ppmi annual meeting...dr. andrew trister dr. carlie tanner dr. kevin biglan dr. karl kieburtz...
TRANSCRIPT
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PPMI ANNUAL MEETING
Day 2: May 14, 2015
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Genetic Recruitment
Genetic Coordination Core
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Genetic Arms • Recruit for:
– LRRK2: G2019S, R1441G, I2020T – SNCA: A53T, G209A – GBA: N370S
• Other mutations can be found in these
genes – Limited the range of mutations – Only mutations that have been shown to
increase the risk of PD – Select mutations that we can find in multiple
families
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LRRK2 Testing at PPMI Sites
0 20 40 60 80 100 120
Barcelona San Sebastian
Norway Northwestern
Columbia Beth Israel
Emory USF
Paris Tel Aviv
UAB UPenn
London INDD
BU CCF
Uwash PI
Banner Tuebingen
Salerno
Number of Subjects Tested
LRRK2-
LRRK2+
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LRRK2 Testing at PPMI Sites
0 100 200 300 400 500 600
Boca Barcelona
San Sebastian Norway
Northwestern Columbia
Beth Israel Emory
USF Paris
Tel Aviv UAB
UPenn London
INDD BU
CCF Uwash
PI Banner
Tuebingen Salerno
Number of Subjects Tested
LRRK2-
LRRK2+
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SNCA Testing at PPMI Sites
0 5 10 15 20 25
Salerno
Greece
Number of Subjects Tested
SNCA- SNCA+
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GBA Testing at PPMI Sites
0 10 20 30 40 50 60
Barcelona
Boca
UAB
Northwestern
Number of Subjects Tested
Pending GBA- GBA+
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Widespread Recruitment Initiative
0
200
400
600
800
1000
1200
1400
Sent kit Results returned
Positive LRRK2
G2019S
With previous testing
LRRK2+ G2019S
GBA+ N370S
Num
ber o
f Sub
ject
s 134 LRRK2+ individuals identified!
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Genetic Counseling in WRI
• Over 975 individuals have received genetic counseling as part of the WRI
Jennifer Verbrugge, MS, CGC Lisa Cushman Spock, MS, PhD, CGC
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Widespread Recruitment Initiative
0 10 20 30 40 50
Cohort Unaffected
Cohort with PD
Registry Unaffected
Registry with PD
# of individuals referred
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WRI Site Referrals
0 5 10 15 20 25
Northwestern Beth Israel
Columbia UCSD
Banner PI
Upenn BU
Emory Boca
Baylor INDD UCSF
London Oregon
USF Hopkins
UR Uwash
CCF Tel Aviv
# of subjects
Site
Nam
e
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0 10 20 30 40 50 60
Greece Tel Aviv Salerno Norway
Barcelona San Sebastian
London Tuebingen
Boca Paris
Banner CCF
UWash Northwestern
Beth Israel UCSF UAB
BU INDD
Emory Johns Hopkins
UCSD USF
Upenn PI
Baylor OHSU
Columbia Rochester
Number of Subjects
Genetic Registry PD Genetic Registry UNAF Genetic Cohort PD Genetic Cohort UNAF
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Current Enrollment
3
66
0
69
1
44
0
45
8
70
0
78
2
55
0
57
0
10
20
30
40
50
60
70
80
90
SNCA LRRK2 GBA Total
Num
ber o
f Sub
ject
s Enr
olle
d
Genetic Registry PD
Genetic Registry UNAF
Genetic Cohort PD
Genetic Cohort UNAF
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PPMI Goals for Genetics • 600 cohort
– 300 PD – 300 unaffected
• 600 registry
– 300 PD – 300 unaffected
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0
50
100
150
Genetic Registry PD Genetic Registry UNAF Genetic Cohort PD Genetic Cohort UNAF
LRRK2
LRRK2 Actual LRRK2 Target
0
20
40
60
Genetic Registry PD Genetic Registry UNAF Genetic Cohort PD Genetic Cohort UNAF
SNCA
SNCA Actual SNCA Target
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How will we reach our study recruitment goals?
