Alzheimer’s Disease Neuroimaging Initiative (ADNI) - PowerPoint Presentation

Alzheimer’s Disease Neuroimaging Initiative (ADNI) Ronald C. Petersen, PhD, MD Co-Director, Clinical Core Mayo Clinic College of Medicine Rochester, MN Alzheimer’s Disease International Toronto March 28, 2011

Disclosures Pfizer, Inc. (Wyeth): Chair, DMC Janssen Alzheimer’s Immunotherapy Program (Elan): Chair, DMC Elan Pharmaceuticals: Consultant GE Healthcare: Consultant Funding: National Institute on Aging U01 AG006786, P50 AG 016574, R01 AG011378, R01 AG034676 and the Robert and Clarice Smith and Abigail Van Buren Alzheimer’s Disease Research Program

M. Weiner, P. Aisen, R Petersen, C. Jack, W. Jagust, J Trojanowski, L. Shaw, A. Toga, L. Beckett, D. Harvey, C Mathis, A. Gamst. R. Green, A Saykin, J Morris, L Thal (D) Neil Buckholz, David Lee, Mark Schmidt Industry Scientific Advisory Board (ISAB) And Site PIs, Study Coordinators and 821 subjects enrolled in 58 Sites in US and Canada FUNDED BY NATIONAL INSTITUTE ON AGING NIBIB,NIMH,NINR,NINDS,NCRR,NIDA and CIHR

ADNI Structure Executive Committee Clinical Core MRI Core PET Core Biomarker Core Biostatistics CoreInformatics CoreGenetics CoreNeuropathology Core

GOALS OF ADNI Validate biomarkers as measures of change Validate biomarkers as diagnostics or predictors: symptomatic and presymptomatic Optimize biomarker methods Standardize biomarker methods Establish a world-wide network for clinical AD studies and treatment trials

ADNI Naturalistic study of AD progression 200 NORMAL 4 yrs 400 MCI 4 yrs 200 AD 2 yrs Visits every 6 months 57 sites Clinical, blood, LP Cognitive Tests 1.5T MRI Some also have 3.0T MRI (25%) FDG-PET (50%) PiB-PET (approx 100) All data in public database: UCLA/LONI/ADNI: No embargo of data

AD Progression Jack et al: Lancet Neurology, 2010 FDG PET Function (ADL) Cognitive performance MRI hippocampal volume CSF Tau Amyloid imaging CSF abeta42 Abnormal Normal Time Pre-symptomatic EMCI LMCI Dementia

AD Progression Jack et al: Lancet Neurology, 2010 FDG PET Function (ADL) Cognitive performance MRI hippocampal volume CSF Tau Amyloid imaging CSF abeta42 Abnormal Normal Time Pre-symptomatic EMCI LMCI Dementia

AD Progression Jack et al: Lancet Neurology, 2010 FDG PET Function (ADL) Cognitive performance MRI hippocampal volume CSF Tau Amyloid imaging CSF abeta42 Abnormal Normal Time Pre-symptomatic EMCI LMCI Dementia

AD Progression Jack et al: Lancet Neurology, 2010 FDG PET Function (ADL) Cognitive performance MRI hippocampal volume CSF Tau Amyloid imaging CSF abeta42 Abnormal Normal Time Pre-symptomatic EMCI LMCI Dementia

AD Progression Jack et al: Lancet Neurology, 2010 FDG PET Function (ADL) Cognitive performance MRI hippocampal volume CSF Tau Amyloid imaging CSF abeta42 Abnormal Normal Time Pre-symptomatic EMCI LMCI Dementia

Clinical Core Paul Aisen, UCSD Ron Petersen, Mayo Clinic

ADNI Conversion Rates NL 229 MCI 398 AD 192 3003446-26 192 225 215 12+ 2 158+ 2 15 Year Normal  MCI MCI  AD 0-1 1.4% (0.0-3.2) 16.0% (11.3-20.4) 1-2 2.4% (0.0- 4.7) 23.9% (19.0-29.5) 2-3 0.0% (0.0-3.4) 9.5% (5.8-13.5)

ADNI Withdrawal Rates 3003446-26 p<0.001 P<0.001

3003731-7 ADAS Cog 11

3003731-8 ADAS Cog Change

Summary Clinical groups are performing as expected MCI to AD rates are accelerating from 16%/yr to 24%/yr Significant variability in clincal instruments Opportunity for imaging and fluid biomarkers to define subsets

