Longitudinal studies of familial and Longitudinal studies of familial and sporadic Alzheimer’s disease sporadic Alzheimer’s disease

provide strategies for preclinical provide strategies for preclinical intervention trialsintervention trials

ADI, Puerto Rico

May 2014

The Incidence of Alzheimer’s Disease

Crude Annual

Incidence per 1,000

100

90

80

70

60

50

40

30

20

10

0

0-39 40-49 50-59 60-69 70-79 80-89 90+ All

Age

X XX X

X

X

X

Framingham (Bachman et al, 1993) East Boston (Hebert et al, 1995)

Chicago (Evans et al, 2003) Baltimore (Kawas et al, 2000)X

X

The Amyloid Cascade HypothesisThe Amyloid Cascade Hypothesis

A, -amyloid; AD, Alzheimer’s disease; APP, amyloid precursor protein

AAAggregationAggregation

AmyloidAmyloidplaqueplaque

P3

Amyloidgenic Pathway

NonamyloidgenicPathway

APPAPP

Neuronal loss Neuronal loss and ADand AD

A monomers

Tau pathology

Inflammation

Aβ PRODUCTION AAββ40, 42 40, 42 dimerdimerAAββ40, 42 40, 42 dimerdimer

Aβ – Aβ INTERACTIONS(Oligomeric intermediates)

Aβ CLEARANCE

APP BACE1 C99 γ-sec Integral membrane, (α–helix)

Membrane free diffusible, (β–turn)

Extracellular, (β–sheet)

Membrane associatedMembrane associated and/or diffusible 1° nucleation (Zn++/Cu++)dependent on [monomer/oligomer]Fibrillar Fibrillar amyloid amyloid depositsdeposits

Fibrillar Fibrillar amyloid amyloid depositsdeposits

AAββ toxic toxic oligomeoligomerrAAββ toxic toxic oligomeoligomerr AAββ40, 42 40, 42 oligomeoligomerr

AAββ40, 42 40, 42 oligomeoligomerr

AAββ40, 42 40, 42 oligomeoligomerrAAββ40, 42 40, 42 oligomeoligomerr

ApoE, Clu, ApoE, Clu, ABCA7, CD33, ABCA7, CD33, TYROBP, etc TYROBP, etc (phagocytosis (phagocytosis pathway)pathway)

2° nucleationdependent on [fibril]⇌

⇌⇌

⇌ApoEApoE

AAββ Metabolic Pools (CSF reflecting brain ISF) Metabolic Pools (CSF reflecting brain ISF)

sAD (Mawuenyega, Bateman et al 2010)•Production rate Aβ42 is equal to controls•Clearance rate of Aβ42 is 49% slower in AD•It takes 13 hours for the complete turnover of the CSF pool for controls and 19 hours for sAD. There is a 42% impairment in the production:clearance ratio in sAD•Protective effect of A673T substitution in APP adjacent to BACE1 cleavage site results in 40% reduction in Aβ in vitro production (Jonsson et al., 2012)

ADAD (Potter, Bateman et al., 2013•Production rate of Aβ42 is increased 18%. No change Aβ38,40

•Soluble Aβ42:40 fractional turnover rate is increased 65%, consistent with the increased removal of Aβ42 through extracellular deposition•Newly formed Aβ is in exchange equilibrium with pre-existing Aβ, possibly in oligomers or other aggregates, possibly by 20 nucleation events derived from existing fibrillar aggregates

What Is the Best Target for a What Is the Best Target for a Disease-Modifying Drug (DMD)?Disease-Modifying Drug (DMD)?

-secretase inhibitor?-secretase inhibitor?

• A oligomer?

• Aggregated fibrillar A?

• A clearance mechanism?

• APP/A processing?

• ….or a combination of any above?

P3 oligomer model based on P3 oligomer model based on crystal structurecrystal structure

Streltsov, Nuttall2011

The Australian Imaging, Biomarkers and Lifestyle The Australian Imaging, Biomarkers and Lifestyle Study of AgingStudy of Aging

Australian ADNIAustralian ADNI

AIBL: Longitudinal cohort: Baseline to 54 months.

