitoring of nutritional status. The reasons for the preserved nutritional status have to be explored prospectively.

 

Key words: Duration, nutrition, Parkinson’s disease, weight.


 

Introduction

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor symptoms such as bradykinesia, rigidity and tremor. Complications such as a fluctuating drug response and dyskinesias often develop over time. Non-motor symptoms, e.g., dysautonomia, are also common (1). One poorly understood feature is unintentional weight loss and undernutrition (2, 3).

Unintentional weight loss has been reported to occur among up to a third of people

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with PD (4), and the prevalence of undernutrition and undernutrition risk have been reported to be up to 24% and 60%, respectively (5). A recent meta-analysis of studies reporting body mass index (BMI) among people with PD and healthy controls found a significant difference with an average BMI in PD 1.73 units below that of controls (95% CI, 1.11- 2.35) (6). Although weight loss has been found associated with PD severity rather than duration (6), some studies have found a relationship with disease duration (7), and it may also occur early in the disease, even before PD onset despite an increased energy intake (8). Furthermore, longitudinal data have suggested an association with PD duration with decreasing BMI and increasing risk for undernutrition over time (9).

However, a weakness of many previous studies in this area is that most of them have only examined BMI or unintentional weight loss, without addressing nutritional status in a broader sense by the use of valid and reliable tools and indicators for nutritional status.

The cause of weight loss and undernutrition in PD remains unknown, but reduced energy intake and/or increased energy expenditure have been suggested as possible factors (4). However, there is also evidence against this explanation (10), and other factors may also contribute. For example, since autonomic centers such as the hypothalamus are involved in weight control, pathology within such areas may be related to weight loss (10). Furthermore, insufficient awareness of nutritional risks and failure to monitor nutritional status may also contribute.

The objectives of this study were to explore nutritional status, motor and autonomic features in relation to disease duration in PD, as well as the association between nutritional status and motor and autonomic features.

 

Methods

The study setting was a multidisciplinary outpatient PD clinic at a South-Swedish central hospital serving a population of about 170 000. Ninety-eight consecutive people with idiopathic PD were invited to participate. Inclusion criteria were independent living and absence of clinically significant cognitive impairment (as determined by the attending clinician and routine cognitive screening (11)). All participants provided written informed consent. The study was approved by the regional Research Ethics Committee.

Procedures and data collection

The week before the study visit, participants were sent a booklet of patient-reported rating scales to be completed before the clinic visit. All visits were scheduled in the morning at about 10-11 am following a light breakfast. All data collection was conducted by the same assessor, a PD specialized nurse trained in using the rating scales, nutritional screening tools and anthropometric measures employed here.

Nutritional status was screened by using the SCREEN II (12), MUST (13) and MEONF II (14) (Table 1). MEONF II and MUST are clinical undernutrition screening tools, whereas SCREEN II is a tool for screening of malnutrition in general (not just undernutrition). Although the MEONF II has been found to display advantages compared to the MUST (13) we used both because the MUST is more widely known to have previous PD studies (7). Anthropometric measures (15, 16) included body weight (kg), BMI (weight in kg/height in meters2), estimation of body muscle and fat mass by Triceps Skin Fold (TSF; mm) and Mid Arm Circumference (MAC; cm). Mid-Upper Arm Muscle Circumference (MUAMC) was calculating based on TSF and MAC using the formula: MUAMC (cm) = MAC – 0.1 x TSF). In addition, Hand Grip Strength (HGS; kg) was measured in the right hand. Body weight and height were measured using standard clinical equipment, an analog scale (Stathmos-Lindell, Sweden) and a stadiometer (Hultafors, Sweden), respectively, with patients wearing light clothing and no shoes. TSF was measured with a caliper (Skinfold Caliper Baseline, Enterprises Inc., USA) at the back of the upper arm. Subcutaneous fat was gripped 1 cm above the midpoint between the shoulder (acromion) and the tip of the elbow when the arm was hanging and relaxed. MAC was measured using a flexible measuring tape (included with the TSF caliper), halfway between the shoulder (acromion) and the tip of the elbow. HGS was measured using the Baseline Hydraulic Hand Dynamometer (Enterprises Inc., USA), with a capacity of 90 kg.

