Parkinson's Disease Severity Research Articles

Gait initiation in Parkinson's disease: comparison of timing and displacement during anticipatory postural adjustments as a function of motor severity and apathy in a large cohort

IntroductionGait initiation is preceded by three anticipatory postural adjustment (APA) phases. In Parkinson's disease (PD) generated force, displacement and timing during APA differ from healthy controls. APA might be influenced by disease status, weight or emotion. It is unknown how motor severity, disease duration or presence of apathy influences APA timing and displacement. MethodsWe included 99 people with PD and 50 healthy controls (HC) to perform five gait initiation trials following an auditory cue. Force plates measured timing and center of pressure (CoP) displacement during APA phases. ResultsTime to gait initiation (tGI) was higher in the PD group (p < 0.001, t = 2.74, 95%CI (0.008, 0.066)). The first two APA phases (APA1 and APA2a) lasted longer in PD (respectively p < 0.001, t = 3.87, 95%CI (0.091, 0.28) and p < 0.001, t = 4.1, 95%CI (0.031, 0.091)). Mean CoP displacement, variability in timing and displacement did not differ. A multiple regression model was used to determine if clinical variables were related to gait initiation parameters. tGI was predicted by age (p < 0.001) and weight (p = 0.005). The duration of APA1 was predicted by weight (p = 0.006) and APA2a by age (p < 0.001). Variability in duration of the locomotor phase (LOC) was predicted by age (p < 0.001). ConclusiontGI and initial APA phases are longer in PD than in HC. There are no significant differences in variability of timing or displacement between the two groups. Gait initiation parameters are independent of disease duration, motor severity, medication usage or apathy in PD. Our findings suggest that cueing does not speed up gait initiation but reduces variability.

Emerging Role of Long Noncoding RNAs in Regulating Inflammasome-Mediated Neurodegeneration in Parkinson's Disease.

Parkinson's disease (PD) is one of the complex neurodegenerative disorders, primarily characterized by motor deficits, including bradykinesia, tremor, rigidity, and postural instability. The underlying pathophysiology involves the progressive loss of dopaminergic neurons within the substantia nigra pars compacta, leading to dopamine depletion in the basal ganglia circuitry. While motor symptoms are hallmark features of PD, emerging research highlights a wide range of non-motor symptoms, including cognitive impairments, mood disturbances, and autonomic dysfunctions. Inflammasome activation is pivotal in inducing neuroinflammation and promoting disease onset, progression, and severity of PD. Several studies have shown that long noncoding RNAs (lncRNAs) modulate inflammasomes in the pathogenesis of neurodegenerative diseases. Dysregulation of lncRNAs is linked to aberrant gene expression and cellular processes in neurodegeneration, causing the activation of inflammasomes that contribute to neuroinflammation and neurodegeneration. Inflammasomes are cytosolic proteins that form complexes upon activation, inducing inflammation and neuronal cell death. This review explores the significance of lncRNAs in regulating inflammasomes in PD, primarily focusing on specific lncRNAs such as nuclear paraspeckle assembly transcript 1 (NEATNEAT1), X-inactive specific transcript (XIST), growth arrest-specific 5 (GAS5), and HOX transcript antisense RNA (HOTAIR), which have been shown to activate or inhibit the NLRP3 inflammasome and induce the release of proinflammatory cytokines. Moreover, some lncRNAs mediate inflammasome activation through miRNA interactions. Understanding the roles of lncRNAs in inflammasome regulation provides new therapeutic targets for controlling neuroinflammation and reducing the progression of neurodegeneration. Identifying lncRNA-mediated regulatory pathways paves the way for novel therapies in the battle against these devastating neurodegenerative disorders.

Mendelian randomization reveals association between retinal thickness and non-motor symptoms of Parkinson’s disease