Working together…
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Upcoming Recruitment Plans: 23 and Me
• Sending emails to individuals with positive results for: – LRRK2 G2019S (700-1000 individuals) – GBA N370S (~2500 individuals)
• 23 and Me sending these emails in waves to states with PPMI sites
• Individuals directed to WRI – Rapid referral to sites following confirmation
of genetic test results and genetic counseling
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Upcoming Recruitment Plans: WRI
• Newsletter being sent to all WRI LRRK2- individuals (n=820) – Invite individuals to come back to WRI – Sign Informed Consent for GBA N370S
testing – MGH perform genetic testing
• Typical WRI referral – Subjects complete genetic counseling – Subjects referred to PPMI site with typical
paperwork
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Don’t stop with one person, recruit families…
At least 1 family member
participating (%)
No other family members participating
currently (% )
Totals
MGH tested 51 (52%) 47 (48%) 98 Previous testing 9 (22%) 31 (78%) 40 totals 60 (43%) 76 (57%) 138
• WRI identified LRRK2+ individuals • During counseling, obtain a pedigree • During counseling, discuss opportunity for family members to
participate (including nonclosure of test results) • We reviewed the pedigree and the WRI database to identify
family members who came through WRI
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Take home! • LRRK2 recruitment is going well
– Need to keep looking for new probands – Need to try to recruit other family
members • GBA is likely to be very productive
recruitment – Outreach in place to start
• SNCA still challenging – Need to expand recruitment, if possible
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Phenoconversion for PPMI Prodromal and Genetic
Cohorts PPMI Prodromal Cohort Training
May 14, 2015
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Defining Phenoconversion to PD in the PPMI cohort
• Critical outcome for PPMI cohorts • Established phenoconversion
definition not available • Approach: develop a standardized
diagnosis with minimal interrater variability
• Phenoconversion = motor Parkinsonian syndrome
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Phenoconversion Measures • Primary Measure:
– Based on UK Brain Bank Criteria – Data mapped from the ‘Diagnostic
Features Questionnaire’ • Secondary Measures:
– Prodromal Diagnostic Questionnaire • Current most likely clinical diagnosis (Q#1) • Confidence level regarding motor symptoms
c/w a diagnosis of Parkinsonian syndrome (Q#2)
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UK PD Society Brain Bank Diagnostic Criteria
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PPMI Primary Definition for Phenoconversion
(Based on the ‘Diagnostic Features Questionnaire’)
3/16/2015 5
Bradykinesia and at least one of the following: • Muscular rigidity • Rest tremor (4-6 Hz) • Postural instability unrelated to primary visual,
cerebellar, vestibular or proprioceptive dysfunction
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Primary Outcome for Phenoconversion:
‘Diagnostic Features Questionnaire’
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Primary Outcome for Phenoconversion:
‘Diagnostic Features Questionnaire’
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P-PPMI Primary Definition for Phenoconversion
(Based on the ‘Diagnostic Features Questionnaire’)
3/16/2015 8
Features that could exclude phenoconversion: • History of repeated strokes, excessive stroke risk factors (question 1) • Neuroleptic exposure or history of repeated head injury, definite encephalitis,
MPTP exposure (question 2) • Oculogyric crisis, oculomotor disturbances, or supranuclear gaze palsy
(question 13) • Wide based gait or ataxia (question 8.2) • Other neurological abnormalities atypical of parkinsonism (e.g. hyperreflexia,
Babinski sign, sensory deficit, apraxia, sleep apnea , dsymetria or other cerebellar dysfunction) (question 15)
• Early severe autonomic involvement, unusual or atypical presentation (eg presentation, symptoms, signs, course, response to therapy, etc.), which could indicate an alternative diagnosis to Parkinsonian sndrome, (question 15)
• Early severe dementia with disturbances of memory, language, and praxis; • Mental changes: Cognitive (question 9.2) • Little or no response to levodopa or a dopamine agonist, if applicable (question
16) • Presence of very rapid speech (tachyphemia) (question 17) • Presence of dysphagia or other bulbar dysfunction (question 18) • CT/MRI is suggestive of another cause of parkinsonism (eg vascular) (question
19, 20)
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Phenoconversion for PPMI Cohort: Key Points
• Be attentive to the Diagnostic Features Questionnaire
• Ensure completion of the correct Diagnostic Questionnaire (‘Prodromal Diagnostic Questionnaire’)
• Same investigator rating the subject at each visit to reduce variability
• Call/email if there are questions regarding how to best complete the form based on special cases.
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Objective measures of PD – smartphones
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Acknowledgements
2
Dr. Max Little
Dr. Stephen Friend Dr. Andrew Trister
Dr. Carlie Tanner
Dr. Kevin Biglan Dr. Karl Kieburtz Solomon Abiola Denzil Harris
Dr. Suchi Saria Andong Zhan
Dr. Max Little
Sources: IEEE Transactions on Biomedical Engineering 2009;56:1015-22, IEEE Transactions on Biomedical Engineering 2010;57:884-93
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Outline
• Rationale and pilot study
• Android study
• mPower
3
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Many of our current outcome measures are subjective and sub-optimal Characteristics of 20th vs 21st century studies Clinical Trials
Source: JAMA Neurol. Published online March 02, 2015. doi:10.1001/jamaneurol.2014.4524. 4
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Because of rapid adoption and functionality, smartphones have great research potential
5
Number of U.S. smartphone users, 2010 – 2016
Source: Statista. Available at: http://www.statista.com/statistics/201182/forecast-of-smartphone-users-in-the-us/.
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Smartphones can provide objective measures of Parkinson disease
6
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Movement disorders have external manifestations suited for assessment
Figure 1: Picture of Android smartphone and software application.
