Clifford R. Jack

The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of revising the 1984 criteria for Alzheimer's disease (AD) dementia. The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. We present criteria for all‐cause dementia and for AD dementia. We retained the general framework of probable AD dementia from the 1984 criteria. On the basis of the past 27 years of experience, we made several changes in the clinical criteria for the diagnosis. We also retained the term possible AD dementia, but redefined it in a manner more focused than before. Biomarker evidence was also integrated into the diagnostic formulations for probable and possible AD dementia for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis of AD dementia. Much work lies ahead for validating the biomarker diagnosis of AD dementia.

In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a "research framework" because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long "preclinical" phase of AD would provide a critical opportunity for therapeutic intervention; however, we need to further elucidate the link between the pathological cascade of AD and the emergence of clinical symptoms. The National Institute on Aging and the Alzheimer's Association convened an international workgroup to review the biomarker, epidemiological, and neuropsychological evidence, and to develop recommendations to determine the factors which best predict the risk of progression from "normal" cognition to mild cognitive impairment and AD dementia. We propose a conceptual framework and operational research criteria, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies. These recommendations are solely intended for research purposes and do not have any clinical implications at this time. It is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD, and ultimately, aid the field in moving toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious.

The First Key Symposium was held in Stockholm, Sweden, 2-5 September 2003. The aim of the symposium was to integrate clinical and epidemiological perspectives on the topic of Mild Cognitive Impairment (MCI). A multidisciplinary, international group of experts discussed the current status and future directions of MCI, with regard to clinical presentation, cognitive and functional assessment, and the role of neuroimaging, biomarkers and genetics. Agreement on new perspectives, as well as recommendations for management and future research were discussed by the international working group. The specific recommendations for the general MCI criteria include the following: (i) the person is neither normal nor demented; (ii) there is evidence of cognitive deterioration shown by either objectively measured decline over time and/or subjective report of decline by self and/or informant in conjunction with objective cognitive deficits; and (iii) activities of daily living are preserved and complex instrumental functions are either intact or minimally impaired.

Currently available evidence strongly supports the position that the initiating event in Alzheimer's disease (AD) is related to abnormal processing of beta-amyloid (Abeta) peptide, ultimately leading to formation of Abeta plaques in the brain. This process occurs while individuals are still cognitively normal. Biomarkers of brain beta-amyloidosis are reductions in CSF Abeta(42) and increased amyloid PET tracer retention. After a lag period, which varies from patient to patient, neuronal dysfunction and neurodegeneration become the dominant pathological processes. Biomarkers of neuronal injury and neurodegeneration are increased CSF tau and structural MRI measures of cerebral atrophy. Neurodegeneration is accompanied by synaptic dysfunction, which is indicated by decreased fluorodeoxyglucose uptake on PET. We propose a model that relates disease stage to AD biomarkers in which Abeta biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegenerative biomarkers become abnormal later, and correlate with clinical symptom severity.

In 2010, we put forward 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. Since then, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of our assumptions, which has allowed us to modify our original model. Refinements to our model include indexing of individuals by time rather than clinical symptom severity; incorporation of interindividual variability in cognitive impairment associated with progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and recognition that the two major proteinopathies underlying AD biomarker changes, amyloid β (Aβ) and tau, might be initiated independently in sporadic AD, in which we hypothesise that an incident Aβ pathophysiology can accelerate antecedent limbic and brainstem tauopathy.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's disease. Magnetic resonance imaging (MRI), (18F)-fluorodeoxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquired at multiple time points. All data will be cross-linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications that guided protocol development. A major effort was devoted to evaluating 3D T(1)-weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced-scale clinical trial. The protocol selected for the ADNI study includes: back-to-back 3D magnetization prepared rapid gradient echo (MP-RAGE) scans; B(1)-calibration scans when applicable; and an axial proton density-T(2) dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom-based monitoring of all scanners could be used as a model for other multisite trials.

Criteria for the clinical diagnosis of Alzheimer's disease (AD) were established in 1984. A broad consensus now exists that these criteria should be revised to incorporate state-of-the-art scientific knowledge.The National Institute on Aging (NIA) and the Alzheimer's Association sponsored a series of advisory round table meetings in 2009 whose purpose was to establish a process for revising diagnostic and research criteria for AD. The recommendation from these advisory meetings was that three separate work groups should be formed with each assigned the task of formulating diagnostic criteria for one phase of the disease: the dementia phase; the symptomatic, pre-dementia phase; and the asymptomatic, preclinical phase of AD.Two notable differences from the AD criteria published in 1984 are incorporation of biomarkers of the underlying disease state and formalization of different stages of disease in the diagnostic criteria. There was a broad consensus within all three workgroups that much additional work is needed to validate the application of biomarkers for diagnostic purposes. In the revised NIA-Alzheimer's Association criteria, a semantic and conceptual distinction is made between AD pathophysiological processes and clinically observable syndromes that result, whereas this distinction was blurred in the 1984 criteria.The new criteria for AD are presented in three documents. The core clinical criteria of the recommendations regarding AD dementia and MCI due to AD are intended to guide diagnosis in the clinical setting. However, the recommendations of the preclinical AD workgroup are intended purely for research purposes.

Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.To characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.

MRI-based structural imaging has become an integral component of the clinical assessment of patients with suspected Alzheimer disease (AD), and atrophy of medial temporal structures is now considered to be a valid diagnostic marker at the mild cognitive impairment stage. In this article, Frisoni et al. consider the roles of structural MRI markers in the diagnosis of AD and non-AD dementias, and in the tracking of disease progression during clinical trials. Structural imaging based on magnetic resonance is an integral part of the clinical assessment of patients with suspected Alzheimer dementia. Prospective data on the natural history of change in structural markers from preclinical to overt stages of Alzheimer disease are radically changing how the disease is conceptualized, and will influence its future diagnosis and treatment. Atrophy of medial temporal structures is now considered to be a valid diagnostic marker at the mild cognitive impairment stage. Structural imaging is also included in diagnostic criteria for the most prevalent non-Alzheimer dementias, reflecting its value in differential diagnosis. In addition, rates of whole-brain and hippocampal atrophy are sensitive markers of neurodegeneration, and are increasingly used as outcome measures in trials of potentially disease-modifying therapies. Large multicenter studies are currently investigating the value of other imaging and nonimaging markers as adjuncts to clinical assessment in diagnosis and monitoring of progression. The utility of structural imaging and other markers will be increased by standardization of acquisition and analysis methods, and by development of robust algorithms for automated assessment.

Biomarkers have become an essential component of Alzheimer disease (AD) research and because of the pervasiveness of AD pathology in the elderly, the same biomarkers are used in cognitive aging research. A number of current issues suggest that an unbiased descriptive classification scheme for these biomarkers would be useful. We propose the "A/T/N" system in which 7 major AD biomarkers are divided into 3 binary categories based on the nature of the pathophysiology that each measures. "A" refers to the value of a β-amyloid biomarker (amyloid PET or CSF Aβ42); "T," the value of a tau biomarker (CSF phospho tau, or tau PET); and "N," biomarkers of neurodegeneration or neuronal injury ([(18)F]-fluorodeoxyglucose-PET, structural MRI, or CSF total tau). Each biomarker category is rated as positive or negative. An individual score might appear as A+/T+/N-, or A+/T-/N-, etc. The A/T/N system includes the new modality tau PET. It is agnostic to the temporal ordering of mechanisms underlying AD pathogenesis. It includes all individuals in any population regardless of the mix of biomarker findings and therefore is suited to population studies of cognitive aging. It does not specify disease labels and thus is not a diagnostic classification system. It is a descriptive system for categorizing multidomain biomarker findings at the individual person level in a format that is easy to understand and use. Given the present lack of consensus among AD specialists on terminology across the clinically normal to dementia spectrum, a biomarker classification scheme will have broadest acceptance if it is independent from any one clinically defined diagnostic scheme.

In the past 10 years, there has been a virtual explosion in the literature concerning the construct of mild cognitive impairment. The interest in this topic demonstrates the increasing emphasis on the identification of the earliest features of cognitive disorders such as Alzheimer disease and other dementias. Mild cognitive impairment represents the earliest clinical features of these conditions and, hence, has become a focus of clinical, epidemiologic, neuroimaging, biomarker, neuropathological, disease mechanism, and clinical trials research. This review summarizes the progress that has been made while also recognizing the challenges that remain.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

The purpose of this study was to use serial imaging to gain insight into the sequence of pathologic events in Alzheimer's disease, and the clinical features associated with this sequence. We measured change in amyloid deposition over time using serial (11)C Pittsburgh compound B (PIB) positron emission tomography and progression of neurodegeneration using serial structural magnetic resonance imaging. We studied 21 healthy cognitively normal subjects, 32 with amnestic mild cognitive impairment and 8 with Alzheimer's disease. Subjects were drawn from two sources--ongoing longitudinal registries at Mayo Clinic, and the Alzheimer's disease Neuroimaging Initiative (ADNI). All subjects underwent clinical assessments, MRI and PIB studies at two time points, approximately one year apart. PIB retention was quantified in global cortical to cerebellar ratio units and brain atrophy in units of cm(3) by measuring ventricular expansion. The annual change in global PIB retention did not differ by clinical group (P = 0.90), and although small (median 0.042 ratio units/year overall) was greater than zero among all subjects (P < 0.001). Ventricular expansion rates differed by clinical group (P < 0.001) and increased in the following order: cognitively normal (1.3 cm(3)/year) < amnestic mild cognitive impairment (2.5 cm(3)/year) < Alzheimer's disease (7.7 cm(3)/year). Among all subjects there was no correlation between PIB change and concurrent change on CDR-SB (r = -0.01, P = 0.97) but some evidence of a weak correlation with MMSE (r =-0.22, P = 0.09). In contrast, greater rates of ventricular expansion were clearly correlated with worsening concurrent change on CDR-SB (r = 0.42, P < 0.01) and MMSE (r =-0.52, P < 0.01). Our data are consistent with a model of typical late onset Alzheimer's disease that has two main features: (i) dissociation between the rate of amyloid deposition and the rate of neurodegeneration late in life, with amyloid deposition proceeding at a constant slow rate while neurodegeneration accelerates and (ii) clinical symptoms are coupled to neurodegeneration not amyloid deposition. Significant plaque deposition occurs prior to clinical decline. The presence of brain amyloidosis alone is not sufficient to produce cognitive decline, rather, the neurodegenerative component of Alzheimer's disease pathology is the direct substrate of cognitive impairment and the rate of cognitive decline is driven by the rate of neurodegeneration. Neurodegeneration (atrophy on MRI) both precedes and parallels cognitive decline. This model implies a complimentary role for MRI and PIB imaging in Alzheimer's disease, with each reflecting one of the major pathologies, amyloid dysmetabolism and neurodegeneration.

Magnetic resonance imaging (MRI)-based volumetric measurements of medial temporal lobe (MTL) structures can discriminate between normal elderly control subjects and patients with Alzheimer9s disease (AD) of moderate to advanced severity. In terms of clinical utility, however, a more important issue concerns the ability of the technique to differentiate between normal elderly control subjects and AD patients with the very mildest form of the disease. We performed MRI-based volumetric measurements of the hippocampus, parahippocampal gyrus, and amygdala in 126 cognitively normal elderly control subjects and 94 patients with probable AD. The diagnosis of AD was made according to NINDS/ADRDA criteria, and disease severity was categorized by Clinical Dementia Rating (CDR) scores. Patients with CDR 0.5 were classified as very mild, CDR 1 as mild, and CDR 2 as moderate disease severity. Volumes of each structure declined with increasing age in control subjects and did so in parallel for men and women. The volume of each measured MTL structure also declined with age in patients with AD. The volume of each MTL structure was significantly smaller in AD patients than control subjects (<i>p</i> &lt; 0.001). Of the several MTL measures, the total hippocampal volumetric measurements were best at discriminating control subjects from AD patients. The mean hippocampal volumes for AD patients relative to control subjects by severity of disease were as follows: very mild AD (CDR 0.5) -1.75 SD below the control mean, mild AD (CDR 1) -1.99 SD, and moderate AD (CDR 2) -2.22 SD. Age- and gender-adjusted, normalized MRI-based hippocampal volumetric measurements provide a sensitive marker of the MTL neuroanatomic degeneration in AD early in the disease process.

Abstract With the increasing life expectancy in developed countries, the incidence of Alzheimer's disease (AD) and thus its socioeconomic impact are growing. Increasing knowledge over the last years about the pathomechanisms involved in AD allow for the development of specific treatment strategies aimed at slowing down or even preventing neuronal death in AD. However, this requires also that (1) AD can be diagnosed with high accuracy, because non‐AD dementias would not benefit from an AD‐specific treatment; (2) AD can be diagnosed in very early stages when any intervention would be most effective; and (3) treatment efficacy can be reliably and meaningfully monitored. Although there currently is no ideal biomarker that would fulfill all these requirements, there is increasing evidence that a combination of currently existing neuroimaging and cerebrospinal fluid (CSF) and blood biomarkers can provide important complementary information and thus contribute to a more accurate and earlier diagnosis of AD. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is exploring which combinations of these biomarkers are the most powerful for diagnosis of AD and monitoring of treatment effects.

With increasing life expectancy in developed countries, the incidence of Alzheimer's disease (AD) and its socioeconomic impact are growing. Increasing knowledge of the mechanisms of AD facilitates the development of treatment strategies aimed at slowing down or preventing neuronal death. AD treatment trials using clinical outcome measures require long observation times and large patient samples. There is increasing evidence that neuroimaging and cerebrospinal fluid and blood biomarkers may provide information that may reduce sample sizes and observation periods. The Alzheimer's Disease Neuroimaging Initiative will help identify clinical, neuroimaging, and biomarker outcome measures that provide the highest power for measurement of longitudinal changes and for prediction of transitions.

