2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Alzheimer's & dementia: the journal of the Alzheimer's Association (Impact Factor: 12.41). 06/2015; 11(6):e1-e120. DOI: 10.1016/j.jalz.2014.11.001


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 initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas 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 select and combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) 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. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data 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 (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

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    • "All the participants were categorized as SCD as patients with MCI were excluded from the study. However , within the SCD group we identified an EMCI group, almost equal to the ADNI-2 protocol [1] [17], requiring MMSE scores between 25–30, a subjective memory complaint, and memory loss measured by normative data on the RAVLT delayed recall (between 0.5 to 1.3 SD below the mean of cognitively normal ), absence of significant levels of impairment in other cognitive domains based on initial interview and evaluation, essentially preserved activities of daily living, and an absence of dementia. In the ADNI-2 protocol memory loss was measured by educationadjusted performance on the Logical Memory task (delayed memory) from Wechlser Memory Scale- Revised (WMS-R) [40]. "
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    ABSTRACT: Background: There is a need to find very early markers for pre-clinical Alzheimer's disease as interventions early in the disease process are thought to be most effective. Objective: The present study aimed to address the potential relation between cerebrospinal fluid (CSF) biomarkers and reduced cognitive function in a relatively young cohort of memory clinic patients with subjective cognitive decline. Methods: 122 patients (mean age 63 years) with subjective cognitive decline were recruited from two university memory clinics and followed for two years. Results: The main finding was that the subgroup with objective memory decline during the study period had significantly higher T-tau at baseline than the group with improved memory. Baseline CSF variables showed a trend toward more pathological values in the patients with memory decline compared to those who improved or remained stable. The baseline memory score of those who declined was significantly better than the baseline score of those who improved over two years. The general trend for the whole group was improved memory and executive test scores. There were no differences in cognitive scores based on CSF quartiles at baseline, nor were there differences in cognitive outcome for patients with early amnestic mild cognitive impairment versus average cognitive function at baseline. Conclusions: The main finding that T-tau rather than amyloid-β was associated with memory decline do not support the prevailing opinion about the chain of events assumed to take place in Alzheimer's disease. In addition, memory decline was not associated with poor baseline memory score. Thus, a memory cut-off indicating low baseline memory would not would have identified the declining group.
    Journal of Alzheimer's disease: JAD 09/2015; 47(3):619-628. DOI:10.3233/JAD-150109 · 4.15 Impact Factor
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    • "Specifically, the FCP pooled previously collected data from independent sites around the world, and demonstrated that discovery science could be performed on the aggregate sample. The FCP model of open sharing for the purposes of hypothesis testing and generation was not new, as a number of like minded efforts attempted sharing in the past (Van Horn et al., 2001; Marcus et al., 2007b; Weiner et al., 2012). "

    Frontiers in Systems Neuroscience 01/2012; 6. DOI:10.3389/fnsys.2012.00062
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    ABSTRACT: Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
    NeuroImage 03/2014; 95. DOI:10.1016/j.neuroimage.2014.03.033 · 6.36 Impact Factor
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