Retinal thickness is related to Parkinson’s disease (PD), but its association with the severity of PD is still unclear. We conducted a Mendelian randomized (MR) study to explore the association between retinal thickness and PD. For the two-sample MR analysis, the summary statistics obtained from genome-wide association studies on the thickness of Retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) were employed as exposure, while the summary statistics associated with PD were used as the outcome. The primary approach utilized was inverse variance weighted. To correct for multiple testing, the false discovery rate (FDR) was employed. For sensitivity analysis, an array of robust MR methods was utilized. We found genetically predicted significant association between reduced RNFL thickness and a reduced risk of constipation in PD (odds ratio [OR] = 0.854, 95% confidence interval [CI] (0.782, 0.933), P < 0.001, FDR-corrected P = 0.018). Genetically predicted reduced RNFL thickness was associated with a reduced Unified Parkinson’s Disease Rating Scale total score (β = −0.042, 95% CI (−0.079, 0.005), P = 0.025), and reduced GCIPL thickness was associated with a lower risk of constipation (OR = 0.901, 95% CI (0.821, 0.988), P = 0.027) but a higher risk of depression (OR = 1.103, 95% CI (1.016, 1.198), P = 0.020), insomnia (OR = 1.090, 95% CI (1.013, 1.172), P = 0.021), and rapid eye movement sleep behaviour disorder (RBD) (OR = 1.198, 95% CI (1.061, 1.352), P = 0.003). In conclusion, we identify an association between retinal thickness and non-motor symptoms (constipation, depression, insomnia and RBD) in PD, highlighting the potential of retinal thickness as a biomarker for PD nonmotor symptoms.

Association Study Between Kynurenine 3-Monooxygenase (KMO) Gene and Parkinson's Disease Patients.

The influence of various risk factors such as aging, intricate cellular molecular processes, and lifestyle factors like smoking, alcohol consumption, caffeine intake, and occupational factors has received increased focus in relation to the risk and development of Parkinson's disease (PD). Limited research has been conducted on the assessment of lifestyle impact on kynurenine 3-monooxygenase (KMO) gene in PD. A total of 164 subjects, including 82 PD cases and 82 healthy individuals, were recruited based on specific inclusion and exclusion criteria. The severity of PD and clinical assessment were evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS) and Hoehn and Yahr (HY) scaling. Sanger sequencing was performed to analyse the KMO gene in the recruited subjects, and case-control studies were conducted. The UPDRS assessment revealed significant impairments in smell, tremors, walking, and posture instability in the late-onset PD cohorts. The HY scaling indicated a higher proportion of late-onset cohorts in stage 2. Moreover, both alcoholic and non-alcoholic groups showed significantly increased levels of 3-HK in late-onset PD. Gene analysis identified missense variants at position g.241593373T > A (rs752312199) and intronic variants at positions g.241592623A > G (rs640718), g.241592800C > A (rs990388262), g.241592802A > C (rs1350160268), g.241592808T > C (rs1478255936), and g.241592812G > T (rs948928931). The alterations in the KMO gene were found to influence the levels of kynurenic acid (KYNA) and 3-hydroxykynurenine (3-HK). Genomic analysis revealed a high prevalence of missense mutations in the late-onset PD groups, leading to a decline in 3-HK levels in patients. This leads to the reduction of the progression of disease in late-onset groups which shows that this mutation may lead to the protective effect on the PD subjects. This study suggests the use of KYNA and 3-HK as potential biomarkers in analysing the progression of disease. This study is limited by its small sample size. To overcome this limitation, a larger study involving in greater number of participants is needed to thoroughly investigate the KMO gene and KP metabolites, to enhance our understanding of Parkinson's disease progression, and to enhance diagnostic capabilities.

The impact of gender‐specific survival on the incidence of dementia in Parkinson’s disease ‐ A cohort analysis of Parkinson’s disease patients in German health claims data for the years 2006 to 2017

AbstractBackgroundThe aim of our study is to analyze gender‐specific patterns of Parkinson’s disease dementia (PDD) incidence. In addition, we are investigating the extent to which gender differences in survival after initial Parkinson’s disease (PD) diagnosis influence differences in PDD risk among PD patients.MethodWe used a random sample of German longitudinal health claims data of persons at ages 65 years or older (2006‐2017). We identified incident PD cases who were followed‐up for a PDD diagnosis or death. We computed age‐ and gender‐specific PDD incidence rates, death rates, and cumulative PDD incidence functions with death as competing risk. In addition, we performed Cox regression models and Fine and Gray competing‐risk regression models, considering death as a competing event, to calculate PDD hazard ratios (HR), adjusted for important risk factors such as age at PD onset, PD severity in terms of modified Hoehn&amp;Yahr (HY) scale, comorbidities, and medications.ResultOf 2,195 incident PD cases, 602 people died and 750 people received a dementia diagnosis by the end of 2017. 44% of PD men and 45% of PD women had received a dementia diagnosis, 45% of PD men and 32% of PD women had died, and only 11% of PD men but 23% of PD women had survived without a PDD diagnosis. PDD risk among PD patients differs by gender when controlled for age at onset, severity of PD, comorbidities and medications, with men having a higher PDD risk than women (HR = 1.18, p = 0.029). When accounting for death, men and women do not differ regarding their PDD risk (HR = 1.02, p = 0.770). Gender‐specific analyses showed significant age and severity effects in women (Age: HR = 1.05, p&lt;0.001, HY 0‐2.5: reference, HY 3‐5: HR = 1.46, p = 0.011), but not in men.ConclusionWe found that older age at first PD diagnosis and higher disease severity increase PDD risk, but this association is attenuated for PD men when we consider death as a competing risk. This implies that the most frail PD men die rapidly before receiving a dementia diagnosis, whereas women with PD survive at higher rates than men, regardless of their age at onset and disease severity.

