Schwarz, Adam J.

At autopsy, individuals with Alzheimer’s disease (AD) exhibit heterogeneity in the distribution of neurofibrillary tangles in neocortical and hippocampal regions. Subtypes of AD, defined using an algorithm based on the relative number of tangle counts in these regions, have been proposed—hippocampal sparing (relative sparing of the hippocampus but high cortical load), limbic predominant (high hippocampal load but lower load in association cortices), and typical (balanced neurofibrillary tangles counts in the hippocampus and association cortices) AD—and shown to be associated with distinct antemortem clinical phenotypes. The ability to distinguish these AD subtypes from the more typical tau signature in vivo could have important implications for clinical research. Flortaucipir positron emission tomography (PET) images acquired from 45 amyloid-positive participants, defined clinically as mild cognitive impairment or AD, aged 50–92 years, 56% female, and estimated to be Braak V-VI based on their PET pattern of tau pathology, were studied. By translating the neuropathologic algorithm to flortaucipir PET scans, patterns of tau pathology consistent with autopsy findings, and with a similar prevalence, were identified in vivo. 6/45 (13%) participants were identified as hippocampal sparing and 6/45 (13%) as limbic predominant AD subtypes. Hippocampal sparing participants were significantly younger than those assigned to the other two subtypes. Worse performance on delayed recall was associated with increased hippocampal tau signal, and worse performance on the trail making test B-A was associated with lower values of the hippocampus to cortex ratio. Prospective studies can further validate the flortaucipir SUVR cut-points and the phenotype of the corresponding AD subtypes.

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 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, [ 18 F]‐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.

AbstractBackgroundLow HCV has recently been qualified by the European Medicines Agency as a biomarker for enrichment of clinical trials in predementia stages of Alzheimer's disease. For automated methods to meet the necessary regulatory requirements, it is essential they be standardized and their performance be well characterized.MethodsThe within‐image and between‐field strength reproducibility of automated hippocampal volumetry using the Learning Embeddings for Atlas Propagation (or LEAP) algorithm was assessed on 153 Alzheimer's Disease Neuroimaging Initiative subjects.ResultsTests/retests at 1.5 T and 3 T, and a comparison between 1.5 T and 3 T, yielded average unsigned variabilities in HCVs of 1.51%, 1.52%, and 2.68%. A small bias between field strengths (mean signed difference, 1.17%; standard deviation, 3.07%) was observed.ConclusionsThe measured reproducibility characteristics confirm the suitability of using automated magnetic resonance imaging analyses to assess HCVs quantitatively and to represent a fundamental characterization that is critical to meet the regulatory requirements for using hippocampal volumetry in clinical trials and health care.

AbstractBackgroundRegulatory qualification of a biomarker for a defined context of use provides scientifically robust assurances to sponsors and regulators that accelerate appropriate adoption of biomarkers into drug development.MethodsThe Coalition Against Major Diseases submitted a dossier to the Scientific Advice Working Party of the European Medicines Agency requesting a qualification opinion on the use of hippocampal volume as a biomarker for enriching clinical trials in subjects with mild cognitive impairment, incorporating a scientific rationale, a literature review and a de novo analysis of Alzheimer's Disease Neuroimaging Initiative data.ResultsThe literature review and de novo analysis were consistent with the proposed context of use, and the Committee for Medicinal Products for Human Use released an opinion in November 2011.ConclusionsWe summarize the scientific rationale and the data that supported the first qualification of an imaging biomarker by the European Medicines Agency.