We describe a recently recognized disease entity, limbic-predominant age-related TDP-43 encephalopathy (LATE). LATE neuropathological change (LATE-NC) is defined by a stereotypical TDP-43 proteinopathy in older adults, with or without coexisting hippocampal sclerosis pathology. LATE-NC is a common TDP-43 proteinopathy, associated with an amnestic dementia syndrome that mimicked Alzheimer's-type dementia in retrospective autopsy studies. LATE is distinguished from frontotemporal lobar degeneration with TDP-43 pathology based on its epidemiology (LATE generally affects older subjects), and relatively restricted neuroanatomical distribution of TDP-43 proteinopathy. In community-based autopsy cohorts, ∼25% of brains had sufficient burden of LATE-NC to be associated with discernible cognitive impairment. Many subjects with LATE-NC have comorbid brain pathologies, often including amyloid-β plaques and tauopathy. Given that the 'oldest-old' are at greatest risk for LATE-NC, and subjects of advanced age constitute a rapidly growing demographic group in many countries, LATE has an expanding but under-recognized impact on public health. For these reasons, a working group was convened to develop diagnostic criteria for LATE, aiming both to stimulate research and to promote awareness of this pathway to dementia. We report consensus-based recommendations including guidelines for diagnosis and staging of LATE-NC. For routine autopsy workup of LATE-NC, an anatomically-based preliminary staging scheme is proposed with TDP-43 immunohistochemistry on tissue from three brain areas, reflecting a hierarchical pattern of brain involvement: amygdala, hippocampus, and middle frontal gyrus. LATE-NC appears to affect the medial temporal lobe structures preferentially, but other areas also are impacted. Neuroimaging studies demonstrated that subjects with LATE-NC also had atrophy in the medial temporal lobes, frontal cortex, and other brain regions. Genetic studies have thus far indicated five genes with risk alleles for LATE-NC: GRN, TMEM106B, ABCC9, KCNMB2, and APOE. The discovery of these genetic risk variants indicate that LATE shares pathogenetic mechanisms with both frontotemporal lobar degeneration and Alzheimer's disease, but also suggests disease-specific underlying mechanisms. Large gaps remain in our understanding of LATE. For advances in prevention, diagnosis, and treatment, there is an urgent need for research focused on LATE, including in vitro and animal models. An obstacle to clinical progress is lack of diagnostic tools, such as biofluid or neuroimaging biomarkers, for ante-mortem detection of LATE. Development of a disease biomarker would augment observational studies seeking to further define the risk factors, natural history, and clinical features of LATE, as well as eventual subject recruitment for targeted therapies in clinical trials.

Mild cognitive impairment (MCI) represents a transitional state between the cognitive changes of normal aging and very early dementia and is becoming increasingly recognized as a risk factor for Alzheimer disease (AD). The Memory Impairment Study (MIS) is a multicenter clinical trial in patients with MCI designed to evaluate whether vitamin E or donepezil is effective at delaying the time to a clinical diagnosis of AD.To describe the baseline characteristics of patients with MCI recruited for the MIS and compare them with those of elderly controls and patients with AD in another clinical trial.Descriptive and comparative study of patients with MCI participating in a multicenter clinical trial.Memory disorder centers in the United States and Canada.A total of 769 patients with MCI, 107 cognitively normal elderly controls, 122 patients with very mild AD (Clinical Dementia Rating [CDR] 0.5), and 183 patients with mild AD (CDR 1.0) were evaluated. Patients in the MIS met operational criteria for amnestic MCI. Controls were recruited in parallel with the MCI group, underwent the same assessments, and had a CDR of 0.Clinical, neuropsychologic, functional, neuroimaging, and genetic measures.Mean +/- SD Alzheimer's Disease Assessment Scale-Cognitive Subscale scores were 5.6 +/- 3.3 for controls, 11.3 +/- 4.4 for patients with MCI, 18.0 +/- 6.2 for the AD CDR 0.5 group, and 25.2 +/- 8.8 for the AD CDR 1.0 group. Compared with controls, patients with MCI were most impaired on memory tasks, with less severe impairments in other cognitive domains. Patients with MCI were more likely than controls but less likely than patients with AD to carry the apolipoprotein E epsilon4 allele. Patients with MCI had hippocampal volumes that were intermediate between those of controls and patients with AD.Patients with MCI had a predominant memory impairment with relative sparing of other cognitive domains and were intermediate between clinically normal individuals and patients with AD on cognitive and functional ratings. These results demonstrate the successful implementation of operational criteria for this unique group of at-risk patients in a multicenter clinical trial.

Abstract Multifactorial mechanisms underlying late-onset Alzheimer’s disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system’s integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions.

To date, most diagnostic imaging comparisons between amyloid labelling ligands and other imaging modalities have been between the use of amyloid labelling ligand (11)C Pittsburgh Compound B (PiB) and FDG-PET. Our objectives were to compare cognitive performance and diagnostic group-wise discrimination between cognitively normal, amnestic mild cognitive impairment (MCI) and Alzheimer's disease subjects with MRI-based measures of hippocampal volume and PiB retention, and secondly to evaluate the topographic distribution of PiB retention and grey matter loss using 3D voxel-wise methods. Twenty cognitively normal, 17 amnestic MCI and 8 probable Alzheimer's disease subjects were imaged with both MRI and PiB. PiB retention was quantified as the ratio of uptake in cortical to cerebellar regions of interest (ROIs) 40-60 min post-injection. A global cortical PiB retention summary measure was derived from six cortical ROIs. Statistical parametric mapping (SPM) and voxel-based morphometry (VBM) were used to evaluate PiB retention and grey matter loss on a 3D voxel-wise basis. Alzheimer's disease subjects had high global cortical PiB retention and low hippocampal volume; most cognitively normal subjects had low PiB retention and high hippocampal volume; and on average amnestic MCI subjects were intermediate on both PiB and hippocampal volume. A target-to-cerebellar ratio of 1.5 was used to designate subjects with high or low PiB cortical retention. All Alzheimer's disease subjects fell above this ratio, as did 6 out of 20 cognitively normal subjects and 9 out of 17 MCI subjects, indicating bi-modal PiB retention in the latter two groups. Interestingly, we found no consistent differences in learning and memory performance between high versus low PiB cognitively normal or amnestic MCI subjects. The SPM/VBM voxel-wise comparisons of Alzheimer's disease versus cognitively normal subjects provided complementary information in that clear and meaningful similarities and differences in topographical distribution of amyloid deposition and grey matter loss were shown. The frontal lobes had high PiB retention with little grey matter loss, anteromedial temporal areas had low PiB retention with significant grey matter loss, whereas lateral temporoparietal association cortex displayed both significant PiB retention and grey matter loss. A voxel-wise SPM conjunction analysis revealed that subjects with high PiB retention shared a common PiB retention topographical pattern regardless of clinical category, and this matched that of amyloid plaque distribution from autopsy studies of Alzheimer's disease. Both global cortical PiB retention and hippocampal volumes demonstrated significant correlation in the expected direction with cognitive testing performance; however, correlations were stronger with MRI than PiB. Pair-wise inter-group diagnostic separation was significant for all group-wise pairs for both PiB and hippocampal volume with the exception of the comparison of cognitively normal versus amnestic MCI, which was not significant for PiB. PiB and MRI provided complementary information such that clinical diagnostic classification using both methods was superior to using either in isolation.

The cognitive continuum in the elderly population can be conceptually divided into those who are functioning normally (control subjects), those with a mild cognitive impairment (MCI), and those with probable AD.To test the hypothesis that the annualized rates of hippocampal atrophy differ as a function of both baseline and change in clinical group membership (control, MCI, or AD).The authors identified 129 subjects from the Mayo Clinic AD Research Center/AD Patient Registry who met established criteria for normal control subjects, MCI, or probable AD, both at entry and at the time of a subsequent clinical follow-up evaluation 3 +/- 1 years later. Each subject underwent an MRI examination of the head at the time of the initial assessment and at follow-up clinical assessment; the annualized percentage change in hippocampal volume was computed. Subjects who were classified as controls or patients with MCI at baseline could either remain cognitively stable or could decline to a lower functioning group over the period of observation.The annualized rates of hippocampal volume loss for each of the three initial clinical groups decreased progressively in the following order: AD > MC > control. Within the control and MCI groups, those who declined had a significantly greater rate of volume loss than those who remained clinically stable. The mean annualized rates of hippocampal atrophy by follow-up clinical group were: control-stable 1.73%, control-decliner 2.81%, MCI-stable 2.55%, MCI-decliner 3.69%, AD 3. 5%.Rates of hippocampal atrophy match both baseline cognitive status and the change in cognitive status over time in elderly persons who lie along the cognitive continuum from normal to MCI to AD.

We evaluated a new magnetic resonance (MR)-based technique for performing volumetric measurements of temporal lobe structures. The technique was designed to assist in making the clinical diagnosis of dementia of the Alzheimer type (DAT). We chose specific anatomic regions of interest because of their known involvement in memory function and in the neuropathology of DAT and used a regression model to assess the effects of age on the volumes of the anterior temporal lobe (ATL) and the hippocampal formation (HF). These measurements were normalized by total intracranial volume (TIV). The volumetric measurements of both the normalized ATL and HF were significantly smaller (p &lt; 0.001) in DAT patients (N = 20) than in controls (N = 22), but the HF volumes provided much better separation between the two groups. Eighty-five percent of the DAT patients fell below the range of the HF/TIV measurement for the control subjects. This separation held up over the entire age range studied. Normalized volumes of both the HF and ATL decreased with age significantly for both the DAT patients and the controls. These results support the contention that MR-based HF volumetric measurements are accurate in differentiating DAT patients from cognitively normal elderly individuals. This technique may be a useful adjunct in making the clinical diagnosis of DAT.

To correlate different methods of measuring rates of brain atrophy from serial MRI with corresponding clinical change in normal elderly subjects, patients with mild cognitive impairment (MCI), and patients with probable Alzheimer disease (AD).One hundred sixty subjects were recruited from the Mayo Clinic Alzheimer's Disease Research Center and Alzheimer's Disease Patient Registry Studies. At baseline, 55 subjects were cognitively normal, 41 met criteria for MCI, and 64 met criteria for AD. Each subject underwent an MRI examination of the brain at the time of the baseline clinical assessment and then again at the time of a follow-up clinical assessment, 1 to 5 years later. The annualized changes in volume of four structures were measured from the serial MRI studies: hippocampus, entorhinal cortex, whole brain, and ventricle. Rates of change on several cognitive tests/rating scales were also assessed. Subjects who were classified as normal or MCI at baseline could either remain stable or convert to a lower-functioning group. AD subjects were dichotomized into slow vs fast progressors.All four atrophy rates were greater among normal subjects who converted to MCI or AD than among those who remained stable, greater among MCI subjects who converted to AD than among those who remained stable, and greater among fast than slow AD progressors. In general, atrophy on MRI was detected more consistently than decline on specific cognitive tests/rating scales. With one exception, no differences were found among the four MRI rate measures in the strength of the correlation with clinical deterioration at different stages of the disease.These data support the use of rates of change from serial MRI studies in addition to standard clinical/psychometric measures as surrogate markers of disease progression in AD. Estimated sample sizes required to power a therapeutic trial in MCI were an order of magnitude less for MRI than for change measures based on cognitive tests/rating scales.

<h3>Context</h3>Docosahexaenoic acid (DHA) is the most abundant long-chain polyunsaturated fatty acid in the brain. Epidemiological studies suggest that consumption of DHA is associated with a reduced incidence of Alzheimer disease. Animal studies demonstrate that oral intake of DHA reduces Alzheimer-like brain pathology.<h3>Objective</h3>To determine if supplementation with DHA slows cognitive and functional decline in individuals with Alzheimer disease.<h3>Design, Setting, and Patients</h3>A randomized, double-blind, placebo-controlled trial of DHA supplementation in individuals with mild to moderate Alzheimer disease (Mini-Mental State Examination scores, 14-26) was conducted between November 2007 and May 2009 at 51 US clinical research sites of the Alzheimer’s Disease Cooperative Study.<h3>Intervention</h3>Participants were randomly assigned to algal DHA at a dose of 2 g/d or to identical placebo (60% were assigned to DHA and 40% were assigned to placebo). Duration of treatment was 18 months.<h3>Main Outcome Measures</h3>Change in the cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-cog) and change in the Clinical Dementia Rating (CDR) sum of boxes. Rate of brain atrophy was also determined by volumetric magnetic resonance imaging in a subsample of participants (n = 102).<h3>Results</h3>A total of 402 individuals were randomized and a total of 295 participants completed the trial while taking study medication (DHA: 171; placebo: 124). Supplementation with DHA had no beneficial effect on rate of change on ADAS-cog score, which increased by a mean of 7.98 points (95% confidence interval [CI], 6.51-9.45 points) for the DHA group during 18 months vs 8.27 points (95% CI, 6.72-9.82 points) for the placebo group (linear mixed-effects model: P = .41). The CDR sum of boxes score increased by 2.87 points (95% CI, 2.44-3.30 points) for the DHA group during 18 months compared with 2.93 points (95% CI, 2.44-3.42 points) for the placebo group (linear mixed-effects model: P = .68). In the subpopulation of participants (DHA: 53; placebo: 49), the rate of brain atrophy was not affected by treatment with DHA. Individuals in the DHA group had a mean decline in total brain volume of 24.7 cm³ (95% CI, 21.4-28.0 cm³) during 18 months and a 1.32% (95% CI, 1.14%-1.50%) volume decline per year compared with 24.0 cm³ (95% CI, 20-28 cm³) for the placebo group during 18 months and a 1.29% (95% CI, 1.07%-1.51%) volume decline per year (P = .79).<h3>Conclusion</h3>Supplementation with DHA compared with placebo did not slow the rate of cognitive and functional decline in patients with mild to moderate Alzheimer disease.<h3>Trial Registration</h3>clinicaltrials.gov Identifier: NCT00440050

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, [(18)F]-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 processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

Abstract Introduction Our goal was to develop cut points for amyloid positron emission tomography (PET), tau PET, flouro‐deoxyglucose (FDG) PET, and MRI cortical thickness. Methods We examined five methods for determining cut points. Results The reliable worsening method produced a cut point only for amyloid PET. The specificity, sensitivity, and accuracy of cognitively impaired versus young clinically normal (CN) methods labeled the most people abnormal and all gave similar cut points for tau PET, FDG PET, and cortical thickness. Cut points defined using the accuracy of cognitively impaired versus age‐matched CN method labeled fewer people abnormal. Discussion In the future, we will use a single cut point for amyloid PET (standardized uptake value ratio, 1.42; centiloid, 19) based on the reliable worsening cut point method. We will base lenient cut points for tau PET, FDG PET, and cortical thickness on the accuracy of cognitively impaired versus young CN method and base conservative cut points on the accuracy of cognitively impaired versus age‐matched CN method.