Figure 2: Procedure for collecting voice recordings, finger tapping, and passive sensor data from gait and postural sway test
Source: Parkinsonism & Related Disorders, http://dx.doi.org/10.1016/j.parkreldis.2015.02.026. 7
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Source: Parkinsonism and Related Disorders 2015 (epub ahead of print)
Smartphones can distinguish those with PD from those without
Gait and posture tests in Parkinson disease
8
-2 0 2 4 6 8
x 10-4
0.8
1
1.2
1.4
Teager-Kaiser energy operator
Det
rended
flu
ctuat
ion a
nal
ysi
s
a) Gait test
Participant with Parkinson desease
Control participant
0 0.5 1 1.5
0.6
0.8
1
1.2
1.4b) Postural sway test
Teager-Kaiser energy operator
Det
rended
flu
ctuat
ion a
nal
ysi
s
Gait test
-2 0 2 4 6 8
x 10-4
0.8
1
1.2
1.4
Teager-Kaiser energy operator
Det
rended
flu
ctuat
ion a
nal
ysi
s
a) Gait test
Participant with Parkinson desease
Control participant
0 0.5 1 1.5
0.6
0.8
1
1.2
1.4b) Postural sway test
Teager-Kaiser energy operator
Det
rended
flu
ctuat
ion a
nal
ysi
s
Postural sway test
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Outline
• Rationale and pilot study
• Android study
• mPower
9
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Smartphones allow for global participation anytime anywhere
Geographical representation of study participants (N=653)
10
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Most participants were recently diagnosed
11
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Participants produced 46,000 hours of high fidelity and high frequency data
One hundred eighty five instances of active tests collected (black dots in the graph)
One hundred twenty six days of passive monitoring (each blue line segment stands
for one complete passive monitoring)
Instances of active tests collected in each day of a week
Instances of active tests collected in each house of a day
12
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The signal from the smartphone could be quite sensitive in response to drugs Sample accelerometry tracing in three dimensions
13 Withdrawn participant
Active participant
Confidential
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Outline
• Rationale and pilot study
• Android study – Smartphone-PD
• mPower
14
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In March Apple released ResearchKit and five medical research smartphone apps
mPower smartphone application for Parkinson disease
15 Withdrawn participant
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ResearchKit is an open source platform empowering patients and providers
It is open source and available to developers globally
Works with Apple’s HealthKit, pooling daily step counts, heart rate, and other health metrics
16
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Sage, Apple, Aston University, MJFF and UR collaborated to develop mPower
17
Data • Data are de-identified are
stored on a secure server operated by Sage Bionetworks
• Depending on the preference of the participants, data are available to all researchers or the study’s investigators
• Participants receive real-time feedback on their performance so they can generate their own insights
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mPower consist of three main components
Surveys
Structured tasks
Passive measures
18
• Demographics • Co-morbidities • Medications • MDS-UPDRS • Open responses from participants
• Voice recording • Speeded tapping • Gait • Posture • Memory
• GPS • Activity data
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mPower surveys provide insight into medication usage and quality of life
19
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mPower structured test assess cognitive, speech, and gait function
20
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Passive tasks provide additional data and feedback around activities
21
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We plan to have new generations of mPower with greater functionality
Pilot
•Differentiate between controls and PD
Android
•Global reach
• Passive monitoring
mPower 1.0
• Participant empowerment and feedback
22
In two months, over 13,000
individuals have enrolled in the study of whom
10% have Parkinson disease
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Incorporating mPower into PPMI could support additional insights into PD
mPower • 80+% of those in Fox Trial Finder have Apple smartphones
PPMI • Some PPMI participants may already be enrolled in mPower
mPower + PPMI
• Marriage of PPMI and mPower could add frequent, objective measures of phenotype to detailed neuroimaging, genotyping, and clinical characterization in the study
23
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Other wearables can provide additional measures of Parkinson disease
Medication reporting
Medication reminder
Report something
PATIENT REPORTED
OTHER
Configurable data
collections Contribution
score
Integrated Login and
registration Pebble notifications
OBJECTIVE MEASURES
Gait
Sleep
Tremor
Activity Level
Controlled Tests
24 Source: Fox Insight Mobile Overview; slide courtesy of Ken Kubota
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The Precision Medicine Initiative aims to incorporate sensors into its efforts
Source: Precision Medicine Initiative http://www.nih.gov/precisionmedicine/ 25
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PPMI and new measures could be well positioned for this Initiative
Source: NEJM 2015;372:793-5 26
• “The initiative will encourage and support the next generation of scientists to develop creative new approaches for detecting, measuring, and analyzing a wide range of biomedical information – including … data from mobile devices … Such innovations will first need to be tested in pilot studies.”
• “[The initiative] will also pioneer new models for doing science that
emphasize engaged participants and open, responsible data sharing.” • “The (1 million) research cohort will be assembled in part from some existing
cohort studies ... that have already collected or all well positioned to collect data from participants willing to be involved in the new initiative.”
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6/6/2015
1
Motor symptoms in
prodromal Parkinson’s disease
Anat Mirelman PhD Laboratory for Early Markers of Neurodegeneration
Center for the study of Movement , Cognition and Mobility Department of Neurology
Tel Aviv Medical Center Sackler School of Medicine
Tel Aviv University Israel
Rationale
• Gait disturbances play a major role in the motor manifestation of PD.
• Gait changes frequently observed include decreased stride length and an increased stride time variability even early in the disease.
