Search

BackgroundThe penetrance of common genetic risk variants for Parkinson's disease (PD) is low. Pesticide exposure increases PD risk, but how exposure affects penetrance is not well understood.ObjectiveTo determine the relationship between occupational pesticide exposure and PD in people with LRRK2 and GBA risk variants.MethodsParticipants of the Parkinson's Progression Markers Initiative (PPMI) with a LRRK2-G2019 S or GBA risk variant provided information about occupational pesticide exposure. We compared exposure in carriers with and without PD. Among carriers with PD, we used Cox proportional hazard models to compare time-to impairment in balance, cognition, and activities of daily living (ADLs) between participants with and without prior occupational pesticide exposure.Results378 participants with a risk variant provided exposure information; 176 with LRRK2-G2019 S (54 with and 122 without PD) and 202 with GBA variants (47 with and 155 without PD). Twenty-six participants reported pesticide exposure. People with a GBA variant and occupational pesticide exposure had much higher odds of PD (aOR: 5.4, 95% CI 1.7-18.5, p

Background: The association between body mass index (BMI) and rapid eye-movement (REM) sleep-related behavioral disorder (RBD) in Parkinson's disease (PD) remains unknown. Our study was to investigate the association of BMI with RBD in PD patients. Methods: In this cross-sectional study, a total of 1,115 PD participants were enrolled from Parkinson's Progression Markers Initiative (PPMI) database. BMI was calculated as weight divided by height squared. RBD was defined as the RBD questionnaire (RBDSQ) score with the cutoff of 5 or more assessed. Univariable and multivariable logistic regression models were performed to examine the associations between BMI and the prevalence of RBD. Non-linear correlations were explored with use of restricted cubic spline (RCS) analysis. And the inflection point was determined by the two-line piecewise linear models. Results: We identified 426 (38.2%) RBD. The proportion of underweight, normal, overweight and obese was 2.61, 36.59, 40.36, and 20.44%, respectively. In the multivariate logistic regression model with full adjustment for confounding variables, obese individuals had an odds ratio of 1.77 (95% confidence interval: 1.21 to 2.59) with RBD compared with those of normal weight. In the RCS models with three knots, BMI showed a non-linear association with RBD. The turning points of BMI estimated from piecewise linear models were of 28.16 kg/m², 28.10 kg/m², and 28.23 kg/m² derived from univariable and multivariable adjusted logistic regression models. The effect modification by depression on the association between BMI and RBD in PD was also found in this study. Furthermore, the sensitivity analyses linked with cognition, education, and ethnic groups indicated the robustness of our results. Conclusion: The current study found a significant dose-response association between BMI and RBD with a depression-based difference in the impact of BMI on RBD in PD patients. [ABSTRACT FROM AUTHOR]

BackgroundLittle is known about the impact of the dopamine system on development of cognitive impairment (CI) in Parkinson disease (PD).ObjectivesWe used data from a multi-site, international, prospective cohort study to explore the impact of dopamine system-related biomarkers on CI in PD.MethodsPD participants were assessed annually from disease onset out to 7 years, and CI determined by applying cut-offs to four measures: (1) Montreal Cognitive Assessment; (2) detailed neuropsychological test battery; (3) Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) cognition score; and (4) site investigator diagnosis of CI (mild cognitive impairment or dementia). The dopamine system was assessed by serial Iodine-123 Ioflupane dopamine transporter (DAT) imaging, genotyping, and levodopa equivalent daily dose (LEDD) recorded at each assessment. Multivariate longitudinal analyses, with adjustment for multiple comparisons, determined the association between dopamine system-related biomarkers and CI, including persistent impairment.ResultsDemographic and clinical variables associated with CI were higher age, male sex, lower education, non-White race, higher depression and anxiety scores and higher MDS-UPDRS motor score. For the dopamine system, lower baseline mean striatum dopamine transporter values (P range 0.003-0.005) and higher LEDD over time (P range

BackgroundIn the last decades, the association of household pesticide usage with Parkinson's disease (PD) has been poorly explored, with discordant results. Based on the Parkinson's Progression Markers Initiative (PPMI) cohort study, we analyzed (1) the association of household pesticide exposure with the development of PD and (2) the effect of household pesticides on progression of PD.MethodsData from participants of the “FOllow Up persons with Neurologic Disease” (FOUND study) included in the PPMI cohort database were analyzed. The PPMI FOUND study applied the Parkinson's Disease Risk Factor Questionnaire to collect information regarding the use of pesticides in non-work settings during periods of life, and the lifetime pesticide exposure for each participant was estimated. We defined a high use of pesticides if the exposure estimate had a z-score higher than one standard deviation from the mean. Also, we evaluated longitudinal data of people with PD to analyze the effect of high use of household pesticides on disease progression according to motor impairment, cognitive dysfunction, depressive symptoms, and modification of motor clinical phenotype.ResultsWe analyzed data from 206 people with PD and 64 healthy controls, almost all from the USA. High use of household pesticides was not associated with the odds of developing PD. Regarding PD progression, only cognitive dysfunction was associated with the high use of household fungicides (HR 5.64 per standard deviation increase in exposure estimate, 95% CI 1.41–22.6).ConclusionsChronic exposure to household pesticides may impact the clinical progression of PD, especially cognitive symptoms.

