PPMI was designed to provide all investigators in the scientific community with full, open access to study data. Investigators accessing PPMI data for the first time must complete the registration process, electronically sign the PPMI Data Use Agreement and undergo limited screening by the Data and Publications Committee (DPC), which is appointed by the study Steering Committee. The DPC reviews an investigator’s affiliation with a scientific or educational institution and/or the rationale for the data request. It is anticipated that most requests for access will be approved rapidly.
How can I tell what subjects in the database have been consented and which ones are enrolled in the study?
The SCREEN table contains a list of all consented subjects at any given time. The RANDOM table contains a list of all enrolled subjects. The variable PATNO captures the subject-specific ID. If reports or analyses are desired based on enrolled subjects, the RANDOM table should be merged by PATNO with any other tables of interest. All users should note that the number of enrolled subjects found in the RANDOM table may not be exactly equal to the total number of enrolled subjects due to delays in submitted forms at a clinical site.
New entries into the clinical database are transferred nightly from the Clinical Core to the database. Each Sunday, a complete update to the database is conducted. Imaging data will be integrated into the database separately. Images are uploaded every Thursday, with DAT SPECT and MRI (including DTI) being transfered every other week (uploads will alternate between DAT SPECT and MRI/DTI each week resulting in each type of data being updated every two weeks).
Urine, DNA, serum, plasma, RNA, whole blood, and cerebrospinal fluid are being collected. Investigators seeking to conduct verification studies must submit information about themselves and a letter of intent describing the proposed use of the specimens for the study for review by the Biospecimen Review Committee. Select applicants will be invited to submit full proposals. Additional information about requesting PPMI specimens and what specimens are currently available can be found in the Request Specimens section of the website.
It is anticipated that the samples being collected in PPMI will be useful in biomarker studies, which will bolster scientists understanding of the natural history of early PD. Because these samples are a limited resource, they are primarily reserved for biomarker verification studies, such as protein and mRNA analyses. Investigators may request access to samples for such studies through an online application process. Click here for more information about Requesting Specimens or to review the Procedure and Guidelines to Access Banked Biospecimens.
Are there any stipulations that I have to agree to if I download data and/or gain access to biospecimens?
A core tenet underpinning PPMI is that new data generated by investigators using the study data or samples be made available to the research public as quickly as possible. To that end, investigators who download data agree to provide their new data back to the Data and Publications Committee to be incorporated into the PPMI study database. Similarly, investigators who receive access to banked samples will be required to submit data generated in their experiments to the Biospecimen Review Committee. Again, these results will be appropriately incorporated into the PPMI study database. By reserving the right to include investigators’ results in the study database, it is hoped that new investigators will build upon the research findings generated by their colleagues. In addition to providing new findings back to the overseeing committees, investigators using PPMI data and specimens are required to provide summary information about their analyses in an Ongoing Analyses section of the Web site on an annual basis.
The following clinical information and assessment results are included in the PPMI database:
• Medical and family history (including demographics)
• Physical examination
• Neurological examination
• Vital signs
• MDS-UPDRS scores (including Part III and Hoehn & Yahr)
• Modified Schwab & England ADL
• UPSIT (olfactory testing )
• Hopkins Verbal Learning Test
• Benton Judgment of Line Orientation
• Semantic fluency
• Letter number sequencing
• Symbol digit modalities
• Montreal Cognitive Assessment (MoCA)
• Epworth Sleepiness Scale
• REM Sleep Behavior Questionnaire
• Geriatric Depression Scale (GDS-15)
• State-Trait Anxiety Inventory for Adults
• Current medical conditions review
• Concomitant medication review
Imaging data will include:
• DaTSCAN Imaging for PD subjects and controls subjects
• Structural MRI Imaging
• Diffusion Tensor Imaging (DTI) will be available from a subset of participants
Results from the analysis of the following will also be included:
• Clinical laboratory evaluations (including CSF hemoglobin)
• DNA sampling
In addition, the database will incorporate a running inventory of available samples collected from patient and control subjects. Samples of the following body fluids will be collected: serum, plasma, urine and cerebrospinal fluid.
A schedule of the frequency of these tests, assessments and sample collections is found in the Research Documents and SOPs section of this site.
