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1.  Ventricular atrophy and its clinical correlates in the imaging cohort from the ADCS MCI Donepezil/Vitamin E study 
We analyzed the baseline and 3-year T1-weighted magnetic resonance imaging data of 110 amnestic mild cognitive impairment (MCI) participants with minimal hippocampal atrophy at baseline from the Alzheimer’s Disease Cooperative Study group (ADCS) MCI Donepezil/Vitamin E trial. 46 subjects converted to AD (MCIc) while 64 remained stable (MCInc). We used the radial distance technique to examine the differences in lateral ventricle shape and size between MCIc and MCInc and the associations between ventricular enlargement and cognitive decline.
MCIc group had significantly larger frontal and right body/occipital horns relative to MCInc at baseline and significantly larger bilateral frontal, body/occipital and left temporal horns at follow-up. Global cognitive decline measured with ADAScog and MMSE and decline in activities of daily living (ADL) were associated with posterior lateral ventricle enlargement. Decline in ADAScog and ADL were associated with left temporal and decline in MMSE with right temporal horn enlargement. After correction for baseline hippocampal volume decline in ADL showed a significant association with right frontal horn enlargement. Executive decline was associated with right frontal and left temporal horn enlargement.
doi:10.1097/WAD.0b013e3182677b3d
PMCID: PMC3662002  PMID: 23694947
Alzheimer’s disease; AD; mild cognitive impairment; MCI; imaging; MRI; brain atrophy; ventricular enlargement
2.  Health-Related Resource Use and Costs in Elderly Adults with and without Mild Cognitive Impairment 
OBJECTIVES
To assess differences in resource use and cost between older adults with and without mild cognitive impairment (MCI) over time.
DESIGN
Multicenter, longitudinal study.
SETTING
Sixty-eight Alzheimer’s Disease Cooperative Study (ADCS) sites in the United States.
PARTICIPANTS
Two hundred fifty-nine individuals diagnosed with MCI and 107 cognitively normal elderly adults followed annually for 3 years.
MEASUREMENTS
The Resource Use Instrument (RUI) was used to capture medical and nonmedical care use. Generalized linear latent and mixed models were used to estimate differences in resource use and costs in older adults with and without MCI after controlling for clinical and demographic characteristics.
RESULTS
At baseline, average annual direct medical cost per person was substantially higher for participants with MCI ($6,499) than for those without ($2,969) P < .001). Informal care use was also substantially higher (33% vs 8.4%, P < .001). Results from multivariate analyses of longitudinal data show that, after controlling for participant and informant characteristics, direct medical costs were 44% higher for participants with MCI than for those without. Participants with MCI were almost five times as likely to use informal care as those without. Number of medical conditions and older age were associated with higher medical cost. Worse functional and cognitive status, older age, being married, and being female were associated with higher likelihood of informal care use. Having an adult child informant was associated with higher likelihood of using informal care.
CONCLUSION
The RUI captured differences in resource use and costs between individuals with and without MCI. Clinicians who care for individuals with MCI should address informal care needs early in the disease course.
doi:10.1111/jgs.12132
PMCID: PMC3928966  PMID: 23414481
mild cognitive impairment; case–control study; medical care; resource use; cost; informal care
3.  Update on hypothetical model of Alzheimer’s disease biomarkers 
Lancet neurology  2013;12(2):207-216.
In 2010, the authors published a hypothetical model of the major biomarkers of Alzheimer’s disease (AD). The model was received with interest because we described the temporal evolution of AD biomarkers in relation to each other and to the onset and progression of clinical symptoms. In the interim, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of the assumptions underlying our original model. Recent evidence has allowed us to modify our original model. Refinements include indexing subjects by time rather than clinical symptom severity; incorporating inter-subject variability in cognitive response to the progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and, recognition that the two major proteinopathies underlying AD biomarker changes, Aβ and tau, may be initiated independently in late onset AD where we hypothesize that an incident Aβopathy can accelerate an antecedent tauopathy.
doi:10.1016/S1474-4422(12)70291-0
PMCID: PMC3622225  PMID: 23332364
4.  Effect of study partner on the conduct of Alzheimer disease clinical trials 
Neurology  2013;80(3):282-288.
Objective:
Alzheimer disease (AD) dementia clinical trials require 2 participants: a patient and a study partner. We assessed the prevalence of study partner types and how these types associate with patient-related outcome measures.
Methods:
Retrospective analyses of 6 Alzheimer’s Disease Cooperative Study (ADCS) randomized clinical trials were conducted. Study partners were categorized as spouse, adult child, or other. Prevalence of study partner type and associations between study partner type and trial outcomes including study completion and placebo decline on the Mini-Mental State Examination, the Alzheimer’s Disease Assessment Scale–cognitive subscale, the Clinical Dementia Rating scale Sum of the Boxes score, and the ADCS–Activities of Daily Living were examined.
Results:
More participants (67%) enrolled with spouses than adult children (26%) or other study partners (7%). Participants with spouse partners had a lower dropout rate (25%) than those with adult child (32%) or other study partners (34%); only the difference vs others was statistically significant. Participants with adult child and other partners randomized to placebo performed worse at baseline than those with spouse partners on the ADCS–Activities of Daily Living (p = 0.04), but were not different at 18 months. There were no differences at baseline for the Mini-Mental State Examination, Clinical Dementia Rating scale Sum of the Boxes score, or Alzheimer’s Disease Assessment Scale–cognitive subscale. In multivariate models of the rates of change over time among placebo participants, no differences among study partner groups reached statistical significance.