• Increased stride time variability has been reported as one of the hallmarks of gait in PD
In a disease diagnosed based on motor symptoms it is unlikely that early motor signs are absent in the
prodromal phase
Pow
er sp
ec
tra
l
de
nsity (p
rs)
Stride time Variability
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6/6/2015
2
0
0.5
1
1.5
2
2.5
usual walk dual task walk fast walk
Non-Carriers Carriers
p=0.07
p=0.04
p=0.02
Non carriers = 81, carriers = 72
Stri
de
var
iab
ility
(C
V%
)
Gait variability in healthy subjects at risk
Mirelman et al. Annals of Neurology 2011
Stride time variability under challenging conditions
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
NMNC NMC PD- PD+
Stri
de
CV
(%
)
usual walking dual task
P=0.02
P=0.03
Non carriers=61 , carriers =62, PD non-carriers= 50, PD carriers =50
Non carriers carriers PD non- carriers PD carriers
0.0002
0.0003
0.0004
0.0005
Vel
oci
ty (
m/s
)
Mean CoM Velocity Eyes Closed (AP)
NMNC NMC PDnC PDC
p = 0.03
p = 0.02
NS
Postural stability – Sway
Data collected by the ‘gait consortium’
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6/6/2015
3
0.01
0.02
0.03
0.04
Sway
Pat
h (
m)
Absolute value of the Sway Path of the CoM Eyes Closed (AP)
NMNC NMC PDnC PDC NMNC NMC PDnC PDC
p = 0.04
p = 0.01 NS
Postural stability – Sway
Data collected by the ‘gait consortium’
Arm swing- PD compared to Healthy
Healthy subject (age=52)
Patient with PD (age =53)
deg
ree
deg
ree
0
0.05
0.1
0.15
0.2
0.25
0.3
Usual walk Dual task walk
Sy
mm
etr
y r
ati
o
NMNC NMC
Group differences in arm swing symmetry between healthy carriers and non-carriers
Non carriers = 61, carriers = 62
p=0.37
p=0.03
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Data Analysis –
• Baseline comparison of cohorts • Prediction of disease progression • Rate of disease progression
How to establish PD subsets??
1
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Analysis –PD subsets • PD subsets
– Need for DA meds – Subjects with highest change in
UPDRS, DAT, Synuclein – Subjects with low MoCa, low amyloid,
high tau – Subjects with relative hypotension,
RBD on questionnaire, low amyloid, high tau
– Subjects with high depression/anxiety/Reduced SERT
2
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Planning for clinical trials
Longitudinal data analysis – sample size estimate • Change in UPDRS • Change in DAT • Change in CSF
3
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Longitudinal PD, HS vs SWEDD MDS-UPDRS
PD - Time to Start Dopaminergic Meds
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PPMI –UPDRS CHANGE IN UPDRS at 12 months – BY TREATMENT
CHANGE IN UPDRS by TREATMENT
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Preliminary Sample Size Estimate - ALL PD
Total number of subjects assume 2 arms
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Preliminary Sample Size Estimate - PD
Total number of subjects assume 2 arms
Table 2.Sample Sizes Necessary to Detect Differences in Mean UPDRS Scores in PD subjects who began treatment within one year
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Preliminary Sample Size Estimate - PD
Total number of subjects assume 2 arms
Table 3. Sample Sizes Necessary to Detect Differences in Mean UPDRS Scores in PD subjects who did not begin treatment within one year
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Preliminary Sample Size Estimate - CSF synuclein
Change from Baseline 50% 30 %
80% power 90% power 80% power 90% power CSF synuclein 45 55 95 110
Total number of subjects assume 2 arms
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“Why use a RBD cohort in clinical trials for PD”
New York 2015
Eduardo Tolosa Barcelona, Catalonia, Spain
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REM behaviour disorder • Occurs in manifest PD (50%) and in premotor PD (about
15% of cases).
• Idiopathic RBD is associated with subclinical features of manifest PD:
- abnormal DAT SPECT,
- hiperechogenicity of substantia nigra
- abnormal MIBG uptake
- depression, constipation
• In longitudinal studies IRBD patients frequently develop a synucleinopathy (e.g. PD, DLB,MSA)
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Rapid eye movement sleep behaviour disorder
Delayed emergence of a parkinsonian disorder in 38% older men initially diagnosed with idiopathic rapid eye movement sleep behaviour disorder
Shenck, Bundlie and Mahowald. Neurology 1996; 46: 388
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Lancet Neurol 2013
• 44 patients with IRBD • After a mean follow up of 10 years, 82% were diagnosed with either PD or DLB or MSA
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33% at 5 years
76% at 10 years
91% at 14 years
Estimated rates of conversion from the diagnosis of IRBD (n=174)
Iranzo et al. PLOS One 2014
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• 69-year-old man was diagnosed as having RBD at age 58 years
• During a ten year follow-up period, development of hyposmia, constipation, depression and mild cognitive changes.
• Parkinsonism was never detected • Serial DAT SPECT imaging showed progressive
subclinical substantia nigra damage. • Diagnosis: Premotor PD • Died at age 77 of lung cancer.