Association between malnutrition and motor/non-motor symptoms in elderly with Parkinson disease

Background: Parkinson disease (PD) is a prevalent neurodegenerative disorder characterized by both movement and non-motor symptoms, potentially contributing to malnutrition. This study aims to investigate the association between malnutrition, assessed through the mini nutritional assessment-short form (MNA-SF), and motor/non-motor symptoms in elderly PD patients.Methods: A total of 48 PD patients were recruited, and their nutritional status was evaluated using MNA-SF. Motor/non-motor symptoms were assessed using the unified Parkinson’s disease rating scale (UPDRS). Statistical analysis was performed using linear regression, considering various covariates such as disease severity, cognitive function, and disease duration.Results: The mean age of the study group was 76.8 years, with 75% displaying abnormal nutritional status. An inverse correlation was evident between MNA-SF and UPDRS I, II, III, and overall scores. Patients with abnormal nutritional status developed severe limitations in daily activities and motor dysfunction. Both motor and non-motor symptoms were associated with malnutrition.Conclusions: This study suggests the significant relationship between nutritional status and motor/non-motor symptoms in elderly PD patients. The prevalence of malnutrition was particularly notable among older PD patients, highlighting the importance of consistent nutritional assessment due to its impact on PD severity. These findings suggest a complex interplay between PD symptoms and malnutrition, warranting further investigation with larger participant cohorts.

NR-SAFE: a randomized, double-blind safety trial of high dose nicotinamide riboside in Parkinson’s disease

Nicotinamide adenine dinucleotide (NAD) replenishment therapy using nicotinamide riboside (NR) shows promise for Parkinson’s disease (PD) and other neurodegenerative disorders. However, the optimal dose of NR remains unknown, and doses exceeding 2000 mg daily have not been tested in humans. To evaluate the safety of high-dose NR therapy, we conducted a single-center, randomized, placebo-controlled, double-blind, phase I trial on 20 individuals with PD, randomized 1:1 on NR 1500 mg twice daily (n = 10) or placebo (n = 10) for four weeks. The trial was conducted at the Department of Neurology, Haukeland University Hospital, Bergen, Norway. The primary outcome was safety, defined as the frequency of moderate and severe adverse events. Secondary outcomes were tolerability defined as frequency of mild adverse events, change in the whole blood and urine NAD metabolome, and change in the clinical severity of PD, measured by MDS-UPDRS. All 20 participants completed the trial. The trial met all prespecified outcomes. NR therapy was well tolerated with no moderate or severe adverse events, and no significant difference in mild adverse events. NR therapy was associated with clinical improvement of total MDS-UPDRS scores. However, this change was also associated with a shorter interval since the last levodopa dose. NR greatly augmented the blood NAD metabolome with up to 5-fold increase in blood NAD+ levels. While NR-recipients exhibited a slight initial rise in serum homocysteine levels, the integrity of the methyl donor pool remained intact. Our results support extending the dose range of NR in phase II clinical trials to 3000 mg per day, with appropriate safety monitoring. Clinicaltrials.gov identifier: NCT05344404.

