Neil Buckholtz, Ph.D. National Institute on Aging/NIH
70 yo Normal
72 yo MCI
74 yo AD
CMRgI Abnormalities in Probable Alzheimer’s Dementia
From Reiman et al, New Engl J Med 1996
Importance of Brain Imaging/Fluid Biomarkers in Alzheimer’s Disease 1) Tools for research 2) Identifying markers for detection of early brain changes in pathogenesis of AD 3) Assessing brain markers of disease progression 4) Potential surrogate markers for assessment of interventions
Cognitive Continuum Normal
Mild Cognitive Impairment
Alzheimer's Disease
CP926864- 35
MILD COGNITIVE IMPAIRMENT ORIGINAL CRITERIA
• MEMORY COMPLAINT • MEMORY IMPAIRED FOR AGE • NORMAL GENERAL COGNITIVE FUNCTION • NORMAL ACTIVITIES OF DAILY LIVING • NOT DEMENTED
Mild Cognitive Impairment MCI AD 12%/yr
Control AD 1-2%/yr
100
100
90
90
80
80
70
70
60
60
50
Initial 12 exam
36
24 Months
48
50
Petersen RC et al: Arch Neurol 56:303-308, 1999
Initial 12 exam
24 36 Months
48
CP926864- 12
New Diagnostic Criteria The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on workgroups on diagnostic guidelines for Alzheimer's disease. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH. Alzheimers Dement. 2011 May;7(3):263-9. The diagnosis of mild cognitive impairment due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Albert MS, Dekosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH. Alzheimers Dement. 2011 May;7(3):270-9. Toward defining the preclinical stages of Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, Iwatsubo T, Jack CR Jr, Kaye J, Montine TJ, Park DC, Reiman EM, Rowe CC, Siemers E, Stern Y, Yaffe K, Carrillo MC, Thies B, Morrison-Bogorad M, Wagster MV, Phelps CH. Alzheimers Dement. 2011 May;7(3):280-92.
GOALS OF THE ADNI: LONGITUDINAL MULTI-SITE OBSERVATIONAL STUDY • Major goal is collection of data and samples to establish a brain imaging, biomarker, and clinical database in order to identify the best markers for following disease progression and monitoring treatment response • Determine the optimum methods for acquiring, processing, and distributing images and biomarkers in conjunction with clinical and neuropsychological data in a multi-site context • “Validate” imaging and biomarker data by correlating with neuropsychological and clinical data. • Rapid public access of all data and access to samples
STUDY DESIGN-ADNI1 • • • • • • • •
•
MCI (n= 400): 0, 6, 12, 18, 24, 36 months AD (n= 200): 0, 6, 12, 24 months Controls (n= 200): 0, 6, 12, 24, 36 months Clinical/neuropsychological evaluations, MRI (1.5 T) at all time points FDG PET at all time points in 50% 3 T MRI at all time points in 25% PIB sub-study on 120 subjects Blood and urine at all time points from all subjects; CSF from 50% of subjects 0, 1 yr, 2 yr (subset); DNA and immortalized cell lines from all subjects GWAS study
ADNI Public-Private Partnership Structure
Private/Philanthropic + Public ADNI Executive Steering Committee PET Core: Berkeley: Jagust
MRI Core: Mayo: Jack
Clinical Core: UCSD: Aisen Mayo: Petersen
FDA NIBIB and other ICs
PI: Mike Weiner Administrative Core: UCSF Biomarkers Core: UPenn: Trojanowski/ Shaw Genetics Core: Indiana,Saykin
57 Clinical Sites: ADNI PIs and Cores
Publications Core: Harvard: Green
Biostatistics Core: UCD: Beckett
Informatics Core: UCLA: Toga
Pathology Core: WashU: Morris
ADNI 2 Private Partner Scientific Board 23 companies, 1 government entity and 2 non-profit organizations
ADNI MRI Standardization Methods
Steps taken before Subject Enrollment Began
Our goal: Standardization of image qualities (CNR, spatial resolution, resistance to artifact, reliability) across sites/platforms, and consistency across time in the face of ongoing upgrades Site equipment survey – determine technical specifications for each potential scanner in the study, select optimum scanner at each site Create a generic, non-platform specific MRI protocol Organize vendor support With vendor support, create a platform specific protocol for each scanner – 91 scanners, 48 distinct compiled versions of the ADNI protocol Deliver protocol to each scanner electronically, not manual creation Create an ADNI MRI procedures manual and deliver to sites Phone/email training of MRI site personnel by ADNI MR tech Site certification – phantom and human volunteer scans
