Dataset Information

Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI).

ABSTRACT: 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.

SUBMITTER: Nalls MA

PROVIDER: S-EPMC4724309 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI).

Nalls Mike A MA Keller Margaux F MF Hernandez Dena G DG Chen Lan L Stone David J DJ Singleton Andrew B AB

Movement disorders : official journal of the Movement Disorder Society 20150813 1

<h4>Background</h4>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.<h4>Methods</h4>Three hundred eighty-three ...[more]

PMID: 26268663

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Project description:BackgroundIdentifying a meaningful progression metric for Parkinson's disease (PD) that reflects heterogeneity remains a challenge.ObjectiveTo assess the frequency and baseline predictors of progression to clinically relevant motor and non-motor PD milestones.MethodsUsing data from the Parkinson's Progression Markers Initiative (PPMI) de novo PD cohort, we monitored 25 milestones across six domains ("walking and balance"; "motor complications"; "cognition"; "autonomic dysfunction"; "functional dependence"; "activities of daily living"). Milestones were intended to be severe enough to reflect meaningful disability. We assessed the proportion of participants reaching any milestone; evaluated which occurred most frequently; and conducted a time-to-first-event analysis exploring whether baseline characteristics were associated with progression.ResultsHalf of participants reached at least one milestone within five years. Milestones within the cognitive, functional dependence, and autonomic dysfunction domains were reached most often. Among participants who reached a milestone at an annual follow-up visit and remained active in the study, 82% continued to meet criteria for any milestone at one or more subsequent annual visits and 55% did so at the next annual visit. In multivariable analysis, baseline features predicting faster time to reaching a milestone included age (p < 0.0001), greater MDS-UPDRS total scores (p < 0.0001), higher GDS-15 depression scores (p = 0.0341), lower dopamine transporter binding (p = 0.0043), and lower CSF total α-synuclein levels (p = 0.0030). Symptomatic treatment was not significantly associated with reaching a milestone (p = 0.1639).ConclusionClinically relevant milestones occur frequently, even in early PD. Milestones were significantly associated with baseline clinical and biological markers, but not with symptomatic treatment. Further studies are necessary to validate these results, further assess the stability of milestones, and explore translating them into an outcome measure suitable for observational and therapeutic studies.

Project description:BackgroundThe Parkinson's Progression Markers Initiative (PPMI) is an ongoing observational, longitudinal cohort study of participants with Parkinson's disease, healthy controls, and carriers of the most common Parkinson's disease-related genetic mutations, which aims to define biomarkers of Parkinson's disease diagnosis and progression. All participants are assessed annually with a battery of motor and non-motor scales, 123-I Ioflupane dopamine transporter (DAT) imaging, and biological variables. We aimed to examine whether non-manifesting carriers of LRRK2 and GBA mutations have prodromal features of Parkinson's disease that correlate with reduced DAT binding.MethodsThis cross-sectional analysis is based on assessments done at enrolment in the subset of non-manifesting carriers of LRRK2 and GBA mutations enrolled into the PPMI study from 33 participating sites worldwide. The primary objective was to examine baseline clinical and DAT imaging characteristics in non-manifesting carriers with GBA and LRRK2 mutations compared with healthy controls. DAT deficit was defined as less than 65% of putamen striatal binding ratio expected for the individual's age. We used t tests, ?2 tests, and Fisher's exact tests to compare baseline demographics across groups. An inverse probability weighting method was applied to control for potential confounders such as age and sex. To account for multiple comparisons, we applied a family-wise error rate to each set of analyses. This study is registered with ClinicalTrials.gov, number NCT01141023.FindingsBetween Jan 1, 2014, and Jan 1, 2019, the study enrolled 208 LRRK2 (93% G2019S) and 184 GBA (96% N370S) non-manifesting carriers. Both groups were similar with respect to mean age, and about 60% were female. Of the 286 (73%) non-manifesting carriers that had DAT imaging results, 18 (11%) LRRK2 and four (3%) GBA non-manifesting carriers had a DAT deficit. Compared with healthy controls, both LRRK2 and GBA non-manifesting carriers had significantly increased mean scores on the Movement Disorders Society Unified Parkinson's Disease Rating Scale (total score 4·6 [SD 4·4] healthy controls vs 8·4 [7·3] LRRK2 vs 9·5 [9·2] GBA, p<0·0001 for both comparisons) and the Scale for Outcomes for PD - autonomic function (5·8 [3·7] vs 8·1 [5·9] and 8·4 [6·0], p<0·0001 for both comparisons). There was no difference in daytime sleepiness, anxiety, depression, impulsive-compulsive disorders, blood pressure, urate, and rapid eye movement (REM) behaviour disorder scores. Hyposmia was significantly more common only in LRRK2 non-manifesting carriers (69 [36%] of 194 healthy controls vs 114 [55%] of 208 LRRK2 non-manifesting carriers; p=0·0003). Finally, GBA but not LRRK2 non-manifesting carriers showed increased DAT striatal binding ratios compared with healthy controls in the caudate (healthy controls 2·98 [SD 0·63] vs GBA 3·26 [0·63]; p<0·0001), putamen (2·15 [0·56] vs 2·48 [0·52]; p<0·0001), and striatum (2·56 [0·57] vs 2·87 [0·55]; p<0·0001).InterpretationOur data show evidence of subtle motor and non-motor signs of Parkinson's disease in non-manifesting carriers compared with healthy controls that can precede DAT deficit. Longitudinal data will be essential to confirm these findings and define the trajectory and predictors for development of Parkinson's disease.FundingMichael J Fox Foundation for Parkinson's Research.

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.

Dataset Information

Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI).

Publications

Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI).

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