BackgroundInvestigation of sex-related motor and non-motor differences and biological markers in Parkinson's disease (PD) may improve precision medicine approach.ObjectiveTo examine sex-related longitudinal changes in motor and non-motor features and biologic biomarkers in early PD.MethodsWe compared 5-year longitudinal changes in de novo, untreated PD men and women (at baseline N = 423; 65.5%male) of the Parkinson's Progression Markers Initiative (PPMI), assessing motor and non-motor manifestations of disease; and biologic measures in cerebrospinal fluid (CSF) and dopamine transporter deficit on DaTscanTM uptake.ResultsMen experienced greater longitudinal decline in self-reported motor (p

Abstract Background Dementia is a prevalent non-motor manifestation among individuals with advanced Parkinson’s disease (PD). Glial fibrillary acidic protein (GFAP) is an inflammatory marker derived from astrocytes. Research has demonstrated the potential of plasma GFAP to forecast the progression to dementia in PD patients with mild cognitive impairment (PD–MCI). However, the predictive role of cerebrospinal fluid (CSF) GFAP on future cognitive transformation and alterations in Alzheimer’s disease (AD)-associated CSF biomarkers in newly diagnosed PD patients has not been investigated. Methods 210 de novo PD patients from the Parkinson’s Progression Markers Initiative were recruited. Cognitive progression in PD participants was evaluated using Cox regression. Cross-sectional and longitudinal associations between baseline CSF GFAP and cognitive function and AD-related CSF biomarkers were evaluated using multiple linear regression and generalized linear mixed model. Results At baseline, the mean age of PD participants was 60.85 ± 9.78 years, including 142 patients with normal cognition (PD–NC) and 68 PD–MCI patients. The average follow-up time was 6.42 ± 1.69 years. A positive correlation was observed between baseline CSF GFAP and age (β = 0.918, p

Background: Dementia is a prevalent non-motor manifestation among individuals with advanced Parkinson's disease (PD). Glial fibrillary acidic protein (GFAP) is an inflammatory marker derived from astrocytes. Research has demonstrated the potential of plasma GFAP to forecast the progression to dementia in PD patients with mild cognitive impairment (PD–MCI). However, the predictive role of cerebrospinal fluid (CSF) GFAP on future cognitive transformation and alterations in Alzheimer's disease (AD)-associated CSF biomarkers in newly diagnosed PD patients has not been investigated. Methods: 210 de novo PD patients from the Parkinson's Progression Markers Initiative were recruited. Cognitive progression in PD participants was evaluated using Cox regression. Cross-sectional and longitudinal associations between baseline CSF GFAP and cognitive function and AD-related CSF biomarkers were evaluated using multiple linear regression and generalized linear mixed model. Results: At baseline, the mean age of PD participants was 60.85 ± 9.78 years, including 142 patients with normal cognition (PD–NC) and 68 PD–MCI patients. The average follow-up time was 6.42 ± 1.69 years. A positive correlation was observed between baseline CSF GFAP and age (β = 0.918, p < 0.001). There was no statistically significant difference in baseline CSF GFAP levels between PD–NC and PD–MCI groups. Higher baseline CSF GFAP predicted greater global cognitive decline over time in early PD patients (Montreal Cognitive Assessment, β = − 0.013, p = 0.014). Furthermore, Cox regression showed that high baseline CSF GFAP levels were associated with a high risk of developing dementia over an 8-year period in the PD–NC group (adjusted HR = 3.070, 95% CI 1.119–8.418, p = 0.029). In addition, the baseline CSF GFAP was positively correlated with the longitudinal changes of not only CSF α-synuclein (β = 0.313, p < 0.001), but also CSF biomarkers associated with AD, namely, amyloid-β 42 (β = 0.147, p = 0.034), total tau (β = 0.337, p < 0.001) and phosphorylated tau (β = 0.408, p < 0.001). Conclusions: CSF GFAP may be a valuable prognostic tool that can predict the severity and progression of cognitive deterioration, accompanied with longitudinal changes in AD-associated pathological markers in early PD. [ABSTRACT FROM AUTHOR]

ObjectiveReduction in glucocerebrosidase (GCase; encoded by GBA) enzymatic activity has been linked to Parkinson's disease (PD). Here, we correlated GCase activity and PD phenotype in the Parkinson's Progression Markers Initiative (PPMI) cohort.MethodsWe measured GCase activity in dried blood spots from 1559 samples of participants in the inception PPMI cohort, collected in four annual visits (from baseline visit to Year-3). Participants (PD, n = 392; controls, n = 175) were fully sequenced for GBA variants by means of genome-wide genotyping arrays, whole-exome sequencing, whole-genome sequencing, Sanger sequencing, and RNA-sequencing.ResultsFifty-two PD participants (13.4%) and 13 (7.4%) controls carried a GBA variant. GBA status was strongly associated with GCase activity. Among noncarriers, GCase activity was similar between PD and controls. Among GBA p.E326K carriers (PD, n = 20; controls, n = 5), activity was significantly lower in PD carriers than control carriers (9.53 µmol/L/h vs. 11.68 µmol/L/h, P = 0.035). Glucocerebrosidase activity was moderately (r = 0.45) associated with white blood cell (WBC) count. Next, we divided the noncarriers with PD to tertiles based on WBC count-corrected enzymatic activity. Members of the lower tertile had higher MDS-Unified Parkinson's Disease Rating Scale motor score in the "off" medication examination at year-III exam. Longitudinal analyses demonstrated slight reduction of activity in samples collected earlier on in the study, likely because of longer storage time.InterpretationGCase activity is associated with GBA genotype, WBC count, and among p.E326K variant carriers, with PD status. Reduced activity may also be associated with worse phenotype but longer follow up is required to confirm this observation.

ObjectiveTo determine the evolution of numerous neuropsychiatric symptoms and cognitive abilities in Parkinson disease from disease onset.MethodsProspectively collected, longitudinal (untreated, disease onset to year 5), observational data from Parkinson's Progression Markers Initiative annual visits was used to evaluate prevalence, correlates, and treatment of 10 neuropsychiatric symptoms and cognitive impairment in Parkinson disease participants and matched healthy controls.ResultsOf 423 Parkinson disease participants evaluated at baseline, 315 (74.5%) were assessed at year 5. Eight neuropsychiatric symptoms studied increased in absolute prevalence by 6.2-20.9% at year 5 relative to baseline, and cognitive impairment increased by 2.7-6.2%. In comparison, the frequency of neuropsychiatric symptoms in healthy controls remained stable or declined over time. Antidepressant and anxiolytic/hypnotic use in Parkinson disease were common at baseline and increased over time (18% to 27% for the former; 13% to 24% for the latter); antipsychotic and cognitive-enhancing medication use was uncommon throughout (2% and 5% of patients at year 5); and potentially harmful anticholinergic medication use was common and increased over time. At year 5 the cross-sectional prevalence for having three or more neuropsychiatric disorders/cognitive impairment was 56% for Parkinson disease participants versus 13% for healthy controls, and by then seven of the examined disorders had either occurred or been treated at some time point in the majority of Parkinson disease patients. Principal component analysis suggested an affective disorder subtype only.InterpretationNeuropsychiatric features in Parkinson disease are common from the onset, increase over time, are frequently comorbid, and fluctuate in severity.

