scholarly journals Sex-Related Longitudinal Change of Motor, Non-Motor, and Biological Features in Early Parkinson’s Disease

2021 ◽  
pp. 1-16
Author(s):  
Marina Picillo ◽  
David-Erick LaFontant ◽  
Susan Bressman ◽  
Chelsea Caspell-Garcia ◽  
Christopher Coffey ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
De Novo ◽  
Longitudinal Change ◽  
Csf Biomarkers ◽  
Longitudinal Changes ◽  
Multiplicative Factor ◽  
Progression Markers ◽  
And Biological Markers ◽  
Updrs Part

Background: Investigation of sex-related motor and non-motor differences and biological markers in Parkinson’s disease (PD) may improve precision medicine approach. Objective: To examine sex-related longitudinal changes in motor and non-motor features and biologic biomarkers in early PD. Methods: We 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. Results: Men experienced greater longitudinal decline in self-reported motor (p <  0.001) and non-motor (p = 0.009) aspects of experiences of daily living, such that men had a yearly increase in MDS-UPDRS part II by a multiplicative factor of 1.27 compared to women at 0.7, while men had a yearly increase in MDS-UPDRS part I by a multiplicative factor of 0.98, compared to women at 0.67. Compared to women, men had more longitudinal progression in clinician-assessed motor features in the ON medication state (p = 0.010) and required higher dopaminergic medication dosages over time (p = 0.014). Time to reach specific disease milestones and longitudinal changes in CSF biomarkers and DaTscanTM uptake were not different by sex. Conclusion: Men showed higher self-assessed motor and non-motor burden of disease, with possible contributions from suboptimal dopaminergic therapeutic response in men. However, motor features of disease evaluated with clinician-based scales in the OFF medication state, as well as biological biomarkers do not show specific sex-related progression patterns.

scholarly journals Predicting the onset of freezing of gait in de novo Parkinson’s disease

2021 ◽  
Author(s):  
Fengting Wang ◽  
Yixin Pan ◽  
Miao Zhang ◽  
Kejia Hu
Keyword(s):  
Risk Factors ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
De Novo ◽  
Freezing Of Gait ◽  
Poor Quality ◽  
Csf Biomarkers ◽  
Genetic Characteristics ◽  
Progression Markers ◽  
Independent Risk Factors

AbstractFreezing of gait (FoG) is a debilitating symptom of Parkinson’s disease (PD) related to higher risks of falls and poor quality of life. In this study, we predicted the onset of FoG in PD patients using a battery of risk factors from patients enrolled in the Parkinson’s Progression Markers Initiative (PPMI) cohort. The endpoint was the presence of FoG, which was assessed every year during the five-year follow-up visit. Overall, 212 PD patients were included in analysis. Seventy patients (33.0%) developed FoG during the visit (pre-FoG group). Age, bradykinesia, TD/PIGD classification, fatigue, cognitive impairment, impaired autonomic functions and sleep disorder were found to be significantly different in patients from pre-FoG and non-FoG groups at baseline. The logistic regression model showed that motor factors such as TD/PIGD classification (OR = 2.67, 95% CI = 1.41-5.09), MDS-UPDRS part III score (OR = 1.05, 95% CI = 1.01-1.09) were associated with FoG occurrence. Several indicators representing non-motor symptoms such as SDMT total score (OR = 0.95, 95% CI = 0.91-0.98), HVLT immediate/Total recall (OR = 0.91, 95% CI = 0.86-0.97), MOCA (OR = 0.87, 95% CI = 0.76-0.99), Epworth Sleepiness Scale (OR = 1.13, 95% CI = 1.03-1.24), fatigue(OR = 1.98, 95% CI = 1.32-3.06), SCOPA-AUT gastrointestinal score (OR = 1.27, 95% CI = 1.09-1.49) and SCOPA-AUT urinary score (OR = 1.18, 95% CI = 1.06-1.32) were found to have the predictive value. PD patients that developed FoG showed a significant reduction of DAT uptake in the striatum. However, no difference at baseline was observed in genetic characteristics and CSF biomarkers between the two patient sets. Our model indicated that TD/PIGD classification, MDS-UPDRS total score, and Symbol Digit Modalities score were independent risk factors for the onset of FoG in PD patients. In conclusion, the combination of motor and non-motor features including the akinetic subtype and poor cognitive functions should be considered in identifying PD patients with high risks of FoG onset.