Conclusions:
Patients with nonspouse caregivers less frequently participate in AD dementia trials. Increased enrollment of AD patients with nonspouse caregivers may require additional recruitment and retention strategies.
doi:10.1212/WNL.0b013e31827debfe
PMCID: PMC3589183  PMID: 23255824
5.  Dependence as a unifying construct in defining Alzheimer’s disease severity 
This article reviews measures of Alzheimer’s disease (AD) progression in relation to patient dependence and offers a unifying conceptual framework for dependence in AD. Clinicians typically characterize AD by symptomatic impairments in three domains: cognition, function, and behavior. From a patient’s perspective, changes in these domains, individually and in concert, ultimately lead to increased dependence and loss of autonomy. Examples of dependence in AD range from a need for reminders (early AD) to requiring safety supervision and assistance with basic functions (late AD). Published literature has focused on the clinical domains as somewhat separate constructs and has given limited attention to the concept of patient dependence as a descriptor of AD progression. This article presents the concept of dependence on others for care needs as a potential method for translating the effect of changes in cognition, function, and behavior into a more holistic, transparent description of AD progression.
doi:10.1016/j.jalz.2009.09.004
PMCID: PMC3884683  PMID: 21044778
Alzheimer’s disease; Dementia; Functional impairment; Dependence; Disease progression
6.  Genome-wide pathway analysis of memory impairment in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort implicates gene candidates, canonical pathways, and networks 
Brain imaging and behavior  2012;6(4):634-648.
Memory deficits are prominent features of mild cognitive impairment (MCI) and Alzheimer’s disease (AD). The genetic architecture underlying these memory deficits likely involves the combined effects of multiple genetic variants operative within numerous biological pathways. In order to identify functional pathways associated with memory impairment, we performed a pathway enrichment analysis on genome-wide association data from 742 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants. A composite measure of memory was generated as the phenotype for this analysis by applying modern psychometric theory to item-level data from the ADNI neuropsychological test battery. Using the GSA-SNP software tool, we identified 27 canonical, expertly-curated pathways with enrichment (FDR-corrected p-value < 0.05) against this composite memory score. Processes classically understood to be involved in memory consolidation, such as neurotransmitter receptor-mediated calcium signaling and long-term potentiation, were highly represented among the enriched pathways. In addition, pathways related to cell adhesion, neuronal differentiation and guided outgrowth, and glucose- and inflammation-related signaling were also enriched. Among genes that were highly-represented in these enriched pathways, we found indications of coordinated relationships, including one large gene set that is subject to regulation by the SP1 transcription factor, and another set that displays co-localized expression in normal brain tissue along with known AD risk genes. These results 1) demonstrate that psychometrically-derived composite memory scores are an effective phenotype for genetic investigations of memory impairment and 2) highlight the promise of pathway analysis in elucidating key mechanistic targets for future studies and for therapeutic interventions.
doi:10.1007/s11682-012-9196-x
PMCID: PMC3713637  PMID: 22865056
memory; psychometrics; Alzheimer’s disease; mild cognitive impairment; pathway analysis; genome-wide association study
7.  Developing an international network for Alzheimer research: The Dominantly Inherited Alzheimer Network 
Clinical investigation  2012;2(10):975-984.
The Dominantly Inherited Alzheimer Network (DIAN) is a collaborative effort of international Alzheimer disease (AD) centers that are conducting a multifaceted prospective biomarker study in individuals at-risk for autosomal dominant AD (ADAD). DIAN collects comprehensive information and tissue in accordance with standard protocols from asymptomatic and symptomatic ADAD mutation carriers and their non-carrier family members to determine the pathochronology of clinical, cognitive, neuroimaging, and fluid biomarkers of AD. This article describes the structure, implementation, and underlying principles of DIAN, as well as the demographic features of the initial DIAN cohort.
doi:10.4155/cli.12.93
PMCID: PMC3489185  PMID: 23139856
Alzheimer disease; autosomal dominant; biomarkers of Alzheimer disease; PSEN1; PSEN2; APP; amyloid-beta; preclinical Alzheimer disease
8.  Amyloid Deposition, Hypometabolism, and Longitudinal Cognitive Decline 
Annals of neurology  2012;72(4):578-586.
Objective
Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) population, we examined (1) cross-sectional relationships between amyloid deposition, hypometabolism, and cognition, and (2) associations between amyloid and hypometabolism measurements and longitudinal cognitive measurements.
Methods
We examined associations between mean cortical florbetapir uptake, mean 18F-fluorodeoxyglucose–positron emission tomography (FDG-PET) within a set of predefined regions, and Alzhiemer’s Disease Assessment Scale (ADAS-cog) performance in 426 ADNI participants (126 normal, 162 early mild cognitive impairment [EMCI], 85 late MCI [LMCI], 53 Alzheimer disease [AD] patients). For a subset of these (76 normal, 81 LMCI) we determined whether florbetapir and FDG-PET were associated with retrospective decline in longitudinal ADAS-cog measurements.
Results
Twenty-nine percent of normal subjects, 43% of EMCI patients, 62% of LMCI patients, and 77% of AD patients were categorized as florbetapir positive. Florbetapir was negatively associated with concurrent FDG and ADAS-cog in both MCI groups. In longitudinal analyses, florbetapir-positive subjects in both normal and LMCI groups had greater ongoing ADAS-cog decline than those who were florbetapir negative. However, in normal subjects, florbetapir positivity was associated with greater ADAS-cog decline than FDG, whereas in LMCI, FDG positivity was associated with greater decline than florbetapir.
