Longitudinal Change of Clinical and Biological Measures in Early Parkinson's Disease: Parkinson's Progression Markers Initiative Cohort.
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ABSTRACT:
SUBMITTER: Simuni T
PROVIDER: S-EPMC6001458 | biostudies-literature | 2018 May
REPOSITORIES: biostudies-literature
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Longitudinal Change of Clinical and Biological Measures in Early Parkinson's Disease: Parkinson's Progression Markers Initiative Cohort.
Simuni Tanya T Siderowf Andrew A Lasch Shirley S Coffey Chris S CS Caspell-Garcia Chelsea C Jennings Danna D Tanner Caroline M CM Trojanowski John Q JQ Shaw Leslie M LM Seibyl John J Schuff Norbert N Singleton Andrew A Kieburtz Karl K Toga Arthur W AW Mollenhauer Brit B Galasko Doug D Chahine Lana M LM Weintraub Daniel D Foroud Tatiana T Tosun Duygu D Poston Kathleen K Arnedo Vanessa V Frasier Mark M Sherer Todd T Chowdhury Sohini S Marek Kenneth K
Movement disorders : official journal of the Movement Disorder Society 20180323 5
<h4>Objective</h4>The objective of this study was to assess longitudinal change in clinical and dopamine transporter imaging outcomes in early, untreated PD.<h4>Methods</h4>We describe 5-year longitudinal change of the MDS-UPDRS and other clinical measures using results from the Parkinson's Progression Markers Initiative, a longitudinal cohort study of early Parkinson's disease (PD) participants untreated at baseline. We also provide data on the longitudinal change in dopamine transporter 123-I ...[more]
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Project description: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 < 0.03). Similarly, t-tau (45/53) and p-tau (16/18) were reduced in PD versus HC (P < 0.01).InterpretationPPMI has detailed the biomarker signature for an early PD cohort defined by clinical features and imaging biomarkers. This strategy provides the framework to establish biomarker cohorts and to define longitudinal progression biomarkers to support future PD treatment trials.
| S-EPMC6292383 | biostudies-literature
Project description:Background: Orthostatic hypotension (OH) in Parkinson's disease (PD) can lead to falls, impair quality of life, and increase mortality. A trajectory analysis of OH could be useful to predict and prevent the hypotension incidence early. Methods: The longitudinal data of 660 patients with PD with disease duration up to 12 years were extracted from an integrated PD database. We used latent class mixed modeling (LCMM) to identify patient subgroups, demonstrating trajectories of changes in orthostatic blood pressure (BP) over time. The optimal number of subgroups was selected by several criteria including the Bayesian Information Criterion. Baseline information comparison between groups and backward stepwise logistic regression were conducted to define the distinguishing characteristics of these subgroups and to investigate the predictors for BP trajectory. Results: We identified three trajectories for each orthostatic change of systolic blood pressure (ΔSBP), namely, Class 1 (i.e., the increasing class) consisted of 18 participants with low ΔSBP that increased continuously during the follow-up; Class 2 (i.e., the low-stable class) consisted of 610 participants with low ΔSBP that remained low throughout the follow-up; and Class 3 (i.e., the high-stable class) consisted of 32 participants with high ΔSBP at baseline that was relatively stable throughout the follow-up. Several parameters differed among subgroups, but only male sex [odds ratio (OR) = 4.687, 95% confidence interval (CI) = 1.024-21.459], lower supine diastolic blood pressure (DBP) (OR = 0.934, 95% CI = 0.876-0.996), and lower level of total protein at baseline (OR = 0.812, 95% CI = 0.700-0.941) were significant predictors of an increasing ΔSBP trajectory. Conclusion: This study provides new information on the longitudinal development of ΔSBP in patients with PD with distinct trajectories of rapidly increasing, low-stable, and high-stable class. The parameters such as male sex, lower supine DBP, and lower total proteins help to identify the rapidly increasing class.
| S-EPMC8720927 | biostudies-literature
Project description: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 (?-syn), amyloid-beta1-42 (A?1-42), 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 ?-syn, t-tau and p-tau levels, but not A?1-42, 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 ?-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 A?1-42, or highest t-tau/A?1-42 and t-tau/?-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 ?-syn was significantly associated with worse cognitive test performance. APOE ?4 genotype was associated with lower levels of A?1-42, 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.