 

Table 1: Rating scales and risk screening tools used in the current study a.

a. All scales are patient-reported except for the MEONF II, UPDRS II (clinical interview and observation) and UPDRS III (clinical examination); b. Risk cut-off scores: <54 = any risk; <50 = high risk; c. Risk cut-off scores: >2 = moderate risk; >4 = high risk; d. Risk cut-off scores: 0 = low risk; 1 = medium risk; ≥2 = high risk; SCOPA-AUT, SCales for Outcomes in PArkinson’s disease – Autonomic symptoms; mGPAS, modified Grimby Physical Activity Scale; SCREEN II, Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II; MEONF II, Minimal Eating Observation and Nutrition Form – version II; MUST, Malnutrition Universal Screening Tool; NHP-PM, Physical Mobility section of the Nottingham Health Profile; UPDRS III, Unified Parkinson’s Disease Rating Scale, part III (motor examination); UPDRS II, Unified Parkinson’s Disease Rating Scale, part II (activities of daily living); NA, not applicable

 

Anthoprometric measures were recorded as the mean of three consecutive measurements, and cut-off scores were applied as recommended in the literature, including age- adjusted BMI classifications (≤69 years old, BMI ˂20 = underweight; BMI ≥25 = overweight/obese, ≥70 years old, BMI ˂22 = underweight; ≥27 = overweight/obese) (15-17).

The presence or absence of dyskinesias was noted, and PD motor symptoms were assessed by part III (motor examination) of the Unified PD Rating Scale (UPDRS III) (18) during the “on” phase (i.e., periods with good antiparkinsonian drug response). Disability was assessed by the disability score (19) of UPDRS part II (activities of daily living) both for the “on” and the “off” (periods with poor drug response and increased disability) phases. The UPDRS III includes rating of the presence and severity of various motor symptoms while conducting a standardized neurological examination and the UPDRS II disability score includes ratings of various patient- reported disabilities in daily life as assessed during a standardized interview (18). Autonomic dysfunction, physical activity and mobility were assessed by patient- reported rating scales (the SCales for Outcomes in PArkinson’s disease – Autonomic symptoms (SCOPA- AUT), the modified Grimby Physical activity scale (mGPAS), and the Physical Mobility section of the Nottingham Health Profile (NHP-PM), respectively). Further details on all applied rating scales and screening tools (12-14,18-22) are summarized in Table 1. In addition, orthostatic hypotension (OH) was determined by blood pressure measurements using a manual blood pressure cuff (Jewel Movement Sphygmomanometer, AB Henry Eriksson, Sweden) after 10 minutes rest, immediately after standing up, and following 3 minutes of standing (23).

 

Analyses

Data were checked regarding underlying assumptions and described and analyzed accordingly using IBM SPSS 20 (Armonk, NY: IBM Corp.) and Confidence Interval Analysis 2.2 (www.som.soton.ac.uk/cia/). The alpha- level of significance was set at 0.05 (2-tailed). We did not adjust for multiple testing due to the exploratory nature of the study. The sample was divided into those with shorter (˂5 years) and longer (≥5 years) PD duration according to the median, and variables were compared between these groups using chi-squared, Mann-Whitney and independent samples t-tests, as appropriate; 95% confidence intervals (CIs) were calculated. Spearman correlations were computed between disease duration and nutritional variables, and between nutritional variables and motor and autonomic scores. Nutritional variables were also compared between those with and without orthostatic hypotension (Mann-Whitney and independent samples t-test, as appropriate).