POWER CALCULATIONS Hypothetical clinical trial Two arms: Treatment and Placebo Estimate the sample size/arm required to detect a significant treatment effect 1 year trial 25% slowing of rate of changetwo-sided tests, alpha=0.05, 80% power 23 ADNI publications on longitudinal change

Test Sample Size MMSE 803 RAVLT 607 ADAS 592 CDR SOB 449 POWER OF CLINICAL/COGNITIVE TESTS 25% CHANGE 1YR STUDY (2 ARM) : AD (155 Subjects)

POWER OF CLINICAL/COGNITIVE TESTS 25% CHANGE 1YR STUDY (2 ARM) : MCI (355 Subjects) Test Sample Size RAVLT 6056 ADAS 4547 MMSE 3879 CDR SOB 853

MRI CORE Clifford Jack MD Mayo Clinic 60 publications on MRI

FREESURFER PARCELATION

Feb-09; N. Schuff

Mean Cortical Thickness Change over 12 Months Holland et al. Diagnosed as NC Diagnosed as AD +2% -2% Lateral View Medial View

Baseline White Matter Hyperintensities Normal MCI AD Normal and MCI had similar WMH distributions; increased WMH burden in AD with suggestions of anterior-posterior progression

26 1.5T MRI Comparisons - AD (n=69) Lab Variable SS/arm Alexander L. Hippo. Formation 334 Dale Whole Brain 207 Schuff - FS Hippocampus 201 Dale Ventricles 132 Dale Hippocampus 126 Studholme Temporal lobe % change 123 Schuff - FS Ventricles 119 Studhome CV - % change 106 Fox VBSI % change 105 Fox BSI % change 71 Thompson CV - % change 54

PET CORE William Jagust UC Berkeley 12 papers on PET

Normal Aging vs. Alzheimer’s Disease FDG PET Normal AD

FDG-PET ANALYSIS Jagust Lab Composite ROI - Based on published coordinates

Defined using data from 27 training-set patients using bootstrap with replacement Number of AD patients per group needed in a 12-month multi-center RCT to detect a 25% treatment effect with power=80%, p=0.05 & no need to correct for multiple comparisons FDG PET ADAS-COG11 MMSE 61 612 493 Characterized in 29 test-set patients (excluding HiRez & HRRT scanners) Statistical ROI of12-Month CMRgl declines Reiman et al Banner Alzheimer Institute

31 PET Comparisons - AD (n=36) Lab Variable SS/arm Foster hypometabolism1 638 Foster hypometabolism2 549 Jagust ROI-avg 412 Reiman CV-fROI 96

32 PET Comparisons - MCI (n=81) Lab Variable SS/arm Jagust ROI- avg 7649 Foster hypometabolism1 1876 Foster hypometabolism2 1280 Reiman CV - fROI 280

First Conclusion In general atrophy, measured by MRI is a more sensitive and robust measure of rate of change Hippocampus, ventricles, not that different With the exception of Eric Reiman’s statistically generated ROI, PET measures have less statistical power to detect a slowing of change than MRI BUT PET may be more sensitive to detect a treatment effect which improves function!!!

Biomarker Core John Trojanowski, U Penn Les Shaw, U Penn

BIOMARKERS John Trojanowski, Les Shaw, U Penn. 24 papers on biomarkers p<0.0001, for each of the 5 biomarker tests for AD vs NC and for MCI vs NC. For AD vs MCI:p<0.005, Tau; p<0.01, A b 1-42; p<0.01, P-Tau 181P; p<0.0005, Tau/A b 1-42 ; p<0.005, P-Tau 181P /A b 1-42 . Mann-Whitney test

Survival analyses for ADNI MCI subjects: progression to AD for BASELINE CSF biomarkers > or < cutpoints A b 42 < 192 pg/mL t-tau/A b 42 > 0.39 riskTAA2 > 0.34 As of June 28, 2010

Lower CSF Aβ1-42 is Associated with Increased Rates of Atrophy in MCI Consistent with the view that MCI patients with low CSF Aβ 1–42 have the AD

A b 1-42 <192pg/mL A b 1-42 >192pg/mL ALL -5.6±4.7 -2.6±4.1 AD -8.0±5.9 -4.2±3.5 MCI -4.8±3.6 -2.9±3.7 NC -3.6±3.2 -2.2±4.3 ADNI: HC atrophy and CSF A β