Ongoing Standardization Methods During Study
Recertification of scanners after upgrades (79 scanners re- certified to date, some numerous times) Hands-on trouble shooting by ADNI technical personal (ie MR physicist, MR tech, radiologist) QA of images: visual + electronic inspection in 3 areas protocol compliance – electronically check every relevant MRI parameter against the master protocol for that system for each image acquired in the study, also identify scanner upgrades that were not reported by sites Visual inspection and rating of image quality – request patient re scan if necessary Identify medical abnormalities – for inclusion/exclusion as well as medical care purposes
MRI PHANTOM
Data and Sample Sharing • Goal is rapid public access of all raw and processed data • Central repository for all QA’d MRI and PET [Laboratory of Neuroimaging, UCLA (LONI)] • Clinical data base at UCSD is linked to LONI • Databases- in the public domain, available to all qualified investigators • Sample sharing-Resource Allocation Review Committee • No special access • Data Sharing & Publication Committee (DPC) -ADNI Data Use Agreement
ADNI1 Demographics Normal controls (n=229)
MCI (n=398)
AD (n=192)
P
76.4 (5.0)
75.3 (7.5)
75.8 (7.4)
0.15
48.0
35.4
47.4
0.002
Years of education, mean (SD)
15.6 (3.1)
16.0 (2.9)
14.7 (3.1)
<0.001
Apolipoprotein E e4: Positive (%)
26.6
53.5
65.6
<0.001
Age, mean (SD) Female (%)
CP1307278-1
Subject Evaluation • Baseline/screening eval and q 6 mo. – – – – – – – – –
Labs, Apo E Hamilton(S) Beck MMSE ANART ADAS-cog NPI CDR ADL
• Neuropsyc(B and q 6 mo) – – – – – – –
Logical Memory(S) AVLT BNT Trails A &B Symbol digit Clock drawing Category fluency
ADAS Cog 11
3003731-7
MMSE
3003731-9
ADNI Progression Rates 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)
Diagnosed as AD
Mean Cortical Thickness Change over 12 Months
Diagnosed as NC
+2%
-2%
Lateral View
Medial View
Holland et al.
12 month CMRgl Decline in AD
P<0.001
12 month CMRgl Decline in MCI
P<0.001
Kewei Chen, Ph.D., Eric M. Reiman, M.D. Banner Alzheimer's Institute Translational Genomics Research Institute University of Arizona Arizona Alzheimer’s Consortium Phoenix, Arizona, USA
P<0.001
Statistical ROI’s of 12-Month CMRglDecline AD
MCI
Human Amyloid Imaging in AD Using Pittsburgh Compound-B
Appearance in expected gray matter areas
Very little retention
Absence in areas where there is no amyloid
Absence of retention in gray matter
Klunk et al., Annals of Neurology 2004
PIB Imaging: Chet Mathis
FDG
PIB
Mean Cortical SUVR
3
2.5
2
1.5
Cutoff > 1.46 PIB+ (Berkeley Data) 1
Normals MCI AD 9/19 (47%) 47/63 (68%)17/19 (89%) PIB+ PIB+ PIB+
Follow-Up of PIB-Positive ADNI MCI’s ADNI PiB MCI’s N = 65, 12 mo. follow-up
PiB(-) Converters to AD PiB(+)
18 3 47
Converters to AD 21
Prediction of Conversion (3 yrs):AIBL Study
Rowe et al HC
MCI
(n=106)
(n=65)
PiB-ve Subjects: Converters to naMCI
PiB-ve Subjects:
74 2
(3%)
20
Converters to AD:
1
(5%)
Converters to DLB:
2
(10%)
Converters to FTD:
1
(5%)
1 45
(5%)
32
(71%)
PiB+ve Subjects:
32
Converters to VaD: PiB+ve Subjects:
Converters to MCI/AD
8 (25%)
Converters to AD
Follow-Up of ADNI PiB Controls ADNI PiB Ctrl’s N = 19, 24 mo. follow-up
PiB(-)
10
Converters to MCI 0 PiB(+)
9
Converters to MCI 2
Total Tau, p-Tau181p and Ab1-42 in CSF of ADNI subjects at Baseline using a bioanalytically validated xMAP Luminex immunoassay system and Innogenetics immunoassay reagents Clinical Core Leslie M Shaw, John Trojanowski University of Pennsylvania Medical Center
ADNI BASELINE CSF biomarker concentrations show the expected average differences between AD and MCI and NC AD (n=102) Mean±SD
Tau
Ab1-42
P-Tau181P Tau/Ab1-42 P-Tau181P/Ab1-42
122±58
143±41
42±20
0.9±0.5
0.3±0.2
103±61
164±55
35±18
0.8±0.6
0.3±0.2
70±30
206±55
25±15
0.4±0.3
0.1±0.1
MCI (n=200) Mean±SD
NC (n=114) Mean±SD
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, Ab1-42; p<0.01, P-Tau 181P; p<0.0005, Tau/Ab1-42; p<0.005, PTau 181P/Ab1-42. Mann-Whitney test for statistical differences used for these non-normally distributed data sets.