Levetiracetam for the treatment of mild cognitive impairment in Parkinson’s disease: a double-blind controlled proof-of-concept trial protocol

BackgroundMild memory impairment, termed amnestic mild cognitive impairment (aMCI), is associated with rapid progression towards dementia in Parkinson’s disease (PD). Studies have shown hyperactivation of hippocampal DG/CA3 subfields during an episodic memory task as a biomarker of aMCI related to Alzheimer’s disease. This project investigates the feasibility of a trial to establish the efficacy of a repurposed antiepileptic drug, levetiracetam, in low doses as a putative treatment to target DG/CA3 hyperactivation and improve episodic memory deficits in aMCI in PD. Based on previous work, it is hypothesized that levetiracetam will normalize DG/CA3 overactivation in PD-aMCI participants and improve memory performance.MethodsTwenty-eight PD-aMCI participants, 28 PD participants without memory impairment (PD-nMI), and 28 healthy controls will be recruited. PD-aMCI participants will undertake a 12-week randomized, placebo-controlled, double-blind cross-over trial with a 14-day treatment of 125 mg levetiracetam or placebo twice daily, separated by a 4-week washout period. After each treatment period, participants will complete an episodic memory task designed to tax hippocampal subregion-specific function during high-resolution functional magnetic resonance imaging (fMRI). PD-nMI and healthy controls will undergo the fMRI protocol only, to compare baseline DG/CA3 subfield activity.ResultsEpisodic memory task performance and functional activation in the DG/CA3 subfield during the fMRI task will be primary outcome measures. Global cognition, PD severity, and adverse events will be measured as secondary outcomes. Recruitment, eligibility, and study completion rates will be explored as feasibility outcomes.ConclusionsThis study, the first of its kind, will establish hippocampal subregion functional impairment and proof of concept of levetiracetam as an early therapeutic option to reduce dementia risk in PD.Trial registrationClinicalTrials.gov, NCT04643327. Registered on 25 November 2020.

The semicircular canal function is preserved with little impact on falls in patients with mild Parkinson's disease

IntroductionPostural instability is a cardinal symptom of Parkinson's disease (PD), which suggests the vestibular system may be affected in PD. This study aimed to determine whether vestibular dysfunction is associated with the risk of falls in PD. MethodsWe prospectively recruited patients with de-novo PD at a tertiary medical center between December 2019 and March 2023. During initial assessment, each patient was queried about falls within the preceding year. All patients underwent evaluation of video head-impulse tests (video-HITs), motion analysis, mini-mental state examination (MMSE), and Montreal Cognitive Assessment (MOCA). We determined whether head impulse gain of the vestibulo-ocular reflex (VOR) was associated with clinical severity of PD or risk of falls. ResultsOverall, 133 patients (mean age ± SD = 68 ± 10, 59 men) were recruited. The median Movement Disorder Society-Unified Parkinson's Disease Rating Scale motor part (MDS-UPDRS-III) was 23 (interquartile range = 16–31), and 81 patients (61 %) scored 2 or less on the Hoehn and Yahr scale. Fallers were older (p = 0.001), had longer disease duration (p = 0.001), slower gait velocity (p = 0.009), higher MDS-UPDRS-III (p < 0.001) and H&Y scale (p < 0.001), lower MMSE (p = 0.018) and MOCA scores (p = 0.001) than non-fallers. Multiple logistic regression showed that MDS-UPDRS-III had a positive association with falling (p = 0.004). Falling was not associated with VOR gain (p = 0.405). The VOR gain for each semicircular canal showed no correlation with the MDS-UPDRS-III or disease duration. ConclusionsThe semicircular canal function, as determined by video-HITs, is relatively spared and has little effect on the risk of falls in patients with mild-to-moderate PD.

High use of non-hydrogenated plant source oils and mayonnaise sauce increase the risk of Parkinson disease

ABSTRACT Objectives: This study aimed to assess the contribution of edible/cooking oils and mayonnaise sauce in the severity, motor and non-motor symptoms, and risk of Parkinson's disease (PD). Methods: In this study, 120 patients with PD and 50 healthy individuals participated. The frequency and quantity of edible/cooking oils including animal and plant source oils (hydrogenated and nonhydrogenated) and mayonnaise sauce used by participants were determined using a food frequency questionnaire. The severity of PD was determined by the Unified Parkinson's Disease Rating Scale (UPDRS). Results: Patients with PD had lower use of hydrogenated plant-based oil (HPO) (p < 0.001) and animal oils (p < 0.001) but had higher use of non-hydrogenated plant-based oil (NHPO) (p < 0.001), olive oil (p = 0.02), and mayonnaise sauce (p < 0.001) compared with the healthy subjects. Use of each unit HPO reduced 4% the odds of PD (p = 0.01). The odds of PD increased 20% by each unit increase in NHPO usage (p = 0.001), 49% by olive oil (p = 0.02), and 127% by mayonnaise sauce (p = 0.004) intake. According to receiver operator characteristics curve analysis, mayonnaise sauce and NHPO had the largest area under the curve in predicting PD. Intake of animal oil was positively correlated with total score of UPDRS (p = 0.05) and motor symptoms (p = 0.04). Intake of butter was positively correlated with total score of UPDRS (p = 0.047), nonmotor aspects of experiences of daily living (p = 0.02), and motor examination (p = 0.02). Discussion: The findings indicate that high intake of HPO reduces, while high intake of NHPO, olive oil, and mayonnaise sauce increases the odds of PD.