Abstract Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

<b>Objectives: </b> To determine the annual rates of volumetric change of the hippocampus and temporal horn in cognitively normal elderly control subjects and individually matched patients with AD, and to test the hypothesis that these rates were different. <b>Background: </b> Cross-sectional studies consistently reveal cerebral atrophy in elderly nondemented subjects compared with healthy young adults, and greater atrophy in patients with AD relative to elderly control subjects. However, rates of atrophy are estimated most accurately by performing serial measurements in the same individuals. <b>Methods: </b> MRI-based volumetric measurements of the hippocampi and temporal horns were performed in 24 cognitively normal subjects aged 70 to 89 years who were individually matched with respect to gender and age with 24 patients with AD. Each subject underwent an MRI protocol twice, separated by 12 months or more. <b>Results: </b> The mean annual rate of hippocampal volume loss among control subjects was -1.55 ± 1.38% and the temporal horns increased in volume by 6.15 ± 7.69% per year. These rates were significantly greater among AD patients: hippocampus, -3.98 ± 1.92% per year, <i>p</i> &lt; 0.001; temporal horn, 14.16 ± 8.47% per year, <i>p</i> = 0.002. <b>Conclusion: </b> A statistically significant yearly decline in hippocampal volume and an increase in temporal horn volume was identified in elderly control subjects who represent typical aging individuals. These rates were approximately 2.5 times greater in patients with AD than in individually age- and gender-matched control subjects.

Volumes of the right and left anterior temporal lobes and hippocampal formations were measured from magnetic resonance images in 52 healthy volunteers, aged 20-40 years. Subjects were selected by age, sex, and handedness to evaluate possible effect of these variables. Data were normalized for variation in total intracranial volume between individuals. Right-left asymmetry in the volumes of the anterior temporal lobes and hippocampal formations was a normal finding. The anterior temporal lobe of the non-dominant (right) hemisphere was larger than the left by a small (mean right-left difference, 2.3 cm3) but statistically significant amount (P less than .005) in right-handed subjects. No significant effect of age or sex was seen in normalized right or left anterior temporal lobe volume. The right hippocampal formation was larger than the left for all subjects by a small (mean right-left difference, 0.3 cm3) but statistically significant amount (P less than .001). No effect of age, sex, or handedness was seen in normalized hippocampal formation volumes.

A variety of measurements have been individually linked to decline in mild cognitive impairment (MCI), but the identification of optimal markers for predicting disease progression remains unresolved. The goal of this study was to evaluate the prognostic ability of genetic, CSF, neuroimaging, and cognitive measurements obtained in the same participants.APOE epsilon4 allele frequency, CSF proteins (Abeta(1-42), total tau, hyperphosphorylated tau [p-tau(181p)]), glucose metabolism (FDG-PET), hippocampal volume, and episodic memory performance were evaluated at baseline in patients with amnestic MCI (n = 85), using data from a large multisite study (Alzheimer's Disease Neuroimaging Initiative). Patients were classified as normal or abnormal on each predictor variable based on externally derived cutoffs, and then variables were evaluated as predictors of subsequent conversion to Alzheimer disease (AD) and cognitive decline (Alzheimer's Disease Assessment Scale-Cognitive Subscale) during a variable follow-up period (1.9 +/- 0.4 years).Patients with MCI converted to AD at an annual rate of 17.2%. Subjects with MCI who had abnormal results on both FDG-PET and episodic memory were 11.7 times more likely to convert to AD than subjects who had normal results on both measures (p <or= 0.02). In addition, the CSF ratio p-tau(181p)/Abeta(1-42) (beta = 1.10 +/- 0.53; p = 0.04) and, marginally, FDG-PET predicted cognitive decline.Baseline FDG-PET and episodic memory predict conversion to AD, whereas p-tau(181p)/Abeta(1-42) and, marginally, FDG-PET predict longitudinal cognitive decline. Complementary information provided by these biomarkers may aid in future selection of patients for clinical trials or identification of patients likely to benefit from a therapeutic intervention.

Amyloid imaging related abnormalities (ARIA) have now been reported in clinical trials with multiple therapeutic avenues to lower amyloid-β burden in Alzheimer's disease (AD). In response to concerns raised by the Food and Drug Administration, the Alzheimer's Association Research Roundtable convened a working group to review the publicly available trial data, attempts at developing animal models, and the literature on the natural history and pathology of related conditions. The spectrum of ARIA includes signal hyperintensities on fluid attenuation inversion recoverysequences thought to represent "vasogenic edema" and/or sulcal effusion (ARIA-E), as well as signal hypointensities on GRE/T2* thought to represent hemosiderin deposits (ARIA-H), including microhemorrhage and superficial siderosis. The etiology of ARIA remains unclear but the prevailing data support vascular amyloid as a common pathophysiological mechanism leading to increased vascular permeability. The workgroup proposes recommendations for the detection and monitoring of ARIA in ongoing AD clinical trials, as well as directions for future research.

A workgroup commissioned by the Alzheimer's Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer disease (AD). We performed a preliminary assessment of these guidelines.We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis, and (18) fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cutpoints. A group of 450 cognitively normal (CN) subjects from a population-based sample was used to develop cognitive cutpoints and to assess population frequencies of the different preclinical AD stages using different cutpoint criteria.The new criteria subdivide the preclinical phase of AD into stages 1 to 3. To classify our CN subjects, 2 additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected non-AD pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cutpoints corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0, 16% stage 1, 12 % stage 2, 3% stage 3, and 23% SNAP.This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1-3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving only 3% unclassified. Future longitudinal validation of the criteria will be important.

Hippocampal volume change over time, measured with MRI, has huge potential as a marker for Alzheimer's disease. The objectives of this study were: (i) to test if constant and accelerated hippocampal loss can be detected in Alzheimer's disease, mild cognitive impairment and normal ageing over short periods, e.g. 6–12 months, with MRI in the large multicentre setting of the Alzheimer's Disease Neuroimaging Initiative (ADNI); (ii) to determine the extent to which the polymorphism of the apolipoprotein E (ApoE) gene modulates hippocampal change; and (iii) to determine if rates of hippocampal loss correlate with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease, such as the β-amyloid (Aβ1–42) and tau proteins (tau). The MRI multicentre study included 112 cognitive normal elderly individuals, 226 mild cognitive impairment and 96 Alzheimer's disease patients who all had at least three successive MRI scans, involving 47 different imaging centres. The mild cognitive impairment and Alzheimer's disease groups showed hippocampal volume loss over 6 months and accelerated loss over 1 year. Moreover, increased rates of hippocampal loss were associated with presence of the ApoE allele ɛ4 gene in Alzheimer's disease and lower CSF Aβ1–42 in mild cognitive impairment, irrespective of ApoE genotype, whereas relations with tau were only trends. The power to measure hippocampal change was improved by exploiting correlations statistically between successive MRI observations. The demonstration of considerable hippocampal loss in mild cognitive impairment and Alzheimer's disease patients over only 6 months and accelerated loss over 12 months illustrates the power of MRI to track morphological brain changes over time in a large multisite setting. Furthermore, the relations between faster hippocampal loss in the presence of ApoE allele ɛ4 and decreased CSF Aβ1–42 supports the concept that increased hippocampal loss is an indicator of Alzheimer's disease pathology and a potential marker for the efficacy of therapeutic interventions in Alzheimer's disease.

To assess the diagnostic specificity of MRI-defined hippocampal atrophy for AD among individuals with a variety of pathologically confirmed conditions associated with dementia as well as changes attributable to typical aging, and to measure correlations among premortem MRI measurements of hippocampal atrophy, mental status examination performance, and the pathologic stage of AD.An unselected series of 67 individuals participating in the Mayo Alzheimer's Disease Research Center/Alzheimer's Disease Patient Registry who had undergone a standardized antemortem MRI study and also postmortem examination were identified. Hippocampal volumes were measured from antemortem MRI. Each postmortem specimen was assigned a pathologic diagnosis and in addition, the severity of AD pathology was staged using the method of Braak and Braak.Individuals with an isolated pathologic diagnosis of AD, hippocampal sclerosis, frontotemporal degeneration, and neurofibrillary tangle--only degeneration usually had substantial hippocampal atrophy, while those with changes of typical aging did not. Among all 67 subjects, correlations (all p < 0.001) were observed between hippocampal volume and Braak and Braak stage (r = -0.39), between hippocampal volume and Mini-Mental State Examination (MMSE) score (r = 0.60), and between MMSE score and Braak and Braak stage (r = -0.41).Hippocampal atrophy, while not specific for AD, was a fairly sensitive marker of the pathologic AD stage (particularly among subjects with isolated AD pathology [r = -0.63, p = 0.001]) and consequent cognitive status.

Mild cognitive impairment (MCI), particularly the amnestic subtype (aMCI), is considered as a transitional stage between normal aging and a diagnosis of clinically probable Alzheimer's disease (AD). The aMCI construct is particularly useful as it provides an opportunity to assess a clinical stage which in most subjects represents prodromal AD. The aim of this study was to assess the progression of cerebral atrophy over multiple serial MRI during the period from aMCI to progression to AD. Thirty-three subjects were selected that fulfilled clinical criteria for aMCI and had three serial MRI scans: the first scan ∼3 years before the diagnosis of AD, the second scan ∼1 year before, and the third scan at the time of the diagnosis of AD. A group of 33 healthy controls were age and gender-matched to the study cohort. Voxel-based morphometry (VBM) was used to assess patterns of grey matter atrophy in the aMCI subjects at each time-point compared to the control group. Customized templates and prior probability maps were used to avoid normalization and segmentation bias. The pattern of grey matter loss in the aMCI subject scans that were 3 years before the diagnosis of AD was focused primarily on the medial temporal lobes, including the amygdala, anterior hippocampus and entorhinal cortex, with some additional involvement of the fusiform gyrus, compared to controls. The extent and magnitude of the cerebral atrophy further progressed by the time the subjects were 1 year before the diagnosis of AD. At this point atrophy in the temporal lobes spread to include the middle temporal gyrus, and extended into more posterior regions of the temporal lobe to include the entire extent of the hippocampus. The parietal lobe also started to become involved. By the time the subjects had progressed to a clinical diagnosis of AD the pattern of grey matter atrophy had become still more widespread with more severe involvement of the medial temporal lobes and the temporoparietal association cortices and, for the first time, substantial involvement of the frontal lobes. This pattern of progression fits well with the Braak and Braak neurofibrillary pathological staging scheme in AD. It suggests that the earliest changes occur in the anterior medial temporal lobe and fusiform gyrus, and that these changes occur at least 3 years before progression to the diagnosis of AD. These results also suggest that 3D patterns of grey matter atrophy may help to predict the time to the first diagnosis of AD in subjects with aMCI.

Traditional side-by-side visual interpretation of ictal and interictal single-photon emission computed tomography (SPECT) scans can be difficult in identifying the surgical focus, particularly in patients with extratemporal or otherwise unlocalized intractable epilepsy. Computer-aided subtraction ictal SPECT co-registered to MRI (SISCOM) may improve the clinical usefulness of SPECT in localizing the surgical seizure focus. We studied 51 consecutive intractable partial epilepsy patients who had interictal and ictal scans. The SPECT studies were blindly reviewed and classified as either localizing to 1 of 16 sites in the brain or as nonlocalizing. SISCOM images were localizing in 45 of 51 (88.2%) compared with 20 of 51 (39.2%) for traditional side-by-side inspection of ictal and interictal SPECT images (p < 0.0001). Inter-rater agreement for two independent reviewers was better for SISCOM (84.3% versus 41.2%, kappa = 0.83 versus 0.26; p < 0.0001). Concordance of seizure localization with the more established tests was also higher for SISCOM. Late injection of the radiotracer (> 45 seconds), but not secondary generalization of the seizure, was associated with a falsely localizing or nonlocalizing SISCOM. Epilepsy surgery patients whose SISCOM localization was concordant with a falsely localizing or nonlocalizing SISCOM. Epilepsy surgery patients whose SISCOM localization was concordant with the surgical site were more likely to have excellent outcome than patients with nonconcordant or nonlocalizing findings (62.5% [10/16] versus 20% [2/10]; p < 0.05). On the other hand, seizure localization by the traditional method of SPECT inspection had no significant association with postsurgical outcome. We conclude that SISCOM improves the sensitivity and the specificity of SPECT in localizing the seizure focus for epilepsy surgery. Concordance between SISCOM localization and site of surgery is predictive of postsurgical improvement in seizure outcome.

The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.

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?

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6‐year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C‐11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C‐11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI‐like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.

Biomarkers of brain Aβ amyloid deposition can be measured either by cerebrospinal fluid Aβ42 or Pittsburgh compound B positron emission tomography imaging. Our objective was to evaluate the ability of Aβ load and neurodegenerative atrophy on magnetic resonance imaging to predict shorter time-to-progression from mild cognitive impairment to Alzheimer’s dementia and to characterize the effect of these biomarkers on the risk of progression as they become increasingly abnormal. A total of 218 subjects with mild cognitive impairment were identified from the Alzheimer’s Disease Neuroimaging Initiative. The primary outcome was time-to-progression to Alzheimer’s dementia. Hippocampal volumes were measured and adjusted for intracranial volume. We used a new method of pooling cerebrospinal fluid Aβ42 and Pittsburgh compound B positron emission tomography measures to produce equivalent measures of brain Aβ load from either source and analysed the results using multiple imputation methods. We performed our analyses in two phases. First, we grouped our subjects into those who were ‘amyloid positive’ (n = 165, with the assumption that Alzheimer's pathology is dominant in this group) and those who were ‘amyloid negative’ (n = 53). In the second phase, we included all 218 subjects with mild cognitive impairment to evaluate the biomarkers in a sample that we assumed to contain a full spectrum of expected pathologies. In a Kaplan–Meier analysis, amyloid positive subjects with mild cognitive impairment were much more likely to progress to dementia within 2 years than amyloid negative subjects with mild cognitive impairment (50 versus 19%). Among amyloid positive subjects with mild cognitive impairment only, hippocampal atrophy predicted shorter time-to-progression (P < 0.001) while Aβ load did not (P = 0.44). In contrast, when all 218 subjects with mild cognitive impairment were combined (amyloid positive and negative), hippocampal atrophy and Aβ load predicted shorter time-to-progression with comparable power (hazard ratio for an inter-quartile difference of 2.6 for both); however, the risk profile was linear throughout the range of hippocampal atrophy values but reached a ceiling at higher values of brain Aβ load. Our results are consistent with a model of Alzheimer’s disease in which Aβ deposition initiates the pathological cascade but is not the direct cause of cognitive impairment as evidenced by the fact that Aβ load severity is decoupled from risk of progression at high levels. In contrast, hippocampal atrophy indicates how far along the neurodegenerative path one is, and hence how close to progressing to dementia. Possible explanations for our finding that many subjects with mild cognitive impairment have intermediate levels of Aβ load include: (i) individual subjects may reach an Aβ load plateau at varying absolute levels; (ii) some subjects may be more biologically susceptible to Aβ than others; and (iii) subjects with mild cognitive impairment with intermediate levels of Aβ may represent individuals with Alzheimer’s disease co-existent with other pathologies.

