The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Abstract

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 control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. 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 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 consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers 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 combine optimum features from multiple modalities, including MRI, [18F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) 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; (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 ...

Destruction of White Matter Integrity in Patients with Mild Cognitive Impairment and Alzheimer Disease

“…The principal investigator of this initiative is Michael W. Weiner, MD. 21 The ADNI is the result of efforts of many co-investigators from a broad range of academic institutions and private corporations, and subjects have been recruited from more than 50 sites across the United States and Canada. To date, more than 1500 adults, aged 55 to 90 years, have been recruited, consisting of cognitively healthy older individuals, people with early or late MCI, and people with early AD (for up-to-date information, see ).…”

Models for predicting risk of dementia: a systematic review

“…While research on dementia risk prediction has been developing rapidly in the past decade, new risk factors and biomarkers were identified to be associated with dementia or AD, and subsequently incorporated into newly constructed models to increase the predictive accuracy 3. Besides, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was initiated in 2003 to test whether serial MRI, positron emission tomography, the biomarkers and clinical and neuropsychological assessments can be combined to accurately describe the natural history and measure trajectories of AD progression 4. Many models were constructed using the data from the ADNI, especially the models for predicting mild cognitive impairment (MCI) to AD conversion 5–8…”

Cortical signatures of cognition and their relationship to Alzheimer’s disease

“…MPRAGE sequences were optimized for each scanner to maximize compatibility across scanners. Scanners at each site were calibrated for ADNI with ongoing quality assurance examinations using a specially designed ADNI phantom and human volunteers; these scans were quality-checked by investigators at the Mayo site (Kruggel et al, 2010; Weiner et al, 2012). …”

“…However, the field continues to struggle with how to identify individuals at the highest risk ofdeveloping signs and symptoms of clinical AD. The pathological cascade of AD is likely present years before clinically noticeable changes, and likely begins 20 to 30 years before clinical onset when an individual is still cognitively normal (Weiner et al, 2012). Thus, early detection of AD pathology using biomarkers is of practical and clinical relevance (Clark et al, 2008; Shaw, 2008).…”