Interpretation
Although both hypometabolism and β-amyloid (Aβ) deposition are detectable in normal subjects and all diagnostic groups, Aβ showed greater associations with cognitive decline in normal participants. In view of the minimal cognitive deterioration overall in this group, this suggests that amyloid deposition has an early and subclinical impact on cognition that precedes metabolic changes. At moderate and later stages of disease (LMCI/AD), hypometabolism becomes more pronounced and more closely linked to ongoing cognitive decline.
doi:10.1002/ana.23650
PMCID: PMC3786871  PMID: 23109153
9.  Early Indications of Future Cognitive Decline: Stable versus Declining Controls 
PLoS ONE  2013;8(9):e74062.
This study aimed to identify baseline features of normal subjects that are associated with subsequent cognitive decline. Publicly available data from the Alzheimer’s Disease Neuroimaging Initiative was used to find differences in baseline clinical assessments (ADAScog, AVLT, FAQ) between cognitively healthy individuals who will suffer cognitive decline within 48 months and those who will remain stable for that period. Linear regression models indicated an individual’s conversion status was significantly associated with certain baseline neuroimaging measures, including posterior cingulate glucose metabolism. Linear Discriminant Analysis models built with baseline features derived from MRI and FDG-PET measures were capable of successfully predicting whether an individual will convert to MCI within 48 months or remain cognitively stable. The findings from this study support the idea that there exist informative differences between normal people who will later develop cognitive impairments and those who will remain cognitively stable for up to four years. Further, the feasibility of developing predictive models that can detect early states of cognitive decline in seemingly normal individuals was demonstrated.
doi:10.1371/journal.pone.0074062
PMCID: PMC3767625  PMID: 24040166
10.  CSF Biomarker and PIB-PET–Derived Beta-Amyloid Signature Predicts Metabolic, Gray Matter, and Cognitive Changes in Nondemented Subjects 
Cerebral Cortex (New York, NY)  2011;22(9):1993-2004.
Beta-amyloid (Aβ) is a histopathological hallmark of Alzheimer’s disease dementia, but high levels of Aβ in the brain can also be found in a substantial proportion of nondemented subjects. Here we investigated which 2-year rate of brain and cognitive changes are present in nondemented subjects with high and low Aβ levels, as assessed with cerebrospinal fluid and molecular positron emission tomography (PET)–based biomarkers of Aβ. In subjects with mild cognitive impairment, increased brain Aβ levels were associated with significantly faster cognitive decline, progression of gray matter atrophy within temporal and parietal brain regions, and a trend for a faster decline in parietal Fludeoxyglucose (FDG)-PET metabolism. Changes in gray matter and FDG-PET mediated the association between Aβ and cognitive decline. In contrast, elderly cognitively healthy controls (HC) with high Aβ levels showed only a faster medial temporal lobe and precuneus volume decline compared with HC with low Aβ. In conclusion, the current results suggest not only that both functional and volumetric brain changes are associated with high Aβ years before the onset of dementia but also that HC with substantial Aβ levels show higher Aβ pathology resistance, lack other pathologies that condition neurotoxic effects of Aβ, or accumulated Aβ for a shorter time period.
doi:10.1093/cercor/bhr271
PMCID: PMC3500862  PMID: 22038908
Aβ; FDG-PET; MCI; PIB-PET
11.  Testing the Right Target and the Right Drug at the Right Stage 
Science translational medicine  2011;3(111):111cm33.
Alzheimer’s disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Recent disappointing trial results at the dementia stage of AD have raised multiple questions about our current approaches to the development of disease-modifying agents. Converging evidence suggests that the pathophysiological process of AD begins many years before the onset of dementia. So why do we keep testing drugs aimed at the initial stages of the disease process in patients at the end-stage of the illness?
Alzheimer’s disease (AD) remains one of the most feared consequences of aging, affecting more than one out of every ten individuals over the age of 65. With more than 10,000 baby boomers turning 65 every day in the United States alone, we are truly facing an AD epidemic. Over the past decade, a string of disappointing clinical trial results have raised concerns about our current strategy for development of AD-modifying therapies. Three hypotheses can explain these recent AD trial failures: (i) We are targeting the wrong pathophysiological mechanisms; (ii) The drugs do not engage the intended targets in patients; and (iii) The drugs are hitting the right targets, but are doing so at the wrong stage of the disease. Here, we address the third supposition and suggest that specific amyloid-based therapies be directed at much earlier stages of ADperhaps even prior to the emergence of clinical symptoms. Furthermore, we argue that the field has sufficient tools to begin “secondary prevention” trials in asymptomatic individuals whoare at high risk for progression to cognitive impairment and AD dementia.
doi:10.1126/scitranslmed.3002609
PMCID: PMC3752906  PMID: 22133718
12.  Influence of Genetic Variation on Plasma Protein Levels in Older Adults Using a Multi-Analyte Panel 
PLoS ONE  2013;8(7):e70269.