ADNI baseline visit CSF biomarkers-general statistics separated by APO E4+/concentration (pg/mL)
group ( apo E genotype)
Ab 1-42
Tau
ratio
P-Tau 181P
Tau/Ab 1-42
P-Tau181P/Ab 1-42
AD4+ (n=70)
121.41±53.07
131.61±27.42
42.24±19.32
0.97±0.48
0.34±0.19
AD4-(n=30)
122.07±67.92
171.27±53.07
40.43±21.72
0.8±0.49
0.27±0.17
no, yes
yes,yes
no, yes
no, yes
no, yes
0.77
p<0.0001*
0.47
0.12
0.10
Normal distribution (4+, 4-) p value
* parametric test Control4+(n=27)
80.48±40.23
156.85±48.50
32.3±20.93
0.57±0.37
0.24±0.19
Control4-(n=87) Normal distribution (4+, 4-)
66.32±25.97 no, no
220.71±47.95 yes, no
22.55±11.14 no, no
0.33±0.19 no, no
0.11±0.09 no, no
0.11
p<0.0001
0.03
p<0.0001
p<0.0001
MCI4+(n=105)
118.42±67.32
143.08±41.12
40.58±18.20
0.93±0.71
0.32±0.19
MCI4-(n=91) Normal distribution (4+, 4-)
86.31±46.93 no, no
186.33±59.48 no, no
30.33±16.71 no, no
0.55±0.40 no, no
0.20±0.15 no, no
p<0.0001
p<0.0001
p<0.0001
p<0.0001
p<0.0001
p value
p value
**p value calculated using Mann-Whitney test for each biomarker in each study group, segregated by APO E4, except for the one instance for which both 4+ & 4- subgroups were both normally distributed. Each value in the table is the mean + SD for the respective biomarker concentration in CSF.
CSF biomarker cutpoints established using CSFs collected from ADNI-independent autopsy-based AD and age-matched cognitively normal
subjects Tau
Ab1-42
pTau181p
Tau/Ab1- pLR TAA tau181p/Ab1-42 42
ROC AUC
0.831
0.913
0.753
0.917
0.856
0.938
Threshold values
93 ng/mL
192 ng/mL
23 ng/mL
0.39
0.10
0.22
Sensitivity (%)
69.6
6.4
67.9
85.7
91.1
100
Specificity (%)
92.3
76.9
73.1
84.6
71.2
76.9
Test accuracy (%)
80.6
87.0
73.1
85.2
81.5
88.9
Positive predictive value (%)
90.7
81.8
67.9
85.7
77.3
82.4
Negative predictive value (%)
73.8
95.2
70.4
84.6
88.1
100
MCI converters to AD at YEAR 1(n=37)
MCI converters to normal
Ab1-42 concentrations in CSF, collected at the baseline visit, of 37 ADNI MCI subjects who at their one year visit converted to a diagnosis of probable AD. The data points for the MCI→AD converters are presented as a horizontal dot plot with the x axis scale identical to that of the Ab1-42 frequency plot for the entire ADNI MCI group. The vertical line indicates the Ab1-42 cutoff concentration obtained from ROC analysis of an ADNI-independent cohort of autopsy-based AD subjects’ CSF.