Mov Disord 2014
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Neuronal loss + Lewy bodies CNS Olfactory bulb Dorsal motor vagal Subcoeruleus Substantia nigra Amygdala N. basalis of Meynert PNS Stellate ganglia Paravertebral chain Cardiac plexus Myenteric plexus
α-synuclein
Introduction Tissue-based Biomarkers Conclusion Imaging Biomarkers Clinical Biomarkers
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33% at 5 years
76% at 10 years
91% at 14 years
Estimated rates of conversion from the diagnosis of IRBD (n=174)
Iranzo et al. PLOS One 2014
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• 62 patients with iRBD
• 21 converted at follow up
• Compared to those remaining disease free,
patients destined to develop disease had worse baseline olfaction and vision test
Olfaction and color vision identify early-stage synuclein-mediated neurodegenerative diseases
Postuma 2011
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Olfactory dysfunction predicts early transition to a Lewy body disorder in idiopathic RBD
• 34 PSG confirmed RBD cases studied
• Olfactory testing with Sniffing Stick test
• Prospectively followed for 4.9 years: 9 (26%) developed a Lewy body disorder
• Compared to patients who remained disease free, patients who went on to develop disease had lower olfactory scores at baseline
Mahlknecht et al. Neurology 2015
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43 Idiopathic REMs BD
DAT-SPECT +
SN Sonography
27 Individuals with DAT-SPECT and/or Hyperechogenicity
15 Individuals with normal examens
8 Individuals affected by Parkinsonism
NONE affected by Parkinsonism
After 2.5 years Follow-up
Decreased DAT SPECT and TCS as risk markers for PD: a prospective study
Iranzo et al. Lancet Neurol 2010
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Parkinson risk in idiopathic RBD
• Test the ability of prodromal markers to identify patients at higher risk
• 30% developed disease at 3 years;66% at 7.5 years
• Advanced age, olfactory loss,abnormal color vision, subtle motor dsyfunction and no use of antidepressants identified higher risk of disease conversion
Postuma 2015
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Markers of disease progression in IRBD
• No change with time Olfactory tests
Color vision tests
Hiperechogenicity of the nigra
• Worsens with time
DAT scaning
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UPSIT score does not change over a 4 years follow-up
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Serial DAT imaging in iRBD
Iranzo et al. Lancet Neurol 2011 20 iRBD, 20 HC, 3 year follow-up
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Why use a RBD cohort in clinical trials for PD?
IRBD is a specific prodromal PD marker
IRBD is an indicator of an evolving synucleinopathy.
In iRBD, olfactory and color vision tests, DAT- SPECT
and TCS: markers of short term phenoconversion.
Serial DAT- SPECT (but not serial olfactory and color vision tests): marker of disease progression.
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• Thank you very much for your attention!!
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The Prospect of Using Genetic Synucleinopathy Cohorts in
Clinical Trials
Leonidas Stefanis
Second Department of Neurology University of Athens Medical School
Foundation of Biomedical Research of the Academy of Athens Athens, Greece
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The G209A mutation in the SNCA gene
• First discovered in families of Italian or Greek origin with autosomal dominant PD (Polymeropoulos et al., 1997)
• Has since been described also in families of Northern European and Korean origin (Puschmann et al., 2009; Choi et al., 2008)
• The clinical picture is variable, but generally consistent with PD or PDD (Bostanjopoulou et al., 2001; Papapetropoulos et al., 2001, 2003; Kasten and Klein, 2013), rarely DLB (Morfis and Cordato, 2006)
• Some cases with very prominent autonomic involvement, resembling MSA
• AAO 30s to 60s, mean AAO 45-50 • Approximately 70 cases reported
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Other missense point mutations in SNCA leading to familial PD
• Other point mutations identified (A30P, E46K, H50Q, G51D, A53E)
• Autosomal dominant inheritance • Clinical picture PD, PDD, MSA-like, DLB
(rarely) • AAO 50s to 60s, more typical for iPD • Few cases: Approximately 15 reported total
Kasten and Klein, 2013 Kiely et al., 2013 Pasanen et al., 2014
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Multiplications in SNCA leading to familial PD
• Duplications and triplications of the SNCA gene
• Autosomal dominant pattern of inheritance • AAO 40s (tri) 50s (di) • Protein levels of ASYN in peripheral tissues
and iPS-derived neurons with commensurate increase
• Dementia dose-dependent in incidence, timing, severity
• Total of around 70 cases reported
Kasten and Klein, 2013
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Strategy for recruitment
• Getting in touch with already identified families with carriers of the G209A SNCA mutation (Profs. Athanasiadou, Papadimitriou, Bostanjopoulou)
• PD patients with increased chance of genetic load (AAO<50 and/or family history) presenting to outpatient clinic appointments
• Referrals from other Neurologists
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• Systematic genetic analysis of 111 patients with PD with early AOO (<50) or with positive family history
• Subjects with no known link to families with the G209A SNCA mutation
• 5/111 were found positive for the G209A SNCA mutation • In all cases autosomal dominant family pattern of
inheritance • Except for one case, early age of onset • Amongst patients with early age of onset and family history,
frequency at 15%
Bozi et al, 2014
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Greek MEFOPA Cohort of G209A SNCA carriers
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0
10
20
30
40
50
60
70
80
90
100
age
max age of disease onset
mean age of disease onset
min age of disease onset
Age of Asymptomatic Carriers