PiB Imaging Chet Mathis, U Pitt

PIB Imaging:Chet Mathis FDG PIB

Follow-Up of PIB-Positive ADNI MCI’s PiB(+) 47 Converters to AD 21 PiB(-) 18 Converters to AD 3 ADNI PiB MCI’s N = 65, 12 mo. follow-up

Follow-Up of ADNI PiB Controls ADNI PiB Ctrl’s N = 19, 12 mo. follow-up PiB(+) 9 Converters to MCI 2 PiB(-) 10 Converters to MCI 0

PIB vs CSF Biomarkers: A  Penn Autopsy Sample (56 AD, 52 Cog normal) 192 pg/ml Total N = 55 (11 Control, 34 MCI, 10 AD)

PREDICTING TIME TO CONVERSION Time to conversion from MCI to AD (using Cox proportional hazards) is predicted by Baseline ADAS-cog FAQ Use of acetylcholinesterase inhibitors Baseline biomarkers: hippocampus, FDG PET, PIB PET, CSF

PREDICTING RATE OF ADAS COG-11 CHANGE In controls: Hippocampal volume In MCI: ApoE, CSF AB and tau, FDG PET, PIB PET, hippocampal and ventricular volumes In AD: CSF tau and FDG PET

PREDICTING FUTURE RATE OF HIPPOCAMPAL ATROPHY Controls: CSF AB and tau MCI: APOE, CSF AB and tau, FDG and PIB PET AD: CSF AB and tau

INFORMATICS CORE Arthur Toga UCLA

ADNI Extensions ADNI GO ADNI 2 World Wide ADNI

NIA GRAND OPPORTUNITES (GO) GRANT GO grant ($24 million from NIA) will Add a cohort of 200 early MCI subjects (EMCI) LPs on 100% of these new subjects Follow controls/MCI an additional year F18 amyloid imaging on ALL existing and new ADNI/GO subjects (AV-45) Complete analysis of all ADNI data

ADNI 2Clinical Core

Mild Cognitive Impairment Normal MCI AD 0 0.5 1 CDR 3004153-1 ADNI 1 (LMCI) ADNI GO ADNI 2 ( EMCI)

Alzheimer’s Disease Neuroimaging Initiative Normal LMCI AD ADNI 1 EMCI ADNI GO EMCI LMCI AD ADNI 2 Normal

SCOPE OF ADNI 2 ADNI2 ($69 million) will: Continue to follow more than 400 controls and MCI from ADNI 1 for 5 more years Enroll: 100 additional EMCI (supplements 200 from GO) 150 new controls, LMCI, and AD MRI at 3,6, months and annuallyF18 amyloid (AV-45)/FDG baseline and Yr2LP on all subjects at enrollmentGenetics

9/2009 N. Schuff

SUMMARY Standardized methods Rate of change: MRI Predictors: many Earlier diagnosis: caution Clinical trial designData sharingWorld wide impact

These slides and much more atADNI-INFO.ORG All data at www.loni.ucla.edu/ADNI/

MANY THANKS TO NIA: Drs Hodes and Buckholz Industry Scientific Advisory Board Foundation for NIH ADNI Core leaders and Core members ADNI Site PIsOur volunteer subjects

ADNI 1 Private Partner Scientific Board: 20 companies/2 non-profits PIB/PET Supplement : Alzheimer’s Association and GE Healthcare Cerebrospinal Fluid Extension: Alzheimer’s Association, AstraZeneca, Cure Alzheimer’s Fund, Merck, Pfizer and an anonymous foundation Genome-Wide Genotyping : Gene Network Sciences, Merck, Pfizer and an anonymous foundation Genome-Wide Genotyping Genetic Analysis: NIBIB, Merck, Pfizer and an anonymous foundation