Proteins, widely studied as potential biomarkers, play important roles in numerous physiological functions and diseases. Genetic variation may modulate corresponding protein levels and point to the role of these variants in disease pathophysiology. Effects of individual single nucleotide polymorphisms (SNPs) within a gene were analyzed for corresponding plasma protein levels using genome-wide association study (GWAS) genotype data and proteomic panel data with 132 quality-controlled analytes from 521 Caucasian participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Linear regression analysis detected 112 significant (Bonferroni threshold p = 2.44×10−5) associations between 27 analytes and 112 SNPs. 107 out of these 112 associations were tested in the Indiana Memory and Aging Study (IMAS) cohort for replication and 50 associations were replicated at uncorrected p<0.05 in the same direction of effect as those in the ADNI. We identified multiple novel associations including the association of rs7517126 with plasma complement factor H-related protein 1 (CFHR1) level at p<1.46×10−60, accounting for 40 percent of total variation of the protein level. We serendipitously found the association of rs6677604 with the same protein at p<9.29×10−112. Although these two SNPs were not in the strong linkage disequilibrium, 61 percent of total variation of CFHR1 was accounted for by rs6677604 without additional variation by rs7517126 when both SNPs were tested together. 78 other SNP-protein associations in the ADNI sample exceeded genome-wide significance (5×10−8). Our results confirmed previously identified gene-protein associations for interleukin-6 receptor, chemokine CC-4, angiotensin-converting enzyme, and angiotensinogen, although the direction of effect was reversed in some cases. This study is among the first analyses of gene-protein product relationships integrating multiplex-panel proteomics and targeted genes extracted from a GWAS array. With intensive searches taking place for proteomic biomarkers for many diseases, the role of genetic variation takes on new importance and should be considered in interpretation of proteomic results.
doi:10.1371/journal.pone.0070269
PMCID: PMC3720913  PMID: 23894628
13.  Considerations in the Design of Clinical Trials for Cognitive Aging 
What will it take to develop interventions for the treatment of age-related cognitive decline? Session V of the Summit provided perspectives on the design of clinical trials to evaluate promising but unproven interventions, and some of the steps needed to accelerate the discovery and evaluation of promising treatments. It considered strategies to further characterize the biological and cognitive changes associated with normal aging and their translation into the development of new treatments. It provided regulatory, scientific, and clinical perspectives about neurocognitive aging treatments, their potential benefits and risks, and the strategies and endpoints needed to evaluate them in the most rapid, rigorous, and clinically meaningful way. It considered lessons learned from the study of Alzheimer's disease, the promising roles of biomarkers in neurocognitive aging research, and ways to help galvanize the scientific study and treatment of neurocognitive aging.
doi:10.1093/gerona/gls124
PMCID: PMC3391068  PMID: 22573913
Cognition; Clinical trials; Aging
14.  Longitudinal Stability of Subsyndromal Symptoms of Depression in Individuals with Mild Cognitive Impairment: Relationship to Conversion to Dementia after Three Years 
Objective
To evaluate the degree to which longitudinal stability of subsyndromal symptoms of depression (SSD) is associated with conversion to dementia in patients with Mild Cognitive Impairment (MCI).
Methods
Data from 405 MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were analyzed. Participants were evaluated at baseline and 12 month intervals over three years. Participants were designated as MCI Converters if dementia was diagnosed within 3 years or as Cognitively Stable MCI if dementia was not diagnosed during this interval. SSD were evaluated utilizing the 15-item Geriatric Depression Scale (GDS). Endorsement of specific SSD at baseline and the stability of SSD over 36 months were compared between the two MCI groups.
Results
Baseline symptom endorsement and stability of total GDS scores did not differentiate MCI groups. Worsening of 4 individual items from the GDS over time (memory problems, feelings of helplessness, loss of interest, and preference for staying at home) differentiated MCI converters from cognitively stable MCI (p <0.05 for all). However, only increased endorsement of memory symptoms over time was associated with progression to dementia after controlling for other clinical variables (p=0.05).
Conclusions
SSD in MCI participants largely consist of cognitive symptoms and activity limitations and the stability of SSD over time differentiated the MCI groups better than baseline endorsement of symptoms. However, the only significant predictor of conversion to dementia was increased endorsement of memory problems, which likely represents insight into cognitive problems more than depressive symptomatology in MCI individuals.
doi:10.1002/gps.2713
PMCID: PMC3685477  PMID: 21744390
subsyndromal depression; longitudinal stability; mild cognitive impairment; insight; dementia
15.  Antioxidants for Alzheimer Disease 
Archives of neurology  2012;69(7):836-841.
Objective
To evaluate whether antioxidant supplements presumed to target specific cellular compartments affected cerebrospinal fluid (CSF) biomarkers.
Design
Double-blind, placebo-controlled clinical trial.
Setting
Academic medical centers.
Participants
Subjects with mild to moderate Alzheimer disease.
Intervention
Random assignment to treatment for 16 weeks with 800 IU/d of vitamin E (α-tocopherol) plus 500 mg/d of vitamin C plus 900 mg/d of α-lipoic acid (E/C/ALA); 400 mg of coenzyme Q 3 times/d; or placebo.
Main Outcome Measures
Changes from baseline to 16 weeks in CSF biomarkers related to Alzheimer disease and oxidative stress, cognition (Mini-Mental State Examination), and function (Alzheimer’s Disease Cooperative Study Activities of Daily Living Scale).
Results
Seventy-eight subjects were randomized; 66 provided serial CSF specimens adequate for biochemical analyses. Study drugs were well tolerated, but accelerated decline in Mini-Mental State Examination scores occurred in the E/C/ALA group, a potential safety concern. Changes in CSF Aβ42, tau, and P-tau181 levels did not differ between the 3 groups. Cerebrospinal fluid F2-isoprostane levels, an oxidative stress biomarker, decreased on average by 19% from baseline to week 16 in the E/C/ALA group but were unchanged in the other groups.