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Clinical Picture of affected carriers
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0
0.5
1
1.5
2
2.5
3
H&Y
SCAL
E U
NIT
S
baseline
followup
0
5
10
15
20
25
30
35
40
UPDRS I UPDRS II UPDRS III UPDRS IV
SCAL
E U
NIT
S baseline
follow up
0
5
10
15
20
25
30
MOCA
units
baseline
follow up
Disease Progression over 2 years
0
2
4
6
8
10
12
stic
ks
Sniffin' test
baseline
follow up
* *
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0
5
10
15
20
25
30
35
BASELINE FOLLOW UP
SCAL
E U
NIT
S MOCA RATING FOR EACH COHORT MEMBER
1
2
3
4
5
6
7
8
9
10
11
12
13
14
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Global Impression of Progression: Non-motor Symptoms
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0
0.5
1
1.5
2
2.5
3
3.5
4
UPD
RS sc
ore
at q
uest
ion
1.1
cognitive impairment
baseline
follow up
0
0.5
1
1.5
2
2.5
3
3.5
4
UPD
RS sc
ore
at q
uest
ion
1.2
psychosis
baseline
follow up
0
0.5
1
1.5
2
2.5
3
3.5
4
UPD
RS sc
ore
at q
uest
ion
1.10
urinary problems
baseline
follow up
0
0.5
1
1.5
2
2.5
3
3.5
4
UPD
RS sc
ore
at q
uest
ion
1.11
constipation
baseline
follow up
Impression of Progression confirmed by UPDRS-I subscores
*
* *
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Examples of phenotypic variability
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Lower levels of a-synuclein in serum of A53T carriers
CTL A53T0
10
20
30
40
50
60
**α
-syn
ucle
in(n
g/m
l)
Emmanouilidou et al., unpublished data
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DAT Scans in A53T cohort (PPMI)
asymptomatic Early disease (<3years)
Mid-disease (<7 years)
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CONCLUSIONS • 5-8 years after disease onset dementia, psychosis
and autonomic dysfunction may ensue, but are not obligate events
• Unusually severe and early dementia may occur in some cases
• Progression of motor impairment and cognitive and autonomic dysfunction occurs over 2 years
• DAT scans appear to show unusually severe nigrostriatal degenration, and this rapid progression may serve as a good biomarker in this cohort
• There is substantial heterogeneity in clinical manifestations and course of the disease
• Peripheral markers of ASYN may be telling us something and may be useful as biomarkers in this population
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The Prospect of Using Genetic Synucleinopathy Cohorts in Clinical Trials:
Pros • Defined pathogenic link of genetic defect to
disease-modifying approach • Possibility of recruiting asymptomatic at risk
individuals (e.g. carriers with abnormal DAT scan)
• Clinical progression is measurable, especially in terms of cognitive function
• DAT scans may serve as a useful biomarker of disease progression in this cohort
• Possibility of useful peripheral a-syn biomarker
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• Small number of subjects • Question whether the genetic defects share
the same pathogenic cascade • Heterogeneity in clinical manifestations and
course
The Prospect of Using Genetic Synucleinopathy Cohorts in Clinical Trials: Cons
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Recruitment of G209A SNCA carriers into MULTISYN (1)
• Main aim of project is to develop an a-synuclein radiotracer
• This will then be applied to our A53T cohort • 10 subjects (manifesting carriers or non-
manifesting carriers with pathological DAT scan)
• 2 PETs over 6-12 months to assess sensitivity to progression
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Recruitment of G209A SNCA carriers into MULTISYN (2)
• Interventional phase • Treatment with PD01A (all subjects) • PETs every 6 months • Clinical follow-up, wet biomarkers • Main outcome: comparison of PETs with
PETs in run-in period • Secondary outcomes: effects on motor,
cognitive, autonomic functions, using rating scales
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LRRK2 Trials: Who/ When, and What:
Who/ When: -pre-symptomatic? (gene carriage only) -pre-symptomatic and higher risk? (gene +others) BUT by how many years? very mild motor but not meeting PD criteria? -OR early (<xx years?) PD?
What Outcomes: -Change in surrogate markers? -imaging (which ligand?) -CSF marker -motor prior to PD -Prevention Phenoconversion? -Improvement Motor Features after diagnosis/ (Disease Modifying Design)?
LRRK2 Specific Challenges: -reduced age related G2019S penetrance (approx 26% age 80 AJ, but wide range)
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Domain— (Some representative measures)
LRRK2 G2019S PD (vs. control)
LRRK2 G2019SPD vs IPD NMC: vs. NC-F or vs. control (“trait”)
NMC: Subgroup? 30% or fewer? (“state”)
Timing (Phenoconversion-PD)
Motor
UPDRS + = (overall) -4 ?
Gait + + (several measures) + Prior to phenoconvers
Spiral + = (faster dom hand mean speed)
- (NMC vs. NC-F) + (NMC vs. controls)
Yes (two classes) ?Prior (BUT only 2 cases)
Non-motor Symptoms (0verall) NMS
+ = or < ?sl > (const/urg) >>(all >50 y/o)5 ?
Cognitive impairment + <1,2 or = (R1441G)3 (Executive dysfx)/- ? ?
Olfaction + < or = No diff Yes (latent classes) ?Before PD6
RBD (RBD questionnaire polysomnography)
+ (subgroup) <9 (Questionnaire) - no ?Not early <3 yr
Dysautonomia (Questionnaire, MIBG?, colonic biopsy, HRV)
+ =6, or < ? ?Constip/hypos/depression/EDS before PD6
Psychiatric Depression Anxiety
+ =6 (or >?apathy, hallucination)
? - -
(all >50 y/o) +5
?
*Combined Battery (battery derivation on 3 yr or less LRRK2 PD)
vs NC-F:(UPDRS-III, UPSIT, NMS, spiral AUC 0.77) w/out spiral 0.678
??
Selected studies referenced– not complete! (1)Helmich, (2)Alcalay 15, (3) Estanga 14, (4) Somme 15, (5) Mirelman 15, (6) Gaig 14 (7) Mirelman (8) Ortega (9) Trinh 14(10) Tijero 13, (11) Saunders-Pullman 15
Consider imaging (DAT/ fMRI/ TCS and others?); CSF or other biofluid
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LRRK2 Trials: Who/ When, and What
Who/ When: -pre-symptomatic(by gene carriage only)? c need longitudinal data -very mild motor but not meeting PD criteria? -early <xx years? (?untreated) PD?