PIB vs CSF Biomarkers: Ab Total N = 55 (11 Control, 34 MCI, 10 AD) 300 MCI AD Control
CSF Ab 1-42
250
200
Penn Autopsy Sample (56 AD, 52 Cog normal)
150
192 pg/ml
100
50.0 1
1.2
1.4
1.6
1.8
2
Mean Cortical SUVR
2.2
2.4
ADNI Plasma and CSF Proteomics Studies GOAL: Leverage ADNI Plasma and CSF samples to assess the utility of existing AD biomarker panels studies. PLASMA STUDY: • Baseline and 1 year ADNI plasma samples analyzed using RBM190 analyte multiplex immunoassay platform (Luminex xMAP) containing proteins previously reported in the literature to be altered as a result of cancer, cardiovascular disease, metabolic disorders, inflammation, Alzheimer’s disease • All data posted to ADNI website and available as of Nov, 2010 • Project Team - completed statistical analyses; finalizing manuscript CSF STUDY: • ADNI CSF samples to be sent to RBM for analysis (July, 2011) • Additional studies planned to qualify a Multiple Reaction Monitoring (MRM) Mass Spectrometry panel and to examine Beta-Site APP Cleaving Enzyme (BACE-1) levels and enzymatic activity in CSF.
Plasma RBM studies • Using data from two independent cohorts (Penn & WU) we identified 16 analytes that were associated with MCI and AD and 5 of them were validated in a third independent cohort (ADNI). • In addition two of the five analytes that were validated in the final step correlated with the CSF Aβ 1-42 and tau. • Validation of new potential biomarkers using independent cohorts is a powerful and essential screening and validation tool. • More work needed on analytes that were replicated in 2 cohorts (Penn&WU, WU&ADNI, Penn&ADNI)
Hippocampal atrophy rates (L+R) – free surfer data – in ADNI subjects with CSF Ab1-42 >192 pg/mL or <192 pg/mL Hippocampal % atrophy rates (BL→12 mos), for ADNI subjects with Ab1-42< 192 or >192 pg/mL
ALL AD MCI NC
Ab1-42 <192pg/mL
Ab1-42 >192pg/mL
-5.6±4.7
-2.6±4.1
-8.0±5.9
-4.2±3.5
-4.8±3.6
-2.9±3.7
-3.6±3.2
-2.2±4.3
These data show that in ADNI AD, MCI and NC subjects the rate of hippocampal atrophy increases at a significantly higher rate in subjects with Ab1-42 <192 pg/mL cutoff concentration compared to those >192 pg/mL
Feb-09; N. Schuff
POWER OF CLINICAL/COGNITIVE TESTS 25% CHANGE 1YR STUDY (2 ARM) : AD
Test MMSE RAVLT ADAS CDR SOB
Sample Size 803 607 592 449
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 45
ADNI Genotyping • Initial goal: high density genome wide scan – Identified major microarray platforms for GWAS • Compared marker selection strategies, HapMap coverage of genome, performance & reliability, as well as cost/sample – Illumina platform was selected by consensus of the Genetics Committee & ISAB for this project – TGen (Phoenix, AZ) was selected to perform the assays – Illumina Human 610-Quad
Shen et al 2010: Overview QC’ed genotyping data
Baseline MRI Scans
FreeSurfer: 56 volume or cortical thickness measures
530,992 SNPs 142 QTs
GWAS of Imaging Phenotypes
Strong associations represented by heat maps
VBM: 86 GM density measures
R
L
R
GWAS of candidate QT
L
L
R
R
VBM of candidate SNP
Refined modeling of candidate association
Conclusion: Imaging Gene Discovery Gene Identification with Imaging “Deep Phenotypes”: GWAS
Structural MRI + 600k SNPs = GRIN2b as Novel Risk Factor for MTL deficits in Alzheimers Stein et al 2010; ADNI
Amyloid Gene Pathway PET Study: [11C]PiB DHCR24 (seladin selective AD indicator – cholesterol synthesis pathway)
Swaminathan et al, Brain Imaging & Behavior (2012) DOI 10.1007/s11682-011-9136-1
Continue to follow all EMCI, LMCI and NC from ADNI 1 and ADNI GO for 5 more years Enroll:
100 additional EMCI (supplements 200 from GO) 150 new controls, LMCI, and AD
3T MRI at 3, 6, months and annually F18 amyloid (AV-45)/FDG every other year LP on 100% of subjects at enrollment Genetics
Normal
MCI
AD
ADNI 2 ADNI 1 (EMCI) (LMCI)
0
0.5 CDR
1 3004153-1
Inclusion Criteria for ADNI GO & 2* CDR MMSE 26
CN
EMCI
LMCI AD
0
0.5
0.5 0.5-1
24-30
24-30
24-30 20-
LM-DR (cut-off scores)
Educ 0-7 8-15 16
3 5 9
3-6 5-9 9-11
2 4 8
Dementia
No
No
No Yes
* Ron Petersen
2 4 8
EMCI have milder memor dysfunction than LMCI— approximately 0.5-1.5 SD below the mean for CN. They are CDR 0.5 as are LMCI. LMCI were ≥ 1.5 SD below the mean for memo function.