Baseline(1,112)

18 month (972)*

36 month (824)*

(33) (29) (50)(29)

(97) (114) (7) (13)(4) (1) (3) (32)

(39)(41) (62)(26)

(1)(78) (62) (4)(5) (14) (1) (16)

(220) (254) (161)

(212) (241)

(65)

(35) (134)

(14)

(50) (72) (7) (4) (19) (1) (6)(202) (207) (27) (68)

Non-return:74

Deceased:NMC 2SMC 1MCI 1AD 27VDM 1

Non-AD dementia:MCI-X 2VDM 2

Non-return:74

Deceased:NMC 2SMC 1MCI 1AD 27VDM 1

Non-AD dementia:MCI-X 2VDM 2

54 month¤

(676)*

255 NMC255 NMC255 NMC255 NMC 290 SMC290 SMC290 SMC290 SMC 51 MCI51 MCI51 MCI51 MCI 76 AD76 AD76 AD76 AD

(2)

ApoE4 carrier

107 (28.8%)ApoE4 carrier97 (24.5%)

ApoE4 carrier66 (49.6%)

ApoE4 carrier132 (62.6%)

ApoE4 carrier90 (28.4%)

ApoE4 carrier94 (25.1%)

ApoE4 carrier32 (39.0%)

ApoE4 carrier136 (69.0%)

ApoE4 carrier82 (27.2%)

ApoE4 carrier80 (25.8%)

ApoE4 carrier24 (43.6%)

ApoE4 carrier106 (68.8%)

ApoE4 carrier64 (25.1%)

ApoE4 carrier74 (25.5%)

ApoE4 carrier19 (37.3%)

ApoE4 carrier52 (68.4%)

396 SMC396 SMC396 SMC396 SMC 133 MCI133 MCI133 MCI133 MCI 211 AD211 AD211 AD211 AD

Non-return:112

Deceased:NMC 2SMC 4MCI 5AD 17

Non-AD dementia:PDD 1

Non-return:112

Deceased:NMC 2SMC 4MCI 5AD 17

Non-AD dementia:PDD 1

Non-return:120

Deceased:NMC 3SMC 3MCI 4AD 34

Non-AD dementia:PDD 1

MCI-X 1VDM 3

Non-return:120

Deceased:NMC 3SMC 3MCI 4AD 34

Non-AD dementia:PDD 1

MCI-X 1VDM 3

Returned at 36 months:NMC 11

SMC 1MCI 1AD 3

Returned at 36 months:NMC 11

SMC 1MCI 1AD 3

Returned at 54 months:NMC 1 SMC 4MCI 1AD 1

Returned at 54 months:NMC 1 SMC 4MCI 1AD 1

372 NMC372 NMC372 NMC372 NMC

317 NMC317 NMC317 NMC317 NMC 375 SMC375 SMC375 SMC375 SMC 82 MCI82 MCI82 MCI82 MCI 197 AD197 AD197 AD197 AD

(20) (62)(10)

301 NMC301 NMC301 NMC301 NMC 309 SMC309 SMC309 SMC309 SMC 55 MCI55 MCI55 MCI55 MCI 154 AD154 AD154 AD154 AD

Methodology: Key outcomesMethodology: Key outcomes

11

CLINICAL/COGNITIVE

BIOMARKERS

LIFESTYLE

NEUROIMAGING

Comprehensive clinical blood pathology

Genotype• Apolipoprotein E, WGA in subgroup

Stored fractions (stored in LN within 2.5 hrs of collection) • Serum• Plasma• Platelets• red blood cell,• white blood cell (in dH20) • white blood cell (in RNAlater, Ambion).

Lifestyle information

Detailed dietary information Detailed exercise information Objective activity measures (actigraph – 100 volunteers)Body composition scans (DEXA)

Neuroimaging scans (in 287 volunteers)

PET Pittsburgh Compound B (PiB)

Magnetic Resonance Imaging • 3D T1 MPRAGE •T2 turbospin echo •FLAIR sequence

Clinical and cognitive measures• MMSE, CDR, Mood measures, Neuropsychological battery

Clinical classification information• NINCDS-ADRDA (possible/probable) AD classifications• ICD-10 AD classifications• MCI classifications • Memory complaint status (in HC)

Medical History, Medications and demography

Villemagne / Rowe

1111C-PIB for AC-PIB for A imaging imaging

SUVR3.0

1.5

0.0

ADHC

13

A burden quantification

3.50

2.50

1.00

HC(n = 117)30% pos

MCI(n = 79)64% pos

AD(n = 68)

DLB(n = 14)

FTD(n = 21)

NE

OC

OR

TIC

AL

SU

VR

40-

70 * † * * †

1.50

2.00

3.00

(n = 299)

Villemagne and Rowe

Neo

cort

ical

SU

VR

Age (years)

** PiB+/PiB- SUVR cut-off = 1.5

HC(n=104)

Progression to aMCIProgression to naMCIProgression to AD

Longitudinal PiB PET follow-upLongitudinal PiB PET follow-up

Villemagne / Rowe

Neo

cort

ical

SU

VR

Age (years)

** PiB+/PiB- SUVR cut-off = 1.5

MCI(n=48)