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Introduction: Parkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD. Objective: In this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months. Result: Compared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes. Conclusion: In conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and networkmetricsmight yield insight into network reorganization that occurs in PD. [ABSTRACT FROM AUTHOR]

ObjectiveThe Parkinson's Progression Markers Initiative (PPMI) is an observational, international study designed to establish biomarker-defined cohorts and identify clinical, imaging, genetic, and biospecimen Parkinson's disease (PD) progression markers to accelerate disease-modifying therapeutic trials.MethodsA total of 423 untreated PD, 196 Healthy Control (HC) and 64 SWEDD (scans without evidence of dopaminergic deficit) subjects were enrolled at 24 sites. To enroll PD subjects as early as possible following diagnosis, subjects were eligible with only asymmetric bradykinesia or tremor plus a dopamine transporter (DAT) binding deficit on SPECT imaging. Acquisition of data was standardized as detailed at www.ppmi-info.org.ResultsApproximately 9% of enrolled subjects had a single PD sign at baseline. DAT imaging excluded 16% of potential PD subjects with SWEDD. The total MDS-UPDRS for PD was 32.4 compared to 4.6 for HC and 28.2 for SWEDD. On average, PD subjects demonstrated 45% and 68% reduction in mean striatal and contralateral putamen Specific Binding Ratios (SBR), respectively. Cerebrospinal fluid (CSF) was acquired from >97% of all subjects. CSF (PD/HC/SWEDD pg/mL) α-synuclein (1845/2204/2141) was reduced in PD vs HC or SWEDD (P

IntroductionParkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD.ObjectiveIn this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months.ResultCompared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes.ConclusionIn conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and network metrics might yield insight into network reorganization that occurs in PD.

Background: Neurofilament light chain protein (NfL) in cerebrospinal fluid (CSF) reflects the severity of neurodegeneration, with its altered concentrations discovered in Parkinson’s disease (PD) and Parkinson’s disease dementia (PDD). Objective: To determine whether CSF NfL, a promising biomarker of neuronal/ axonal damage, can be used to monitor cognitive progression in de novo Parkinson’s disease and predict future cognitive decline. Methods: A total of 259 people were recruited in this study, including 85 healthy controls (HC) and 174 neonatal PD patients from the Parkinson’s Progression Markers Initiative (PPMI). Multiple linear regression and linear mixed effects models were used to examine the associations of baseline/ longitudinal CSF NfL with cognitive decline and other CSF biomarkers. Kaplan–Meier analysis and log-rank test were used to compare the cumulative probability risk of cognition progression during the follow-up. Multivariate cox regression was used to detect cognitive progression in de novo PD. Results: We found PD patients with mild cognitive impairment (PD-MCI) was higher than with normal cognition (PD-NC) in terms of CSF NfL baseline levels (p = 0.003) and longitudinal increase rate (p = 0.034). Both baseline CSF NfL and its rate of change predicted measurable cognitive decline in de novo PD (MoCA, β = −0.010, p = 0.011; β = −0.0002, p < 0.001, respectively). The predictive effects in de novo PD patients aged >65, male, ill-educated (<13 years) and without carrying Apolipoprotein E ε4 (APOE ε4) seemed to be more obvious and reflected in more domains investigated. We also observed that CSF NfL levels predicted progression in de novo PD patients with different cognitive diagnosis and amyloid status. After an average follow-up of 6.66 ± 2.54 years, higher concentration above the median of baseline CSF NfL was associated with a future high risk of PD with dementia (adjusted HR 2.82, 95% CI: 1.11– 7.20, p = 0.030). Conclusion: Our results indicated that CSF NfL is a promising prognostic predictor of PD, and its concentration and dynamics can monitor the severity and progression of cognitive decline in de novo PD patients. [ABSTRACT FROM AUTHOR]

INTRODUCTION:Several characteristics associated with increased risk for Parkinson's disease (PD) have been identified, including specific genotypes and various non-motor symptoms. Characterizing non-motor features, such as cognitive abilities, among individuals considered at-risk for PD is essential to improving prediction of future neurodegeneration. METHODS:Participants belonging to the following cohorts of the Parkinson Progression Markers Initiative (PPMI) study were included: de novo PD with dopamine transporter binding deficit (n = 423), idiopathic REM sleep behavior disorder (RBD, n = 39), hyposmia (n = 26) and non-PD mutation carrier (NMC; Leucine-rich repeat kinase 2 (LRRK2) G2019S (n = 88) and glucocerebrosidase (GBA) gene (n = 38) mutations)). Inclusion criteria enriched the RBD and hyposmia cohorts, but not the NMC cohort, with individuals with dopamine transporter binding deficit. Baseline neuropsychological performance was compared, and analyses were adjusted for age, sex, education, and depression. RESULTS:The RBD cohort performed significantly worse than the hyposmia and NMC cohorts on Symbol Digit Modality Test (mean (SD) 32.4 (9.16) vs. 41.8 (9.98), p = 0.002 and vs. 45.2 (10.9), p

ObjectivesTo assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments.MethodsWe longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.ResultsBy year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes).ConclusionsCognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.