Dietary approach to stop hypertension (DASH), but not Mediterranean and MIND, dietary pattern protects against Parkinson's disease.

The neuroprotective effects of dietary patterns have been reported in previous studies. This study aimed to examine the association between the dietary approach to stop hypertension (DASH), the Mediterranean diet (MeDi), and the Mediterranean-DASH intervention for neurodegenerative delay (MIND) with the severity and risk of Parkinson's disease (PD). In this comparative cross-sectional study, 120 patients with PD and 50 healthy participants participated. Adherence to DASH, MeDi, and MIND dietary patterns was determined according to the dietary intake data using a food frequency questionnaire (FFQ). The Severity of PD was determined by the Unified Parkinson's Disease Rating Scale (UPDRS). The mean score of the DASH was significantly lower in the PD group compared to the healthy group (p = .006), but the mean score of MeDi and MIND did not significantly differ between the two groups (p > .05). Also, the mean score of the DASH was significantly lower in men than in women in the healthy group (p = .018). High adherence to the DASH diet decreased the risk of PD by 15% (OR = 0.856, 95% CI: 0.751, 0.976, p = .020). Participants in quartiles 3 and 4 of the DASH dietary pattern had 86% (p = .003) and 87% (p = .007), respectively, lower risk of PD. MeDi and MIND diets were not significantly associated with the risk of PD. There was no significant association between dietary patterns and the severity of PD. The findings indicate that high adherence to the DASH dietary pattern may protect against PD.

Objective assessment of eye alignment and disparity-driven vergence in Parkinson's disease.

Self-reported diplopia is described in up to one-third of Parkinson's disease (PD) patients. The purpose of our study was to expand our understanding of the mechanistic underpinnings of diplopia in PD. We hypothesize that the time-based control of eye alignment and increased eye deviation under binocular viewing will be related to the fusion-initiating and fusion-maintaining component deficits of disparity-driven vergence in PD. We used high-resolution video-oculography to measure eye alignment under binocular and monocular viewing and disparity-driven vergence in 33 PD and 10 age-matched healthy participants. We computed eye deviation and time-based control of eye alignment, occurrence of conjugate saccadic eye movements, latency and gain of vergence (fusion initiation), and variance of eye position at the end of dynamic vergence (fusion maintenance). We categorized PD subjects into three groups, considering their time-based control of eye alignment as compared to healthy controls in binocular viewing. Group 1 = 45% had good control and spent >80% of the time when the eyes were well-aligned, Group 2 = 26% had intermediate control and spent <80% but greater >5% of the time when the eyes were well-aligned, and Group 3 = 29% had very poor control with increased eye deviation majority of the times (<5% of the time when the eyes were well-aligned). All three groups exhibited greater eye deviation under monocular viewing than controls. PD subjects exhibited fusion-initiating and fusion-maintaining vergence deficits (prolonged latencies, reduced vergence gain, increased variance of fusion-maintaining component) with a greater probability of saccadic movements than controls. Group 2 and Group 3 subjects were more likely to exhibit failure to initiate vergence (>20%) than Group 1 (13%) and controls (0%) trials. No significant difference was found in the Unified Parkinson's Disease Rating Scale (UPDRS-a tool to measure the severity of PD) values between the three PD groups (Group 1 = 33.69 ± 14.22, Group 2 = 38.43 ± 22.61, and Group 3 = 23.44 ± 1, p > 0.05). The majority of PD subjects within our cohort had binocular dysfunction with increased eye deviation under monocular viewing and disparity-driven vergence deficits. PD subjects with intermediate or poor control of eye deviation under binocular viewing had greater fusion-initiating and fusion-maintaining vergence deficits. The study highlights the importance of assessing binocular dysfunction in PD subjects independent of the severity of motor symptoms.

The role of immune and inflammatory-related indicators in cognitive dysfunction and disease severity in patients with parkinson's disease.