Progression to FTDProgression to VaDProgression to AD

Longitudinal PiB PET follow-upLongitudinal PiB PET follow-up

Villemagne / Rowe

** PiB+/PiB- SUVR cut-off = 1.5

Neo

cort

ical

SU

VR

Age (years)

AD(n=33)

Longitudinal PiB PET follow-upLongitudinal PiB PET follow-up

Villemagne / Rowe

Neo

cort

ical

SU

VR

cb

Time (years)

Mean SUVR AD+

(2.33)

19.2 yr (95%CI 17-23 yrs)

Mean SUVR HC-

(1.17)12.0 yr

(95%CI 10-15 yrs)

2.9%/yr (95%CI 2.5-3.3%/yr)

HC-

MCI+

AD

MCI-

HC+

0 10 20 30 40

AIBL: Aβ deposition over timeAIBL: Aβ deposition over time

AIBL: Relationship between AIBL: Relationship between ““abnormalityabnormality”” and CDR of 1.0 and CDR of 1.0

Plasma (pg/mL)↑/↓ in

MCI or ADHC (n = 576) MCI (n = 69) AD (n = 125)

A1-40 157.7 ± 31 166.8 ± 37 172.3 ± 41 ↑

A1-42 34.8 ± 10 33.6 ± 11 34.5 ± 10 ↓

A1-42/A1-40 0.22 ± 0.06 0.20 ± 0.05* 0.20 ± 0.04* ↓ CSF (pg/mL)

↑/↓ in MCI or ADHC (n = 24) MCI (n = 62) AD (n = 68)

A1-40 9600 ± 3000 9500 ± 3200 8500 ± 2800* ↓

A1-42 403 ± 125 307 ± 114)* 263 ± 83* ↓

tau 104 ± 59 155 ± 109* 156 ± 87* ↑

p-tau-181 31 ± 17 42 ± 29 43 ± 26* ↑*P < 0.05 vs HC.

Data are represented as mean ± standard deviation.

Kester MI, et al. Neurobiol Aging. 2012;33:1591-1598; Rembach A, et al. Alzheimers Dement. In press.

Plasma APlasma A Levels Compared With Levels Compared With CSF ACSF A Levels Levels

Xilinas, Barnham, Bush, Curtain

Prana Biotechnology, founded 1998 (Geoffrey Kempler)

Model: metal-chaperones with moderate Model: metal-chaperones with moderate affinity for metalsaffinity for metals

(nanomolar 10-9) (low picomolar 10-11)

Strong SAR180+ screened

PBT2

Tox testing

Phase Ia & Ib

‘POC’Clinical trials

CQ(PBT1)

POC

non 8-OHq activity

130+ screened

PBT3 – PBT-x> 45 in vivo candidates

Tox. testing

PBT2: SAR based on PBT2: SAR based on rational drug designrational drug design

Follow Ups

Multiple scaffolds

Phase IIa

Barnham, Kripner, Kok, Gautier (Prana Biotechnology), 2002

Analysis of CQ / PBT2 interactions with AßAnalysis of CQ / PBT2 interactions with Aß

CQ and PBT2 induce the formation of low molecular weight Aß oligomers (consistent with dimers/trimers)

Tim Ryan, Blaine Roberts

Effect of PBT2 Effect of PBT2 and placebo and placebo

on the change in on the change in biomarkers biomarkers

from baseline at from baseline at 12 weeks12 weeks

Lannfelt et al., Lancet Neurology (2008)

(A) CSF Aβ42, (B) CSF Aβ40, (C) CSF T-tau, and (D) CSF P-tau.

Data are least mean squares (SE). Scatter plots of individual actual changes from baseline at 12 weeks for CSF Aβ42 and Aβ40 are shown, with mean values (horizontal bars) included for each treatment group.

13% fall in CSF Aβ42

Protein misfolding diseases:Protein misfolding diseases:strategy for disease modificationstrategy for disease modification

24

Stabilize!Neutralize!Clear!

DIAN and A4: early intervention in DIAN and A4: early intervention in preclinical ADpreclinical AD

DIAN-TU

• Autosomal Dominant AD – genetic mutation causing early onset dementia across generations of the same family

• 50% risk of inheriting gene from mutation +ve parent• If mutation +ve penetrance of ADAD is nearly 100%• DIAN observational trial has been following ADAD families since 2009,

giving valuable insight into changes that occur decades before symptoms appear

• PRIMARY AIM: to determine whether Solanezumab or Gantenerumab can prevent, delay or possibly even reverse AD changes in the brain Monthly infusion/injection for 2 years Measures include: MRI, PET scans (PiB, FDG, AV-45), CSF and blood

biomarkers, cognitive function

STARTING TREATMENT BEFORE SYMPTOMS APPEAR MAY GIVE BETTER OUTCOME

Anti-Amyloid Treatment in Asymptomatic Alzheimer’s disease (the A4 Study)

The Melbourne Composite Site

Key Objectives • Cognitive:

– To test the hypothesis that in preclinical AD, an anti-amyloid therapy (solanezumab) will slow Aβ-associated cognitive decline as compared with placebo.