Conclusions
Antioxidants did not influence CSF biomarkers related to amyloid or tau pathology. Lowering of CSF F2-isoprostane levels in the E/C/ALA group suggests reduction of oxidative stress in the brain. However, this treatment raised the caution of faster cognitive decline, which would need careful assessment if longer-term clinical trials are conducted.
Trial Registration
clinicaltrials.gov Identifier: NCT00117403
PMCID: PMC3661272  PMID: 22431837
16.  Nonlinear time course of brain volume loss in cognitively normal and impaired elders 
Neurobiology of Aging  2010;33(5):845-855.
The goal was to elucidate the time course of regional brain atrophy rates relative to age in cognitively normal (CN) aging, mild cognitively impairment (MCI) and Alzheimer’s disease (AD), without a-priori models for atrophy progression. Regional brain volumes from 147 CN subjects, 164 stable MCI, 93 MCI-to-AD converters and 111 AD patients, between 51 to 91 years old and who had repeated 1.5T magnetic resonance imaging (MRI) scans over 30 months, were analyzed. Relations between regional brain volume change and age were determined using generalized additive models, an established non-parametric concept for approximating nonlinear relations. Brain atrophy rates varied nonlinearly with age, predominantly in regions of the temporal lobe. Moreover, the atrophy rates of some regions leveled off with increasing age in control and stable MCI subjects whereas those rates progressed further in MCI-to-AD converters and AD patients. The approach has potential uses for early detection of AD and differentiation between stable and progressing MCI.
doi:10.1016/j.neurobiolaging.2010.07.012
PMCID: PMC3032014  PMID: 20855131
Alzheimer’s disease; mild cognitive impairment; aging; brain atrophy; hippocampus; magnetic resonance imaging; generalized additive models
17.  Predicting missing biomarker data in a longitudinal study of Alzheimer disease 
Lo, Raymond Y. | Jagust, William J. | Aisen, Paul | Jack, Clifford R. | Toga, Arthur W. | Beckett, Laurel | Gamst, Anthony | Soares, Holly | C. Green, Robert | Montine, Tom | Thomas, Ronald G. | Donohue, Michael | Walter, Sarah | Dale, Anders | Bernstein, Matthew | Felmlee, Joel | Fox, Nick | Thompson, Paul | Schuff, Norbert | Alexander, Gene | DeCarli, Charles | Bandy, Dan | Chen, Kewei | Morris, John | Lee, Virginia M.-Y. | Korecka, Magdalena | Crawford, Karen | Neu, Scott | Harvey, Danielle | Kornak, John | Saykin, Andrew J. | Foroud, Tatiana M. | Potkin, Steven | Shen, Li | Buckholtz, Neil | Kaye, Jeffrey | Dolen, Sara | Quinn, Joseph | Schneider, Lon | Pawluczyk, Sonia | Spann, Bryan M. | Brewer, James | Vanderswag, Helen | Heidebrink, Judith L. | Lord, Joanne L. | Petersen, Ronald | Johnson, Kris | Doody, Rachelle S. | Villanueva-Meyer, Javier | Chowdhury, Munir | Stern, Yaakov | Honig, Lawrence S. | Bell, Karen L. | Morris, John C. | Mintun, Mark A. | Schneider, Stacy | Marson, Daniel | Griffith, Randall | Clark, David | Grossman, Hillel | Tang, Cheuk | Marzloff, George | Toledo-Morrell, Leylade | Shah, Raj C. | Duara, Ranjan | Varon, Daniel | Roberts, Peggy | Albert, Marilyn S. | Pedroso, Julia | Toroney, Jaimie | Rusinek, Henry | de Leon, Mony J | De Santi, Susan M | Doraiswamy, P. Murali | Petrella, Jeffrey R. | Aiello, Marilyn | Clark, Christopher M. | Pham, Cassie | Nunez, Jessica | Smith, Charles D. | Given, Curtis A. | Hardy, Peter | Lopez, Oscar L. | Oakley, MaryAnn | Simpson, Donna M. | Ismail, M. Saleem | Brand, Connie | Richard, Jennifer | Mulnard, Ruth A. | Thai, Gaby | Mc-Adams-Ortiz, Catherine | Diaz-Arrastia, Ramon | Martin-Cook, Kristen | DeVous, Michael | Levey, Allan I. | Lah, James J. | Cellar, Janet S. | Burns, Jeffrey M. | Anderson, Heather S. | Laubinger, Mary M. | Bartzokis, George | Silverman, Daniel H.S. | Lu, Po H. | Graff-Radford MBBCH, Neill R | Parfitt, Francine | Johnson, Heather | Farlow, Martin | Herring, Scott | Hake, Ann M. | van Dyck, Christopher H. | MacAvoy, Martha G. | Benincasa, Amanda L. | Chertkow, Howard | Bergman, Howard | Hosein, Chris | Black, Sandra | Graham, Simon | Caldwell, Curtis | Hsiung, Ging-Yuek Robin | Feldman, Howard | Assaly, Michele | Kertesz, Andrew | Rogers, John | Trost, Dick | Bernick, Charles | Munic, Donna | Wu, Chuang-Kuo | Johnson, Nancy | Mesulam, Marsel | Sadowsky, Carl | Martinez, Walter | Villena, Teresa | Turner, Scott | Johnson, Kathleen B. | Behan, Kelly E. | Sperling, Reisa A. | Rentz, Dorene M. | Johnson, Keith A. | Rosen, Allyson | Tinklenberg, Jared | Ashford, Wes | Sabbagh, Marwan | Connor, Donald | Jacobson, Sandra | Killiany, Ronald | Norbash, Alexander | Nair, Anil | Obisesan, Thomas O. | Jayam-Trouth, Annapurni | Wang, Paul | Lerner, Alan | Hudson, Leon | Ogrocki, Paula | DeCarli, Charles | Fletcher, Evan | Carmichael, Owen | Kittur, Smita | Mirje, Seema | Borrie, Michael | Lee, T-Y | Bartha, Dr Rob | Johnson, Sterling | Asthana, Sanjay | Carlsson, Cynthia M. | Potkin, Steven G. | Preda, Adrian | Nguyen, Dana | Tariot, Pierre | Fleisher, Adam | Reeder, Stephanie | Bates, Vernice | Capote, Horacio | Rainka, Michelle | Hendin, Barry A. | Scharre, Douglas W. | Kataki, Maria | Zimmerman, Earl A. | Celmins, Dzintra | Brown, Alice D. | Gandy, Sam | Marenberg, Marjorie E. | Rovner, Barry W. | Pearlson, Godfrey | Anderson, Karen | Saykin, Andrew J. | Santulli, Robert B. | Englert, Jessica | Williamson, Jeff D. | Sink, Kaycee M. | Watkins, Franklin | Ott, Brian R. | Wu, Chuang-Kuo | Cohen, Ronald | Salloway, Stephen | Malloy, Paul | Correia, Stephen | Rosen, Howard J. | Miller, Bruce L. | Mintzer, Jacobo
Neurology  2012;78(18):1376-1382.