Because of the exploratory nature of the analyses that will be conducted with PPMI data and specimens, it is very difficult to provide a formal sample size justification for the entire model building process. This is further compounded by the broad range of goals that reach beyond any single, pre-planned analysis. Despite this, the study Steering Committee examined the ability of the proposed sample size to detect meaningful effects of interest for the preliminary comparisons of baseline characteristics and univariate assessments of progression markers across the groups of interest.
The table below provides generic information about the detectable effect sizes for three types of statistical analysis that may be performed on the PPMI data. For each analysis the two-sided alpha level is set to 0.05 and the beta level to 0.80. The first column gives the total sample size that is assumed to be available for the analysis: in the first two rows either 400 (total PD sample) or 300 (PD sample after allowance for 25% withdrawals). The third and fourth rows of the table correspond to the total sample size of 600 (400 PD, 200 healthy controls [HC]) when, respectively, 75% and 100% of the subjects are available for analysis. The second column gives the detectable correlation coefficient between two continuous measures (e.g., change in striatal β-CIT uptake vs. change in total MDS-UPDRS). The third column gives the detectable difference in prevalence rates of some characteristic (e.g. presence of dopaminergic side effects) between two “halves” of the sample (e.g. the younger patients vs. the older patients, with age dichotomized at the median for the entire group). For the first two rows, the third column gives the detectable “effect size”, expressed as the ratio of difference in means to standard deviation, for comparing two “halves” of the sample (e.g. younger vs. older patients as above) in relation to a continuous measure (e.g. change in total MDS-UPDRS). For the third and fourth row, the comparisons are between PD patients and HC. The table suggests that the PPMI trial is adequately powered to detect effects that would generally be of clinical interest. Although it is possible that smaller effects than those listed in the table might also be of clinical interest, it was determined that the added power for these comparisons did not offset any additional costs and logistical issues that would accompany a larger study in this population. Rather, the proposed study should prove to be effective for screening a large number of variables and identifying those that show the most promise for further exploration in follow-up studies.
|Total Sample Size||Detectable Correlation||Detectable Difference in Prevalence||Detectable Difference in Means (Standardized)|
PPMI is performing verification studies on alpha-synuclein, DJ-1, urate, total tau, phospho-tau and amyloid beta. These markers have been identified as potential diagnostic markers, not progression markers. What evidence supports their testing as markers of progression?
Preliminary data indicate that alpha-synuclein, urate and DJ-1 change according to disease stage, which warrants a more systematic investigation into whether these markers could serve as markers of progression. Data indicate that total tau, phospho-tau and amyloid beta may change as cognitive function changes. As cognitive deficits occur with Parkinson’s disease and are among the more debilitating symptoms of the disease, the Steering Committee, with the recommendation of a Biomarkers Taskforce, decided to include these markers in the verification studies.
Are Subjects Without Evidence of Dopaminergic Deficiency (SWEDDs) and/or patients with Multiple System Atrophy (MSA) or Progressive Supranuclear Palsy (PSP) enrolled in PPMI?
PPMI is focused on identifying markers of disease progression in early stage PD subjects. Therefore, the subject inclusion and exclusion criteria do not allow for enrollment of MSA or PSP subjects. However, data generated from the study may have applicability to these diseases. As the PPMI got underway, the Steering Committee did decide to add a SWEDD cohort to the PPMI study since little was known about what happens to these individuals in the long term. SWEDDs are now being included in PPMI so that researchers can learn more about the nature of their symptom progression.
The prodromal cohort of PPMI is designed to be a proof-of-concept study to demonstrate that the recruitment of hyposmic and RBD subjects without PD is possible and that the study design is such that some of these subjects will phenoconvert to PD. The power of this cohort as it is originally designed is not large enough to provide findings that are statistically significant. That said, evidence that a larger effort could work operationally and early estimates regarding the frequency of conversion to PD in this critical population will be possible through the planned effort.
Genetic approaches to understanding disease are complex and rapidly changing. Given the increasing opportunity to identify and enroll specific genetic cohorts, PPMI added a genetic cohort to investigate the relationship between idiopathic PD and PD with known genetic mutation and to further explore the prodromal PD period in unaffected family members of individuals with PD with known genetic mutation in LRRK2, GBA, or SNCA.
Please contact us if you have any questions about PPMI.