| S-EPMC5031365 | biostudies-literature
Project description:BACKGROUND:The Parkinson's Progression Marker Initiative is an international multicenter study whose main goal is investigating markers for Parkinson's disease (PD) progression as part of a path to a treatment for the disease. This manuscript describes the baseline genetic architecture of this study, providing not only a catalog of disease-linked variants and mutations, but also quantitative measures with which to adjust for population structure. METHODS:Three hundred eighty-three newly diagnosed typical PD cases, 65 atypical PD and 178 healthy controls, from the Parkinson's Progression Marker Initiative study have been genotyped on the NeuroX or Immunochip arrays. These data are freely available to all researchers interested in pursuing PD research within the Parkinson's Progression Marker Initiative. RESULTS:The Parkinson's Progression Marker Initiative represents a study population with low genetic heterogeneity. We recapitulate known PD associations from large-scale genome-wide association studies and refine genetic risk score models for PD predictability (area under the curve, ?0.74). We show the presence of six LRRK2 p.G2019S and nine GBA p.N370S mutation carriers. CONCLUSIONS:The Parkinson's Progression Marker Initiative study and its genetic data are useful in studies of PD biomarkers. The genetic architecture described here will be useful in the analysis of myriad biological and clinical traits within this study.
| S-EPMC4724309 | biostudies-literature
Project description:ObjectivesDeveloping disease modifying therapies for Parkinson's disease (PD) calls for outcome measurement strategies focused on characterizing early stage disease progression. We explored the psychometric evidence for using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part II (patient motor experience of daily living) and part III (clinician motor examination) in this context.MethodsMDS-UPDRS-II and -III data were collected at screening, month 12, and month 24 from 384 early stage PD patients (diagnosis ≤ 2 years; Hoehn and Yahr stage 1/2) in the Parkinson's Progression Markers Initiative (PPMI) study. Psychometric analysis, based on Rasch measurement theory (RMT), was performed on both the original MDS UPDRS-II and -III scales and exploratory content-driven scale structures.ResultsRMT analyses showed neither scale was well targeted to early PD. A marked floor effect appeared for most items and a clear item gap was consistently observed in very mild severity of motor signs and levels of motor impact. The original MDS-UPDRS-II and -III scales also displayed disordered thresholds (9/13 and 20/33 items, respectively), indicating response scales not functioning as expected, and misfit (5/13 and 12/33 items, respectively), flagging areas for potential improvement.ConclusionsThe MDS-UPDRS-II and -III have psychometric limitations which limits the precision of measurement of motor symptoms and impact in early PD. This can lead to insensitivity in detecting differences and clinical change. Importantly, the diagnostic psychometric evidence provided by the RMT analysis provides a clear starting point for how to improve the quantification of clinically relevant concepts to characterize the course of early PD.
| S-EPMC6647182 | biostudies-literature
Project description:BackgroundThe Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UDPRS) is a commonly used tool to measure Parkinson disease (PD) progression. Longitudinal changes in MDS-UPDRS scores in de novo PD have not been established.ObjectiveDetermine progression rates of MDS-UPDRS scores in de novo PD.Methods362 participants from the Parkinson's Progression Markers Initiative, a multicenter longitudinal cohort study of de novo PD, were included. Longitudinal progression of MDS-UPDRS total and subscale scores were modeled using mixed model regression.ResultsMDS-UPDRS scores increased in a linear fashion over five years in de novo PD. MDS-UPDRS total score increased an estimated 4.0 points/year, Part I 0.25 points/year, Part II 1.0 points/year, and Part III 2.4 points/year.ConclusionsThe expected average progression of MDS-UPDRS scores in de novo PD from this study can assist in clinical monitoring and provide comparative data for detection of disease modification in treatment trials.
| S-EPMC5898442 | biostudies-literature
Project description:Parkinson's disease is the second most common neurological disease and affects about 1% of persons over the age of 60 years. Due to the lack of approved surrogate markers, confirmation of the disease still requires postmortem examination. Identifying and validating biomarkers are essential steps toward improving clinical diagnosis and accelerating the search for therapeutic drugs to ameliorate disease symptoms. Until recently, statistical analysis of multicohort longitudinal studies of neurodegenerative diseases has usually been restricted to a single analysis per outcome with simple comparisons between diagnostic groups. However, an important methodological consideration is to allow the modeling framework to handle multiple outcomes simultaneously and consider the transitions between diagnostic groups. This enables researchers to monitor multiple trajectories, correctly account for the correlation among biomarkers, and assess how these associations may jointly change over the long-term course of disease. In this study, we apply a latent time joint mixed-effects model to study biomarker progression and disease dynamics in the Parkinson's Progression Markers Initiative (PPMI) and examine which markers might be most informative in the earliest phases of disease. The results reveal that, even though diagnostic category was not included in the model, it seems to accurately reflect the temporal ordering of the disease state consistent with diagnosis categorization at baseline. In addition, results indicated that the specific binding ratio on striatum and the total Unified Parkinson's Disease Rating Scale (UPDRS) show high discriminability between disease stages. An extended latent time joint mixed-effects model with heterogeneous latent time variance also showed improvement in model fit in a simulation study and when applied to real data.