Publications Trojanowski JQ. Searching for the biomarkers of Alzheimer’s. Practical Neurol., 3:30-34, 2004. Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack CR, Jagust W, Trojanowski JQ, Toga AW, Beckett L.: Ways toward an early diagnosis in Alzheimer’s disease: The Alzheimer’s Disease Neuroimaging Initiative (ADNI), Alzheimer’s & Dementia 1:55-66, 2005. PMID 17476317 PMC1864941 Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack C, Jagust W, Trojanowski JQ, Toga AW, Beckett L. The Alzheimer’s Disease Neuroimaging Initiative. Neuroimaging Clin N Am, 15(4):869-77, 2005. PMID 16443497 PMC2376747 Fukuyama H. Neuroimaging in mild cognitive impairment. Rinsho Shinkeigaku, 46(11):791-4, 2006. PMID 17432181 Iwatsubo T. Beta-and gamma-secretases. Rinsho Shinkeigaku, 46(11):925-6, 2006. PMID 17432221 Leow AD, Klunder AD, Jack CR Jr, Toga AW, Dale AM, Bernstein MA, Britson PJ, Gunter JL, Ward CP, Whitwell JL, Borowski BJ, Fleisher AS, Fox NC, Harvey D, Kornak J, Schuff N, Studholme C, Alexander GE, Weiner MW, Thompson PM; ADNI Preparatory Phase Study.: Longitudinal stability of MRI for mapping brain change using tensor-based morphometry. Neuroimage, 31(2):627-40, 2006. PMID 16480900 PMC1941663 Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack C, Jagust W, Trojanowski JQ, Toga AW, Beckett LA. Ways toward an early diagnosis in Alzheimer’s disease: The Alzheimer’s Disease Neuroimaging Initiative. Cognition and Dementia, 5(4):56-62, 2006. Arai H. Alzheimer’s Disease Neuroimaging Initiative and mild cognitive impairment. RinshoShinkeigaku, 47(11):905-7, 2007. PMID 18210831 Fletcher PT, Powell S, Foster NL, Joshi SC. Quantifying metabolic asymmetry modulo structure in Alzheimer’s disease. Inf Process Med Imaging, 20:446-57, 2007. PMID 17633720 Ihara Y. Overview on Alzheimer’s disease. Rinsho Shinkeigaku, 47(11):902-4, 2007. PMID 18210830 Murayam S, Saito Y. Neuropathology of mild cognitive impairment Alzheimer’s disease. Rinsho Shinkeigaku, 47(11): 912-4, 2007. PMID 18210833 Haschke M, Zhang YL, Kahle C, Klawitter J, Korecka M, Shaw LM, Christians U. HPLC-atmospheric pressure chemical ionization MS/MS for quantification of 15-F2t-isoprostane in human urine and plasma. Clinical Chemestry, 53:489-497, 2007.PMID 17259231 Shaw LM, Korecka M, Clark CM, Lee VM-Y, and Trojanowski JQ. Biomarkers of neurodegenertaion for diagnosis and monitoring therapeutics. Nat. Rev. Drug Discovery, 6:295-303, 2007.PMID 17347655 Fan Y, Batmanghelich N, Clark CM, Davatzikos C, the Alzheimer’s Disease Neuroimaging Initiative. Spatial Patterns of Brain Atrophy in MCI Patients, Identified via High-Dimensional Pattern Classification, Predict Subsequent Cognitive Decline. NeuroImage, 39(4): 1731-1743, 2008. PMID 18053747 Hampel H, Burger K, Teipel SJ, Bokde ALW, Zetterberg H, Blennow K. Core Candidate Neurochemical and Imaging Biomarkers of Alzheimer’s Disease. Alzheimer’s & Dementia, 4(1):38-48, 2008. PMID 18631949 Nestor SM, Rupsingh R, Borrie M, Smith M, Accomazzi V, Wells JL, Fogarty J, Bartha R, and the Alzheimer’s Disease Neuroimaging Initiative. Ventricular Enlargement as a Possible Measure of Alzheimer’s Disease Progression Validated Using the Alzheimer’s Disease Neuroimaging Initiative Database. Brain 131(Pt 9):2443-54, 2008. PMID 18669512 PMC2724905

