Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

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Neurological Predictors of Huntington’s Disease Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit

Transcript of Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Page 1: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Neurological Predictors of

Huntington’s Disease

Clinical Professor Peter K PanegyresMD PhD FRACP

PREDICT-HD

Neurosciences Unit

Page 2: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

PREDICT-HD Study

Intervention model for HD

Page 3: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Document natural history of premanifest HD

Development of Markers

ClinicalImaging

Outcome measuresPreventativeClinical Trials

PREDICT-HD: Objectives

Page 4: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

32 sites

International

Observational

Premanifest HD

Annual examination

2001-2014

PREDICT-HD N=1013 participants

(premanifest)

N=301 negative control

> 35 CAG expansion repeats = cases

< 36 gene mutation negative = controls

Page 5: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Median duration in study = 6 years (range 1-10)

75% sample > 3 years data

15% - 2 years

<10% - 1 year

N=204 gene expanded participants received a motor diagnosis = converters

Dropout < 5% per year

PREDICT-HD

Page 6: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

CAG-AGE product [CAP] score =CAPE = [age at entry] x [CAG -33.66]

Estimate proximity to HD diagnosis

CAPE can be used to estimate 5 year probability of motor diagnosis

CAPE < 290 [low] 12.78 years

290 CAPE 368 [medium] 7.59-12.78 yrs

> 368 [high] < 7.59 years

Premanifest Staging Group

Page 7: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Change over time – controlling for covariates of age, gender, depressed mood, brain scanner field strength

Comparison of premanifest and control LMER (linear mixed effects regression)

39 variables analysed separately

Graphical analysis to represent phenotypic characteristics of HD:

Motor, cognitive, psychiatric+

Biological (imaging)+

Functional outcomes

PREDICT-HD : Statistics

Page 8: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Variables with largest effect sizes

◦ Regional brain volumes

◦ TMS [UHDRS], esp bradykinesia and chorea

◦ Decline in cognitive performance in every measrue examined, esp symbol digits modalities test

◦ Functional variables, every measure esp TFC

◦ Psychiatric variables, esp Obsessive compulsive scale Frontal systems behavioural scale

executive and apathy scales

PREDICT-HD : Results

Page 9: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

PREDICT-HD : Results

Page 10: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Six variables significant acceleration of the slope of participants who converted:

Dystonia

Stroop

FAS

SDMT

TFC

TMS

PREDICT-HD : Results

Page 11: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Estimated effect size for a two-arm Phase II randomised control trial

Effect size 20%◦ Required sample for say TMS = 981

Dropout rate 20%◦ Sample required TMS = 1131

CSF space◦ 20% effect = 332◦ 20% dropout = 386

PREDICT-HD : Results

Page 12: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

PREDICT-HD

Plots of key outcome variables for preventative clinical trials

Page 13: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

PREDICT-HDData derived model for disease progression

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Longitudinal change in 36 of 39 measures over 10 years of natural observation study

Effect sizes suggest a preventative RCT could be designed to detect treatment effects of 30%

Significant measures◦ Clinical phenotype HD – motor, cognitive, psychiatric◦ Biological◦ Functional

Specific measure a disease state chosen

The effects of ageing

Real natural history data

PREDICT-HD : Conclusions

Page 15: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

1300 gene mutation tested individuals followed prospectively through actual motor diagnosis

Phenotypic and biological changes decade prior to, and just after, manifestations of disease

Biological progression in premanifest HD is◦ Linear for imaging, cognitive and psychiatric◦ Non-linear for motor and functional

Motor expression accelerates as the disease manifests over 15 years prior to motor onset

Worldwide collaboration

Relevant to clinical trials

PREDICT-HD : Conclusions

Page 16: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

Collection of CSF to analyse Huntingtin

protein and other biomarkers as clues

to disease progression

PREDICT-HD : CSF

Page 17: Clinical Professor Peter K Panegyres MD PhD FRACP PREDICT-HD Neurosciences Unit.

•Patients and families

•Huntington’s Study Group

•PREDICT Team – Jane Paulsen & colleagues

•Rachel Zombor, Mark Woodman, Elizabeth Vuletich, Steve Andrews, Maria Tedesco, Carmela Pestell

•Staff at the Neurosciences Unit

PREDICT-HD : Thank You