What Outcomes: -Change in surrogate markers? -imaging (which ligand?) -CSF marker -motor prior to PD -Prevention Phenoconversion? -Improvement Motor Features/ (Disease Modifying Design)?
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PPMI RETENTION UPDATE & SITE AWARDS
2015 PPMI Annual Meeting
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2
PPMI STATUS UPDATE
Cohort Enrolled Recruitment Status De Novo PD 423 Complete Controls 196 Complete SWEDDs 64 Complete Prodromal 64 Complete Genetic Cohort 137 Ongoing Genetic Registry 115 Ongoing Total 999 Active=901
Goal: Retain subjects by keeping them engaged to participate in study visits over time Status: Overall study retention is 93%! (Original cohort: 92%)
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3
RETENTION STRATEGIES Goal: Maintaining the stamina and loyalty of enrolled participants over time
» Site Relationships with Participants – Maintaining relationships with participants, accommodating their
needs » Annual Retention Events
– Participant appreciation lunch/dinner – Opportunity to update participants on study status and published data
» Scientific Update packet (Vol 1 & 2) – Packet of lay abstracts of results using PPMI data to be handed out at
retention events
» Participant Newsletters – 2x per year: study updates and special profiles
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4
RETENTION STRATEGIES CONT.
» Giveaways – PPMI token of appreciation at each study visit – Thank you Cards
• 60 month visit with pedometer
» PPMI Study Update Calls – Quarterly calls featuring presentation by researcher on PPMI data, Q&A session – Recordings available at www.ppmi-info.org/participants – Next call: June 10 @ 12pm ET
• Brit Mollenhauer will present results form analysis of biospecimens
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5
»Danna Jennings (Chair) »Carlie Tanner »Daniela Berg »Christine Hunter »Lola Vilas »Katie Forsberg »Cheryl Halter
RECRUITMENT & RETENTION WORKING GROUP
»Tanya Simuni »Cathi Thomas »Hubert Fernandez »Zoltan Mari »Vanessa Arnedo »Karen Williams »Jim Leverenz »Shirley Lasch
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6
PPMI PATIENT ADVISORY COMMITTEE
»Sheryl Jedlinski »Jean Burns »Peter Burne »Bill Shepard »Carey Christensen »Kevin Kwok »Linda Comerci
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PPMI SITE AWARDS Recognizing site teams for outstanding effort
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8
• The Parkinson's Institute
• Imperial College London
• Macquarie University
SITES WITH 100% RETENTION OF ORIGINAL COHORT PARTICIPANTS
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9
• OHSU
• UCSD
• Macquarie University
• IND
• Imperial College of London
• Salerno University
SITES WITH 100% OF EXPECTED VISITS OF ORIGINAL COHORT COMPLETED
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10
PRODROMAL ENROLLMENT Site Name Hyposmic Enrolled RBD Enrolled Total Enrolled Barcelona 0 5 18 UPenn 6 5 11 Kassel/Marburg 0 7 7 OHSU 4 0 4 Northwestern 2 2 4 IND 3 0 3 Cleveland Clinic 1 1 2 Tuebingen 2 0 2 Emory 1 1 2 Athens 0 2 2 UCSD 2 0 2 UAB 0 1 1 U of Washington 1 0 1 The PI 1 0 1 USF 1 0 1 Salerno 1 0 1
Total 26 38 64
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11
• Hospital Clinic Barcelona
• University of Pennsylvania
• Paracelsus Elena Klinik/Marburg
TOP PRODROMAL ENROLLMENT
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12
• IND – 26 consented
• Banner – 14 consented
• UCSD – 13 consented
• OHSU – 10 consented
• Cleveland - 10 consented
HONORABLE MENTION Sites with high number of consented participants for Prodromal cohort
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13
GENETIC ENROLLMENT Site Name Cohort
Enrolled Registry Enrolled
Total Enrolled
UPenn 2 6 8
Baylor 2 1 3
Imperial 2 0 2
The PI 1 5 6
USF 1 0 1
Emory 1 5 6
Boston University
1 6 7
Cleveland Clinic
1 0 1
Pitie-Salpetriere
0 8 8
OHSU 0 3 3
IND 0 1 1
Tuebingen 0 1 1
Site Name Cohort Enrolled
Registry Enrolled
Total Enrolled
St. Olavs Hospital
25 4 29
Hospital Clinic Barcelona
23 11 14
Hospital U. Donostia
17 3 20
Tel Aviv Sourasky
13 0 13
PD & Mov Dis - Boca
11 25 36
Beth Israel 9 5 14
Athens 9 3 12
Northwestern 8 4 12
Columbia 3 4 7
Banner 3 0 3
UCSD 3 1 4
Salerno 2 1 3
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• St. Olavs Hospital
• Hospital Clinic Barcelona
• Hospital Universitario Donostia
TOP GENETIC COHORT ENROLLMENT
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TIMELY DATA ENTRY (OVER 85%)
Site Name % Timely Data Entry Barcelona 98 IND 94 UCSD 93 Kassel/Marburg 92 Innsbruck 91 Upenn 89 OHSU 86 Salerno 86 Boston 85
*Data is considered to be entered ‘timely’ if entered within 14 days of assessment
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• Hospital Clinic Barcelona
• Institute for Neurodegenerative Disorders
• University of California, San Diego
TOP 3 SITES WITH TIMELIEST DATA ENTRY…
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EXCELLENCE IN DEVELOPING AND IMPLEMENTING RECRUITMENT STRATEGIES
This site has gone the extra mile to recruit for the SNCA cohort by traveling great distances and engaging families
University of Athens
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MOST COMMITTED TO SITE OPTIMIZATION These coordinators new to PPMI have worked diligently to get up to speed on the study and to better optimize operations at their sites
Gretchen Todd Leigh Donharl
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THANK YOU FOR YOUR CONTINUED HARD WORK!