The development of biomarkers to predict the progression of Parkinson's disease (PD) from its earliest stage through its heterogeneous course is critical for research and therapeutic development. The Parkinson's Progression Markers Initiative (PPMI) study is an ongoing international multicenter, prospective study to validate biomarkers in drug-naïve PD patients and matched healthy controls (HC). We quantified cerebrospinal fluid (CSF) alpha-synuclein (α-syn), amyloid-beta1-42 (Aβ1-42), total tau (t-tau), and tau phosphorylated at Thr181 (p-tau) in 660 PPMI subjects at baseline, and correlated these data with measures of the clinical features of these subjects. We found that CSF α-syn, t-tau and p-tau levels, but not Aβ1-42, were significantly lower in PD compared with HC, while the diagnostic value of the individual CSF biomarkers for PD diagnosis was limited due to large overlap. The level of α-syn, but not other biomarkers, was significantly lower in PD patients with non-tremor-dominant phenotype compared with tremor-dominant phenotype. In addition, in PD patients the lowest Aβ1-42, or highest t-tau/Aβ1-42 and t-tau/α-syn quintile in PD patients were associated with more severe non-motor dysfunction compared with the highest or lowest quintiles, respectively. In a multivariate regression model, lower α-syn was significantly associated with worse cognitive test performance. APOE ε4 genotype was associated with lower levels of Aβ1-42, but neither with PD diagnosis nor cognition. Our data suggest that the measurement of CSF biomarkers in early-stage PD patients may relate to disease heterogeneity seen in PD. Longitudinal observations in PPMI subjects are needed to define their prognostic performance.

This study aimed to identify the utility of diffusion tensor imaging (DTI) in measuring the regional distribution of abnormal microstructural progression in patients with Parkinson's disease who were enrolled in the Parkinson's progression marker initiative (PPMI). One hundred and twenty two de-novo PD patients (age = 60.5±9) and 50 healthy controls (age = 60.6±11) had DTI scans at baseline and 12.6±1 months later. Automated image processing included an intra-subject registration of all time points and an inter-subjects registration to a brain atlas. Annualized rates of DTI variations including fractional anisotropy (FA), radial (rD) and axial (aD) diffusivity were estimated in a total of 118 white matter and subcortical regions of interest. A mixed effects model framework was used to determine the degree to which DTI changes differed in PD relative to changes in healthy subjects. Significant DTI changes were also tested for correlations with changes in clinical measures, dopaminergic imaging and CSF biomarkers in PD patients. Compared to normal aging, PD was associated with higher rates of FA reduction, rD and aD increases predominantly in the substantia nigra, midbrain and thalamus. The highest rates of FA reduction involved the substantia nigra (3.6±1.4%/year from baseline, whereas the highest rates of increased diffusivity involved the thalamus (rD: 8.0±2.9%/year, aD: 4.0±1.5%/year). In PD patients, high DTI changes in the substantia nigra correlated with increasing dopaminergic deficits as well as with declining α-synuclein and total tau protein concentrations in cerebrospinal fluid. Increased DTI rates in the thalamus correlated with progressive decline in global cognition in PD. The results suggest that higher rates of regional microstructural degeneration are potential markers of PD progression.

Background: In the last decades, the association of household pesticide usage with Parkinson's disease (PD) has been poorly explored, with discordant results. Based on the Parkinson's Progression Markers Initiative (PPMI) cohort study, we analyzed (1) the association of household pesticide exposure with the development of PD and (2) the effect of household pesticides on progression of PD., Methods: Data from participants of the "FOllow Up persons with Neurologic Disease" (FOUND study) included in the PPMI cohort database were analyzed. The PPMI FOUND study applied the Parkinson's Disease Risk Factor Questionnaire to collect information regarding the use of pesticides in non-work settings during periods of life, and the lifetime pesticide exposure for each participant was estimated. We defined a high use of pesticides if the exposure estimate had a z-score higher than one standard deviation from the mean. Also, we evaluated longitudinal data of people with PD to analyze the effect of high use of household pesticides on disease progression according to motor impairment, cognitive dysfunction, depressive symptoms, and modification of motor clinical phenotype., Results: We analyzed data from 206 people with PD and 64 healthy controls, almost all from the USA. High use of household pesticides was not associated with the odds of developing PD. Regarding PD progression, only cognitive dysfunction was associated with the high use of household fungicides (HR 5.64 per standard deviation increase in exposure estimate, 95% CI 1.41-22.6)., Conclusions: Chronic exposure to household pesticides may impact the clinical progression of PD, especially cognitive symptoms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Santos-Lobato and Schuh.)

UnlabelledThis study was undertaken to determine the prevalence and correlates of cognitive impairment (CI) and neuropsychiatric symptoms (NPS) in early, untreated patients with Parkinson's disease (PD).BackgroundBoth CI and NPS are common in PD and impact disease course and quality of life. However, limited knowledge is available about cognitive abilities and NPS.MethodsParkinson's Progression Markers Initiative (PPMI) is a multi-site study of early, untreated PD patients and healthy controls (HCs), the latter with normal cognition. At baseline, participants were assessed with a neuropsychological battery and for symptoms of depression, anxiety, impulse control disorders (ICDs), psychosis, and apathy.ResultsBaseline data of 423 PD patients and 196 HCs yielded no between-group differences in demographic characteristics. Twenty-two percent of PD patients met the PD-recommended screening cutoff for CI on the Montral Cognitive Assessment (MoCA), but only 9% met detailed neuropsychological testing criteria for mild cognitive impairment (MCI)-level impairment. The PD patients were more depressed than HCs (P

Background: Neurofilament light (NfL) can reflect the extent of neuron/axon damage, thus providing an opportunity to examine the severity and progression of the diseases with such damage. Objective: Whether serum NfL can be used as an indicator to monitor the cognitive progress of de novo Parkinson's disease (PD) remains unclear. Methods: In this research, 144 healthy controls and 301 de novo PD patients from Parkinson's Progression Markers Initiative (PPMI) were recruited. Linear mixed effects models were used to examine the associations of baseline/longitudinal serum NfL with cognitive decline. Cox regression was used to detect cognitive progression in PD participants. Results: We found PD patients had higher serum NfL than controls at baseline (p = 0.031), and NfL increase was faster in PD group (p < 0.001). Both baseline serum NfL and its rate of change predicted measurable cognitive decline in early PD (MoCA, β= –0.014, p < 0.001; β= –0.002, p < 0.001, respectively). Additionally, we observed that NfL levels were also able to predict progression in different diagnostic groups and Amyloid- PD and Amyloid+PD groups. After an average follow-up of 6.37±1.84 years, the baseline NfL of the third tertile of high concentrations was associated with a future high risk of PD dementia (adjusted HR 6.33, 95% CI 2.62–15.29, p < 0.001). Conclusion: In conclusion, our results indicated that the serum NfL concentration could function as an easily accessible biomarker to monitor the severity and progression of cognitive decline in PD. [ABSTRACT FROM AUTHOR]