Objective:
To investigate predictors of missing data in a longitudinal study of Alzheimer disease (AD).
Methods:
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a clinic-based, multicenter, longitudinal study with blood, CSF, PET, and MRI scans repeatedly measured in 229 participants with normal cognition (NC), 397 with mild cognitive impairment (MCI), and 193 with mild AD during 2005–2007. We used univariate and multivariable logistic regression models to examine the associations between baseline demographic/clinical features and loss of biomarker follow-ups in ADNI.
Results:
CSF studies tended to recruit and retain patients with MCI with more AD-like features, including lower levels of baseline CSF Aβ42. Depression was the major predictor for MCI dropouts, while family history of AD kept more patients with AD enrolled in PET and MRI studies. Poor cognitive performance was associated with loss of follow-up in most biomarker studies, even among NC participants. The presence of vascular risk factors seemed more critical than cognitive function for predicting dropouts in AD.
Conclusion:
The missing data are not missing completely at random in ADNI and likely conditional on certain features in addition to cognitive function. Missing data predictors vary across biomarkers and even MCI and AD groups do not share the same missing data pattern. Understanding the missing data structure may help in the design of future longitudinal studies and clinical trials in AD.
doi:10.1212/WNL.0b013e318253d5b3
PMCID: PMC3345787  PMID: 22491869
18.  Incidence of New-Onset Seizures in Mild to Moderate Alzheimer Disease 
Archives of neurology  2012;69(3):368-372.
Objective
To estimate the incidence rate and predictors of seizures in patients with mild to moderate Alzheimer disease (AD).
Design
Cohort study of patients with mild to moderate AD in clinical trials. Risk factors for potential seizures were evaluated by stratified descriptive statistics and univariable and multivariable Cox proportional hazards regressions.
Setting
Pooled patient-level data from 10 Alzheimer Disease Cooperative Study clinical trials in mild to moderate AD from 1995 to 2010.
Patients
Three thousand seventy-eight subjects randomized to the treatment or placebo arms of 10 AD clinical trials. Screening Mini-Mental State Examination scores ranged between 10 and 28.
Results
Eighteen seizures were reported in 3078 randomized subjects, with an incidence rate of 484 per 100 000 person-years (95% CI, 287–764). Statistically significant independent risk factors for seizure were younger age (adjusted hazard ratio, 0.80; 95% CI, 0.69–0.93 per every 5 years of age), greater cognitive impairment at baseline (adjusted hazard ratio, 2.79; 95% CI, 1.06–7.33 for Mini-Mental State Examination scores <18 compared with Mini-Mental State Examination scores ≥18), and antipsychotic use at baseline (adjusted hazard ratio, 3.47; 95% CI, 1.33–9.08).
Conclusions
Seizure rates in patients with mild to moderate AD in clinical trials are similar to rates observed in longer observational cohort studies, but they are greater than expected in the general elderly population. Younger age, greater degree of cognitive impairment, and history of antipsychotic use were independent risk factors for new-onset seizures in AD.
doi:10.1001/archneurol.2011.830
PMCID: PMC3622046  PMID: 22410444
19.  Shapes of the Trajectories of Five Major Biomarkers of Alzheimer’s Disease 
Archives of neurology  2012;69(7):856-867.
Objective
To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.
Design
Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
Patients
Two different samples (n=343 and n=598) were created that spanned the cognitive spectrum from normal to AD dementia. Subgroup analyses were performed in members of both cohorts (n=243 and n=328) who were amyloid positive at baseline.
Main Outcome Measures
The shape of biomarker trajectories as a function of MMSE, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebro spinal fluid (CSF) Aβ42 and tau; amyloid and fluoro deoxyglucose position emission tomography (PET) imaging, and structural magnetic resonance imaging (MRI).