Abstract We performed a prospective study correlating magnetic resonance imaging volume measurements of the hippocampal formation with histopathology in 24 patients with intractable partial epilepsy who subsequently underwent an anterior temporal lobectomy for their seizure disorder. Patients with mass lesions verified pathologically were excluded from this study. In 71% of patients, quantitative hippocampal formation atrophy correctly lateralized the temporal lobe of seizure origin; in 29%, the volume study was indeterminant. The severity of the pathological alterations in the hippocampus correlated with the hippocampal formation volume determination. Mesial temporal sclerosis was identified in the surgically excised temporal lobe in 15 patients. The magnetic resonance imaging volume studies indicated hippocampal atrophy in the temporal lobe resected in 14 of the 15 patients. Magnetic resonance imaging‐based volume measurements of the hippocampal formation increase the diagnostic yield of magnetic resonance imaging scanning in patients with intractable partial epilepsy related to mesial temporal sclerosis.

<b>Objective: </b> To test the hypothesis that the atrophy rate measured from serial MRI studies is associated with time to subsequent clinical conversion to a more impaired state in both cognitively healthy elderly subjects and in subjects with amnestic mild cognitive impairment (MCI). <b>Methods: </b> Ninety-one healthy elderly patients and 72 patients with amnestic MCI who met inclusion criteria were identified from the Mayo Alzheimer’s Disease Research Center and Alzheimer’s Disease Patient Registry. Atrophy rates of four different brain structures—hippocampus, entorhinal cortex, whole brain, and ventricle—were measured from a pair of MRI studies separated by 1 to 2 years. The time of the second scan marked the beginning of the clinical observation period. <b>Results: </b> During follow-up, 13 healthy patients converted to MCI or Alzheimer disease (AD), whereas 39 MCI subjects converted to AD. Among those healthy at baseline, only larger ventricular annual percent volume change (APC) was associated with a higher risk of conversion (hazard ratio for a 1-SD increase 1.9, <i>p</i> = 0.03). Among MCI subjects, both greater ventricular volume APC (hazard ratio for a 1-SD increase 1.7, <i>p</i> &lt; 0.001) and greater whole brain APC (hazard ratio for a 1-SD increase 1.4, <i>p</i> = 0.007) increased the risk of conversion to AD. Both ventricular APC (hazard ratio for a 1-SD increase 1.59, <i>p</i> = 0.001) and whole brain APC (hazard ratio for a 1-SD increase 1.32, <i>p</i> = 0.009) provided additional predictive information to covariate-adjusted cross-sectional hippocampal volume at baseline about the risk of converting from MCI to AD. <b>Discussion: </b> Higher whole brain and ventricle atrophy rates 1 to 2 years before baseline are associated with an increased hazard of conversion to a more impaired state. Combining a measure of hippocampal volume at baseline with a measure of either whole brain or ventricle atrophy rates from serial MRI scans provides complimentary predictive information about the hazard of subsequent conversion from mild cognitive impairment to Alzheimer disease. However, overlap among those who did vs those who did not convert indicate that these measures are unlikely to provide absolute prognostic information for individual patients.

Mild cognitive impairment (MCI) is a recently described transitional clinical state between normal aging and AD. Assuming that amnestic MCI patients had pathologic changes corresponding to an early phase and probable AD patients to a later phase of the disease progression, the authors could approximate the temporal course of proton MR spectroscopic (1H MRS) alterations in AD with a cross-sectional sampling scheme.The authors compared 1H MRS findings in the superior temporal lobe, posterior cingulate gyri, and medial occipital lobe in 21 patients with MCI, 21 patients with probable AD, and 63 elderly controls. These areas are known to be involved at different neurofibrillary pathologic stages of AD.The N-acetylaspartate (NAA)/creatine (Cr) ratios were significantly lower in AD patients compared to both MCI and normal control subjects in the left superior temporal and the posterior cingulate volumes of interest (VOI) and there were no between-group differences in the medial occipital VOI. Myoinositol (MI)/Cr ratios measured from the posterior cingulate VOI were significantly higher in both MCI and AD patients than controls. The choline (Cho)/Cr ratios measured from the posterior cingulate VOI were higher in AD patients compared to both MCI and control subjects.These findings suggest that the initial 1H MRS change in the pathologic progression of AD is an increase in MI/Cr. A decrease in NAA/Cr and an increase in Cho/Cr develop later in the disease course.

We developed a magnetic resonance imaging (MRI)-based technique for measuring the volume of the hippocampal formation. In this study, the relationship between volumes of the hippocampal formation and outcome (i.e., postoperative seizure control) after anterior temporal lobectomy for intractable epilepsy was analyzed in 50 consecutive patients in whom the surgical specimen did not contain an epileptogenic mass lesion. Outcome was classified as either satisfactory or unsatisfactory. A significant relationship was found between outcome and volume of the operated hippocampal formation (p = 0.012), as well as a derived volumetric measure (nonoperated minus operated volume of the hippocampal formation) (p = 0.004). The association between outcome and nonoperated volume was borderline (p = 0.057). Thirty-four (97%) of 35 patients in whom the volumetric study and electroencephalography (EEG) concordantly lateralized the seizure disorder had satisfactory postoperative seizure control. Conversely, only 7 (42%) of 12 patients in whom the volume study was nonlateralizing and 1 (33%) of 3 in whom the EEG and volume study were discordant has a satisfactory outcome. We regard our MRI-based study of hippocampal formation volume as a noninvasive surrogate for the identification of moderate or severe mesial temporal sclerosis. The technique is a useful adjunct in a multidisciplinary, preoperative epilepsy evaluation when T2-weighted MRIs do not reveal an epileptogenic mass lesion. The reasons for the usefulness of this imaging technique are: (1) It is an independent source of information on seizure lateralization, (2) it will provide information as to expected postoperative outcome, and (3) it may aid in appropriately selecting patients for invasive preoperative monitoring studies.

The Clinical Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI) has provided clinical, operational, and data management support to ADNI since its inception. This article reviews the activities and accomplishments of the core in support of ADNI aims. These include the enrollment and follow-up of more than 800 subjects in the three original cohorts: healthy controls, amnestic mild cognitive impairment (now referred to as late MCI, or LMCI), and mild Alzheimer's disease (AD) in the first phase of ADNI (ADNI 1), with baseline longitudinal, clinical, and cognitive assessments. These data, when combined with genetic, neuroimaging, and cerebrospinal fluid measures, have provided important insights into the neurobiology of the AD spectrum. Furthermore, these data have facilitated the development of novel clinical trial designs. ADNI has recently been extended with funding from an NIH Grand Opportunities (GO) award, and the new ADNI GO phase has been launched; this includes the enrollment of a new cohort, called early MCI, with milder episodic memory impairment than the LMCI group. An application for a further 5 years of ADNI funding (ADNI 2) was recently submitted. This funding would support ongoing follow-up of the original ADNI 1 and ADNI GO cohorts, as well as additional recruitment into all categories. The resulting data would provide valuable data on the earliest stages of AD, and support the development of interventions in these critically important populations.

To develop and validate a tool for Alzheimer's disease (AD) diagnosis in individual subjects using support vector machine (SVM)-based classification of structural MR (sMR) images. Libraries of sMR scans of clinically well characterized subjects can be harnessed for the purpose of diagnosing new incoming subjects. One hundred ninety patients with probable AD were age- and gender-matched with 190 cognitively normal (CN) subjects. Three different classification models were implemented: Model I uses tissue densities obtained from sMR scans to give STructural Abnormality iNDex (STAND)-score; and Models II and III use tissue densities as well as covariates (demographics and Apolipoprotein E genotype) to give adjusted-STAND (aSTAND)-score. Data from 140 AD and 140 CN were used for training. The SVM parameter optimization and training were done by four-fold cross validation (CV). The remaining independent sample of 50 AD and 50 CN was used to obtain a minimally biased estimate of the generalization error of the algorithm. The CV accuracy of Model II and Model III aSTAND-scores was 88.5% and 89.3%, respectively, and the developed models generalized well on the independent test data sets. Anatomic patterns best differentiating the groups were consistent with the known distribution of neurofibrillary AD pathology. This paper presents preliminary evidence that application of SVM-based classification of an individual sMR scan relative to a library of scans can provide useful information in individual subjects for diagnosis of AD. Including demographic and genetic information in the classification algorithm slightly improves diagnostic accuracy.

Complex biological systems are organized across various spatiotemporal scales with particular scientific disciplines dedicated to the study of each scale (e.g. genetics, molecular biology and cognitive neuroscience). When considering disease pathophysiology, one must contemplate the scale at which the disease process is being observed and how these processes impact other levels of organization. Historically Alzheimer's disease has been viewed as a disease of abnormally aggregated proteins by pathologists and molecular biologists and a disease of clinical symptoms by neurologists and psychologists. Bridging the divide between these scales has been elusive, but the study of brain networks appears to be a pivotal inroad to accomplish this task. In this study, we were guided by an emerging systems-based conceptualization of Alzheimer's disease and investigated changes in brain networks across the disease spectrum. The default mode network has distinct subsystems with unique functional-anatomic connectivity, cognitive associations, and responses to Alzheimer's pathophysiology. These distinctions provide a window into the systems-level pathophysiology of Alzheimer's disease. Using clinical phenotyping, metadata, and multimodal neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative, we characterized the pattern of default mode network subsystem connectivity changes across the entire disease spectrum (n = 128). The two main findings of this paper are (i) the posterior default mode network fails before measurable amyloid plaques and appears to initiate a connectivity cascade that continues throughout the disease spectrum; and (ii) high connectivity between the posterior default mode network and hubs of high connectivity (many located in the frontal lobe) is associated with amyloid accumulation. These findings support a system model best characterized by a cascading network failure--analogous to cascading failures seen in power grids triggered by local overloads proliferating to downstream nodes eventually leading to widespread power outages, or systems failures. The failure begins in the posterior default mode network, which then shifts processing burden to other systems containing prominent connectivity hubs. This model predicts a connectivity 'overload' that precedes structural and functional declines and recasts the interpretation of high connectivity from that of a positive compensatory phenomenon to that of a load-shifting process transiently serving a compensatory role. It is unknown whether this systems-level pathophysiology is the inciting event driving downstream molecular events related to synaptic activity embedded in these systems. Possible interpretations include that the molecular-level events drive the network failure, a pathological interaction between the network-level and the molecular-level, or other upstream factors are driving both.

Models of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal.Between Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11C-Pittsburgh Compound B (11C-PiB) PET, 18F-Fluorodeoxyglucose (18F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) FINDINGS: 11C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region for each method to show divergence between groups (22·2 years before expected onset for Aβ accumulation, 18·8 years before expected onset for hypometabolism, and 13·0 years before expected onset for cortical thinning).Mutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning compared with non-carriers which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials.US National Institutes of Health, the German Center for Neurodegenerative Diseases, and the Medical Research Council Dementias Platform UK.

Abstract Introduction We examined and compared plasma phospho‐tau181 (pTau181) and total tau: (1) across the Alzheimer's disease (AD) clinical spectrum; (2) in relation to brain amyloid β (Aβ) positron emission tomography (PET), tau PET, and cortical thickness; and (3) as a screening tool for elevated brain Aβ. Methods Participants included 172 cognitively unimpaired, 57 mild cognitively impaired, and 40 AD dementia patients with concurrent Aβ PET (Pittsburgh compound B), tau PET (AV1451), magnetic resonance imaging, plasma total tau, and pTau181. Results Plasma total tau and pTau181 levels were higher in AD dementia patients than those in cognitively unimpaired. Plasma pTau181 was more strongly associated with both Aβ and tau PET. Plasma pTau181 was a more sensitive and specific predictor of elevated brain Aβ than total tau and was as good as, or better than, the combination of age and apolipoprotein E ( APOE ). Discussion Plasma pTau181 may have utility as a biomarker of AD pathophysiology and as a noninvasive screener for elevated brain Aβ.

White matter hyperintensities (WMHs) are areas of increased signal on T2-weighted magnetic resonance imaging (MRI) scans that most commonly reflect small vessel cerebrovascular disease. Increased WMH volume is associated with risk and progression of Alzheimer's disease (AD). These observations are typically interpreted as evidence that vascular abnormalities play an additive, independent role contributing to symptom presentation, but not core features of AD. We examined the severity and distribution of WMH in presymptomatic PSEN1, PSEN2, and APP mutation carriers to determine the extent to which WMH manifest in individuals genetically determined to develop AD.The study comprised participants (n = 299; age = 39.03 ± 10.13) from the Dominantly Inherited Alzheimer Network, including 184 (61.5%) with a mutation that results in AD and 115 (38.5%) first-degree relatives who were noncarrier controls. We calculated the estimated years from expected symptom onset (EYO) by subtracting the affected parent's symptom onset age from the participant's age. Baseline MRI data were analyzed for total and regional WMH. Mixed-effects piece-wise linear regression was used to examine WMH differences between carriers and noncarriers with respect to EYO.Mutation carriers had greater total WMH volumes, which appeared to increase approximately 6 years before expected symptom onset. Effects were most prominent for the parietal and occipital lobe, which showed divergent effects as early as 22 years before estimated onset.Autosomal-dominant AD is associated with increased WMH well before expected symptom onset. The findings suggest the possibility that WMHs are a core feature of AD, a potential therapeutic target, and a factor that should be integrated into pathogenic models of the disease. Ann Neurol 2016;79:929-939.