Shaw LM. PENN biomarker core of the Alzheimer’s Disease Neuroimaging Initiative. Neurosignals, 16(1):19-23, 2008. PMID 18097156 PMC2696349 Visser PJ, Verhey FRJ, Boada M, Bullock R, De Deyn PP, Frisoni GB, Frolich L, Hampel H, Jolles J, Jones R, Minthon L, Nobili F, Olde Rikkert M, Ousset P-J, Rigaurd A-S, Scheltens P, Soininen H, Spiru L, Touchon J, Tsolaki M, Vellas B, Wahlund LO, Wilcock G, Winblad B, DESCRIPA study group. Development of Screening Guidelines and Clinical Criteria for Predementia Alzheimer’s Disease. Neuroepidemiology, 30:254-265, 2008. PMID 18515975 Boyes RG, Gunter JL, Frost C, Janke AL, Yeatman T, Hill DL, Bernstein MA, Thompson PM, Weiner MW, Schuff N, Alexander GE, Killiany RJ, Decarli C, Jack CR, Fox NC, for the ADNI study.: Intensity non-uniformity corrections using N3 on 3-T scanners with multichannel phased array coils. Neuroimage, 39(4):1752-62, 2008. PMID 18063391 PMC2562663 Jack CR Jr, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, Borowski B, Britson PJ, Whitwell J, Ward C, Dale AM, Felmlee JP, Gunter JL, Hill DL, Killiany R, Schuff N, Fox-Bosetti, S, Lin C, Studholme C, Decarli CS, Gunnar Krueger, Ward HA, Metzger GJ, Scott KT, Mallozzi R, Blezek D, Levy J, Debbins JP, Fleisher AS, Albert M, Green R, Bartzokis G, Glover G, Mugler J, Weiner MW, ADNI Study. The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods. J Magn Reson Imaging, 27(4):685-91, 2008. PMID 18302232 PMC2544629 Hua X, Leow AD, Lee S, Klunder AD, Toga A, Lepore N, Chou Y-Y, Brun C, Chiang M-C, Barysheva M, Jack Jr. CR, Bernstein MA, Britson PJ, Ward CP, Whitwell JL, Borowski B, Fleisher AS, Fox NC, Boyes RG, Barnes J, Harvey D, Kornak J, Schuff N, Boreta L, Alexander GE, Weiner MW, Thompson PM, the Alzheimer’s Disease Neuroimaging Initiative. 3D characterization of brain atrophy in Alzheimer’s disease and mild cognitive impairment using tensor-based morphometry. NeuroImage, 41(1):19-34, 2008. PMID 18378167 PMC2556222 Frisoni GB, Henneman WJP, Weiner MW, Scheltens P, Vellas B, Reynish E, Hudecova J, Hampel H, Burger K, Blennow K, Waldemar G, Johannsen P, Wahlund L-O, Zito G, Rossini PM, Winblad B, Barkhof F, Alzheimer’s Disease Neuroimaging Initiative. The pilot European Alzheimer’s Disease Neuroimaging Initiative of the European Alzheimer’s Disease Consortium. Alzheimer’s & Dementia, 4(4): 255-64, 2008. PMID 18631976 PMC2657833 Morra JH, Tu Z, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N, Hua X, Toga AW, Jack CR Jr, Weiner MW, Thompson PM, the Alzheimer’s Disease Neuroimaging Initiative. Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer’s disease mild cognitive impairment , and elderly controls. Neuroimage, 43(1): 59-68, 2008. PMID 19041724 PMC2624575 Hua X, Leow AD, Parikshak N, Lee S, Chiang MC, Toga AW, Jack CR Jr, Weiner MW, Thompson PM, the Alzheimer’s Disease Neuroimaging Initiative. Tensor-based morphometry as a neuroimaging biomarker for Alzheimer’s disease: An MRI study of 676 AD, MCI, and normal subjects. NeuroImage, 43(3):458-69, 2008. PMID 18691658 PMC in Process – NIHMSID 78543 Becker RE, Greig NH. Alzheimer’s disease drug development: old problems require new priorities. CNS Neurol Disord Drug Targets, 7(6):499-511, 2008. PMID 19128207 Clark CM, Davatzikos C, Borthakur A, Newberg A, Leight S, Lee VM-Y, Trojanowski JQ. Biomarkers for early detection of Alzheimer pathology. NeuroSignals, 16:11-18, 2008 PMID 18097155 Mormino EC, Kluth JT, Madison CM, Rabinovici GD, Baker SL, Miller BL, Koeppe RA, Mathis CA, Weiner MW, Jagust WJ, and the Alzheimer’s Disease Neuroimaging Initiative. Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects. Brain, 132(Pt 5):1310-23, 2009. PMID 19042931 PMC2677792