• Neuroimaging:– To test the hypothesis that solanezumab reduces Aβ amyloid burden, as

compared with placebo, as assessed using florbetapir PET imaging ligand.– To determine if there are downstream effects of solanezumab on brain tau

using the novel tau PET imaging ligand, T807.• Biomarkers:

– To assess effects of solanezumab on CSF concentrations of Aβ, p-tau and tau.– To explore the role of polymorphisms in apolipoprotein E (ε carrier [ε4+], ε4

non-carrier [ε4-] and brain derived neurotrophic factor (BDNFVal/Val, BDNFMet) and other genetic loci in the extent to which they moderate the rate of Aβ-related memory decline in both treated and placebo groups.

Key inclusion criteria

– 65-85 years– Evidence of Aβ amyloid (PET)– Asymptomatic (Clinical dementia rating = 0)

Key points: Protocol

• Following screening, 4 weekly solanezumab/placebo (1:1) infusions (IV) for 168 weeks

• Cognitive testing @ baseline then 12/52 from week 6• Aβ amyloid and tau (PET) @ baseline, years 1, 2, 3.• Aβ amyloid and tau (CSF) @ baseline and year 3.• Blood for biomarkers (AIBL protocol)@ baseline,

weeks 12, 24, 48, 108 and 168?

The AIBL Study TeamThe AIBL Study Team

The AIBL Study TeamThe AIBL Study Team

Osca AcostaDavid AmesJennifer AmesManoj AgarwalDavid BaxendaleKiara Bechta-MettiCarlita BevageLindsay BevegePierrick BourgeatBelinda BrownAshley BushTiffany CowieKathleen CrowleyAndrew CurrieDavid DarbyDaniela De FazioDenise El- SheikhKathryn Ellis Kerryn Dickinson  Noel FauxJonathan FosterJurgen FrippChristopher FowlerVeer Gupta Gareth Jones

Jane Khoo Asawari Killedar Neil KilleenTae Wan Kim Eleftheria KotsopoulosGobhathai KunarakRebecca LachovitskiNat LenzoQiao-Xin Li Xiao Liang Kathleen LucasJames LuiGeorgia MartinsRalph Martins Paul MaruffColin MastersAndrew MilnerClaire MontagueLynette MooreAudrey MuirChristopher O’HalloranGraeme O'Keefe Anita PanayiotouAthena PatonJacqui PatonJeremiah Peiffer

Svetlana PejoskaKelly PertileKerryn Pike Lorien PorterRoger PriceParnesh RanigaAlan Rembach Miroslava RimajovaElizabeth RonsisvalleRebecca Rumble Mark RodriguesChristopher RoweOlivier SalvadoJack SachGreg SavageCassandra SzoekeKevin TaddeiTania TaddeiBrett TrounsonMarinos Tsikkos Victor Villemagne Stacey Walker Vanessa WardMichael WoodwardOlga Yastrubetskaya

Neurodegeneration Research Group Neurodegeneration Research Group

• Paul Adlard• Kevin Barnham• Shayne Bellingham• Martin Boland• Ashley Bush• Roberto Cappai• Michael Cater• Robert Cherny• Joe Ciccotosto• Steven Collins• Peter Crouch• Cyril Curtain• Simon Drew• James Duce• Genevieve Evin• Noel Faux

• Michelle Fodero-Tavoletti• David Finkelstein• Catherine Haigh• Andrew Hill• Ya Hui Hung• Vijaya Kenche• Vicky Lawson• Qiao-Xin Li• Gawain McColl• Chi Pham• Blaine Roberts• Laura Vella• Victor Villemagne• Tony White

The University of Melbourne

The Mental Health Research Institute

Collaborators Collaborators

• Alfred Hospital: Catriona McLean

• Austin Health: Chris Rowe, Victor Villemagne

• Chemistry (Uni Melb): Paul Donnelly

• Cogstate: Paul Maruff

• CSIRO (Structural Biology): Jose Varghese, Victor Streltsov,

Stewart Nuttall

• Imperial College London: Craig Ritchie

• Mass General Hospital / Harvard Med School: Rudy Tanzi

• NARI: David Ames, Kathryn Ellis

• SVIMR: Michael Parker, Luke Miles

• Network Aging Research (Heidelberg): Konrad Beyreuther