The Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing AUSTRALIAN ADNI. July 2010 UPDATE

18 month follow-up complete % of MCI progressed to AD Large shifts between NMC and SMC 25% AD, 23% MCI, 8% HC lost

The Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing. Baseline cohort Clinical follow-up Imaging follow-up 18-month Imaging cohort Imaging Cohort Non-returners6 Deceased NMC96 SMC57 MCI53 AD NMC90 SMC32 MCI42 AD

Imaging Cohort Baseline demographics (n=288) HCMCIAD 5753 Age 73.6 ± ± 7.5*74.0 ± 8.7 MMSE 28.8 ± ± 2.3*20.5 ± 4.9* %ApoE  4 43% 54% 71%* 178 *Significantly different from HC, p <0.05

AD 2.33±0.43 MCI 1.89±0.62 HC 1.42±0.41 Neocortical SUVR *†*† * A  burden by clinical classification *Significantly different from HC, p <0.05 † Significantly different from AD, p < % 31% 98%

Preclinical Alzheimer’s Disease? Prevalence of AD (Tobias, 2008) ~15 yrs Prevalence of PiB+ve PET in HC Prevalence (%) Age (years) Prevalence of plaques in HC (Davies, 1988, n=110) (Braak, 1996, n=551) (Sugihara, 1995, n=123)

PiB vs Age and ApoE-  4

† Significantly different from NMC and SMC  4-, p <0.05 * Significantly different from HC and MCI, p <0.05 Neocortical SUVR A  burden by clinical classification NMC  ±0.36 ( n=38 ) MCI 1.95±0.62 ( n=39 ) AD 2.34±0.43 ( n=29 ) SMC  ±0.51 ( n=31 ) NMC  ±0.40 ( n=35 ) SMC  ±0.29 ( n=55 ) † * †

Chetelat G, et al. Brain. In Press Grey matter atrophy vs healthy elderly with no memory complaint SCI MCI AD

GREATER temporal lobe volume (including hippocampus) in PiB +ve healthy vs PiB –ve healthy - Brain reserve or compensatory response to damage? - Better memory performance suggests brain reserve. 3T MRI VBM 5 toolbox Manual HV Chetelat G, et al. Brain. In Press

HC n=159 (89% retention) MCI n=39 (68% retention) AD n=29 (55% retention) * †* † Significantly different from HC (p<0.05) * Significantly different from baseline (p<0.05) PiB INCREASE OVER 18 Months Increase in Neocortical SUVR

SMC non-  4 (n=55) MCI (n=39) AD (n=29) SMC  4 (n=31) nMC non-  4 (n=38) nMC  4 (n=35) * * Significantly different from baseline (p<0.05) Increase in Neocortical SUVR PiB INCREASE OVER 18 Months

HC (n=159) PiB- (n=115) PiB+ (n=44) MCI (n=39) PiB- (n=12) PiB+ (n=27) AD PiB+ (n=28) † Significantly different from PiB- HC (p<0.0002) † Increase in Neocortical SUVR PiB increase much greater in baseline PiB+ve

nMC non-  4 (n=38) PiB- (n=30) PiB+ (n=8) nMC  4 (n=35) PiB- (n=23) PiB+ (n=12) SMC non-  4 (n=55) PiB- (n=48) PiB+ (n=7) SMC  4 (n=31) PiB- (n=14) PiB+ (n=17) Change in Neocortical SUVR Healthy Controls: baseline PiB status has greater influence than ApoE-  4 status on amyloid increase

AIBL follow-up MMSE Decrease in MMSE HCMCIAD †*†* †*†* † Significantly different from HC (p<0.007) * Significantly different from baseline (p<0.03)

-6.0% -5.0% -4.0% -3.0% -2.0% -1.0% 0.0% AIBL follow-up Hippocampal volume † Significantly different from HC (p<0.05) * Significantly different from baseline (p<0.003) Decrease in hippocampal volume HCMCIAD †*†* †*†**

-2.5% -2.0% -1.5% -1.0% -0.5% 0.0% AIBL follow-up Grey matter volume Decrease in grey matter volume HCMCIAD * Significantly different from baseline (p<0.002) †*†***

A  burden vs cognition Baseline Neocortical SUVR CVLT II delayed recall MMSE HCMCIAD r= (p = 0.08) r= (p = 0.04)

Follow-up PiB vs follow-up cognition by baseline diagnosis HC MCI AD Neocortical SUVR CVLT II delayed recall r= (p = 0.03) r= (p = 0.004)

A  burden vs cognition Follow up Neocortical SUVR CVLT II delayed recall at follow-up MMSE at follow-up HC at baseline r= (p = ) r= (p = ) Baseline Neocortical SUVR Change in CVLT II delayed recall r= (p = 0.02) HC MCI AD PiB+ve only

HC (n=170) MCI (n=49) PiB-ve Subjects: 114 Converters to MCI: 2 (2%) AIBL 18 months clinical follow-up PiB+ve Subjects: 56 Converters to MCI/AD: 4 (7%) PiB-ve Subjects: 14 Converters to HC: 2 (14%) Converters to AD: 2 (14%) PiB+ve Subjects: 35 Converters to HC: 2 (6%) Converters to AD: 16 (46%)