Background: Previous studies have highlighted serum uric acid as a putative idiopathic Parkinson's disease (iPD) biomarker. Only one study, so far, showed higher levels of serum uric acid in leucine-rich repeat kinase 2 (LRRK + 2) carriers compared to those who developed PD, however a longitudinal comparison between LRRK2 + PD and healthy controls (HC) has not been performed. Objective: The aim of this study was to determine whether there are longitudinal differences in serum uric acid between iPD, LRRK2 + PD and HC and their association with motor and non-motor features. Methods: Longitudinal data of uric acid of 282 de novo iPD, 144 LRRK2 + PD patients, and 195 age-matched HC were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. We also used longitudinal Montreal Cognitive Assessment (MoCA), Movement Disorder Society–Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III), Geriatric Depression Scale (GDS) scores, and DaTSCAN striatal binding ratios (SBRs). Results: Longitudinal uric acid measurements were significantly lower in LRRK2 + PD patients compared to HC up to 5 years follow-up. There was no significant impact or correlation of adjusted or unadjusted uric acid levels with MoCA, MDS-UPDRS III, or GDS scores, the presence of RBD or DAT-SCAN SBRs. Conclusion: LRRK2 + PD group had significantly lower uric acid concentrations compared to HC after adjusting for age, sex and baseline BMI up to 5 years follow-up. There were no significant associations between uric acid levels and indices of disease severity. These findings identify serum uric acid as a marker linked to LRRK2 + PD. [ABSTRACT FROM AUTHOR]

Background: The substantial heterogeneity of clinical symptoms and lack of reliable progression markers in Parkinson's disease (PD) present a major challenge in predicting accurate progression and prognoses. Increasing evidence indicates that each component of the neurovascular unit (NVU) and blood-brain barrier (BBB) disruption may take part in many neurodegenerative diseases. Since some portions of CSF are eliminated along the neurovascular unit and across the BBB, disturbing the pathways may result in changes of these substances.Methods: Four hundred seventy-four participants from the Parkinson's Progression Markers Initiative (PPMI) study (NCT01141023) were included in the study. Thirty-six initial features, including general information, brief clinical characteristics and the current year's classical scale scores, were used to build five regression models to predict PD motor progression represented by the coming year's Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III score after redundancy removal and recursive feature elimination (RFE)-based feature selection. Then, a threshold range was added to the predicted value for more convenient model application. Finally, we evaluated the CSF and blood biomarkers' influence on the disease progression model.Results: Eight hundred forty-nine cases were included in the study. The adjusted R2 values of three different categories of regression model, linear, Bayesian and ensemble, all reached 0.75. Models of the same category shared similar feature combinations. The common features selected among the categories were the MDS-UPDRS Part III score, Montreal Cognitive Assessment (MOCA) and Rapid Eye Movement Sleep Behavior Disorder Questionnaire (RBDSQ) score. It can be seen more intuitively that the model can achieve certain prediction effect through threshold range. Biomarkers had no significant impact on the progression model within the data in the study.Conclusions: By using machine learning and routinely gathered assessments from the current year, we developed multiple dynamic models to predict the following year's motor progression in the early stage of PD. These methods will allow clinicians to tailor medical management to the individual and identify at-risk patients for future clinical trials examining disease-modifying therapies.

Introduction: Up to 40% of Parkinson’s disease patients taking dopamine agonist medication develop impulse control behaviors which can have severe negative consequences. The current study aimed to utilize dopamine genetics to identify patients most at risk of developing these behaviors. Methods: Demographic, clinical, and genetic data were obtained from the Parkinson’s Progression Markers Initiative for de novo patients (n = 327), patients taking dopamine agonists (n = 146), and healthy controls (n = 160). Impulsive behaviors were identified using the Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease. A dopamine genetic risk score was calculated for each patient according to polymorphisms in genes coding for dopamine D1, D2 and D3 receptors, and catechol-O-methyltransferase. A higher score reflected higher central dopamine neurotransmission. Results: Patients on agonists with a low dopamine genetic risk score were over 18 times more likely to have an impulsive behavior compared to higher scores (p = 0.04). The 38% of patients taking agonists who had at least one impulsive behavior were more likely to be male and report higher Unified Parkinson’s Disease Rating Scale I&II scores. With increasing time on dopamine agonists (range 92–2283 days, mean 798 ± 565 standard deviation), only patients with a high dopamine genetic risk score showed an increase in number of impulsive behaviors (p = 0.033). Predictive effects of the gene score were not present in de novo or healthy control. Conclusions: A dopamine genetic risk score can identify patients most at risk of developing impulsive behaviors on dopamine agonist medication and predict how these behaviors may worsen over time.

ImportanceWe observed a significant correlation between cerebrospinal fluid (CSF) levels of tau proteins and α-synuclein, but not β-amyloid 1-42 (Aβ1-42), and lower concentration of CSF biomarkers, as compared with healthy controls, in a cohort of entirely untreated patients with Parkinson disease (PD) at the earliest stage of the disease studied so far.ObjectiveTo evaluate the baseline characteristics and relationship to clinical features of CSF biomarkers (Aβ1-42, total tau [T-tau], tau phosphorylated at threonine 181 [P-tau181], and α-synuclein) in drug-naive patients with early PD and demographically matched healthy controls enrolled in the Parkinson's Progression Markers Initiative (PPMI) study.Design, setting, and participantsCross-sectional study of the initial 102 research volunteers (63 patients with PD and 39 healthy controls) of the PPMI cohort.Main outcomes and measuresThe CSF biomarkers were measured by INNO-BIA AlzBio3 immunoassay (Aβ1-42, T-tau, and P-tau181; Innogenetics Inc) or by enzyme-linked immunosorbent assay (α-synuclein). Clinical features including diagnosis, demographic characteristics, motor, neuropsychiatric, and cognitive assessments, and DaTscan were systematically assessed according to the PPMI study protocol.ResultsSlightly, but significantly, lower levels of Aβ1-42, T-tau, P-tau181, α-synuclein, and T-tau/Aβ1-42 were seen in subjects with PD compared with healthy controls but with a marked overlap between groups. Using multivariate regression analysis, we found that lower Aβ1-42 and P-tau181 levels were associated with PD diagnosis and that decreased CSF T-tau and α-synuclein were associated with increased motor severity. Notably, when we classified patients with PD by their motor phenotypes, lower CSF Aβ1-42 and P-tau181 concentrations were associated with the postural instability-gait disturbance-dominant phenotype but not with the tremor-dominant or intermediate phenotype. Finally, we found a significant correlation of the levels of α-synuclein with the levels of T-tau and P-tau181.Conclusions and relevanceIn this first report of CSF biomarkers in PPMI study subjects,we found that measures of CSF Aβ1-42, T-tau, P-tau181, and α-synuclein have prognostic and diagnostic potential in early-stage PD. Further investigations using the entire PPMI cohort will test the predictive performance of CSF biomarkers for PD progression