FDG-PET
CSF Aβ42
MRI hipp Cog
Amyloid imaging
CSF tau
Fxn
The eMCI group: selected to be intermediate between NC and later MCI, at baseline.
Baseline eMCI – yellow – is intermediate in ADAS-Cog between NC (green) and MCI (blue).
Also intermediate in complete cortical florbetapir index; considerable heterogeneity in all groups except perhaps AD (red).
Volumetric summaries and FDG-PET measures show eMCI more like NC at baseline.
ECog Memory 4
Self Partner
3
2
1
0 CN
EMCI
LMCI
AD
©2012 MFMER | 3188678-56
New functional measure: everyday cognitive function (ECog). Can be self-reported or informant-reported (better!)
ADNI GO/2 Florbetapir (N=602) 56/194
Frequency
29% positive
89/212 42% positive
83/132 63% positive
1.11 threshold ADNI Data processed with freesurfer & whole cerebellum reference
51/64 80% positive
Florbetapir cortical mean
fibrillar Aβ deposition in ADNI subject groups in comparison with 78 cognitively normal APOE e4 non-carriers
AD (n=53) MCI (n=78)
eMCI (n=150)
0.05 Banner Alzheimer’s Institute
P-value
e-14
cerebral glucose hypometabolism in ADNI patients
in comparison with 78 cognitively normal APOE e4 non-carriers
AD (n=53)
MCI (n=78)
eMCI (n=150)
0.05
p-value Banner Alzheimer’s Institute
e-16
cerebral glucose hypometabolism in 51 Aβ-positive eMCI patients in comparison with 99 Aβ-negative eMCI patients
0.05
P-value
Banner Alzheimer’s Institute
e-4
ADNI GO & ADNI 2 CSF biomarkers t-tau
p-tau181
(pg/mL)
(pg/mL)
(pg/mL)
233±71
73±34
231±72*
Ab1-42
Normal (107)
EMCI (192)
LMCI (66)
AD (25) * Ab1-42:
t-tau/Ab1-42
p-tau/Ab1-42
41.3±20
0.37±0.27
0.21±0.15
81±53**
44.4±28** *
0.45±0.49* ***
0.24±0.22**** *
181±68
103±55
63.8±40
0.68±0.45
0.42±0.31
151±52
134±59
70.1±33
0.97±0.49
0.54±0.33
p<0.000001 vs AD; p<0.00001 vs LMCI, p=0.83 vs NL. ** t-tau: p<0.000005 vs AD, p<0.005 vs LMCI, p=0.86 vs NL. ***p-tau181:p<0.0005 vs AD, p<0.00005 vs LMCI; p=0.91 vs NL. **** t-tau/ Ab1-42: p<0.0000001 vs AD, p<0.00005 vs LMCI, p=0.99 vs NL *****p-tau / Ab : p< 0.00005 vs AD, p<0.000001 vs LMCI; p=0.96 vs NL.