(n=49) Hippocampal atrophy ( < ) Neocortical PiB+ve ( SUVR >1.5 ) ApoE  4+ ACCURACYNPV (CI ) (CI ) (CI ) CVLT II delayed recall ( <0.74 ) (CI ) Plasma A  42 /A  40 ( <0.17 ) (CI ) Prediction of Conversion MCI to AD at 18 mths

79 MCI (mean age 73.5 years) AIBL PLUS 18 months clinical follow-up PiB-ve Subjects: n=27 Converters to non-AD Dementia: 4 (15%) Converters to AD: 3 (10%) PiB+ve Subjects: n=52 Converters to AD: 35 (67%)

Neocortical SUVR Time (months) AD MCI HC Longitudinal PiB PET 5-year follow-up

Biomarker Discovery Plasma A  measures are not robust.Plasma A  measures are not robust. Analysis done with RBM and Pfizer has identified candidate biomarkers with moderate diagnostic accuracy.Analysis done with RBM and Pfizer has identified candidate biomarkers with moderate diagnostic accuracy. Plasma ApoE and apoE4 were lower in AD and inversely correlated with Aβ load in the PiB-PET subset. ApoE levels were also significantly lower among ε4 homozygotes.Plasma ApoE and apoE4 were lower in AD and inversely correlated with Aβ load in the PiB-PET subset. ApoE levels were also significantly lower among ε4 homozygotes. GWAS of PiB cohort performed in collaboration with Harvard – results still awaited.GWAS of PiB cohort performed in collaboration with Harvard – results still awaited.

Healthy Elderly PiB+ vs PiB– AD vs Healthy 70% specificity, sensitivity is 76% Peripheral Blood Biomarkers Simon Laws, et al – poster ICAD 2010

ApoE levels within Clinical groups * Tukey HSD, P < vs. HC and SMC, P = vs. MCI * ANOVA, F = , P < n = 387 n = 125 n = 207 n = 367 ~ ~ 0 n=1086 Apolipoprotein E

Both total physical activity and higher intensity physical activity is associated with; –Lower insulin (Regensteiner, 1991) –Lower triglycerides (Lehtonen, 2009) –Higher levels of HDL (Lehtonen, 2009) Higher levels of intense physical activity is associated with better performance in assessments targeting; –Working memory –Attention –Verbal & Spatial Learning and Recall –Executive Functioning Physical Activity

The Australian Imaging, Biomarkers and Lifestyle Study of ageing (AIBL): methodology and baseline characteristics of 1112 individuals recruited for a longitudinal study of Alzheimer’s disease. Ellis KA, et al. International Psychogeriatrics. 2009;21: Amyloid Imaging Results from the Australian Imaging, Biomarkers and Lifestyle Study of Ageing (AIBL). Rowe CC, et al. Neurobiology of Aging ADNI special edition. Online: 15-MAY-2010 DOI information: /j.neurobiolaging Baseline MRI, PiB scans and corresponding clinical data on 237 participants are available from (go to Current Project drop down menu and select AIBL) or from

Financial Supporters Australian Government through CSIRO Pfizer Alzheimer’s Association Alzheimer’s Drug Discovery Foundation An anonymous Foundation

Osca Acosta David Ames Jennifer Ames Manoj Agarwal David Baxendale Kiara Bechta-Metti Justin Bedo Carlita Bevage Lindsay Bevege Pierrick Bourgeat Belinda Brown Ashley Bush Tiffany Cowie Kathleen Crowley Andrew Currie David Darby Daniela De Fazio James Doecke Denise El- Sheikh Kathryn Ellis Kerryn Dickinson Noel Faux Jonathan Foster Jurgen Fripp Christopher Fowler Veer Gupta Gareth Jones AIBL study team Jane Khoo Asawari Killedar Neil Killeen Tae Wan Kim Adam Kowalczyk Eleftheria Kotsopoulos Gobhathai Kunarak Rebecca Lachovitski Simon Laws Nat Lenzo Qiao-Xin Li Xiao Liang Kathleen Lucas James Lui Georgia Martins Ralph Martins Paul Maruff Colin Masters Andrew Milner Claire Montague Lynette Moore Audrey Muir Christopher O’Halloran Graeme O'Keefe Anita Panayiotou Athena Paton Acknowledgements Jacqui Paton Jeremiah Peiffer Svetlana Pejoska Kelly Pertile Kerryn Pike Lorien Porter Roger Price Parnesh Raniga Alan Rembach Miroslava Rimajova Elizabeth Ronsisvalle Rebecca Rumble Mark Rodrigues Christopher Rowe Olivier Salvado Jack Sach Greg Savage Cassandra Szoeke Kevin Taddei Tania Taddei Brett Trounson Marinos Tsikkos Victor Villemagne Stacey Walker Vanessa Ward Bill Wilson Michael Woodward Olga Yastrubetskaya