It is essential to determine the specificity of AV-1451 PET for tau in brain imaging by using pathological comparisons. We performed autoradiography in autopsy-confirmed Alzheimer disease and other neurodegenerative disorders to evaluate the specificity of AV-1451 binding for tau aggregates.Tissue samples were selected that had a variety of dementia-related neuropathologies including Alzheimer disease, primary age-related tauopathy, tangle predominant dementia, non-Alzheimer disease tauopathies, frontotemporal dementia, parkinsonism, Lewy body disease and multiple system atrophy (n = 38). Brain tissue sections were stained for tau, TAR DNA-binding protein-43, and α-synuclein and compared to AV-1451 autoradiography on adjacent sections.AV-1451 preferentially localized to neurofibrillary tangles, with less binding to areas enriched in neuritic pathology and less mature tau. The strength of AV-1451 binding with respect to tau isoforms in various neurodegenerative disorders was: 3R + 4R tau (e.g., AD) > 3R tau (e.g., Pick disease) or 4R tau. Only minimal binding of AV-1451 to TAR DNA-binding protein-43 positive regions was detected. No binding of AV-1451 to α-synuclein was detected. "Off-target" binding was seen in vessels, iron-associated regions, substantia nigra, calcifications in the choroid plexus, and leptomeningeal melanin.Reduced AV-1451 binding in neuritic pathology compared to neurofibrillary tangles suggests that the maturity of tau pathology may affect AV-1451 binding and suggests complexity in AV-1451 binding. Poor association of AV-1451 with tauopathies that have preferential accumulation of either 4R tau or 3R tau suggests limited clinical utility in detecting these pathologies. In contrast, for disorders associated with 3R + 4R tau, such as Alzheimer disease, AV-1451 binds tau avidly but does not completely reflect the early stage tau progression suggested by Braak neurofibrillary tangle staging. AV-1451 binding to TAR DNA-binding protein-43 or TAR DNA-binding protein-43 positive regions can be weakly positive. Clinical use of AV-1451 will require a familiarity with distinct types of "off-target" binding.

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, [ 18 F]‐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 processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2‐year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI‐2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

Task-free functional magnetic resonance imaging (TF-fMRI) has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs) identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892) population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain's modular organization and assign each region to a "meta-modular" group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN) between 28 subjects with Alzheimer's dementia and 56 cognitively normal elderly subjects matched 1:2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer's disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer's dementia.

The role of the Alzheimer's Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome‐wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within the Alzheimer's Disease Neuroimaging Initiative. Genome‐wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer's disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials.

The purpose of this study was to obtain normative data using magnetic resonance elastography (MRE) (a) to obtain estimates of the shear modulus of human cerebral tissue in vivo and (b) to assess a possible age dependence of the shear modulus of cerebral tissue in healthy adult volunteers. MR elastography studies were performed on tissue-simulating gelatin phantoms and 25 healthy adult volunteers. The data were analyzed using spatiotemporal filters and a local frequency estimating algorithm. Statistical analysis was performed using a paired t-test. The mean shear stiffness of cerebral white matter was 13.6 kPa (95% CI 12.3 to 14.8 kPa); while that of gray matter was lower at 5.22 kPa (95% CI 4.76 to 5.66 kPa). The difference was statistically significant (p < 0.0001).

Three subtypes of Alzheimer's disease (AD) have been pathologically defined on the basis of the distribution of neurofibrillary tangles: typical AD, hippocampal-sparing AD, and limbic-predominant AD. Compared with typical AD, hippocampal-sparing AD has more neurofibrillary tangles in the cortex and fewer in the hippocampus, whereas the opposite pattern is seen in limbic-predominant AD. We aimed to determine whether MRI patterns of atrophy differ between these subtypes and whether structural neuroimaging could be a useful predictor of pathological subtype at autopsy.We identified patients who had been followed up in the Mayo Clinic Alzheimer's Disease Research Center (Rochester, MN, USA) or in the Alzheimer's Disease Patient Registry (Rochester, MN, USA) between 1992 and 2005. To be eligible for inclusion, participants had to have had dementia, AD pathology at autopsy (Braak stage ≥IV and intermediate to high probability of AD), and an ante-mortem MRI. Cases were assigned to one of three pathological subtypes--hippocampal-sparing, limbic-predominant, and typical AD--on the basis of neurofibrillary tangle counts in hippocampus and cortex and ratio of hippocampal to cortical burden, without reference to neuronal loss. Voxel-based morphometry and atlas-based parcellation were used to compare patterns of grey matter loss between groups and with age-matched control individuals. Neuroimaging was obtained at the time of first presentation. To summarise pair-wise group differences, we report the area under the receiver operator characteristic curve (AUROC).Of 177 eligible patients, 125 (71%) were classified as having typical AD, 33 (19%) as having limbic-predominant AD, and 19 (11%) as having hippocampal-sparing AD. Most patients with typical (98 [78%]) and limbic-predominant AD (31 [94%]) initially presented with an amnestic syndrome, but fewer patients with hippocampal-sparing AD (eight [42%]) did. The most severe medial temporal atrophy was recorded in patients with limbic-predominant AD, followed by those with typical disease, and then those with hippocampal-sparing AD. Conversely, the most severe cortical atrophy was noted in patients with hippocampal-sparing AD, followed by those with typical disease, and then limbic-predominant AD. The ratio of hippocampal to cortical volumes allowed the best discrimination between subtypes (p<0·0001; three-way AUROC 0·52 [95% CI 0·47-0·52]; ratio of AUROC to chance classification 3·1 [2·8-3·1]). Patients with typical AD and non-amnesic initial presentation had a significantly higher ratio of hippocampal to cortical volumes (median 0·045 [IQR 0·035-0·056]) than did those with an amnesic presentation (0·041 [0·031-0·057]; p=0·001).Patterns of atrophy on MRI differ across the pathological subtypes of AD. MRI regional volumetric analysis can reliably track the distribution of neurofibrillary tangle pathology and can predict pathological subtype of AD at autopsy.US National Institutes of Health (National Institute on Aging).

A major recent discovery was the identification of an expansion of a non-coding GGGGCC hexanucleotide repeat in the C9ORF72 gene in patients with frontotemporal dementia and amyotrophic lateral sclerosis. Mutations in two other genes are known to account for familial frontotemporal dementia: microtubule-associated protein tau and progranulin. Although imaging features have been previously reported in subjects with mutations in tau and progranulin, no imaging features have been published in C9ORF72. Furthermore, it remains unknown whether there are differences in atrophy patterns across these mutations, and whether regional differences could help differentiate C9ORF72 from the other two mutations at the single-subject level. We aimed to determine the regional pattern of brain atrophy associated with the C9ORF72 gene mutation, and to determine which regions best differentiate C9ORF72 from subjects with mutations in tau and progranulin, and from sporadic frontotemporal dementia. A total of 76 subjects, including 56 with a clinical diagnosis of behavioural variant frontotemporal dementia and a mutation in one of these genes (19 with C9ORF72 mutations, 25 with tau mutations and 12 with progranulin mutations) and 20 sporadic subjects with behavioural variant frontotemporal dementia (including 50% with amyotrophic lateral sclerosis), with magnetic resonance imaging were included in this study. Voxel-based morphometry was used to assess and compare patterns of grey matter atrophy. Atlas-based parcellation was performed utilizing the automated anatomical labelling atlas and Statistical Parametric Mapping software to compute volumes of 37 regions of interest. Hemispheric asymmetry was calculated. Penalized multinomial logistic regression was utilized to create a prediction model to discriminate among groups using regional volumes and asymmetry score. Principal component analysis assessed for variance within groups. C9ORF72 was associated with symmetric atrophy predominantly involving dorsolateral, medial and orbitofrontal lobes, with additional loss in anterior temporal lobes, parietal lobes, occipital lobes and cerebellum. In contrast, striking anteromedial temporal atrophy was associated with tau mutations and temporoparietal atrophy was associated with progranulin mutations. The sporadic group was associated with frontal and anterior temporal atrophy. A conservative penalized multinomial logistic regression model identified 14 variables that could accurately classify subjects, including frontal, temporal, parietal, occipital and cerebellum volume. The principal component analysis revealed similar degrees of heterogeneity within all disease groups. Patterns of atrophy therefore differed across subjects with C9ORF72, tau and progranulin mutations and sporadic frontotemporal dementia. Our analysis suggested that imaging has the potential to be useful to help differentiate C9ORF72 from these other groups at the single-subject level.

<b>Objective: </b> To identify presurgical and postsurgical factors that are independently predictive of the outcome of anterior temporal lobectomy (ATL) for intractable epilepsy. <b>Background: </b> There have been reports of prognostic studied 175 consecutive ATL patients who had at least 2 years of postsurgical follow-up. Significant factors on univariate analyses were subjected to stepwise logistic regression analysis. <b>Results: </b> On univariate analyses, two presurgical conditions were significantly associated with excellent seizure control at last follow-up: (1) unilateral hippocampal formation atrophy as detected on MRI and (2) all scalp interictal epileptiform discharges concordant with the location of ictal onset(<i>p</i> &lt; 0.05). Three postsurgical factors that occurred during the first year were associated with excellent seizure outcome: the absence of interictal epileptiform discharges at 3 months, complete seizure control, and having only nondisabling seizures for those who did not become seizure free. Logistic regression analysis revealed the following to be independently predictive of excellent seizure control: MRI-detected unilateral hippocampal formation atrophy, concordant interictal epileptiform discharges, complete seizure control during the first postsurgical year, and having only nondisabling seizures during the first postsurgical year for those who did not become seizure free. <b>Conclusions: </b> Presurgical identification of unilateral hippocampal formation atrophy, or of interictal epileptiform discharges that are all concordant with the location of ictal onset, predict excellent outcome of ATL. However, the probability of excellent outcome is highest (94%) when both factors are present.

PURPOSE: To describe a clinically useful application of functional magnetic resonance (MR) imaging--presurgical mapping of the sensory motor cortex--and to validate the results with established physiologic techniques. MATERIALS AND METHODS: Functional MR mapping of the sensory motor cortex was performed in two women, aged 24 and 38 years. Both had intractable, simple partial motor seizures due to tumors located in or near the sensory motor cortex. They subsequently underwent invasive cortical mapping--direct cortical stimulation and/or sensory-evoked-potential recording--to localize the affected sensory motor area prior to tumor resection. RESULTS: In both patients, the functional MR study demonstrated task activation of the sensory motor cortex. In both cases, results of cortical functional mapping with invasive techniques matched those obtained with functional MR imaging. CONCLUSION: Presurgical mapping of the sensory motor cortex is a potentially useful clinical application of functional MR imaging.

To investigate the relationship between baseline MRI and CSF biomarkers and subsequent change in continuous measures of cognitive and functional abilities in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and to examine the ability of these biomarkers to predict time to conversion from aMCI to AD.Data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN, aMCI, and AD cohorts with both CSF and MRI, were used. Baseline CSF (t-tau, Abeta(1-42), and p-tau(181P)) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like features in MRI, were computed for each subject.Change on continuous measures of cognitive and functional performance was modeled as average Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination scores over a 2-year period. STAND was a better predictor of subsequent cognitive/functional change than CSF biomarkers. Single-predictor Cox proportional hazard models for time to conversion from aMCI to AD showed that STAND and log (t-tau/Abeta(1-42)) were both predictive of future conversion. The age-adjusted hazard ratio for an interquartile change (95% confidence interval) of STAND was 2.6 (1.7, 4.2) and log (t-tau/Abeta(1-42)) was 2.0 (1.1, 3.4). Both MRI and CSF provided information about future cognitive change even after adjusting for baseline cognitive performance.MRI and CSF provide complimentary predictive information about time to conversion from amnestic mild cognitive impairment to Alzheimer disease and combination of the 2 provides better prediction than either source alone. However, we found that MRI was a slightly better predictor of future clinical/functional decline than the CSF biomarkers tested.

The current study tested the accuracy of primary MRI and cerebrospinal fluid (CSF) biomarker candidates and neuropsychological tests for predicting the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. In a cross-validation paradigm, predictor models were estimated in the training set of AD (N = 81) and elderly control subjects (N = 101). A combination of CSF t-tau/Aβ(1-4) ratio and MRI biomarkers or neuropsychological tests (free recall and trail making test B (TMT-B)) showed the best statistical fit in the AD vs. HC comparison, reaching a classification accuracy of up to 64% when applied to the prediction of MCI conversion (3.3-year observation interval, mean = 2.3 years). However, several single-predictor models showed a predictive accuracy of MCI conversion comparable to that of any multipredictor model. The best single predictors were right entorhinal cortex (prediction accuracy = 68.5% (95% CI (59.5, 77.4))) and TMT-B test (prediction accuracy 64.6% (95% CI (55.5, 73.4%))). In conclusion, short-term conversion to AD is predicted by single marker models to a comparable degree as by multimarker models in amnestic MCI subjects.

To determine whether an fMRI memory encoding task distinguishes among cognitively normal elderly individuals, patients with mild cognitive impairment (MCI), and patients with early Alzheimer's disease (AD).Twenty-nine subjects (11 normal, 9 MCI, 9 AD) were studied with an fMRI memory encoding task. A passive sensory task was also performed to assess potential intergroup differences in fMRI responsiveness. Activation in the medial temporal lobe for the memory task and in the anatomic rolandic area for the sensory task was studied. Intergroup comparisons were performed using receiver operating characteristic (ROC) analyses. The ROC method provides rigorous control of artifactual false-positive "activation." Subjects were tested for recall and recognition of the encoding task stimuli following the fMRI study.Medial temporal lobe activation was greater in normal subjects than MCI and AD patients (p = 0.03 and p = 0.04). There was no difference between AD and MCI patients in fMRI memory performance [corrected]. There was an association between fMRI memory activation (area under the ROC curve) and post-fMRI performance on recognition and free recall. There was no difference among the three groups on the sensory task.MCI and AD patients had less medial temporal lobe activation on the memory task than the normal subjects but similar activation as normal subjects on the sensory task. These findings suggest decreased medial temporal activation may be a specific marker of limbic dysfunction due to the neurodegenerative changes of AD. In addition, fMRI is sufficiently sensitive to detect changes in the prodromal, MCI, phase of the disease.

Apraxia of speech is a disorder of speech motor planning and/or programming that is distinguishable from aphasia and dysarthria. It most commonly results from vascular insults but can occur in degenerative diseases where it has typically been subsumed under aphasia, or it occurs in the context of more widespread neurodegeneration. The aim of this study was to determine whether apraxia of speech can present as an isolated sign of neurodegenerative disease. Between July 2010 and July 2011, 37 subjects with a neurodegenerative speech and language disorder were prospectively recruited and underwent detailed speech and language, neurological, neuropsychological and neuroimaging testing. The neuroimaging battery included 3.0 tesla volumetric head magnetic resonance imaging, [18F]-fluorodeoxyglucose and [11C] Pittsburg compound B positron emission tomography scanning. Twelve subjects were identified as having apraxia of speech without any signs of aphasia based on a comprehensive battery of language tests; hence, none met criteria for primary progressive aphasia. These subjects with primary progressive apraxia of speech included eight females and four males, with a mean age of onset of 73 years (range: 49–82). There were no specific additional shared patterns of neurological or neuropsychological impairment in the subjects with primary progressive apraxia of speech, but there was individual variability. Some subjects, for example, had mild features of behavioural change, executive dysfunction, limb apraxia or Parkinsonism. Voxel-based morphometry of grey matter revealed focal atrophy of superior lateral premotor cortex and supplementary motor area. Voxel-based morphometry of white matter showed volume loss in these same regions but with extension of loss involving the inferior premotor cortex and body of the corpus callosum. These same areas of white matter loss were observed with diffusion tensor imaging analysis, which also demonstrated reduced fractional anisotropy and increased mean diffusivity of the superior longitudinal fasciculus, particularly the premotor components. Statistical parametric mapping of the [18F]-fluorodeoxyglucose positron emission tomography scans revealed focal hypometabolism of superior lateral premotor cortex and supplementary motor area, although there was some variability across subjects noted with CortexID analysis. [11C]-Pittsburg compound B positron emission tomography binding was increased in only one of the 12 subjects, although it was unclear whether the increase was actually related to the primary progressive apraxia of speech. A syndrome characterized by progressive pure apraxia of speech clearly exists, with a neuroanatomic correlate of superior lateral premotor and supplementary motor atrophy, making this syndrome distinct from primary progressive aphasia.