Background: The substantial heterogeneity of clinical symptoms and lack of reliable progression markers in Parkinson's disease (PD) present a major challenge in predicting accurate progression and prognoses. Increasing evidence indicates that each component of the neurovascular unit (NVU) and blood-brain barrier (BBB) disruption may take part in many neurodegenerative diseases. Since some portions of CSF are eliminated along the neurovascular unit and across the BBB, disturbing the pathways may result in changes of these substances. Methods: Four hundred seventy-four participants from the Parkinson's Progression Markers Initiative (PPMI) study (NCT01141023) were included in the study. Thirty-six initial features, including general information, brief clinical characteristics and the current year's classical scale scores, were used to build five regression models to predict PD motor progression represented by the coming year's Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III score after redundancy removal and recursive feature elimination (RFE)-based feature selection. Then, a threshold range was added to the predicted value for more convenient model application. Finally, we evaluated the CSF and blood biomarkers' influence on the disease progression model. Results: Eight hundred forty-nine cases were included in the study. The adjusted R 2 values of three different categories of regression model, linear, Bayesian and ensemble, all reached 0.75. Models of the same category shared similar feature combinations. The common features selected among the categories were the MDS-UPDRS Part III score, Montreal Cognitive Assessment (MOCA) and Rapid Eye Movement Sleep Behavior Disorder Questionnaire (RBDSQ) score. It can be seen more intuitively that the model can achieve certain prediction effect through threshold range. Biomarkers had no significant impact on the progression model within the data in the study. Conclusions: By using machine learning and routinely gathered assessments from the current year, we developed multiple dynamic models to predict the following year's motor progression in the early stage of PD. These methods will allow clinicians to tailor medical management to the individual and identify at-risk patients for future clinical trials examining disease-modifying therapies. [ABSTRACT FROM AUTHOR]

Background: The association between body mass index (BMI) and rapid eye-movement (REM) sleep-related behavioral disorder (RBD) in Parkinson's disease (PD) remains unknown. Our study was to investigate the association of BMI with RBD in PD patients., Methods: In this cross-sectional study, a total of 1,115 PD participants were enrolled from Parkinson's Progression Markers Initiative (PPMI) database. BMI was calculated as weight divided by height squared. RBD was defined as the RBD questionnaire (RBDSQ) score with the cutoff of 5 or more assessed. Univariable and multivariable logistic regression models were performed to examine the associations between BMI and the prevalence of RBD. Non-linear correlations were explored with use of restricted cubic spline (RCS) analysis. And the inflection point was determined by the two-line piecewise linear models., Results: We identified 426 (38.2%) RBD. The proportion of underweight, normal, overweight and obese was 2.61, 36.59, 40.36, and 20.44%, respectively. In the multivariate logistic regression model with full adjustment for confounding variables, obese individuals had an odds ratio of 1.77 (95% confidence interval: 1.21 to 2.59) with RBD compared with those of normal weight. In the RCS models with three knots, BMI showed a non-linear association with RBD. The turning points of BMI estimated from piecewise linear models were of 28.16 kg/m 2 , 28.10 kg/m 2 , and 28.23 kg/m 2 derived from univariable and multivariable adjusted logistic regression models. The effect modification by depression on the association between BMI and RBD in PD was also found in this study. Furthermore, the sensitivity analyses linked with cognition, education, and ethnic groups indicated the robustness of our results., Conclusion: The current study found a significant dose-response association between BMI and RBD with a depression-based difference in the impact of BMI on RBD in PD patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Gu, Yuan, Yin, Li, Wang, Gu, Xu, Gao, Wu, Hu, Yuan, Cao and Ye.)

We investigated patient and clinician impressions of cognitive impairment and whether they correlated with objective measures of cognitive impairment. Cognitive categorization, neuropsychological assessment scores, and Montreal Cognitive Assessment scores were documented at baseline, 3 years, and 7 years for 388 PD patients in the Parkinson's Progression Markers Initiative (PPMI). We found that both patient and clinician impressions of cognitive decline were significantly associated with gold-standard criteria for cognitive impairment to a similar degree. Both patient and clinician perspectives should be considered in determining cognitive status and should be followed up with diagnostic testing. [ABSTRACT FROM AUTHOR]

Background: Levodopa-induced dyskinesia (LID) is a major complication of dopamine replacement drug usage in Parkinson's disease (PD) patients. Since the mechanism of LID is yet unclear, we analyzed serial [I-123] N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl) nortropane (I-123 FP-CIT) single photon emission computed tomography (SPECT) images. We investigated the changes of dopaminergic innervation during the progression of PD in relation to the development of LID.Methods: Data were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. Two hundred and ninety PD dopamine replacement drug-naïve patients (age 61.0 ± 9.7, M: F = 195: 95) were enrolled. I-123 FP-CIT SPECT images from baseline, 12, 24, and 48 months were analyzed among with clinical factors. specific binding ratios (SBRs) of the striatal regions from I-123 FP-CIT SPECT images were analyzed. We used independent tests and logistic regression for analysis of LID risk association.Results: Among 290 patients, 36 patients developed LID after 48 months follow-up. Baseline MDS-UPDRS Part II and III scores were significantly higher in the PD patients with LID, compared with the PD patients without LID. Striatal SBRs were significantly lower in the PD patients with LID at baseline, 24 and 48 months (p < 0.001). Multivariate analysis revealed MDS-UPDRS Part II and putaminal SBRs at baseline and 24 months to be significantly associated with the development of LID (p < 0.001). Also, patients who developed LID at 48 months had a higher decrease rate of putaminal SBR at the 24 months (p < 0.05), and 48 months (p < 0.01) period.Conclusion: In this study, we demonstrated the serial changes of the nigrostriatal dopaminergic innervation in relationship to LID development for the first time. The deterioration rate of dopaminergic innervation was significantly higher in the PD patients who developed LID, compared with the PD patients who did not develop LID. Serial follow up I-123 FP-CIT SPECT acquisition during the course of PD could be helpful in predicting the development of LID.