We aimed to explore the role of immune and inflammatory indicators in cognitive dysfunction and disease severity in patients with Parkinson's disease(PD). A total of 123 patients with Parkinson's disease were enrolled in the PD group and 49 healthy volunteers in the control group. The patients with PD were further divided into 2 subgroups by evaluating cognitive function using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE): the normal cognitive function (PD-NCI) group and the mild cognitive impairment (PD-MCI) group. Moreover, the PD patients were also divided into 2 subgroups using the defined scale of the Hoehn and Yahr (H-Y) stage: the early-stage group and the middle- and late-stage group. Immune and inflammatory indicators, including serum Aβ1-42, Tau, CD4+, CD8+, CD3+, B lymphocytes cell, NK cell, Th17 cell, Treg cell, IL-6, IL-17, and TNF-α levels, were evaluated and analyzed to explore the potential correlation with the cognitive dysfunction and disease severity of PD. Among the 123 PD patients, 60 (48.8%) were diagnosed with mild cognitive impairment. Aβ1-42, CD4+, CD8+, CD3+, and Treg levels observed in the PD-NCI group were lower than the control group (P < 0.001), while higher than the PD-MCI group (P < 0.001). The levels of Tau, Th17, IL-6, IL-17, and TNF-α observed in the PD-NCI group were higher than the control group(P < 0.001), while lower than in the PD-MCI group (P < 0.01). Using the same method, the results of the early-stage group and the middle- and the late-stage group were the same as above. Logistic regression analysis and ROC curve estimation were performed and indicated that the variation of Tau, CD8+, Treg, TNF-α levels was associated with cognitive decline in PD patients, and may serve as markers of PD onset. Furthermore, the variation of Aβ1-42, IL-6, and TNF-α levels was found to correlate with the disease severity of PD. The immune and inflammatory-related indicators may represent an important factor in the pathogenesis of PD, cognitive dysfunction, and disease severity. The variation of Tau protein, CD8+, Treg, and TNF-α levels are associated with the cognitive dysfunction of PD, which may be considered as onset markers. Moreover, the variation of Aβ1-42, IL-6, and TNF-α levels can predict the progression of PD.

Monoaminergic Degeneration and Ocular Motor Abnormalities in De Novo Parkinson's Disease.

Evaluating eye movements in Parkinson's disease (PD) provides valuable insights into the underlying pathophysiological changes. The aim was to investigate the relationship between monoaminergic degeneration and ocular motor abnormalities in de novo PD. Drug-naive PD patients who underwent N-(3-[18 F]fluoropropyl)-2-carbomethoxy-3-(4-iodophenyl) nortropane positron emission tomography scans and video-oculography at diagnosis were eligible. Measurements of saccadic accuracy, latency, and smooth pursuit gain and square wave jerk frequency were collected. Patients underwent Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and detailed cognitive tests. We investigated the associations between ocular motor measurements and specific tracer uptake ratios (SUR) in the caudate nucleus, anterior and posterior putamen, thalamus, and dorsal raphe nuclei, along with motor and cognitive symptoms. One-hundred twenty-four subjects were included in this study. Saccadic accuracy was positively associated with parkinsonian motor severity expressed as Hoehn and Yahr stages, MDS-UPDRS Part III scores, and subscores for bradykinesia and rigidity but not with tremor scores (PFDR < 0.05). Saccadic accuracy correlated with poor performances in the Rey-Complex-Figure copy, and latency with the Digit Symbol Coding and the Montreal Cognitive Assessment scores (PFDR < 0.05). Prolonged saccadic latency correlated with reduced thalamic SUR, whereas decreased saccadic accuracy correlated with reduced SUR in the anterior and posterior putamen (PFDR < 0.05). Reduced smooth pursuit gain showed associations with reduced SUR in the dorsal raphe, a serotonin-predominant region, but did not correlate with parkinsonism severity scores. Defective dopaminergic and nondopaminergic neural systems may discretely influence ocular motor function in de novo PD patients. © 2023 International Parkinson and Movement Disorder Society.

Inflammatory Blood Biomarkers Are Associated with Long-Term Clinical Disease Severity in Parkinson's Disease.

