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ADNI Update (Again). William Jagust. School of Public Health and Helen Wills Neuroscience Institute University of California, Berkeley and Lawrence Berkeley National Laboratory. Disclosures/Conflicts. Consulting : GE Healthcare Bayer Abbott Elan/Janssen Synarc Genentech Merck.
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ADNI Update (Again) William Jagust School of Public Health and Helen Wills Neuroscience Institute University of California, Berkeley and Lawrence Berkeley National Laboratory
Disclosures/Conflicts • Consulting: • GE Healthcare • Bayer • Abbott • Elan/Janssen • Synarc • Genentech • Merck
ADNI PET Achievements • Literature-defined prespecified ROIs • Statistically defined ROIs • Multivariate approaches to prediction of conversion/decline • Cross-sectional and longitudinal PIB studies • Biomarker comparisons (PIB-CSF)
Statistically Defined ROIs in AD and MCI for Longitudinal Progression 12 month trial, 25% treatment effect (power = 0.8, a = 0.05, 2-tailed) 61 AD patients/arm 217 MCI patients/arm AD MCI Chen et al, Neuroimage 2010
26 MCI patients with a higher HCI 71 MCI patients with a lower HCI 21 MCI patients with a smaller hippo vol 76 MCI patients with a larger hippo vol 20 MCI patients with both a higher HCI & smaller hippo vol 38 MCI patients with neither a higher HCI or smaller hippo vol Chen et al, submitted
Enrollment in ADNI PiB Studies to June 2010(All Data Are Available On The LONI Website) Baseline – 103 Subjects at 14 PET Sites • NL: 19, 78±5 y/o, MMSE 29±1 • MCI: 65, 75±8 y/o, MMSE 27±2 • AD: 19, 73±9 y/o, MMSE 22±3 1 Yr Longitudinal Studies – 80 Subjects • NL: 17/19 (89%) • MCI: 50/65 (77%) • AD: 13/19 (68%) 2 Yr Longitudinal Studies – 39 Subjects • NL: 11 • MCI: 26 • AD: 2 3 Yr Longitudinal Studies – 2 Subjects • NL: 2 • MCI: 0 • AD: 0 • PiB Baseline Entry Times • 20 subjects at ADNI true baseline • 69 subjects at ADNI 12 months • 14 subjects at ADNI 24 months Total 224 PiB Scans Mathis, Univ Pittsburgh
Baseline PiB 9/19 Normals PiB+ 47/65 MCI PiB+ 17/19 AD PiB+ Longitudinal PiB MCI Converters (1-2 years) 21/47 PiB+ 3/18 PiB- Mathis, Univ Pittsburgh
Extent of Hypometabolism as a Predictor of MCI Conversion Timing of conversion associated with more hypometabolic voxels Foster, Univ Utah
ROI Generation Identification of ROIs from voxelwise analyses in the literature Peak voxels plotted in MNI coordinates, smoothed, thresholded Post Cingulate Gyrus L Inf Temporal Gyrus R Inf Temporal Gyrus L Angular Gyrus R Angular Gyrus
Combined = 12 fold higher risk of conversion FDG AVLT Landau et al, Neurology 2010
Prediction of Cognitive Decline in Normal ADNI Participants Define normal/abnormal cutoffs using external samples Classification of each subject as normal/abnormal on each marker Determine whether normal/abnormal status predicts cognitive change
Participants 92 cognitively normal ADNI participants (FDG-PET, structural MRI, and ApoE genotyping) Mean followup 2.7 +/- 0.8 yrs Age 75.8 +/- 4.8 yrs Education 15.9 +/- 3.2 yrs Female 39% ApoE4 carriers 23% MMSE 28.9 +/- 1.1
FDG-PET (UC Berkeley) Sensitivity = 90% Specificity = 93% Alzheimer’s patients N = 35 Age = 67.2 +/- 10.4 57% Female Normal older subjects N = 39 Age = 73.1 +/- 5.8 62% Female Mean FDG ROI uptake (relative to cerebellum/vermis region)
Hippocampal volumes (UCSF) Sensitivity = 94% Specificity = 95% Alzheimer’s patients N = 51 Age = 78.6 +/- 8.5 43% Female Normal older subjects N = 53 Age = 74.3 +/- 7.5 53% Female Bilateral hippocampal volume (adjusted for total intracranial volume)
Normals stratified into high/low memory No association between high/low performer status and status on any of the normal/abnormal markers Neither group showed significant ADAS-cog change Median split of normals into high/low performers based on baseline performance on the Auditory Verbal Learning Test (free recall) Auditory Verbal Learning Test
Statistical analyses – multivariateLow performers Parameter estimate p-value Baseline FDG-PET imaging ns Hippocampal volume ADAS-cog decline 1.31 +/- 0.58 0.03 ApoE4 carrier status 0.99 +/- 0.66 0.03 age, sex, education Abnormal hipp volume and ApoE4 carriers 2.3 pts/yr decline relative to normal
Defining the Technical Sources of Variability in ADNI PET Data • What is the effect of changing scanners in a longitudinal study? • How variable are longitudinal measurements on different scanners? • How does instrument variation compare to site variation? • What is the effect of processing on variation?
Effects of Scanner Switch in a Longitudinal Study Rate of FDG Change (in ROI) Stable Stable Switch Switch Stable Switch Normals MCI AD
Variability by Scanner HRRT 2 2 6 7 16 SD of Rate of Change Normal MCI AD
The Future: ADNI2 and GO • Cross-sectional and longitudinal studies of Ab deposition with AV-45 • Comparison with other biomarkers in prediction/multivariate approaches • Comparison with other biomarkers as outcomes • Replication of statistical ROI approach using identical ROI • Further investigate sources of variability
Acknowledgements Julie Price Norman Foster Dan Bandy Danielle Harvey Norbert Schuff Mike Weiner Susan Landau Bob Koeppe Eric Reiman Kewei Chen Chet Mathis The ADNI Executive Committee, Site Investigators, Participants National Institute on Aging/Neil Buckholtz ISAB Alzheimer’s Association