Results
Baseline biomarker values generally worsened (i.e., non-zero slope) with lower baseline MMSE. Baseline hippocampal volume, amyloid PET and FDG PET values plateaued (i.e., non-linear slope) with lower MMSE in one or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE. Non-constant within-subject rates (deceleration) of biomarker change were found in only one model.
Conclusions
Biomarker trajectory shapes by MMSE were complex and were affected by interactions with age and APOE status. Non-linearity was found in several baseline effects models. Non-constant within-subject rates of biomarker change were found in only one model, likely due to limited within-subject longitudinal follow up. Creating reliable models that describe the full trajectories of AD biomarkers will require significant additional longitudinal data in individual participants.
doi:10.1001/archneurol.2011.3405
PMCID: PMC3595157  PMID: 22409939
Alzheimer’s disease biomarkers; Magnetic Resonance Imaging; cerebro spinal fluid; amyloid PET imaging; FDG PET imaging
20.  Clinical and Biomarker Changes in Dominantly Inherited Alzheimer’s Disease 
The New England journal of medicine  2012;367(9):795-804.
BACKGROUND
The order and magnitude of pathologic processes in Alzheimer’s disease are not well understood, partly because the disease develops over many years. Autosomal dominant Alzheimer’s disease has a predictable age at onset and provides an opportunity to determine the sequence and magnitude of pathologic changes that culminate in symptomatic disease.
METHODS
In this prospective, longitudinal study, we analyzed data from 128 participants who underwent baseline clinical and cognitive assessments, brain imaging, and cerebrospinal fluid (CSF) and blood tests. We used the participant’s age at baseline assessment and the parent’s age at the onset of symptoms of Alzheimer’s disease to calculate the estimated years from expected symptom onset (age of the participant minus parent’s age at symptom onset). We conducted cross-sectional analyses of baseline data in relation to estimated years from expected symptom onset in order to determine the relative order and magnitude of pathophysiological changes.
RESULTS
Concentrations of amyloid-beta (Aβ)42 in the CSF appeared to decline 25 years before expected symptom onset. Aβ deposition, as measured by positron-emission tomography with the use of Pittsburgh compound B, was detected 15 years before expected symptom onset. Increased concentrations of tau protein in the CSF and an increase in brain atrophy were detected 15 years before expected symptom onset. Cerebral hypometabolism and impaired episodic memory were observed 10 years before expected symptom onset. Global cognitive impairment, as measured by the Mini–Mental State Examination and the Clinical Dementia Rating scale, was detected 5 years before expected symptom onset, and patients met diagnostic criteria for dementia at an average of 3 years after expected symptom onset.
CONCLUSIONS
We found that autosomal dominant Alzheimer’s disease was associated with a series of pathophysiological changes over decades in CSF biochemical markers of Alzheimer’s disease, brain amyloid deposition, and brain metabolism as well as progressive cognitive impairment. Our results require confirmation with the use of longitudinal data and may not apply to patients with sporadic Alzheimer’s disease. (Funded by the National Institute on Aging and others; DIAN ClinicalTrials.gov number, NCT00869817.)
doi:10.1056/NEJMoa1202753
PMCID: PMC3474597  PMID: 22784036
21.  The Alzheimer’s Disease Neuroimaging Initiative: A review of papers published since its inception 
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD and 200 normal controls and $67 million funding was provided by both the public and private sectors including the National Institutes on Aging, thirteen pharmaceutical companies and two Foundations that provided support through the Foundation for NIH (FNIH). This article reviews all papers published since the inception of the initiative and summarizes the results as of February, 2011. The major accomplishments of ADNI have been 1) the development of standardized methods for clinical, magnetic resonance imaging (MRI) and positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in a multi-center setting; 2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control, MCI and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β amyloid (Aβ) cascade [1] and tau mediated neurodegeneration hypotheses for AD while brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; 3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities including MRI, FDG-PET, CSF biomarkers and clinical tests; 4) the development of methods for the early detection of AD. CSF biomarkers, Aβ42 and tau as well as amyloid PET may reflect the earliest steps in AD pathology in mildly or even non-symptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; 5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities whereas MRI measures of change were shown to be the most efficient outcome measures; 6) the confirmation of the AD risk loci CLU, CR1 and PICALM and the identification of novel candidate risk loci; 7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia and Australia; 8) understanding the biology and pathobiology of normal aging, MCI and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD thereby advancing efforts to find disease modifying drugs for AD; and 9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a two year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI2) in October, 2010 through to 2016, with enrollment of an additional 550 participants.
doi:10.1016/j.jalz.2011.09.172
PMCID: PMC3329969  PMID: 22047634
22.  The role of apolipoprotein E (APOE) genotype in early mild cognitive impairment (E-MCI) 
Objective: Our goal was to evaluate the association of APOE with amyloid deposition, cerebrospinal fluid levels (CSF) of Aβ, tau, and p-tau, brain atrophy, cognition and cognitive complaints in E-MCI patients and cognitively healthy older adults (HC) in the ADNI-2 cohort.
Methods: Two-hundred and nine E-MCI and 123 HC participants from the ADNI-2 cohort were included. We evaluated the impact of diagnostic status (E-MCI vs. HC) and APOE ε4 status (ε4 positive vs. ε4 negative) on cortical amyloid deposition (AV-45/Florbetapir SUVR PET scans), brain atrophy (structural MRI scans processed using voxel-based morphometry and Freesurfer version 5.1), CSF levels of Aβ, tau, and p-tau, and cognitive performance and complaints.