Longitudinal Change and Progression Indicators Using the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale in Two Independent Cohorts with Early Parkinson’s Disease

2021 ◽  
pp. 1-16
Author(s):  
Michael Bartl ◽  
Mohammed Dakna ◽  
Sebastian Schade ◽  
Tamara Wicke ◽  
Elisabeth Lang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Trials ◽  
Rating Scale ◽  
De Novo ◽  
Longitudinal Change ◽  
Single Center ◽  
Square Roots ◽  
Disease Rating

Background: The MDS-Unified Parkinson’s disease (PD) Rating Scale (MDS-UPDRS) is the most used scale in clinical trials. Little is known about the predictive potential of its single items. Objective: To systematically dissect MDS-UPDRS to predict PD progression. Methods: 574 de novo PD patients and 305 healthy controls were investigated at baseline (BL) in the single-center DeNoPa (6-year follow-up) and multi-center PPMI (8-year follow-up) cohorts. We calculated cumulative link mixed models of single MDS-UPDRS items for odds ratios (OR) for class change within the scale. Models were adjusted for age, sex, time, and levodopa equivalent daily dose. Annual change and progression of the square roots of the MDS-UDPRS subscores and Total Score were estimated by linear mixed modeling. Results: Baseline demographics revealed more common tremor dominant subtype in DeNoPa and postural instability and gait disorders-subtype and multiethnicity in PPMI. Subscore progression estimates were higher in PPMI but showed similar slopes and progression in both cohorts. Increased ORs for faster progression were found from BL subscores I and II (activities of daily living; ADL) most marked for subscore III (rigidity of neck/lower extremities, agility of the legs, gait, hands, and global spontaneity of movements). Tremor items showed low ORs/negative values. Conclusion: Higher scores at baseline for ADL, freezing, and rigidity were predictors of faster deterioration in both cohorts. Precision and predictability of the MDS-UPDRS were higher in the single-center setting, indicating the need for rigorous training and/or video documentation to improve its use in multi-center cohorts, for example, clinical trials.

Cortical Thinning Associated with Age and CSF Biomarkers in Early Parkinson’s Disease Is Modified by the SNCA rs356181 Polymorphism

2018 ◽  
Vol 18 (5-6) ◽  
pp. 233-238
Author(s):  
Frederic Sampedro ◽  
Juan Marín-Lahoz ◽  
Saul Martínez-Horta ◽  
Javier Pagonabarraga ◽  
Jaime Kulisevsky
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Decline ◽  
De Novo ◽  
Brain Regions ◽  
Cortical Atrophy ◽  
Csf Biomarkers ◽  
Gene Encoding ◽  
Cortical Thinning ◽  
Age Related

The role of cerebrospinal fluid (CSF) biomarkers such as CSF α-synuclein and CSF tau in predicting cognitive decline in Parkinson’s disease (PD) continues to be inconsistent. Here, using a cohort of de novo PD patients with preserved cognition from the Parkinson’s Progression Markers Initiative (PPMI), we show that the SNCA rs356181 single nucleotide polymorphism (SNP) modulates the effect of these CSF biomarkers on cortical thinning. Depending on this SNP’s genotype, cortical atrophy was associated with either higher or lower CSF biomarker levels. Additionally, this SNP modified age-related atrophy. Importantly, the integrity of the brain regions where this phenomenon was observed correlated with cognitive measures. These results suggest that this genetic variation of the gene encoding the α-synuclein protein, known to be involved in the development of PD, also interferes in its subsequent neurodegeneration. Overall, our findings could shed light on the so far incongruent association of common CSF biomarkers with cognitive decline in PD.

scholarly journals Sex Differences in Cognitive Changes in De Novo Parkinson’s Disease

2019 ◽  
Vol 26 (2) ◽  
pp. 241-249 ◽  
Author(s):  
Ece Bayram ◽  
Sarah J. Banks ◽  
Guogen Shan ◽  
Nikki Kaplan ◽  
Jessica Z.K. Caldwell
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Sex Differences ◽  
Verbal Memory ◽  
Healthy Aging ◽  
De Novo ◽  
Cognitive Changes ◽  
Progression Markers ◽  
Cognitively Intact

AbstractObjective:To evaluate the sex differences in cognitive course over 4 years in Parkinson’s disease (PD) patients with and without mild cognitive impairment (MCI) compared to controls.Methods:Four-year longitudinal cognitive scores of 257 cognitively intact PD, 167 PD-MCI, and 140 controls from the Parkinson’s Progression Markers Initiative were included. Longitudinal scores of men and women, and PD with and without MCI were compared.Results:Women had better verbal memory, men had better visuospatial function. There was no interaction between sex, diagnostic group, and/or time (4-year follow-up period).Conclusions:Sex differences in cognitive course in de novo PD are similar to healthy aging. Cognitive decline rates in PD with and without MCI are similar for the first 4 years of PD.