Background: Depression is a common comorbidity of Parkinson’s disease (PD); however, the impact of antidepressant status on cortical function in parkinsonian depression is not fully understood. While studies of resting state functional MRI in major depression have shown that antidepressant treatment affects cortical connectivity, data on connectivity and antidepressant status in PD is sparse. Objective: We tested the hypothesis that cortico-limbic network (CLN) resting state connectivity is abnormal in antidepressant-treated parkinsonian depression. Methods: Thirteen antidepressant-treated depressed PD and 47 non-depressed PD participants from the Parkinson’s Progression Markers Initiative (PPMI) database were included. Data was collected using 3T Siemens TIM Trio MR scanners and analyzed using SPM and CONN functional connectivity toolbox. Volumetric analysis was also performed using BrainSuite. Results: We found decreased connectivity in the antidepressant-treated depressed PD group when compared to non-depressed PD between the left frontal operculum and bilateral insula, and also reduced connectivity between right orbitofrontal cortex and left temporal fusiform structures. Increased depression scores were associated with decreased insular-frontal opercular connectivity. No ROI volumetric differences were found between groups. Conclusion: Given the relationship between depression scores and cortico-limbic connectivity in PD, the abnormal insular-frontal opercular hypoconnectivity in this cohort may be associated with persistent depressive symptoms or antidepressant effects. [ABSTRACT FROM AUTHOR]

Background and purpose: Constipation is a common non‐motor symptom of Parkinson's disease (PD). Deposition of α‐synuclein inclusions that spread from the gut to the substantia nigra through the vagus nerve has recently been speculated to be a pre‐motor and early stage of PD. The aim of the study was to investigate whether constipation is associated with dopaminergic pathology on dopamine transporter (DAT) single‐photon emission computed tomography in early drug‐naïve patients with PD. Our hypothesis was that constipation is associated with other signs of pre‐motor PD and is independent of DAT pathology. We then investigated for associations with motor and non‐motor symptoms, and with cerebrospinal fluid biomarkers of PD pathology. Methods: Using the Parkinson's Progression Markers Initiative database, we investigated the prevalence of constipation and the association between constipation and clinical features, striatal [123I]Ioflupane uptake and non‐imaging (cerebrospinal fluid and serum) biomarkers. Constipation was evaluated using Movement Disorder Society‐Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS‐UPDRS) Part I item 1.11. Results: One third (132/398) of de‐novo patients with PD had constipation. Higher severity of constipation correlated with older age (r = 0.728, P < 0.001), higher MDS‐UPDRS total score (r = 0.285, P < 0.001), worse postural instability (r = 0.190, P = 0.012), rapid eye movement sleep behaviour disorder (r = 0.228, P < 0.0001) and depression (r = 0.187, P = 0.024). No correlation was found with cerebrospinal fluid, serum and imaging markers of PD pathology. Conclusions: Constipation was not associated with DAT pathology but with rapid eye movement sleep behaviour disorder and depression, which are speculated to be pre‐motor symptoms of PD. This confirms the hypothesis that constipation may be a pre‐motor sign of PD due to an impairment of non‐dopaminergic pathways. [ABSTRACT FROM AUTHOR]

Background: Neurofilament light chain protein (NfL) in cerebrospinal fluid (CSF) reflects the severity of neurodegeneration, with its altered concentrations discovered in Parkinson's disease (PD) and Parkinson's disease dementia (PD-D)., Objective: To determine whether CSF NfL, a promising biomarker of neuronal/axonal damage, can be used to monitor cognitive progression in de novo Parkinson's disease and predict future cognitive decline., Methods: A total of 259 people were recruited in this study, including 85 healthy controls (HC) and 174 neonatal PD patients from the Parkinson's Progression Markers Initiative (PPMI). Multiple linear regression and linear mixed effects models were used to examine the associations of baseline/longitudinal CSF NfL with cognitive decline and other CSF biomarkers. Kaplan-Meier analysis and log-rank test were used to compare the cumulative probability risk of cognition progression during the follow-up. Multivariate cox regression was used to detect cognitive progression in de novo PD., Results: We found PD patients with mild cognitive impairment (PD-MCI) was higher than with normal cognition (PD-NC) in terms of CSF NfL baseline levels ( p  = 0.003) and longitudinal increase rate ( p  = 0.034). Both baseline CSF NfL and its rate of change predicted measurable cognitive decline in de novo PD (MoCA, β  = -0.010, p  = 0.011; β  = -0.0002, p  < 0.001, respectively). The predictive effects in de novo PD patients aged >65, male, ill-educated (<13 years) and without carrying Apolipoprotein E ε4 ( APOE ε4 ) seemed to be more obvious and reflected in more domains investigated. We also observed that CSF NfL levels predicted progression in de novo PD patients with different cognitive diagnosis and amyloid status. After an average follow-up of 6.66 ± 2.54 years, higher concentration above the median of baseline CSF NfL was associated with a future high risk of PD with dementia (adjusted HR 2.82, 95% CI: 1.11-7.20, p  = 0.030)., Conclusion: Our results indicated that CSF NfL is a promising prognostic predictor of PD, and its concentration and dynamics can monitor the severity and progression of cognitive decline in de novo PD patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sheng, Ma, Liu, Ou, Zhao, Ma and Tan.)