Results: E-MCI participants showed significantly impaired cognition, higher levels of cognitive complaints, greater levels of tau and p-tau, and subcortical and cortical atrophy relative to HC participants (p < 0.05). Cortical amyloid deposition and CSF levels of Aβ were significantly associated with APOE ε4 status but not E-MCI diagnosis, with ε4 positive participants showing more amyloid deposition and lower levels of CSF Aβ than ε4 negative participants. Other effects of APOE ε4 status on cognition and CSF tau levels were also observed.
Conclusions: APOE ε4 status is associated with amyloid accumulation and lower CSF Aβ, as well as increased CSF tau levels in early prodromal stages of AD (E-MCI) and HC. Alternatively, neurodegeneration, cognitive impairment, and increased complaints are primarily associated with a diagnosis of E-MCI. These findings underscore the importance of considering APOE genotype when evaluating biomarkers in early stages of disease.
doi:10.3389/fnagi.2013.00011
PMCID: PMC3612590  PMID: 23554593
apolipoprotein E (APOE); early mild cognitive impairment (E-MCI); Florbetapir/AV-45/Amyvid; positron emission tomography (PET); magnetic resonance imaging (MRI); cerebrospinal fluid (CSF); Alzheimer's disease neuroimaging initiative (ADNI)
23.  Adding Delayed Recall to the Alzheimer Disease Assessment Scale is Useful in Studies of Mild Cognitive Impairment But Not Alzheimer Disease 
Objective
To determine if the addition of delayed recall (DR) assessment adds sensitivity to the cognitive subscale of the Alzheimer Disease Assessment Scale (ADAS-cog) in clinical trials in mild cognitive impairment (MCI) and Alzheimer Disease (AD).
Background
Memory, particularly DR, is the most sensitive test for early detection of AD and MCI. However, it is not clear that assessment of DR adds benefit for measuring change over time after a diagnosis is made or in clinical trials. The ADAS-cog is the most commonly used tool to assess treatment efficacy in AD clinical trials. In an attempt to improve sensitivity to change, assessment of DR after the 3-trial, 10-word list was added to the standard 11-item ADAS-cog. We examined the added value of the DR in participants with MCI and AD followed for at least 1 year.
Design/Methods
Data from 111 subjects with AD and 259 subjects with MCI who were randomly assigned to the placebo arm of 2 clinical trials were included. Participants with AD had Mini- Mental State Examination scores of 13 to 27 and those with MCI had 24 to 30. We calculated the ADAS-cog11 score based on the original 11 items (range: best to worse, 0 to 70), the DR item score (range: 0 to 10 words not recalled), and the ADAS-cog12 (range: 0 to 80). We assessed the rate of missing items for DR over time, the change scores, the association between scores and baseline performance, and used longitudinal mixed effects regression models to examine the rate of change.
Results
At baseline AD subjects were near floor on DR (8.93 ± 1.6 SD) and showed little change over 1 year (0.12 ± 1.34); the MCI subjects baseline DR was 6.2 ± 2.2 with 1-year change of 0.20 ± 1.7. We compared standardized change (change/SD) for ADAS-cog11, and 12 in MCI and found a 10% improvement with ADAS-cog12; there was no improvement in the AD group. In a subset of MCI and AD cases with matching Mini-Mental State Examination (23 to 27), the ADAS-cog12 provided an 18% improvement in standardized change in MCI subjects, with no benefit in the AD cohort, primarily owing to increased variance.
Conclusions/Relevance
The addition of DR to the ADAS-cog score increased the ability to detect change in subjects with MCI over 1 year compared with the ADAS-cog11 but increased the variance in subjects with AD, even in those with mild impairment These findings speak to the need to tailor outcome measures to the specific study population and diagnosis for maximal efficiency and economy when conducting clinical trials.
doi:10.1097/WAD.0b013e3181f883b7
PMCID: PMC3526369  PMID: 20921876
Alzheimer disease; mild cognitive impairment; Alzheimer Disease Assessment Scale; delayed recall; clinical trial outcomes
24.  Clinical trial methodologies for disease-modifying therapeutic approaches 
Neurobiology of aging  2011;32(Suppl 1):S64-S66.
In recent years, advances in Alzheimer’s disease (AD) biomarker research have provided powerful tools to improve trial design. In particular, biomarkers provide powerful methods for the selection of individuals with AD prior to the onset of dementia. Data suggests that neuroimaging biomarkers will be useful as endpoints for trials in very early, even asymptomatic disease, though further work is necessary to establish validity for regulatory purposes.
doi:10.1016/j.neurobiolaging.2011.09.008
PMCID: PMC3232303  PMID: 21983242
Alzheimer’s disease; biomarkers; clinical trials
25.  Amyloid-β associated volume loss occurs only in the presence of phospho-tau 
Annals of Neurology  2011;70(4):657-661.
The relationship between neurodegeneration and the two hallmark proteins of Alzheimer's disease, amyloid-β (Aβ) and tau, is still unclear. Here, we examined 286 non-demented participants (107 cognitively normal older adults and 179 memory impaired individuals) who underwent longitudinal MR imaging and lumbar puncture. Using mixed effects models, we investigated the relationship between longitudinal entorhinal cortex atrophy, CSF p-tau181p and CSF Aβ1-42. We found a significant relationship between elevated entorhinal cortex atrophy and decreased CSF Aβ1-42 only with elevated CSF p-tau181p. Our findings indicate that Aβ-associated volume loss occurs only in the presence of phospho-tauin humans at risk for dementia.
doi:10.1002/ana.22509
PMCID: PMC3368003  PMID: 22002658

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