scholarly journals Baseline prevalence and longitudinal evolution of non-motor symptoms in early Parkinson’s disease: the PPMI cohort

2017 ◽  
Vol 89 (1) ◽  
pp. 78-88 ◽  
Author(s):  
Tanya Simuni ◽  
Chelsea Caspell-Garcia ◽  
Christopher S Coffey ◽  
Daniel Weintraub ◽  
Brit Mollenhauer ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Rating Scale ◽  
De Novo ◽  
Controlled Study ◽  
Motor Symptoms ◽  
Biological Variables ◽  
Significant Difference ◽  
Non Motor Symptoms ◽  
Updrs Part

ObjectiveTo examine the baseline prevalence and longitudinal evolution in non-motor symptoms (NMS) in a prospective cohort of, at baseline, patients with de novo Parkinson’s disease (PD) compared with healthy controls (HC).MethodsParkinson’s Progression Markers Initiative (PPMI) is a longitudinal, ongoing, controlled study of de novo PD participants and HC. NMS were rated using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part I score and other validated NMS scales at baseline and after 2 years. Biological variables included cerebrospinal fluid (CSF) markers and dopamine transporter imaging.Results423 PD subjects and 196 HC were enrolled and followed for 2 years. MDS-UPDRS Part I total mean (SD) scores increased from baseline 5.6 (4.1) to 7.7 (5.0) at year 2 in PD subjects (p<0.001) versus from 2.9 (3.0) to 3.2 (3.0) in HC (p=0.38), with a significant difference between the groups (p<0.001). In the multivariate analysis, higher baseline NMS score was associated with female sex (p=0.008), higher baseline MDS-UPDRS Part II scores (p<0.001) and more severe motor phenotype (p=0.007). Longitudinal increase in NMS severity was associated with the older age (0.008) and lower CSF Aβ1–42 (0.005) at baseline. There was no association with the dose or class of dopaminergic therapy.ConclusionsThis study of NMS in early PD identified clinical and biological variables associated with both baseline burden and predictors of progression. The association of a greater longitudinal increase in NMS with lower baseline Aβ1–42 level is an important finding that will have to be replicated in other cohorts.Trial registrationClinicalTrials.gov identifier: NCT01141023.

scholarly journals Network structure of brain atrophy in de novo Parkinson's disease

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Yashar Zeighami ◽  
Miguel Ulla ◽  
Yasser Iturria-Medina ◽  
Mahsa Dadar ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Medial Temporal Lobe ◽  
Healthy Aging ◽  
De Novo ◽  
Progression Markers ◽  
Magnetic Resonance Imaging Mri ◽  
Cortical Regions ◽  
Clinical Measures ◽  
Deformation Based Morphometry

We mapped the distribution of atrophy in Parkinson's disease (PD) using magnetic resonance imaging (MRI) and clinical data from 232 PD patients and 117 controls from the Parkinson's Progression Markers Initiative. Deformation-based morphometry and independent component analysis identified PD-specific atrophy in the midbrain, basal ganglia, basal forebrain, medial temporal lobe, and discrete cortical regions. The degree of atrophy reflected clinical measures of disease severity. The spatial pattern of atrophy demonstrated overlap with intrinsic networks present in healthy brain, as derived from functional MRI. Moreover, the degree of atrophy in each brain region reflected its functional and anatomical proximity to a presumed disease epicenter in the substantia nigra, compatible with a trans-neuronal spread of the disease. These results support a network-spread mechanism in PD. Finally, the atrophy pattern in PD was also seen in healthy aging, where it also correlated with the loss of striatal dopaminergic innervation.

scholarly journals Longitudinal Change of Clinical and Biological Measures in Early Parkinson's Disease: Parkinson's Progression Markers Initiative Cohort

2018 ◽  
Vol 33 (5) ◽  
pp. 771-782 ◽  
Author(s):  
Tanya Simuni ◽  
Andrew Siderowf ◽  
Shirley Lasch ◽  
Chris S. Coffey ◽  
Chelsea Caspell-Garcia ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Longitudinal Change ◽  
Progression Markers ◽  
Early Parkinson’S Disease

scholarly journals P.015 Long-term progression and prognosis in different subtypes of Parkinson’s disease: validation of a new multi-domain subtyping method