The aim of this study was to determine whether the TAR DNA-binding protein of 43 kDa (TDP-43) has any independent effect on the clinical and neuroimaging features typically ascribed to Alzheimer's disease (AD) pathology, and whether TDP-43 pathology could help shed light on the phenomenon of resilient cognition in AD. Three-hundred and forty-two subjects pathologically diagnosed with AD were screened for the presence, burden and distribution of TDP-43. All had been classified as cognitively impaired or normal, prior to death. Atlas-based parcellation and voxel-based morphometry were used to assess regional atrophy on MRI. Regression models controlling for age at death, apolipoprotein ε4 and other AD-related pathologies were utilized to explore associations between TDP-43 and cognition or brain atrophy, stratified by Braak stage. In addition, we determined whether the effects of TDP-43 were mediated by hippocampal sclerosis. One-hundred and ninety-five (57%) cases were TDP-positive. After accounting for age, apolipoprotein ε4 and other pathologies, TDP-43 had a strong effect on cognition, memory loss and medial temporal atrophy in AD. These effects were not mediated by hippocampal sclerosis. TDP-positive subjects were 10× more likely to be cognitively impaired at death compared to TDP-negative subjects. Greater cognitive impairment and medial temporal atrophy were associated with greater TDP-43 burden and more extensive TDP-43 distribution. TDP-43 is an important factor in the manifestation of the clinico-imaging features of AD. TDP-43 also appears to be able to overpower what has been termed resilient brain aging. TDP-43 therefore should be considered a potential therapeutic target for the treatment of AD.

A genome-wide, whole brain approach to investigate genetic effects on neuroimaging phenotypes for identifying quantitative trait loci is described. The Alzheimer's Disease Neuroimaging Initiative 1.5 T MRI and genetic dataset was investigated using voxel-based morphometry (VBM) and FreeSurfer parcellation followed by genome-wide association studies (GWAS). One hundred forty-two measures of grey matter (GM) density, volume, and cortical thickness were extracted from baseline scans. GWAS, using PLINK, were performed on each phenotype using quality-controlled genotype and scan data including 530,992 of 620,903 single nucleotide polymorphisms (SNPs) and 733 of 818 participants (175 AD, 354 amnestic mild cognitive impairment, MCI, and 204 healthy controls, HC). Hierarchical clustering and heat maps were used to analyze the GWAS results and associations are reported at two significance thresholds (p < 10− 7 and p < 10− 6). As expected, SNPs in the APOE and TOMM40 genes were confirmed as markers strongly associated with multiple brain regions. Other top SNPs were proximal to the EPHA4, TP63 and NXPH1 genes. Detailed image analyses of rs6463843 (flanking NXPH1) revealed reduced global and regional GM density across diagnostic groups in TT relative to GG homozygotes. Interaction analysis indicated that AD patients homozygous for the T allele showed differential vulnerability to right hippocampal GM density loss. NXPH1 codes for a protein implicated in promotion of adhesion between dendrites and axons, a key factor in synaptic integrity, the loss of which is a hallmark of AD. A genome-wide, whole brain search strategy has the potential to reveal novel candidate genes and loci warranting further investigation and replication.

To model the temporal trajectory of β-amyloid accumulation using serial amyloid PET imaging.Participants, aged 70-92 years, were enrolled in either the Mayo Clinic Study of Aging (n = 246) or the Mayo Alzheimer's Disease Research Center (n = 14). All underwent 2 or more serial amyloid PET examinations. There were 205 participants classified as cognitively normal and 55 as cognitively impaired (47 mild cognitive impairment and 8 Alzheimer dementia). We measured baseline amyloid PET-relative standardized uptake values (SUVR) and, for each participant, estimated a slope representing their annual amyloid accumulation rate. We then fit regression models to predict the rate of amyloid accumulation given baseline amyloid SUVR, and evaluated age, sex, clinical group, and APOE as covariates. Finally, we integrated the amyloid accumulation rate vs baseline amyloid PET SUVR association to an amyloid PET SUVR vs time association.Rates of amyloid accumulation were low at low baseline SUVR. Rates increased to a maximum at baseline SUVR around 2.0, above which rates declined-reaching zero at baseline SUVR above 2.7. The rate of amyloid accumulation as a function of baseline SUVR had an inverted U shape. Integration produced a sigmoid curve relating amyloid PET SUVR to time. The average estimated time required to travel from an SUVR of 1.5-2.5 is approximately 15 years.This roughly 15-year interval where the slope of the amyloid SUVR vs time curve is greatest and roughly linear represents a large therapeutic window for secondary preventive interventions.

The global impact of Alzheimer's disease (AD) continues to increase, and focused efforts are needed to address this immense public health challenge. National leaders have set a goal to prevent or effectively treat AD by 2025. In this paper, we discuss the path to 2025, and what is feasible in this time frame given the realities and challenges of AD drug development, with a focus on disease-modifying therapies (DMTs). Under the current conditions, only drugs currently in late Phase 1 or later will have a chance of being approved by 2025. If pipeline attrition rates remain high, only a few compounds at best will meet this time frame. There is an opportunity to reduce the time and risk of AD drug development through an improvement in trial design; better trial infrastructure; disease registries of well-characterized participant cohorts to help with more rapid enrollment of appropriate study populations; validated biomarkers to better detect disease, determine risk and monitor disease progression as well as predict disease response; more sensitive clinical assessment tools; and faster regulatory review. To implement change requires efforts to build awareness, educate and foster engagement; increase funding for both basic and clinical research; reduce fragmented environments and systems; increase learning from successes and failures; promote data standardization and increase wider data sharing; understand AD at the basic biology level; and rapidly translate new knowledge into clinical development. Improved mechanistic understanding of disease onset and progression is central to more efficient AD drug development and will lead to improved therapeutic approaches and targets. The opportunity for more than a few new therapies by 2025 is small. Accelerating research and clinical development efforts and bringing DMTs to market sooner would have a significant impact on the future societal burden of AD. As these steps are put in place and plans come to fruition, e.g., approval of a DMT, it can be predicted that momentum will build, the process will be self-sustaining, and the path to 2025, and beyond, becomes clearer.

In one of the largest brain MRI studies to date, we used tensor-based morphometry (TBM) to create 3D maps of structural atrophy in 676 subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy elderly controls, scanned as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). Using inverse-consistent 3D non-linear elastic image registration, we warped 676 individual brain MRI volumes to a population mean geometric template. Jacobian determinant maps were created, revealing the 3D profile of local volumetric expansion and compression. We compared the anatomical distribution of atrophy in 165 AD patients (age: 75.6 ± 7.6 years), 330 MCI subjects (74.8 ± 7.5), and 181 controls (75.9 ± 5.1). Brain atrophy in selected regions-of-interest was correlated with clinical measurements – the sum-of-boxes clinical dementia rating (CDR-SB), mini-mental state examination (MMSE), and the logical memory test scores – at voxel level followed by correction for multiple comparisons. Baseline temporal lobe atrophy correlated with current cognitive performance, future cognitive decline, and conversion from MCI to AD over the following year; it predicted future decline even in healthy subjects. Over half of the AD and MCI subjects carried the ApoE4 (apolipoprotein E4) gene, which increases risk for AD; they showed greater hippocampal and temporal lobe deficits than non-carriers. ApoE2 gene carriers – 1/6 of the normal group – showed reduced ventricular expansion, suggesting a protective effect. As an automated image analysis technique, TBM reveals 3D correlations between neuroimaging markers, genes, and future clinical changes, and is highly efficient for large-scale MRI studies.

Functions of the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre‐processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI‐GO”) and future (“ADNI‐2,” if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled “ADNI‐1” subjects who are followed up longitudinally in ADNI‐GO and ADNI‐2. We will modernize and expand the MRI protocol for all newly enrolled ADNI‐GO and ADNI‐2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1‐weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI‐GO and ADNI‐2 protocol, we will perform vendor‐specific pilot sub‐studies of arterial spin‐labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub‐studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications.

Basic research advances in recent years have furthered our understanding of the natural history of Alzheimer’s disease (AD). It is now recognized that pathophysiological changes begin many years prior to clinical manifestations of disease and the spectrum of AD spans from clinically asymptomatic to severely impaired. Defining AD purely by its clinical presentation is thus artificial and efforts have been made to recognize the disease based on both clinical and biomarker findings. Advances with biomarkers have also prompted a shift in how the disease is considered as a clinico-pathophysiological entity, with an increasing appreciation that AD should not only be viewed with discrete and defined clinical stages, but as a multifaceted process moving along a seamless continuum. Acknowledging this concept is critical to understanding the development process for disease-modifying therapies, and for initiating effective diagnostic and disease management options. In this article, we discuss the concept of a disease continuum from pathophysiological, biomarker, and clinical perspectives, and highlight the importance of considering AD as a continuum rather than discrete stages. While the pathophysiology of AD has still not been elucidated completely, there is ample evidence to support researchers and clinicians embracing the view of a disease continuum in their study, diagnosis, and management of the disease.

Numerous kindreds with familial frontotemporal dementia and/or amyotrophic lateral sclerosis have been linked to chromosome 9, and an expansion of the GGGGCC hexanucleotide repeat in the non-coding region of chromosome 9 open reading frame 72 has recently been identified as the pathogenic mechanism. We describe the key characteristics in the probands and their affected relatives who have been evaluated at Mayo Clinic Rochester or Mayo Clinic Florida in whom the hexanucleotide repeat expansion were found. Forty-three probands and 10 of their affected relatives with DNA available (total 53 subjects) were shown to carry the hexanucleotide repeat expansion. Thirty-six (84%) of the 43 probands had a familial disorder, whereas seven (16%) appeared to be sporadic. Among examined subjects from the 43 families (n = 63), the age of onset ranged from 33 to 72 years (median 52 years) and survival ranged from 1 to 17 years, with the age of onset <40 years in six (10%) and >60 in 19 (30%). Clinical diagnoses among examined subjects included behavioural variant frontotemporal dementia with or without parkinsonism (n = 30), amyotrophic lateral sclerosis (n = 18), frontotemporal dementia/amyotrophic lateral sclerosis with or without parkinsonism (n = 12), and other various syndromes (n = 3). Parkinsonism was present in 35% of examined subjects, all of whom had behavioural variant frontotemporal dementia or frontotemporal dementia/amyotrophic lateral sclerosis as the dominant clinical phenotype. No subject with a diagnosis of primary progressive aphasia was identified with this mutation. Incomplete penetrance was suggested in two kindreds, and the youngest generation had significantly earlier age of onset (>10 years) compared with the next oldest generation in 11 kindreds. Neuropsychological testing showed a profile of slowed processing speed, complex attention/executive dysfunction, and impairment in rapid word retrieval. Neuroimaging studies showed bilateral frontal abnormalities most consistently, with more variable degrees of parietal with or without temporal changes; no case had strikingly focal or asymmetric findings. Neuropathological examination of 14 patients revealed a range of transactive response DNA binding protein molecular weight 43 pathology (10 type A and four type B), as well as ubiquitin-positive cerebellar granular neuron inclusions in all but one case. Motor neuron degeneration was detected in nine patients, including five patients without ante-mortem signs of motor neuron disease. While variability exists, most cases with this mutation have a characteristic spectrum of demographic, clinical, neuropsychological, neuroimaging and especially neuropathological findings.

Neurofibrillary tangles (NFTs), composed of hyperphosphorylated tau proteins, are one of the pathologic hallmarks of Alzheimer disease (AD). We aimed to determine whether patterns of gray matter atrophy from antemortem MRI correlate with Braak staging of NFT pathology.Eighty-three subjects with Braak stage III through VI, a pathologic diagnosis of low- to high-probability AD, and MRI within 4 years of death were identified. Voxel-based morphometry assessed gray matter atrophy in each Braak stage compared with 20 pathologic control subjects (Braak stages 0 through II).In pairwise comparisons with Braak stages 0 through II, a graded response was observed across Braak stages V and VI, with more severe and widespread loss identified at Braak stage VI. No regions of loss were identified in Braak stage III or IV compared with Braak stages 0 through II. The lack of findings in Braak stages III and IV could be because Braak stage is based on the presence of any NFT pathology regardless of severity. Actual NFT burden may vary by Braak stage. Therefore, tau burden was assessed in subjects with Braak stages 0 through IV. Those with high tau burden showed greater gray matter loss in medial and lateral temporal lobes than those with low tau burden.Patterns of gray matter loss are associated with neurofibrillary tangle (NFT) pathology, specifically with NFT burden at Braak stages III and IV and with Braak stage itself at higher stages. This validates three-dimensional patterns of atrophy on MRI as an approximate in vivo surrogate indicator of the full brain topographic representation of the neurodegenerative aspect of Alzheimer disease pathology.