An altered immune response has been identified as a pathophysiological factor in Parkinson's disease (PD). We aimed to identify blood immunity-associated proteins that discriminate PD from controls and that are associated with long-term disease severity in PD patients. Immune response-derived proteins in blood plasma were measured using Proximity Extension Technology by OLINK in a cohort of PD patients (N = 66) and age-matched healthy controls (N = 52). In a selection of 30 PD patients, we evaluated changes in protein levels 7-10 years after the baseline and assessed correlations with motor and cognitive assessments. Data from the Parkinson's Disease Biomarkers Program (PDBP) cohort and the Parkinson's Progression Markers Initiative (PPMI) cohort were used for independent validation. PD patients showed an altered immune response compared to controls based on a panel of four proteins (IL-12B, OPG, CXCL11, and CSF-1). The expression levels of five inflammation-associated proteins (CCL23, CCL25, TNFRSF9, TGF-alpha, and VEGFA) increased over time in PD and were partially associated with more severe motor and cognitive symptoms at follow-up. Increased CCL23 levels were associated with cognitive decline and the APOE4 genotype. Our findings provide further evidence for an altered immune response in PD that is associated with disease severity in PD over a long period of time.

Scaling problem in Parkinson's disease patients with pain

IntroductionAlthough pain is common in Parkinson's disease (PD), the underlying mechanism remains unknown. Scaling function and dopaminergic hypofunction may contribute to pain development because increased pain sensitivity is observed in PD and is normalized after levodopa administration. We aimed to determine whether spatial discrimination (SD) and striatal dopaminergic activity (DA) differed between PD patients with and without pain. MethodsWe divided 90 patients with drug-naïve PD into two groups based on the presence or absence of pain and compared the SD threshold (SDT). We evaluated the correlation of the SDT with pain severity in PD with pain. We also compared the DA of 48 patients and analyzed the correlation with pain severity in PD patients with pain. ResultsThe SDTs did not differ between the two groups, but unmeasurable SDT was more frequent in PD with pain. There was a positive correlation of pain severity with the SDT of the more affected hand but no correlation with the SDT of the less affected hand. The DA did not differ between the groups. There was a negative trend of pain severity with the DA of the ventral striatum (VS) but no correlation with the other striatal subregions. ConclusionsPain in PD may be associated with scaling dysfunction in the sensory system. The abnormal scaling function would render the PD patient hypersensitive to even mild pain. The dopamine in the VS appears to be associated with pain severity; however, the relationship of striatal dopaminergic deficits with pain occurrence requires further investigation.

Enhancing Parkinson's disease severity assessment through voice-based wavelet scattering, optimized model selection, and weighted majority voting

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms that significantly impact an individual's quality of life. Voice changes have shown promise as early indicators of PD, making voice analysis a valuable tool for early detection and intervention. This study aims to assess and detect the severity of PD through voice analysis using the mobile device voice recordings dataset. The dataset consisted of recordings from PD patients at different stages of the disease and healthy control subjects. A novel approach was employed, incorporating a voice activity detection algorithm for speech segmentation and the wavelet scattering transform for feature extraction. A Bayesian optimization technique is used to fine-tune the hyperparameters of seven commonly used classifiers and optimize the performance of machine learning classifiers for PD severity detection. AdaBoost and K-nearest neighbor consistently demonstrated superior performance across various evaluation metrics among the classifiers. Furthermore, a weighted majority voting (WMV) technique is implemented, leveraging the predictions of multiple models to achieve a near-perfect accuracy of 98.62%, improving classification accuracy. The results highlight the promising potential of voice analysis in PD diagnosis and monitoring. Integrating advanced signal processing techniques and machine learning models provides reliable and accessible tools for PD assessment, facilitating early intervention and improving patient outcomes. This study contributes to the field by demonstrating the effectiveness of the proposed methodology and the significant role of WMV in enhancing classification accuracy for PD severity detection.

Diagnostic value of combined magnetic resonance imaging techniques in the evaluation of Parkinson disease.