 

Results

Twenty seven (28%; 16 women; mean (min-max) age and PD duration, 71 (60-87) and 4.8 (1-15) years, respectively) of the 98 invited patients did not respond to the study invitation. The final sample consisted of 71 participants (40 men) with a mean (SD; min-max) age of (8.1; 47-89) years who had been diagnosed with PD for a mean (SD; min-max) of 6.3 (3.6; 0.5-18) and median (q1-q3) of 5 (4-8) years. Fifty-three participants (74%) were married/living as married, and the majority (65%) was retired while the rest were either working (28%) or on long-term sick leave/disability retirement (7%). About two thirds (68%) had some comorbidity. Pharmacological PD treatment consisted of levodopa (n=70), dopamine agonists (n=63), COMT-inhibitors (n=45), MAO-B- inhibitors (n=11), and amantadine (n=3). Two participants had undergone thalamic deep brain stimulation, and one was not on any medical antiparkinsonian therapy.

 

Table 2: Motor and autonomic variables a.

a. Data are median (q1-q3; min-max) unless otherwise noted; higher scores = worse unless otherwise noted; b. Differences in percentages (dyskinesias and orthostatic hypotension) and medians (all other variables) between people with longer (˃5 years) vs shorter (≤5 years) PD duration; c. Mann-Whitney tests (unless otherwise noted); d. Higher scores = better; e. 95% confidence intervals for percentages; f. Orthostatic hypotension was defined as a decrease in systolic/diastolic blood pressure of ≥20/10 mmHg (≥30/15 mmHg in people with hypertension) within 3 minutes of standing (23); g. Chi-squared test; NHP-PM, Physical Mobility section of the Nottingham Health Profile; mGPAS, modified Grimby Physical Activity Scale; UPDRS II, Unified Parkinson’s Disease Rating Scale, part II (activities of daily living); UPDRS III, Unified Parkinson’s Disease Rating Scale, part III (motor examination); SCOPA-AUT, SCales for Outcomes in PArkinson’s disease – Autonomic symptoms.

 

Motor and autonomic variables are reported in Table 2. PD, disability and dyskinesias, as well as autonomic symptoms (total as well as urinary, cardiovascular and thermoregulatory SCOPA-AUT scores) were more pronounced in the longer duration group (Table 2).

Nutritional data are reported in Table 3. Overall, there were no differences between the two duration groups regarding any nutritional variables. Correlations between disease duration and nutritional variables were non- significant and ranged from -0.01 (MEONF II) to 0.11 (TSF) (Table 4). According to BMI, 3 people (2 shorter and 1 longer PD duration) were underweight and 44 (62%) were overweight (68% in the shorter vs. 56% in the longer duration group). However, 46 participants (65%) exhibited high risk for malnutrition according to the

SCREEN II (same proportion for both duration groups), whereas only 2 (3%) and 3 (4%) were found to have undernutrition risk accordingly to the MUST and MEONF II, respectively (Table 3). BMI indicated underweight for both cases with undernutrition risk according to MUST and for two of those with undernutrition risk according to MEONF II.

Correlations between nutritional variables and motor and autonomic scores (Table 4) showed significant but generally weak associations between BMI and NHP-PM; SCREEN II and SCOPA-AUT/thermoregulatory functioning; MEONF II and SCOPA- AUT/gastrointestinal functioning; MUST and SCOPA- AUT/urinary functioning and SCOPA- AUT/thermoregulatory functioning; TSF and SCOPA- AUT/pupillomotor functioning; and between HGS and NHP-PM, UPDRS II/”on”-phase disability, SCOPA- AUT/thermoregulatory functioning, and SCOPA- AUT/pupillomotor functioning. Other correlations were weaker and non-significant (Table 4).

People with OH (n=32) had lower BMI (mean (SD), 26.7 (4.1) vs 29.2 (5.0) kg/m2, respectively; P=0.026) and also lower HGS (mean (SD), 33.2 (11.1) vs 41.6 (17.8) kg, respectively; P=0.025) than those without OH. There were no differences between these groups on any of the other nutritional variables (weight, SCREEN II, MEONF II, MUST, TSF, MAC, MUAMC; data not shown).