The pathophysiology of Parkinson's disease (PD) is a complex process of the interaction between genetic and environmental factors. Studies on the genetic component of PD have predominantly focused on single nucleotide polymorphisms (SNPs) using a cross-sectional case-control design in large genome-wide association studies. This approach while giving insight into a significant portion of the genetics of PD does not fully account for all the genetic components resulting in missing heritability. In this study, we approached this problem by focusing on the non-reference genome transposable elements (TEs) and their impact on the progression of PD using a longitudinal study design within the Parkinson's progression markers initiative (PPMI) cohort. We analyzed 2886 Alu repeats, 360 LINE1 and 128 SINE-VNTR-Alus (SVAs) that were called from the whole-genome sequence data which are not within the reference genome. The presence or absence of these non-reference TE variants is known as a retrotransposon insertion polymorphism, and measuring this polymorphism describes the impact of TEs on the traits. The variations for the presence or absence of the non-reference TE elements were modeled to align with the changes in the 114 outcome measures during the five-year follow-up period of the PPMI cohort. Linear mixed-effects models were used, and many TEs were found to have a highly significant effect on the longitudinal changes in the clinically important PD outcomes such as UPDRS subscale II, UPDRS total scores, and modified Schwab and England ADL scale. In addition, the progression of several imaging and functional measures, including the Caudate/Putamen ratio and levodopa equivalent daily dose (LEDD) were also significantly affected by the TEs. In conclusion, this study identified the overwhelming effect of the non-reference TEs on the progression of PD and is a good example of the impact the variations in the "junk DNA" have on complex diseases.

Introduction: Up to 40% of Parkinson's disease patients taking dopamine agonist medication develop impulse control behaviors which can have severe negative consequences. The current study aimed to utilize dopamine genetics to identify patients most at risk of developing these behaviors., Methods: Demographic, clinical, and genetic data were obtained from the Parkinson's Progression Markers Initiative for de novo patients (n = 327), patients taking dopamine agonists (n = 146), and healthy controls (n = 160). Impulsive behaviors were identified using the Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease. A dopamine genetic risk score was calculated for each patient according to polymorphisms in genes coding for dopamine D1, D2 and D3 receptors, and catechol-O-methyltransferase. A higher score reflected higher central dopamine neurotransmission., Results: Patients on agonists with a low dopamine genetic risk score were over 18 times more likely to have an impulsive behavior compared to higher scores (p = 0.04). The 38% of patients taking agonists who had at least one impulsive behavior were more likely to be male and report higher Unified Parkinson's Disease Rating Scale I&II scores. With increasing time on dopamine agonists (range 92-2283 days, mean 798 ± 565 standard deviation), only patients with a high dopamine genetic risk score showed an increase in number of impulsive behaviors (p = 0.033). Predictive effects of the gene score were not present in de novo or healthy control., Conclusions: A dopamine genetic risk score can identify patients most at risk of developing impulsive behaviors on dopamine agonist medication and predict how these behaviors may worsen over time., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

Background: Levodopa-induced dyskinesia (LID) is a major complication of dopamine replacement drug usage in Parkinson's disease (PD) patients. Since the mechanism of LID is yet unclear, we analyzed serial [I-123] N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl) nortropane (I-123 FP-CIT) single photon emission computed tomography (SPECT) images. We investigated the changes of dopaminergic innervation during the progression of PD in relation to the development of LID. Methods: Data were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. Two hundred and ninety PD dopamine replacement drug-naïve patients (age 61.0 ± 9.7, M: F = 195: 95) were enrolled. I-123 FP-CIT SPECT images from baseline, 12, 24, and 48 months were analyzed among with clinical factors. specific binding ratios (SBRs) of the striatal regions from I-123 FP-CIT SPECT images were analyzed. We used independent tests and logistic regression for analysis of LID risk association. Results: Among 290 patients, 36 patients developed LID after 48 months follow-up. Baseline MDS-UPDRS Part II and III scores were significantly higher in the PD patients with LID, compared with the PD patients without LID. Striatal SBRs were significantly lower in the PD patients with LID at baseline, 24 and 48 months ( p < 0.001). Multivariate analysis revealed MDS-UPDRS Part II and putaminal SBRs at baseline and 24 months to be significantly associated with the development of LID ( p < 0.001). Also, patients who developed LID at 48 months had a higher decrease rate of putaminal SBR at the 24 months ( p < 0.05), and 48 months ( p < 0.01) period. Conclusion: In this study, we demonstrated the serial changes of the nigrostriatal dopaminergic innervation in relationship to LID development for the first time. The deterioration rate of dopaminergic innervation was significantly higher in the PD patients who developed LID, compared with the PD patients who did not develop LID. Serial follow up I-123 FP-CIT SPECT acquisition during the course of PD could be helpful in predicting the development of LID.

Background: Parkinson's disease (PD) can be classified into tremor dominant (TD) and postural instability and gait difficulty (PIGD) subtypes with TD considered as the benign subtype. The neural alterations of the 2 subtypes in the early stages before administration of medications remain elusive., Objective: This study assessed the subtype-related white matter (WM) microstructural features in newly diagnosed and drug-naive PD patients from the Parkinson's Progression Markers Initiative (PPMI)., Methods: Sixty-five early PDs with stable subtypes (52 TD and 13 PIGD patients) and 61 controls underwent diffusion tensor imaging (DTI) scanning and clinical assessment. Tract-based special statistics (TBSS), graph-theoretical and network-based analyses were used to compare WM regional and network features between groups., Results: No differences in disease stages and duration were found between the 2 patient groups. TD patients showed increased fractional anisotropy (FA), but decreased radial and axial diffusivities (RD and AD) in several projection, association, and commissural tracts, compared with PIGD patients and controls. Motor severity had mild-to-moderate correlations with FA and RD of the corpus callosum (genu) in TD, but strong correlations with FA and RD of multiple association tracts in PIGD. Conversely, no significant network changes were noted., Conclusions: TD patients showed regionally increased FA but decreased diffusivities, implying neural reorganization to compensate PD pathology in early stages. PIGD patients, despite having similar disease stages and duration, exhibited more WM degradation. These results demonstrate differential WM regional features between the 2 subtypes in early PD and support the notion of TD being a benign subtype.