| S-EPMC6314496 | biostudies-literature
Project description:BackgroundImproved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.ObjectivesTo examine whether baseline measures and their 1-year change predict longer-term progression in early PD.MethodsParkinson's Progression Markers Initiative study data were used. Participants had disease duration ?2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.ResultsAmong 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (?=?0.351; 95% CI?=?0.146, 0.555), male gender (?=?3.090; 95% CI?=?0.310, 5.869), and baseline (?=?-0.199; 95% CI?=?-0.315, -0.082) and 1-year change (?=?0.540; 95% CI?=?0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (?=?-0.6229; 95% CI?=?-1.2910, 0.0452), baseline (?=?7.232; 95% CI?=?2.268, 12.195) and 1-year change (?=?45.918; 95% CI?=?35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (?=?-0.325;95% CI?=?-0.695, 0.045); predictors in the model accounted for 44.1% of the variance.ConclusionsBaseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding.
| S-EPMC6839498 | biostudies-literature
Project description:OBJECTIVE:The performance characteristics of hyaline articular cartilage measurement on magnetic resonance imaging (MRI) need to be accurately delineated before widespread application of this technology. Our objective was to assess the rate of natural disease progression of cartilage morphometry measures from baseline to 1 year in knees with osteoarthritis (OA) from a subset of participants from the Osteoarthritis Initiative (OAI). METHODS:Subjects included for this exploratory analysis are a subset of the approximately 4700 participants in the OAI Study. Bilateral radiographs and 3T MRI (Siemans Trio) of the knees and clinical data were obtained at baseline and annually in all participants. 160 subjects from the OAI Progression subcohort all of whom had both frequent symptoms and, in the same knee, radiographic OA based on a screening reading done at the OAI clinics were eligible for this exploratory analysis. One knee from each subject was selected for analysis. 150 participants were included. Using sagittal 3D DESSwe (double echo, steady-state sequence with water excitation) MR images from the baseline and 12 follow-up month visit, a segmentation algorithm was applied to the cartilage plates of the index knee to compute the cartilage volume, normalised cartilage volume (volume normalised to bone surface interface area), and percentage denuded area (total cartilage bone interface area denuded of cartilage). RESULTS:Summary statistics of the changes (absolute and percentage) from baseline at 1 year and the standardised response mean (SRM), ie, mean change divided by the SD change were calculated. On average the subjects were 60.9 years of age and obese, with a mean body mass index of 30.3 kg/m2. The SRMs for cartilage volume of various locations are: central medial tibia -0.096; central medial femur -0.394; and patella -0.198. The SRMs for normalised cartilage volume of the various locations are central medial tibia -0.044, central medial femur -0.338 and patella -0.193. The majority of participants had a denuded area at baseline in the central medial femur (62%) and central medial tibia (60%). In general, the SRMs were small. CONCLUSIONS:These descriptive results of cartilage morphometry and its change at the 1-year time point from the first substantive MRI data release from the OAI Progression subcohort indicate that the annualised rates of change are small with the central medial femur showing the greatest consistent change.
| S-EPMC2734969 | biostudies-literature
Project description:BackgroundThe immune system is a promising therapeutic target for disease modification in Parkinson's disease (PD), but appropriate immune-related biomarkers must be identified to allow patient stratification for trials and tracking of therapeutic effects. The objective of this study was to investigate whether immune markers in peripheral blood are candidate prognostic biomarkers through determining their relationship with disease progression in PD.MethodsSerum samples were collected in incident PD cases and age-matched controls. Subjects were clinically evaluated at baseline and 18 and 36 months. Ten cytokines and C-reactive protein were measured, with data reduction using principal-component analysis, and relationships between component scores and motor (MDS Unified Parkinson's Disease Rating Scale - part 3) and cognitive (Mini Mental State Examination [MMSE]) measures of disease severity/progression were investigated.ResultsTNF-?, IL1-?, IL-2, and IL-10 were higher in PD (n = 230) than in controls (n = 93), P ? 0.001). Principal-component analysis of log-transformed data resulted in a 3-component solution explaining 51% of the variance. Higher "proinflammatory" and lower "anti-inflammatory" component scores were associated with more rapid motor progression over 36 months (P < 0.05), and higher "proinflammatory" component scores were associated with lower MMSE at all times (P < 0.05). Multiple linear regression analysis with adjustment for covariates confirmed "anti-inflammatory" component score was the strongest predictor of slower motor progression (? = -0.22, P = 0.002), whereas proinflammatory cytokines were associated with lower baseline MMSE (? = -0.175, P = 0.007).ConclusionsSerum immune marker profile is predictive of disease progression in PD and hence a potential prognostic biomarker. However, interventional trials are needed to clarify whether peripheral immune changes causally contribute to the progression of PD. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
| S-EPMC4957620 | biostudies-literature