 

Table 3: Nutritional variables a

a. Data are mean (SD; min-max) unless otherwise noted; b. For differences in percentages (BMI; mal- and undernutrition classifications; TSF, MAC, MUAMC and HGS according to cut-offs), medians (SCREEN II and MEONF II scores) and means (all other variables) between people with longer (˃5 years) vs shorter (≤5 years) PD duration; c. BMI cut-off scores: ≤69 years old, BMI ˂20 = underweight; ≥70 years old, BMI ˂22 = underweight; ≤69 years old, BMI ≥25 = overweight/obese; ≥70 years old, BMI ≥27 = overweight/obese (17); d. Risk cut-off scores: <54 = any risk; <50 http://abilifygeneric-online.com/catalog/Depression/Paxil.htm = high risk (12); e. Risk cut-off scores: >2 = moderate risk; >4 = high risk (14); f. Risk cut-off scores: 0 = low risk; 1 = medium risk; ≥2 = high risk (13); g. Cut-off scores: Men, ≤6; Women, ≤12 (15); h. Cut-off scores: Men ≤79 years old, ≤26; Men >79 years old, ≤24; Women, ≤79 years old, ≤24; Women >79 years old, ≤22 (15); i. Cut-off scores: Men ≤79 years old, ≤23; Men >79 years old, ≤21; Women, ≤79 years old, ≤19; Women >79 years old, ≤18 (15); j. Cut-off scores: Men, <30; Women, <20 (15, 16); k. Independent samples t-test; l. Fisher’s exact

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test; m. Chi-squared test; n. Mann-Whitney test; BMI, body mass index; SCREEN II, Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II; MEONF II, Minimal Eating Observation and Nutrition Form – version II; MUST, Malnutrition Universal Screening Tool; TSF, Triceps Skin Fold; MAC, Mid Arm Circumference; MUAMC, Mid-Upper Arm Muscle Circumference; HGS, Hand Grip Strength.

 

Discussion

Although undernutrition and low BMI have been frequently reported in PD, related to disease severity and (to a lesser extent) duration (5, 6, 10), we found no evidence for prevalent underweight or undernutrition risk. Motor and autonomic symptoms differed by PD duration as expected. However, associations between nutritional status and disease duration and severity were absent or weak, but there was an association between OH and BMI and HGS. Since malnutrition does not only include undernutrition, but also overweight/obesity and nutrient deficiencies this was also considered by applying SCREEN II, which in contrast to undernutrition screening identified a majority of participants as at risk for malnutrition. Indeed, a larger proportion of participants were overweight rather than underweight. However, similarly to other nutritional and anthropometric variables there were no or only weak associations between SCREEN II and PD duration and severity.

According to Sheard et al. (3) BMI should be interpreted with caution due to limited sensitivity in identifying undernourishment, and additional methods should therefore also be considered. Indeed, while frequencies were low we also found BMI to be less sensitive in identifying undernutrition than clinical screening using the MEONF II, but equal to that of MUST. This is in agreement with previous data (14).

Our observations contrast to most previous studies. For example, a recent study among Australian community-dwelling people with PD (2, 3) identified 15% as moderately undernourished (none as severely undernourished), despite apparent lack of significant cognitive impairments and similar age, gender distribution, disease duration and autonomic symptom severity as in our sample. Similarly, Jaafar et al. identified 23.5% of their UK sample of community-dwelling people with PD as at risk for undernutrition according to the MUST, and both these studies reported generally lower values of BMI and anthropometric measures than found here (7). Despite other sample similarities, motor symptoms appear to have been well controlled in our cohort as indicated by motor and disability scores. Since underweight and undernutrition in PD has been associated with markers of disease severity (3, 6), this could contribute to our observations. However, while undernutrition risk has been found to increase over time (9), studies have observed that weight loss can occur at any stage, even before PD onset (8, 10). Furthermore, the association between motor symptom severity and unintentional weight loss has been generally weak and inconsistent (5). It therefore appears unlikely that better motor symptom control per se would be a major explanation for our observations. One possiblility is that unintentional weight loss does occur without causing underweight because of a relatively high baseline weight. Such a mechanism was hypothesized to underpin recent observations of prevalent overweight/obesity in a Mexican PD accutane how long work sample (24). Longitudinal observations will be required to address this possibility. Interestingly however, and in line with our observations, a recent 3- year study among people with early PD reported weight gain and increased fat mass (25).