Baseline ADAScog results in ADNI subjects with CSF Ab1-42 >192 pg/mL or <192 pg/mL Baseline ADAScog results for ADNI subjects (mean±SD) with Ab1-42 <192 pg/mL or >192 pg/mLAb1-42 Ab 1-42
ALL
<192pg/m L
>192pg/m L
p
18.2±8.4
12.0±6.4
<0.000 1
11.3±4.9
9.4±4.2
0.078
15.2±5.7
11.8±5.4
<0.000 5
21.5±6.1
15.8±7.4
<0.005
30.3±7.7
29.7±8.4
0.75
n=385
NC n=106
EMCI n=190
LMCI n=65
AD n=24
Baseline AV45 SUVR results in ADNI subjects with CSF Ab1-42 >192 pg/mL or <192 pg/mL Baseline AV45 SUVR results for ADNI subjects (mean±SD) with Ab1-42 <192 pg/mL or >192 Abpg/mLAb 1-42
1-42
<192pg/m >192pg/m L L
ALL
1.6±0.23
1.2±0.11
<0.000 1
1.5±0.22
1.2±0.09
<0.000 1
1.5±0.21
1.2±0.13
<0.000 1
1.6±0.27
1.2±0.09
<0.000 5
1.6±0.25
1.1±0.21
<0.05
n=246
NC n=53
EMCI n=148
LMCI n=32
AD n=13
p
AV45 SUVR vs CSF Ab1-42 in ADNI GO and ADNI 2 sub NC
ALL
Spearman’s r=-0.74 AV45 SUVR
AV45 SUVR
Spearman’s r=-0.73
Ab1-42, pg/mL
Ab1-42, pg/mL
1.28 SUVR cutpoint as described by Landau and Jagust (ADNI web site)
EMCI to LMCI 1.0 strata ApoE=e4+ ApoE=e4−
0.8
Probability
p = 0.001 0.6
0.4
0.2
0.0 0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
36 12
27 6
18 4
6 0
2 0
Years ApoE=e4− ApoE=e4+
142 139 91 82 79 57
59 29
53 21
39 17
Numbers at risk
Standardization: imaging, biomarkers Neuroscience: relationships among biomarker trajectories elucidate neurobiology Trials: new understanding of biomarkers has facilitated interventional studies in very early AD Data sharing: ADNI has demonstrated the power of real-time public data sharing Collaboration: academia, industry, non-profits, regulatory agencies world-wide
9/2009 N. Schuff
http://www.adni-info.org http://www.loni.ucla.edu/ADNI
Parkinson’s disease FTD Autism
World-Wide Standardization • Alzheimer’s Association efforts to standardize CSF and hippocampal volume measures
CAMD • Utilization of ADNI data to develop documents to qualify CSF and MRI measures for regulatory purposes to FDA and EMA for enrolling subjects at high risk
National Alzheimer’s Project Act (NAPA) Update Draft framework for National Plan to Address Alzheimer’s proposed January 2012 National Plan released May 15
http://aspe.hhs.gov/daltcp/napa/
NAPA Goals 1. Prevent and effectively treat Alzheimer’s disease by 2025 2. Optimize care quality and efficiency 3. Expand patient and family support 4. Enhance public awareness and engagement 5. Track progress and drive improvement
Identify Research Strategies for Alzheimer’s Disease NIH/NIA hosted AD Research Summit May 14-15, 2012 Research recommendations released May 18 • http://www.nia.nih.gov/newsroom/alzheimersdisease-research-summit-2012-recommendations • Day One Webcast • http://videocast.nih.gov/summary.asp?Live=11196
ADNI Data Investigators
Total Investigators
3135
Approved Investigators
2931
Disapproved Investigators
204
ADNI Data Applications Disapproved Applications (204)
Asked to clarify Nonsense users
28
176
ADNI Data Applications by Sector (cumulative) 1800 1600 1400 1200 1000 800 600 400 200 0 2007
2008
2009
University/Research Pharmaceutical Biotech Scanner Mfg Government Other 2010
2011
Other Government Scanner Mfg Biotech Pharmaceutical University/Research
ADNI Data Users
Investigators (3135) by degree type: • B.A. – 92
• M.S. – 550
• B.S. – 270
• M.D. – 644
• M.A. – 70
• Ph.D. – 1509
Countries with ADNI Data Applicants
Countries with ADNI data applicants
Data Archived and Downloaded
• 140,000 images archived (raw and processed) • 1.2 million image downloads • 90,000 downloads of non-image data (clinical, genetic, proteomic, summary) from 36 countries
ADNI Manuscripts 504 manuscripts utilized ADNI data Published Epub ahead of print
274 16
In Press Under revision In submission
8 2 191
Withdrawn Under review by DPC
11 2
ADNI Manuscripts (reviewed) Of the 504 manuscripts that utilized ADNI data, 469 were submitted for ADNI DPC Review 11 Met initial criteria 238
220
Required one revision Withdrawn
ADNI Manuscripts (not reviewed) 35 manuscripts were not submitted to the ADNI DPC for review Compliant with ADNI policies
6
Non-compliant with ADNI policies
29
Reasons authors cited for not submitting manuscripts for review: • Didn’t submit this time, but will in the future (19) • Forgot to submit, but have since (3) • No response (8) • Author reported paper to us after publication (5)