The incidence of Parkinson disease (PD) has been increasing each year. The development of new magnetic resonance imaging (MRI) technology can help understand its pathogenesis and identify more effective imaging-based biological indicators. The clinical and MRI imaging data of 40 patients with PD and 40 healthy controls were analyzed. All participants underwent susceptibility-weighted imaging (SWI), neuromelanin-sensitive magnetic resonance imaging (NM-MRI), and T2*mapping sequence examination. The diagnostic value of single and combined multiparameter indicators was analyzed using the receiver operating characteristic curve. Compared with the healthy control group, the PD group showed significant differences in the disappearance of bilateral "swallow tail sign", the distribution volume of melanocytes in the substantia nigra and the smaller volume in the bilateral substantia nigra, the maximum signal of the locus coeruleus and the smaller and average volume in the bilateral substantia nigra, and the values of T2* and R2* in the bilateral substantia nigra (P<0.01). The maximum and smaller value and the average value of the bilateral locus coeruleus signal were negatively correlated with the disease course duration (P<0.05), and the smaller distribution volume of the melanin neurons in the bilateral substantia nigra was negatively correlated with Hoehn and Yahr (H-Y) grade (P<0.05). In the joint diagnosis with multiple indicators, some composite parameters were found to be negatively correlated with H-Y grading (P<0.05), while others were negatively correlated with disease course duration (P<0.05). Joint use of multiple parameter indicators greatly improved diagnostic efficacy [area under the curve (AUC) =0.958]. The distribution volume of melanin in substantia nigra and the maximum value of locus coeruleus signal may be the biological imaging indicators for the early diagnosis, severity, and follow-up evaluation of PD. Compared with a single indicator, composite indicators used in combination with multiple techniques have a significantly better diagnostic efficacy for PD.

Longitudinal Analysis of Retinal Microvascular and Choroidal Imaging Parameters in Parkinson's Disease Compared with Controls

To quantify rate of change of retinal microvascular and choroidal structural parameters in subjects with Parkinson's disease (PD) compared with controls using OCT and OCT angiography (OCTA). Prospective longitudinal study. Seventy-four eyes of 40 participants with PD and 149 eyes of 78 control individuals from the Eye Multimodal Imaging in Neurodegenerative Disease database. Subjects underwent OCT and OCTA imaging at 2 time points approximately 12 months apart. Imaging parameters included central subfield thickness, ganglion cell-inner plexiform layer (GC-IPL) thickness, peripapillary retinal nerve fiber layer thickness, choroidal vascularity index, superficial capillary plexus perfusion density (PFD), vessel density (VD), and foveal avascular zone area. Participants with PD had greater rate of yearly decrease in GC-IPL (PD=-0.403μm, control=+ 0.128 μm; P= 0.01), greater yearly decline in PFD in the 3× 3 mm ETDRS circle (PD=-0.016, control=+ 0.002; P<0.001) and ring (PD=-0.016, control=+ 0.002; P < 0.001); 6× 6 mm ETDRS circle (PD=-0.021, control= 0.00; P= 0.001), and outer ring (PD=-0.022, control= 0.00; P= 0.001). Participants with PD had greater rate of yearly decline in VD in 3× 3 mm circle (PD=-0.939/mm, control=+ 0.006/mm; P < 0.001) and ring (PD=-0.942/mm, control=+ 0.013/mm; P < 0.001); 6× 6 mm circle (PD=-0.72/mm, control=-0.054/mm; P= 0.006), and outer ring (PD=-0.746/mm, control=-0.054/mm; P= 0.005). When stratified by PD severity based on Hoehn and Yahr stage, faster rates of decline were seen in Hoehn and Yahr stages 3 to 4 in the 3× 3 mm circle PFD and VD as well as 3× 3 mm ring VD. Individuals with PD experience more rapid loss of retinal microvasculature quantified on OCTA and more rapid thinning of the GC-IPL than controls. There may be more rapid loss in patients with greater disease severity. The author(s) have no proprietary or commercial interest in any materials discussed in this article.

A Two-Stream 3D-CNN Network Based on Pressure Sensor Data and Its Application in Gait Recognition

Accurate diagnosis of Parkinson’s disease (PD) is challenging in clinical medicine. To reduce the diagnosis time and decrease the diagnosis difficulty, we constructed a two-stream Three-Dimensional Convolutional Neural Network (3D-CNN) based on pressure sensor data. The algorithm considers the stitched surface of the feet as an “image”; the geometric positions of the pressure sensors are considered as the “pixel coordinates” and combines the time dimension to form 3D data. The 3D-CNN is used to extract the spatio-temporal features of the gait. In addition, a twin network of 3D-CNN with shared parameters is used to extract the spatio-temporal features of the left and right foot respectively to further obtain symmetry information, which not only extracts the spatial information between the multiple sensors but also obtains the symmetry features of the left and right feet at different spatio-temporal locations. The results show that the proposed model is superior to other advanced methods. Among them, the average accuracy of Parkinson’s disease diagnosis is 99.07%, and the average accuracy of PD severity assessment is 98.02%.