2019 ◽  
Vol 46 (s1) ◽  
pp. S17
Author(s):  
S Fereshtehnejad ◽  
Y Zeighami ◽  
A Dagher ◽  
RB Postuma
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
De Novo ◽  
Early Stage ◽  
Real Life ◽  
Clinical Manifestations ◽  
Personalized Care ◽  
Autonomic Disturbance ◽  
Progression Markers

Background: Parkinson’s disease (PD) varies in clinical manifestations and course of progression from person to person. Identification of distinct PD subtypes is of great priority to develop personalized care approaches. We aimed to compare long-term progression and prognosis between different PD subtypes. Methods: Data on 421 individuals with de novo early-onset PD was retrieved from Parkinson’s Progression Markers Initiative (PPMI). Using a newly developed multi-domain subtyping method (based on motor phenotype, RBD, autonomic disturbance, early cognitive deficit), we divided PD population into three subtypes at baseline: “mild motor-predominant”, “Diffuse malignant” and “Intermediate”. Rate of global progression (mixed motor and non-motor features) and developing dementia were compared between the subtypes. Results: Patients with “diffuse malignant” PD experienced 0.5 z-score further worsening of global composite outcome (p=0.017) and 2.2 further decline in MOCA score (p=0.001) after 6-years of follow-up. Hazard for MCI/dementia was significantly higher in “diffuse malignant” (HR=3.2, p&lt;0.001) and “intermediate” (HR=1.8, p&lt;0.001) subtypes. Individuals with “diffuse malignant” PD had the lowest level of CSF amyloid-beta (p=0.006) and SPECT striatal binding ratio (p=0.001). Conclusions: This multi-domain subtyping is a valid method to predict subgroups of PD with distinct patterns of long-term progression at drug-naïve early-stage with potential application in real-life clinical practice.

scholarly journals High diagnostic performance of independent alpha-synuclein seed amplification assays for detection of early Parkinson’s disease

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Marco J. Russo ◽  
Christina D. Orru ◽  
Luis Concha-Marambio ◽  
Simone Giaisi ◽  
Bradley R. Groveman ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Diagnosis ◽  
Diagnostic Performance ◽  
De Novo ◽  
Alpha Synuclein ◽  
Diagnostic Tools ◽  
Dat Spect ◽  
Progression Markers ◽  
Early Parkinson’S Disease

AbstractAlpha-synuclein seed amplification assays (αSyn-SAAs) are promising diagnostic tools for Parkinson’s disease (PD) and related synucleinopathies. They enable detection of seeding-competent alpha-synuclein aggregates in living patients and have shown high diagnostic accuracy in several PD and other synucleinopathy patient cohorts. However, there has been confusion about αSyn-SAAs for their methodology, nomenclature, and relative accuracies when performed by various laboratories. We compared αSyn-SAA results obtained from three independent laboratories to evaluate reproducibility across methodological variations. We utilized the Parkinson’s Progression Markers Initiative (PPMI) cohort, with DATSCAN data available for comparison, since clinical diagnosis of early de novo PD is critical for neuroprotective trials, which often use dopamine transporter imaging to enrich their cohorts. Blinded cerebrospinal fluid (CSF) samples for a randomly selected subset of PPMI subjects (30 PD, 30 HC, and 20 SWEDD), from both baseline and year 3 collections for the PD and HC groups (140 total CSF samples) were analyzed in parallel by each lab according to their own established and optimized αSyn-SAA protocols. The αSyn-SAA results were remarkably similar across laboratories, displaying high diagnostic performance (sensitivity ranging from 86 to 96% and specificity from 93 to 100%). The assays were also concordant for samples with results that differed from clinical diagnosis, including 2 PD patients determined to be clinically inconsistent with PD at later time points. All three assays also detected 2 SWEDD subjects as αSyn-SAA positive who later developed PD with abnormal DAT-SPECT. These multi-laboratory results confirm the reproducibility and value of αSyn-SAA as diagnostic tools, illustrate reproducibility of the assay in expert hands, and suggest that αSyn-SAA has potential to provide earlier diagnosis with comparable or superior accuracy to existing methods.

scholarly journals Motor Progression in Early-Stage Parkinson's Disease: A Clinical Prediction Model and the Role of Cerebrospinal Fluid Biomarkers

2021 ◽  
Vol 12 ◽  
Author(s):  
Ling-Yan Ma ◽  
Yu Tian ◽  
Chang-Rong Pan ◽  
Zhong-Lue Chen ◽  
Yun Ling ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dynamic Models ◽  
Rating Scale ◽  
Early Stage ◽  
Neurovascular Unit ◽  
Progression Model ◽  
Progression Markers ◽  
Updrs Part ◽  
Threshold Range

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.

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