 

Table 4: Spearman correlations between disease duration and nutritional variables, and between nutritional variables and motor and autonomic scores.

a. Not computable due to constant MUST scores (0) among those with valid Sexual functioning (SCOPA-AUT) scores; * P<0.05. BMI, body mass index; SCREEN II, Seniors in the Community: Risk Evaluation for Eating and Nutrition, version II; MEONF II, Minimal Eating Observation and Nutrition Form – version II; MUST, Malnutrition Universal Screening Tool; TSF, Triceps Skin Fold; MAC, Mid Arm Circumference; MUAMC, Mid-Upper Arm Muscle Circumference; HGS, Hand Grip Strength; NHP-PM, Physical Mobility section of the Nottingham Health Profile; mGPAS, modified Grimby Physical Activity Scale; UPDRS II, Unified Parkinson’s Disease Rating Scale, part II (activities of daily living); UPDRS III, Unified Parkinson’s Disease Rating Scale, part III (motor examination); SCOPA-AUT, SCales for Outcomes in PArkinson’s disease – Autonomic symptoms.

 

There were few associations between nutritional and autonomic variables. This is in agreement with observations by Sheard et al. (2), who also used the SCOPA-AUT in a community-dwelling sample of people with PD and found a somewhat higher degree of gastrointestinal dysfunction among participants identified as at risk for undernutrition, but no other SCOPA-AUT scores were related to undernutrition. In our study, we also included OH as a more objective autonomic marker and found lower BMI and HGS among people with OH. This is in agreement with previous population based observations (26-28). Although the basis for this association remains to be established, it may seem reasonable to suggest that lower BMI and less muscle strength may yield people more prone to develop OH. On the other hand, presence of OH per se seems to be an independent risk factor for mortality in general as well as for coronary events. Consequently, OH could be a marker for more advanced morbidity (28). Furthermore, since OH is an important marker of dysautonomia and autonomic functioning is central to weight and gastrointestinal control the association found here could suggest a more profound relationship, particularly since pathological changes occur in the hypothalamus as well as in the gastrointestinal tract in PD (10, 29). However, this cannot be addressed further in the present study.

As not only PD but also its management appears to contribute to an increased risk for undernutrition (30), it is reasonable to assume that continuity of care with regular and frequent follow-up and awareness of propensity for unintentional weight loss and other non- motor symptoms may be preventive. Together with the relatively high malnutrition risk, this emphasizes the need for regular clinical monitoring of nutritional status. Our study was carried out at a multidiciplinary (including a dietician) PD clinic with well-established routines including regular patient education. Weight problems are therefore probably identified and intervened upon relatively early, which may have contributed to the low prevalence of underweight and undernutrition. Nevertheless, the use of a single-centre sample with mild motor symptoms and lack of clinically significant cognitive impairments challenges the generalizability of results to the wider PD population.

In conlusion, we found a low prevalence of underweight and undernutrition risk, frequent malnutrition (overweight) risk, but no associations between nutritional variables and PD duration. In this perspective, it should be noted that overweight may conceal a redistribution of muscle mass to fat mass (31).The possible reasons for our findings are still speculative but appear multi-factorial, e.g. regular patient care, relatively high BMI in the population at large, and effective symptom management. Longitudinal studies are needed to better understand the development of nutritional status and other disease aspects over time.

 

Funding: The study was supported by the Research Platform for Collaboration for Health, Kristianstad University, the Central Hospital Kristianstad, the Parkinson Foundation, the Swedish Parkinson Academy, and the Swedish Research Council. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

Acknowledgments: The authors want to thank all participating patients for their cooperation, Dr Caroline Marktorp for assistance with patient recruitment and dietician Erika Norberg for valuable discussions.

Conflicts of interest: Mrs. Lindskov has nothing to disclose. Dr. Sjöberg has nothing to disclose. Dr. Westergren has nothing to disclose. Dr. Hagell has nothing to disclose.

Ethical standards: This study was approved by the regional Research Ethics Committee, Lund, Sweden, according to the registration number 2009/429 and 2009/226.

 

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