Typical cognitive aging may be defined as age-associated changes in cognitive performance in individuals who remain free of dementia. Ideally, the full adult age spectrum should be included to assess brain imaging findings associated with typical aging.To compare age, sex, and APOE ε4 effects on memory, brain structure (adjusted hippocampal volume [HVa]), and amyloid positron emission tomography (PET) in cognitively normal individuals aged 30 to 95 years old.Cross-sectional observational study (March 2006 to October 2014) at an academic medical center. We studied 1246 cognitively normal individuals, including 1209 participants aged 50 to 95 years old enrolled in a population-based study of cognitive aging and 37 self-selected volunteers aged 30 to 49 years old.Memory, HVa, and amyloid PET.Overall, memory worsened from age 30 years through the 90s. The HVa worsened gradually from age 30 years to the mid-60s and more steeply beyond that age. The median amyloid PET was low until age 70 years and increased thereafter. Memory was worse in men than in women overall (P < .001) and more specifically beyond age 40 years. The HVa was lower in men than in women overall (P < .001) and more specifically beyond age 60 years. There was no sex difference in amyloid PET at any age. Within each sex, memory performance and HVa were not different by APOE ε4 status at any age. From age 70 years onward, APOE ε4 carriers had significantly greater median amyloid PET than noncarriers. However, the ages at which 10% of the population were amyloid PET positive were 57 years for APOE ε4 carriers and 64 years for noncarriers.Male sex is associated with worse memory and HVa among cognitively normal individuals, while APOE ε4 is not. In contrast, APOE ε4 is associated with greater amyloid PET (from age 70 years onward), while sex is not. Worsening memory and HVa occur at earlier ages than abnormal amyloid PET. Therefore, neuropathological processes other than β-amyloidosis must underlie declines in brain structure and memory function in middle age. Our findings are consistent with a model of late-onset Alzheimer disease in which β-amyloidosis arises in later life on a background of preexisting structural and cognitive decline that is associated with aging and not with β-amyloid deposits.

See Hansson and Mormino (doi:10.1093/brain/awy065) for a scientific commentary on this article. Our objective was to compare different whole-brain and region-specific measurements of within-person change on serial tau PET and evaluate its utility for clinical trials. We studied 126 individuals: 59 cognitively unimpaired with normal amyloid, 37 cognitively unimpaired with abnormal amyloid, and 30 cognitively impaired with an amnestic phenotype and abnormal amyloid. All had baseline amyloid PET and two tau PET, MRI, and clinical assessments. We compared the topography across all cortical regions of interest of tau PET accumulation rates and the rates of four different whole-brain or region-specific meta-regions of interest among the three clinical groups. We computed sample size estimates for change in tau PET, cortical volume, and memory/mental status indices for use as outcome measures in clinical trials. The cognitively unimpaired normal amyloid group had no observable tau accumulation throughout the brain. Tau accumulation rates in cognitively unimpaired abnormal amyloid were low [0.006 standardized uptake value ratio (SUVR), 0.5%, per year] but greater than rates in the cognitively unimpaired normal amyloid group in the basal and mid-temporal, retrosplenial, posterior cingulate, and entorhinal regions of interest. Thus, the earliest elevation in accumulation rates was widespread and not confined to the entorhinal cortex. Tau accumulation rates in the cognitively impaired abnormal amyloid group were 0.053 SUVR (3%) per year and greater than rates in cognitively unimpaired abnormal amyloid in all cortical areas except medial temporal. Rates of accumulation in the four meta-regions of interest differed but only slightly from one another. Among all tau PET meta-regions of interest, sample size estimates were smallest for a temporal lobe composite within cognitively unimpaired abnormal amyloid and for the late Alzheimer’s disease meta-region of interest within cognitively impaired abnormal amyloid. The ordering of the sample size estimates by outcome measure was MRI < tau PET < cognitive measures. At a group-wise level, observable rates of short-term serial tau accumulation were only seen in the presence of abnormal amyloid. As disease progressed to clinically symptomatic stages (cognitively impaired abnormal amyloid), observable rates of tau accumulation were seen uniformly throughout the brain providing evidence that tau does not accumulate in one area at a time or in start-stop, stepwise sequence. The information captured by rate measures in different meta-regions of interest, even those with little topographic overlap, was similar. The implication is that rate measurements from simple meta-regions of interest, without the need for Braak-like staging, may be sufficient to capture progressive within-person accumulation of pathologic tau. Tau PET SUVR measures should be an efficient outcome measure in disease-modifying clinical trials.

To estimate a regional progression pattern of amyloid deposition from cross-sectional amyloid-sensitive PET data and evaluate its potential for in vivo staging of an individual's amyloid pathology.Multiregional analysis of florbetapir (18F-AV45)-PET data was used to determine individual amyloid distribution profiles in a sample of 667 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, including cognitively normal older individuals (CN) as well as patients with mild cognitive impairment and Alzheimer disease (AD) dementia. The frequency of regional amyloid positivity across CN individuals was used to construct a 4-stage model of progressing amyloid pathology, and individual distribution profiles were used to evaluate the consistency of this hierarchical stage model across the full cohort.According to a 4-stage model, amyloid deposition begins in temporobasal and frontomedial areas, and successively affects the remaining associative neocortex, primary sensory-motor areas and the medial temporal lobe, and finally the striatum. Amyloid deposition in these brain regions showed a highly consistent hierarchical nesting across participants, where only 2% exhibited distribution profiles that deviated from the staging scheme. The earliest in vivo amyloid stages were mostly missed by conventional dichotomous classification approaches based on global florbetapir-PET signal, but were associated with significantly reduced CSF Aβ42 levels. Advanced in vivo amyloid stages were most frequent in patients with AD and correlated with cognitive impairment in individuals without dementia.The highly consistent regional hierarchy of PET-evidenced amyloid deposition across participants resembles neuropathologic observations and suggests a predictable regional sequence that may be used to stage an individual's progress of amyloid pathology in vivo.

To compare the patterns of gray matter loss in subjects with amnestic mild cognitive impairment (aMCI) who progress to Alzheimer disease (AD) within a fixed clinical follow-up time vs those who remain stable.Twenty-one subjects with aMCI were identified from the Mayo Clinic Alzheimer's research program who remained clinically stable for their entire observed clinical course (aMCI-S), where the minimum required follow-up time from MRI to last follow-up assessment was 3 years. These subjects were age- and gender-matched to 42 aMCI subjects who progressed to AD within 18 months of the MRI (aMCI-P). Each subject was then age- and gender-matched to a control subject. Voxel-based morphometry (VBM) was used to assess patterns of gray matter atrophy in the aMCI-P and aMCI-S groups compared to the control group, and compared to each other.The aMCI-P group showed bilateral loss affecting the medial and inferior temporal lobe, temporoparietal association neocortex, and frontal lobes, compared to controls. The aMCI-S group showed no regions of gray matter loss when compared to controls. When the aMCI-P and aMCI-S groups were compared directly, the aMCI-P group showed greater loss in the medial and inferior temporal lobes, the temporoparietal neocortex, posterior cingulate, precuneus, anterior cingulate, and frontal lobes than the aMCI-S group.The regions of loss observed in subjects with amnestic mild cognitive impairment (aMCI) who progressed to Alzheimer disease (AD) within 18 months of the MRI are typical of subjects with AD. The lack of gray matter loss in subjects with aMCI who remained clinically stable for their entire observed clinical course is consistent with the notion that patterns of atrophy on MRI at baseline map well onto the subsequent clinical course.

Major imaging biomarkers of Alzheimer's disease include amyloid deposition [imaged with [(11)C]Pittsburgh compound B (PiB) PET], altered glucose metabolism (imaged with [(18)F]fluro-deoxyglucose PET), and structural atrophy (imaged by MRI). Recently we published the initial subset of imaging findings for specific regions in a cohort of individuals with autosomal dominant Alzheimer's disease. We now extend this work to include a larger cohort, whole-brain analyses integrating all three imaging modalities, and longitudinal data to examine regional differences in imaging biomarker dynamics. The anatomical distribution of imaging biomarkers is described in relation to estimated years from symptom onset. Autosomal dominant Alzheimer's disease mutation carrier individuals have elevated PiB levels in nearly every cortical region 15 y before the estimated age of onset. Reduced cortical glucose metabolism and cortical thinning in the medial and lateral parietal lobe appeared 10 and 5 y, respectively, before estimated age of onset. Importantly, however, a divergent pattern was observed subcortically. All subcortical gray-matter regions exhibited elevated PiB uptake, but despite this, only the hippocampus showed reduced glucose metabolism. Similarly, atrophy was not observed in the caudate and pallidum despite marked amyloid accumulation. Finally, before hypometabolism, a hypermetabolic phase was identified for some cortical regions, including the precuneus and posterior cingulate. Additional analyses of individuals in which longitudinal data were available suggested that an accelerated appearance of volumetric declines approximately coincides with the onset of the symptomatic phase of the disease.

Abstract Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late‐onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. Methods We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news‐publications/publications/ ). Results (1) Data‐driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β‐Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a “typical AD” subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. Discussion ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

To investigate age-related default mode network (DMN) connectivity in a large cognitively normal elderly cohort and in patients with Alzheimer disease (AD) compared with age-, gender-, and education-matched controls.We analyzed task-free-fMRI data with both independent component analysis and seed-based analysis to identify anterior and posterior DMNs. We investigated age-related changes in connectivity in a sample of 341 cognitively normal subjects. We then compared 28 patients with AD with 56 cognitively normal noncarriers of the APOE ε4 allele matched for age, education, and gender.The anterior DMN shows age-associated increases and decreases in fontal lobe connectivity, whereas the posterior DMN shows mainly age-associated declines in connectivity throughout. Relative to matched cognitively normal controls, subjects with AD display an accelerated pattern of the age-associated changes described above, except that the declines in frontal lobe connectivity did not reach statistical significance. These changes survive atrophy correction and are correlated with cognitive performance.The results of this study indicate that the DMN abnormalities observed in patients with AD represent an accelerated aging pattern of connectivity compared with matched controls.

Dementia with Lewy bodies (DLB) is the second most common cause of degenerative dementia after Alzheimer's disease. However, unlike the latter, the patterns of cerebral atrophy associated with DLB have not been well established. The aim of this study was to identify a signature pattern of cerebral atrophy in DLB and to compare it with the pattern found in Alzheimer's disease. Seventy-two patients that fulfilled clinical criteria for probable DLB were age- and gender-matched to 72 patients with probable Alzheimer's disease and 72 controls. Voxel-based morphometry (VBM) was used to assess patterns of grey matter (GM) atrophy in the two patient groups, relative to controls, after correction for multiple comparisons (P < 0.05). Study-specific templates and prior probability maps were used to avoid normalization and segmentation bias. Region-of-interest (ROI) analyses were also performed comparing loss of the midbrain, substantia innominata (SI), temporoparietal cortex and hippocampus between the groups. The DLB group showed very little cortical involvement on VBM with regional GM loss observed primarily in the dorsal midbrain, SI and hypothalamus. In comparison, the Alzheimer's disease group showed a widespread pattern of GM loss involving the temporoparietal association cortices and the medial temporal lobes. The SI and dorsal midbrain were involved in Alzheimer's disease; however, they were not identified as a cluster of loss discrete from uninvolved surrounding areas, as observed in the DLB group. On direct comparison between the two groups, the Alzheimer's disease group showed greater loss in the medial temporal lobe and inferior temporal regions than the DLB group. The ROI analysis showed reduced SI and midbrain GM in both patient groups, with a trend for more reduction of SI GM in Alzheimer's disease than DLB, and more reduction of midbrain in DLB than Alzheimer's disease. Significantly greater loss in the hippocampus and temporo-parietal cortex was observed in the Alzheimer's disease patients when the two patient groups were compared. A pattern of relatively focused atrophy of the midbrain, hypothalamus and SI, with a relative sparing of the hippocampus and temporoparietal cortex is, therefore, suggestive of DLB and this may aid in the differentiation of DLB from Alzheimer's disease. These findings support recent pathological studies showing an ascending pattern of Lewy body progression from brainstem to basal areas of the brain. Damage to this network of structures in DLB may affect a number of different neurotransmitter systems which in turn may contribute to a number of the core clinical features of DLB.

As preclinical Alzheimer's disease becomes a target for therapeutic intervention, the overlap between imaging abnormalities associated with typical ageing and those associated with Alzheimer's disease needs to be recognised. We aimed to characterise how typical ageing and preclinical Alzheimer's disease overlap in terms of β-amyloidosis and neurodegeneration.We measured age-specific frequencies of amyloidosis and neurodegeneration in individuals with normal cognitive function aged 50-89 years. Potential participants were randomly selected from the Olmsted County (MN, USA) population-based study of cognitive ageing and invited to participate in cognitive and imaging assessments. To be eligible for inclusion, individuals must have been judged clinically to have no cognitive impairment and have undergone amyloid PET, (18)F-fluorodeoxyglucose ((18)F-FDG) PET, and MRI. Imaging results were obtained from March 28, 2006, to Dec 3, 2013. Amyloid status (positive [A(+)] or negative [A(-)]) was determined by amyloid PET with (11)C Pittsburgh compound B. Neurodegeneration status (positive [N(+)] or negative [N(-)]) was determined by an Alzheimer's disease signature (18)F-FDG PET or hippocampal volume on MRI. We determined age-specific frequencies of the four groups (amyloid negative and neurodegeneration negative [A(-)N(-)], amyloid positive and neurodegeneration negative [A(+)N(-)], amyloid negative and neurodegeneration positive [A(-)N(+)], or amyloid positive and neurodegeneration positive [A(+)N(+)]) cross-sectionally using multinomial regression models. We also investigated associations of group frequencies with APOE ɛ4 status (assessed with DNA extracted from blood) and sex by including these covariates in the multinomial models.The study population consisted of 985 eligible participants. The population frequency of A(-)N(-) was 100% (n=985) at age 50 years and fell to 17% (95% CI 11-24) by age 89 years. The frequency of A(+)N(-) increased to 28% (24-32) at age 74 years, then decreased to 17% (11-25) by age 89 years. The frequency of A(-)N(+) increased from age 60 years, reaching 24% (16-34) by age 89 years. The frequency of A(+)N(+) increased from age 65 years, reaching 42% (31-52) by age 89 years. The results from our multinomial models suggest that A(+)N(-) and A(+)N(+) were more frequent in APOE ɛ4 carriers than in non-carriers and that A(+)N(+) was more, and A(+)N(-) less frequent in men than in women.Accumulation of amyloid and neurodegeneration are nearly inevitable by old age, but many people are able to maintain normal cognitive function despite these imaging abnormalities. Changes in the frequency of amyloidosis and neurodegeneration with age, which seem to be modified by APOE ɛ4 and sex, suggest that pathophysiological sequences might differ between individuals.US National Institute on Aging and Alexander Family Professorship of Alzheimer's Disease Research.