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Weiner MW, Thal L, Jack C, Jagust W, Toga A, Beckett L, Peterson R: Alzheimer’s disease neuroimaging initiative, Alzheimer’s Disease and Parkinson’s Diseases: Insights, Progress and Perspectives 7 th International Conference, Sorrento, Italy March 9-13, 2005. Weiner MW, Thal L, Petersen R, Jagust W, Trojanowski J, Toga A, Beckett L, Jack C.: Alzheimer’s disease neuroimaging initiative. Poster from 2 nd Congress of the International Society for Vascular Behavioural and Cognitive Disorders, Florence, Italy, June 8-12, 2005. Weiner MW, Thal LJ, Petersen RC, Jack Jr. CR, Jagust W, Trojanowski JQ, Beckett LA. Imaging biomarkers to monitor treatment effects for Alzheimer’s Disease trials: The Alzheimer’s Disease Imaging Initiative. Alzheimer’s Association 10th International Conference on Alzheimer’s Disease and Related Disorders. Madrid, Spain. 2(3 Suppl 1): S311 (P2-254). July 15-20, 2006.Weiner MW, Thal L, Petersen R, Jack C, Jagust W, Trojanowski J, Shaw L, Toga A, Beckett L, Stables L, Mueller S, Lorenzen P, Schuff N. MRI of Alzheimer’s and Parkinson’s: The Alzheimer’s Disease Neuroimaging Initiative (ADNI-Info.Org). Neurodegenerative Dis, 4(Suppl 1):276, 832, 2007.Gunter JL, Bernstein MA, Britson PJ, Felmlee JP, Schuff N, Weiner M, Jack CR.: MRI system tracking and correction using the ADNI phantom. Alzheimer’s & Dementia, 3(3 Suppl 2):S109 P-038. Second Alzheimer’s Association International Conference on Prevention of Dementia, Washington, DC. June 9-12, 2007. Fletcher PT, Wang AY, Tasdizen T, Chen K, Jagust WJ, Koeppe RA, Reiman EM, Weiner MW, Minoshima S, Foster NL.: Variability of Normal Cerebral Glucose Metabolism from the Alzheimer’s Disease Neuroimaging Initiative (ADNI): Implication for Clinical Trials. Annals of Neurology, 62(Suppl 11):S52-3. American Neurological Association 132 nd Annual Meeting, Washington, DC. October 7-10, 2007. Chen K, Reiman EM, Alexander GE, Lee W, Reschke C, Smilovici O, Bandy D, Weiner MW, Koeppe RA, Jagust WJ.: Six-month cerebral metabolic declines in Alzheimer’s Disease, amnestic mild cognitive impairment and elderly normal control groups: Preliminary findings from the Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s & Dementia, 3(3 Suppl 2):S174 O1-04-05. Second Alzheimer’s Association International Conference on Prevention of Dementia, Washington, DC. June 9-12, 2007. Chen K, Reiman EM, Alexander GE, Smilovici O, Lee W, Reschke C, Bandy D, Foster NL, Weiner MW, Koeppe RA, Jagust WJ.: The pattern and severity of FDG PET abnormalities in Alzheimer’s Disease and amnestic mild cognitive impairment: Preliminary findings from the Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s & Dementia, 3(3 Suppl 2):S103 P-024. Second Alzheimer’s Association International Conference on Prevention of Dementia, Washington, DC. June 9-12, 2007. Alexander GE, Chen K, Reiman EM, Aschenbrenner M, Merkley TL, Hanson KD, Dale AM, Berstein MA, Kornak J, Schuff N, Fox NC, Thompson PM, Weiner MW, Jack CR Jr.: Regional gray matter reductions in Alzheimer’s dementia and amnestic mild cognitive impairment: Preliminary findings from the Alzheimer’s Disease Neuroimaging Initiative using voxel-based morphomety. Alzheimer’s & Dementia, 3(3 Suppl 2):S102 P-020. Second Alzheimer’s Association International Conference on Prevention of Dementia, Washington, DC, June 9-12, 2007. Weiner MW, Thal L, Petersen R, Jack C, Jagust W, Trojanowski J, Shaw L, Toga A, Beckett L.: The Alzheimer’s Disease Imaging Initiative: Progress report. Alzheimer’s & Dementia, 3(3 Suppl 2):S174 O1-04-04. Second Alzheimer’s Association International Conference on Prevention of Dementia, Washington, DC. June 9-12, 2007. Abstracts