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PPMI – Post 5 year Plans – Amendment 10
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Current Plan for Existing Cohorts (PD, Healthy, SWEDD)
• PPMI Early PD and Healthy subjects – All followed for 5 years using current protocol – First subject to reach 5 year June 2015 – All subjects reach 5 yr follow-up in June 2018 – Range of follow-up 5-7+ years
• PPMI – SWEDD – Most will end PPMI participation after 2 year f/u – All Swedd subjects reach 2 yr follow-up in June
2015
2
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Why f/u 5 years
• Assess long-term PD progression outcomes – Focus on progression of identifed PD subsets – Focus on dopa non-responsive milestones
• Assess predictability of biomarkers identified at earlier stage
• Comparison of PD and Genetic outcomes • Integration of new markers
3
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PPMI PD and HV Follow-up post 5 years
• Focus on retention – • Reduce frequency of clinic visits • Focus assessments based on existing data
and disease stage • Add options for remote visits to encourage
retention – FOUND/Fox Insight • Customize assessments for different cohorts • Need for path core
4
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PD subjects p 5 year f/u
• q 12 months clinic visits • In clinic
– UPDRS on/off – Cognition – any change – Focus on gait – Non –motor – Blood – CSF q 2 years – DAT imaging at year 9
5
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PD subjects p 5 year f/u
• q 12 month remote visit – Found – Fox Insight
6
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SOE – post 5 year - PD, HV Visit Number SC/BL (year 5) Year 6 Year 7 Year 8 Year 9 Year 10 Visit Description Months (+30 days) -45 days 12 24 36 48 60 Written Informed Consent X Review Inclusion/Exclusion Criteria X Medical & Family History/Demographics X Physical Examination X Neurological Examination X X Vital Signs X X X X Xc X Clinical Laboratory Assessments X X Biomic blood sample X X Xf X Xf X MDS-UPDRS (including Hoehn & Yahr)h X X X X X X Modified Schwab & England ADL X X X X X X Clinical Diagnosis Assessment(s) X X X X X X MDS-UPDRS Repeat Part III/Hoehn & Yahrj X X X X X X
Physical Activity Scale for the Elderly (PASE) X X
Hopkins Verbal Learning Test – Revised X X X X X X Benton Judgment of Line Orientation X X X X X X Semantic Fluency X X X X X X Letter Number Sequencing X X X X X X Symbol Digit Modalities Test X X X X X X Montreal Cognitive Assessment (MoCA) X X X X X X Epworth Sleepiness Scale X X X X X X REM Sleep Behavior Questionnaire X X X X X X Geriatric Depression Scale (GDS-15) X X X X X X State-Trait Anxiety Inventory for Adults X X X X X X QUIP X X X X X X SCOPA-AUT X X X X X X Cognitive Categorization X X X X X X MRI (DTI)e X DAT imagingm,o X VMAT-2 imagingm,o, r (see companion protocol) X
Lumbar puncture (CSF collection) X X X Adverse Eventsa X X X X X X Current Medical Conditions Review X X X X X Concomitant Medication Review X X X X X X assessment of Falls X X X X X X Gait assessment X X X X X X Synucelin imaging X X X X
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Current Plan for Existing Cohorts through 2018 (Prodromal, Genetic)
• Prodromal - RBD/olfactory – Enrollment complete Jan 2015 – All followed for 3+ to 5 years in June 2018
• Genetic -PD – Enrollment complete Jan 2016 – All followed for 2+ to 4 years in June 2018
• Genetic Unaffected – Enrollment complete Jan 2016 – All followed for 2+ to 4 years in June 2018
8
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Prodromal subjects p 2018 -
• Timing of clinic vs remote vs wearables • Suggest in clinic q 12 months for 5 years • Possibility for Milestone
driven/Phenoconversion visit? • In clinic
– UPDRS on/off – Cognition – UPSIT – as precursor to motor – Non –motor – Blood – CSF q 2 years? – DAT imaging at year 6,8 – Synuclien imaging
9
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Cohort specific f/u
• PD vs Prodromal/unaffected • Genetic Cohort specific
assessments • Flexibility – Identify cohort
specific milestones – phenoconversion, treatment, dyskinesia, falls, dementia,
10
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PPMI Future plans
Ken Marek
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Challenges for 2015/2016
• Subject Retention – Longitudinal assessment • Enroll Genetic cohort • Data Quality/Data Entry • PPMI fatigue • Increase industry sponsorship
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PPMI Goals for 2015/16
• Novel analytes, imaging tools, clinical assessments, analyses • Focus on PPMI data analyses – longitudinal data, PD subsets, prodromal data • Develop tools for Prodromal assessments – Phenoconversion • Focus on genetic enrollment/retention • Implement pathology core • Long-term PPMI follow-up • How can PPMI inform clinical trials