Weiner MW, Aisen P, Petersen R, Jack C, Jagust W, Trojanowski J, Shaw L, Toga A, Beckett L, Gamst A. Alzheimer’s Disease Neuroimaging Initiative (ADNI): Progress Report. 11 th International Conference on Alzheimer’s Disease, Chicago, IL, 2008. Weiner MW. Alzheimer’s Disease Neuroimaging Initiative (ADNI): Progress Report. S1-01-01, Page T99, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Reiman EM, Chen K, Ayutyanont N, Lee W, Bandy D, Reschke C, Alexander GE, Weiner MW, Koeppe RA, Foster NL, Jagust WJ. Twelve-Month Cerebral Metabolic Declines in Probable Alzheimer’s Disease and Amnestic Mild Cognitive Impairment: Preliminary Findings From the Alzheimer’s Disease Neuroimaging Initiative (ADNI), 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.Schuff N, Woerner N, Boreta L, Kornfield T, Jack Jr. CR, Weiner MW. Rate of Hippocampal Atrophy in the Alzheimer’s Disease Neuroimaging Initiative (ADNI): Effects of ApoE4 and Value of Additional MRI Scans. O3-03-06, Page T164, 11th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Donohue M, Aisen P, Gamst A, Weiner M. Using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Data to Improve Power For Clinical Trials, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Alexander GE, Hanson KD, Chen K, Reiman EM, Bernstein MA, Kornak J, Schuff NW, Fox NC, Thompson PM, Weiner MW, Jack CR. Six-Month MRI Gray Matter Declines in Alzheimer Dementia Evaluated by Voxel-Based Morphometry with Multivariate Network Analysis: Preliminary Findings from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). IC-03-06, Page T8, & P1-216, Page T273, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Landau SM, Madison C, Wu D, Cheung C, Foster N, Reiman E, Koeppe R, Weiner M, Jagust WJ. Pinpointing Change in Alzheimer’s Disease: Longitudinal FDG-PET Analysis From the Alzheimer’s Disease Neuroimaging Initiative (ADNI). PI-258, Page T291, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Landau SM, Madison C, Wu D, Cheung C, Foster N, Reiman E, Koeppe R, Weiner M, Jagust WJ. Pinpointing Change in Alzheimer’s Disease: Longitudinal FDG-PET Analysis From the Alzheimer’s Disease Neuroimaging Initiative (ADNI). PI-258, Page T291, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Gunter JL, Borowski B, Bernstein M, Ward C, Britson P, Felmlee J, Schuff N, Weiner M, Jack C. Systematics of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Phantom. P2-011, Page T369, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.Gunter JL, Borowski B, Britson P, Bernstein M, Ward C, Felmlee J, Schuff N, Weiner M, Jack C. Alzheimer’s Disease Neuroimaging Initiative (ADNI) Phantom and Scanner Longitudinal Performance. P2-012, Page T370, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.Lee W, Langbaum JBS, Chen K, Recshke C, Bandy D, Alexander GE, Foster NL, Weiner MW, Koeppe RA, Jagust WJ, Reiman EM. Categorical and Correlational Analyses of Baseline Fluorodeoxyglucose Positron Emission Tomography Images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). IC-P1-036, Page T23 & P2-037, Page T379, 11th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.Petersen RC, Aisen P, Beckett L, Donohue M, Weng Q, Salmon D, Weiner M. Alzheimer’s Disease Neuroimaging Initiative (ADNI): Baseline Characteristics. P3-040, Page T528, 11th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.

Gunter JL, Borowski B, Britson P, Bernstein M, Ward C, Felmlee J, Schuff N, Weiner M, Jack CR, the Alzheimer’s Disease Neuroimaging Initiative. ADNI Phantom & Scanner Longitudinal Performance. IC-P3-181, Page T80, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Schuff N, Woerner N, Boreta L, Kornfield T, Jack Jr. CR, Weiner MW. Rate of Hippocampal Atrophy in the Alzheimer’s Disease Neuroimaging Initiative (ADNI): Effects of APOE4 and Value of Additional MRI Scans. IC-P3-213, Page T91, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Vanderstichele H, De Meyer G, Shapiro F, Engelborghs B, DeDeyn PP, Shaw LM, and Trojanowski JQ. Alzheimer’s disease biomarkers: From concept to clinical utility. In: Biomarkers For Early Diagnosis Of Alzheimer’s Disease, D. Galimberti, E. Scarpini (Eds.), Nova Science Publishers, Inc., Hauppauge, NY, pp. 81-122, 2008.Chen K, Reschke C, Lee W, Bandy D, Foster NL, Weiner MW, Koeppe RA, Jagust WJ, Reiman EM. The Pattern of Cerebral Hypometablism in Amnestic Mild Cognitive Impairment and Its Relationship to Subsequent Conversion to Probable Alzheimer’s Disease: Preliminary Findings from the Alzheimer’s Disease Neuroimaging Initiative. IC-P2-086, Page T42, 11th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Reiman EM, Chen K, Ayutyanont N, Lee W, Bandy D, Reschke C, Alexander GE, Weiner MW, Koeppe RA, Foster NL, Jagust WJ. Twelve-Month Cerebral Metabolic Declines in Probable Alzheimer’s Disease and Amnestic Mild Cognitive Impairment: Preliminary Findings from the Alzheimer’s Disease Neuroimaging Initiative. IC-P2-128, Page T58, 11 th International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008. Posner H, Cano S, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S, Hobart J. The ADAS-cog’s Performance as a Measure - Lessons from the ADNI Study: Part 1 – Evaluation Using Traditional Psychometric Methods. AAN 61 st Annual Meeting, Seattle, WA, April 25-May 2, 2009. Hobart J, Posner H, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S, Cano S. The ADAS-cog’s Performance as a Measure – Lessons from the ADNI Study: Part 3 – Do the Scale Modifications Add Value? AAN 61 st Annual Meeting, Seattle, WA, April 25-May 2, 2009. Apostolova LG, Green AE, Hwang K, Morra JH, Cummings JL, Toga AW, Jack CR, Weiner MW, Thompson PM. Mapping correlations between serum Abeta and tau and hippocampal atrophy measures in 282 ADNI subjects. AAN 61 st Annual Meeting, Seattle, WA, April 25-May 2, 2009. Tosun D, Schuff N, Raptentsetsang S, Truran-Sacrey D, Shaw L, Trojanowski J, Weiner M. Associations Between Baseline Concentration of Alzheimer’s Disease Biochemical Markers and MRI Regional Rates of Brain Tissue Loss in ADNI Data. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Risacher SL, Saykin AJ, Shen L, West JD, Kim S, McDonald BC. Volumetric, Cortical Thickness and Grey Matter Density Changes on MRI over 12 Months: Relationship to Conversion Status in the ADNI Cohort. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Belaroussi B, Bracoud L, Vincent F, Pachai C. Detection of Hippocampal Volume Changes on Elderly Control, MCI and Alzheimer Patients from the ADNI Database: A One-Year Follow Up. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.

Thompson P, Hua X, Leow A, Morra JH, Apostolova LG, Lee S, Avedissian C, Madsen SK, Green AE, Toga AW, Jack CR Jr, Shaw LM, Trojanowski JQ, Weiner MW. Brain Changes in 676 ADNI Subjects: Summary of 10 Studies Using Tensor-Based Morphometry and Automated Hippocampal Mapping. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Nikelski J, Evans A, Chertkow H. Assessment of Structural Differences in Normal Aging and Alzheimer’s Disease: Quantitative and Qualitative Differences Using Subjects From the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Ito K, Corrigan B, Zhao Q, French J, Miller R, Fullerton T. Disease Progression Analysis of ADAS-Cog from ADNI Database in Normal Elderly, Mild Cognitive Impairment and Alzheimer’s Disease Patients. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Posner H, Cano S, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S, Hobart J. The ADAS-Cog’s Performance as a Measure: Lessons from the ADNI Study – Part 1, Evaluation Using Traditional Psychometric Methods. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Hobart J, Posner H, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zejicek J, Zeger S, Cano S. The ADAS-Cog’s Performance as a Measure: Lessons from the ADNI Study – Part 3, Do the Scale Modifications Add Value? Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Shaw LM. The ADNI Multicenter Study: CSF Biomarkers Data Report. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Das SR, Pluta J, Avants BB, Soares HD, Yushkevich PA. A Preliminary Study of Hippocampal Subfield Atrophy Using the ADNI Dataset. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Nestor SM, Borrie M, Smith M, Bartha R. A Direct Comparison of Ventricular Volumes Derived from 1.5 Tesla and 3.0 Tesla MRI in 115 ADNI Participants. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Donohue M, Gamst A. Mining ADNI for a Predictive Model of Diagnostic Conversions Using Classification and Regression Trees (CART). Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Landau SM, Harvey D, Madison C, Foster NL, Reiman EM, Shaw LM, Trojanowski JQ, Petersen RC, Weiner MW, Jagust WJ. Comparing predictors of conversion: Data from the Alzheimer’s disease neuroimaging initiative. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Cano S, Posner H, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S, Hobart J. The ADAS-Cog’s Performance as a Measure – Lessons from the ADNI Study: Part 2 – Evaluation using Modern Psychometric Methods. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009. Soleda O. et al. Segmentation of Anatomical Structures in Brain MR Images Using Atlases in FSL – A Quantitative Approach. Submitted. ICPR 2009.

These slides and much more atADNI-INFO.ORG All data at www.loni.ucla.edu/ADNI/