To test patient acceptance and reproducibility of the 3D magnetic resonance elastography (MRE) brain exam using a soft vibration source, and to determine if MRE could noninvasively measure a change in the elastic properties of the brain parenchyma due to Alzheimer's disease (AD).MRE exams were performed using an accelerated spin-echo echo planar imaging (EPI) pulse sequence and stiffness was calculated with a 3D direct inversion algorithm. Reproducibility of the technique was assessed in 10 male volunteers, who each underwent four MRE exams separated into two imaging sessions. The effect of AD on brain stiffness was assessed in 28 volunteers, 7 with probable AD, 14 age- and gender-matched PIB-negative (Pittsburgh Compound B, a PET amyloid imaging ligand) cognitively normal controls (CN-), and 7 age- and gender-matched PIB-positive cognitively normal controls (CN+).The median stiffness of the 10 volunteers was 3.07 kPa with a range of 0.40 kPa. The median and maximum coefficients of variation for these volunteers were 1.71% and 3.07%. The median stiffness of the 14 CN- subjects was 2.37 kPa (0.44 kPa range) compared to 2.32 kPa (0.49 kPa range) within the CN+ group and 2.20 kPa (0.33 kPa range) within the AD group. A significant difference was found between the three groups (P = 0.0055, Kruskal-Wallis one-way analysis of variance). Both the CN+ and CN- groups were significantly different from the AD group.3D MRE of the brain can be performed reproducibly and demonstrates significantly reduced brain tissue stiffness in patients with AD.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently added diffusion tensor imaging (DTI), among several other new imaging modalities, in an effort to identify sensitive biomarkers of Alzheimer's disease (AD). While anatomical MRI is the main structural neuroimaging method used in most AD studies and clinical trials, DTI is sensitive to microscopic white matter (WM) changes not detectable with standard MRI, offering additional markers of neurodegeneration. Prior DTI studies of AD report lower fractional anisotropy (FA), and increased mean, axial, and radial diffusivity (MD, AxD, RD) throughout WM. Here we assessed which DTI measures may best identify differences among AD, mild cognitive impairment (MCI), and cognitively healthy elderly control (NC) groups, in region of interest (ROI) and voxel-based analyses of 155 ADNI participants (mean age: 73.5 ± 7.4; 90 M/65 F; 44 NC, 88 MCI, 23 AD). Both VBA and ROI analyses revealed widespread group differences in FA and all diffusivity measures. DTI maps were strongly correlated with widely-used clinical ratings (MMSE, CDR-sob, and ADAS-cog). When effect sizes were ranked, FA analyses were least sensitive for picking up group differences. Diffusivity measures could detect more subtle MCI differences, where FA could not. ROIs showing strongest group differentiation (lowest p-values) included tracts that pass through the temporal lobe, and posterior brain regions. The left hippocampal component of the cingulum showed consistently high effect sizes for distinguishing groups, across all diffusivity and anisotropy measures, and in correlations with cognitive scores.

Thal amyloid phase, which describes the pattern of progressive amyloid-β plaque deposition in Alzheimer’s disease, was incorporated into the latest National Institute of Ageing – Alzheimer’s Association neuropathologic assessment guidelines. Amyloid biomarkers (positron emission tomography and cerebrospinal fluid) were included in clinical diagnostic guidelines for Alzheimer’s disease dementia published by the National Institute of Ageing – Alzheimer’s Association and the International Work group. Our first goal was to evaluate the correspondence of Thal amyloid phase to Braak tangle stage and ante-mortem clinical characteristics in a large autopsy cohort. Second, we examined the relevance of Thal amyloid phase in a prospectively-followed autopsied cohort who underwent ante-mortem 11C-Pittsburgh compound B imaging; using the large autopsy cohort to broaden our perspective of 11C-Pittsburgh compound B results. The Mayo Clinic Jacksonville Brain Bank case series (n = 3618) was selected regardless of ante-mortem clinical diagnosis and neuropathologic co-morbidities, and all assigned Thal amyloid phase and Braak tangle stage using thioflavin-S fluorescent microscopy. 11C-Pittsburgh compound B studies from Mayo Clinic Rochester were available for 35 participants scanned within 2 years of death. Cortical 11C-Pittsburgh compound B values were calculated as a standard uptake value ratio normalized to cerebellum grey/white matter. In the high likelihood Alzheimer’s disease brain bank cohort (n = 1375), cases with lower Thal amyloid phases were older at death, had a lower Braak tangle stage, and were less frequently APOE-ε4 positive. Regression modelling in these Alzheimer’s disease cases, showed that Braak tangle stage, but not Thal amyloid phase predicted age at onset, disease duration, and final Mini-Mental State Examination score. In contrast, Thal amyloid phase, but not Braak tangle stage or cerebral amyloid angiopathy predicted 11C-Pittsburgh compound B standard uptake value ratio. In the 35 cases with ante-mortem amyloid imaging, a transition between Thal amyloid phases 1 to 2 seemed to correspond to 11C-Pittsburgh compound B standard uptake value ratio of 1.4, which when using our pipeline is the cut-off point for detection of clear amyloid-positivity regardless of clinical diagnosis. Alzheimer’s disease cases who were older and were APOE-ε4 negative tended to have lower amyloid phases. Although Thal amyloid phase predicted clinical characteristics of Alzheimer’s disease patients, the pre-mortem clinical status was driven by Braak tangle stage. Thal amyloid phase correlated best with 11C-Pittsburgh compound B values, but not Braak tangle stage or cerebral amyloid angiopathy. The 11C-Pittsburgh compound B cut-off point value of 1.4 was approximately equivalent to a Thal amyloid phase of 1–2. Murray et al. examine the correspondence between Thal amyloid phase, tau pathology and clinical characteristics in a large Alzheimer’s disease autopsy series. They extrapolate their findings to an autopsy cohort for which Pittsburgh compound-B imaging data are available, and evaluate the neuropathological significance of a quantitative amyloid-β imaging cut-off point.

Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and 18F-fluorodeoxyglucose (18F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and 18F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies.

TDP-43 immunoreactivity occurs in 19–57 % of Alzheimer’s disease (AD) cases. Two patterns of TDP-43 deposition in AD have been described involving hippocampus (limbic) or hippocampus and neocortex (diffuse), although focal amygdala involvement has been observed. In 195 AD cases with TDP-43, we investigated regional TDP-43 immunoreactivity with the aim of developing a TDP-43 in AD staging scheme. TDP-43 immunoreactivity was assessed in amygdala, entorhinal cortex, subiculum, hippocampal dentate gyrus, occipitotemporal, inferior temporal and frontal cortices, and basal ganglia. Clinical, neuroimaging, genetic and pathological characteristics were assessed across stages. Five stages were identified: stage I showed scant-sparse TDP-43 in the amygdala only (17 %); stage II showed moderate-frequent amygdala TDP-43 with spread into entorhinal and subiculum (25 %); stage III showed further spread into dentate gyrus and occipitotemporal cortex (31 %); stage IV showed further spread into inferior temporal cortex (20 %); and stage V showed involvement of frontal cortex and basal ganglia (7 %). Cognition and medial temporal volumes differed across all stages and progression across stages correlated with worsening cognition and medial temporal volume loss. Compared to 147 AD patients without TDP-43, only the Boston Naming Test showed abnormalities in stage I. The findings demonstrate that TDP-43 deposition in AD progresses in a stereotypic manner that can be divided into five distinct topographic stages which are supported by correlations with clinical and neuroimaging features. Given these findings, we recommend sequential regional TDP-43 screening in AD beginning with the amygdala.

Abstract Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI‐3, which began on August 1, 2016, is a 5‐year renewal of the current ADNI‐2 study. Methods ADNI‐3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning will be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition. Results Multimodal analyses will provide insight into AD pathophysiology and disease progression. Discussion ADNI‐3 will aim to inform AD treatment trials and facilitate development of AD disease‐modifying treatments.

Here, we review progress by the Penn Biomarker Core in the Alzheimer's Disease Neuroimaging Initiative (ADNI) toward developing a pathological cerebrospinal fluid (CSF) and plasma biomarker signature for mild Alzheimer's disease (AD) as well as a biomarker profile that predicts conversion of mild cognitive impairment (MCI) and/or normal control subjects to AD. The Penn Biomarker Core also collaborated with other ADNI Cores to integrate data across ADNI to temporally order changes in clinical measures, imaging data, and chemical biomarkers that serve as mileposts and predictors of the conversion of normal control to MCI as well as MCI to AD, and the progression of AD. Initial CSF studies by the ADNI Biomarker Core revealed a pathological CSF biomarker signature of AD defined by the combination of Aβ1‐42 and total tau (T‐tau) that effectively delineates mild AD in the large multisite prospective clinical investigation conducted in ADNI. This signature appears to predict conversion from MCI to AD. Data fusion efforts across ADNI Cores generated a model for the temporal ordering of AD biomarkers which suggests that Aβ amyloid biomarkers become abnormal first, followed by changes in neurodegenerative biomarkers (CSF tau, F‐18 fluorodeoxyglucose‐positron emission tomography, magnetic resonance imaging) with the onset of clinical symptoms. The timing of these changes varies in individual patients due to genetic and environmental factors that increase or decrease an individual's resilience in response to progressive accumulations of AD pathologies. Further studies in ADNI will refine this model and render the biomarkers studied in ADNI more applicable to routine diagnosis and to clinical trials of disease modifying therapies.

Alzheimer's disease (AD) researchers commonly use MRI as a quantitative measure of disease severity. Historically, hippocampal volume has been favored. Recently, "AD signature" measurements of gray matter (GM) volumes or cortical thicknesses have gained attention. Here, we systematically evaluate multiple thickness- and volume-based candidate-methods side-by-side, built using the popular FreeSurfer, SPM, and ANTs packages, according to the following criteria: (a) ability to separate clinically normal individuals from those with AD; (b) (extent of) correlation with head size, a nuisance covariatel (c) reliability on repeated scans; and (d) correlation with Braak neurofibrillary tangle stage in a group with autopsy. We show that volume- and thickness-based measures generally perform similarly for separating clinically normal from AD populations, and in correlation with Braak neurofibrillary tangle stage at autopsy. Volume-based measures are generally more reliable than thickness measures. As expected, volume measures are highly correlated with head size, while thickness measures are generally not. Because approaches to statistically correcting volumes for head size vary and may be inadequate to deal with this underlying confound, and because our goal is to determine a measure which can be used to examine age and sex effects in a cohort across a large age range, we thus recommend thickness-based measures. Ultimately, based on these criteria and additional practical considerations of run-time and failure rates, we recommend an AD signature measure formed from a composite of thickness measurements in the entorhinal, fusiform, parahippocampal, mid-temporal, inferior-temporal, and angular gyrus ROIs using ANTs with input segmentations from SPM12.

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.

Fully automated classification algorithms have been successfully applied to diagnose a wide range of neurological and psychiatric diseases. They are sufficiently robust to handle data from different scanners for many applications and in specific cases outperform radiologists. This article provides an overview of current applications taking structural imaging in Alzheimer's disease and schizophrenia as well as functional imaging to diagnose depression as examples. In this context, we also report studies aiming to predict the future course of the disease and the response to treatment for the individual. This has obvious clinical relevance but is also important for the design of treatment studies that may aim to include a cohort with a predicted fast disease progression to be more sensitive to detect treatment effects. In the second part, we present our own opinions on i) the role these classification methods can play in the clinical setting; ii) where their limitations are at the moment and iii) how those can be overcome. Specifically, we discuss strategies to deal with disease heterogeneity, diagnostic uncertainties, a probabilistic framework for classification and multi-class classification approaches.

Background In preclinical studies, davunetide promoted microtubule stability and reduced tau phosphorylation. Because progressive supranuclear palsy (PSP) is linked to tau pathology, davunetide could be a treatment for PSP. We assessed the safety and efficacy of davunetide in patients with PSP. Methods In a double-blind, parallel group, phase 2/3 trial, participants were randomly assigned with permuted blocks in a 1:1 ratio to davunetide (30 mg twice daily, intranasally) or placebo for 52 weeks at 48 centres in Australia, Canada, France, Germany, the UK, and the USA. Participants met the modified Neuroprotection and Natural History in Parkinson Plus Syndrome study criteria for PSP. Primary endpoints were the change from baseline in PSP Rating Scale (PSPRS) and Schwab and England Activities of Daily Living (SEADL) scale at up to 52 weeks. All participants and study personnel were masked to treatment assignment. Analysis was by intention to treat. The trial is registered with Clinicaltrials.gov, number NCT01110720. Findings 313 participants were randomly assigned to davunetide (n=157) or to placebo (n=156), and 241 (77%) completed the study (118 and 156 in the davunetide and placebo groups, respectively). There were no differences in the davunetide and placebo groups in the baseline PSPRS and SEADL. The davunetide and placebo groups did not differ in the change from baseline in PSPRS (median 11·8 [95% CI 10·5 to 13·0] vs 11·8 [10·5 to 13·0], respectively, p=0·41) or SEADL (−0·20 [−0·20 to −0·17] vs −0·20 [−0·22 to −0·17], respectively, p=0·92). 54 serious adverse events were reported in each of the treatment groups, including 11 deaths in the davunetide group and ten in the placebo group. The frequency of nasal adverse events was greater in the davunetide group than in the placebo group (epistaxis 18 [12%] of 156 vs 13 [8%] of 156, rhinorrhoea 15 [10%] vs eight [5%], and nasal discomfort 15 [10%] vs one [<1%]). Interpretation Davunetide is not an effective treatment for PSP. Clinical trials of disease-modifying treatment are feasible in patients with PSP and should be pursued with other promising tau-directed treatments. Funding Allon Therapeutics.

Background A new classification for biomarkers in Alzheimer's disease and cognitive ageing research is based on grouping the markers into three categories: amyloid deposition (A), tauopathy (T), and neurodegeneration or neuronal injury (N). Dichotomising these biomarkers as normal or abnormal results in eight possible profiles. We determined the clinical characteristics and prevalence of each ATN profile in cognitively unimpaired individuals aged 50 years and older. Methods All participants were in the Mayo Clinic Study of Aging, a population-based study that uses a medical records linkage system to enumerate all individuals aged 50–89 years in Olmsted County, MN, USA. Potential participants are randomly selected, stratified by age and sex, and invited to participate in cognitive assessments; individuals without medical contraindications are invited to participate in brain imaging studies. Participants who were judged clinically as having no cognitive impairment and underwent multimodality imaging between Oct 11, 2006, and Oct 5, 2016, were included in the current study. Participants were classified as having normal (A−) or abnormal (A+) amyloid using amyloid PET, normal (T−) or abnormal (T+) tau using tau PET, and normal (N−) or abnormal (N+) neurodegeneration or neuronal injury using cortical thickness assessed by MRI. We used the cutoff points of standard uptake value ratio (SUVR) 1·42 (centiloid 19) for amyloid PET, 1·23 SUVR for tau PET, and 2·67 mm for MRI cortical thickness. Age-specific and sex-specific prevalences of the eight groups were determined using multinomial models combining data from 435 individuals with amyloid PET, tau PET, and MRI assessments, and 1113 individuals who underwent amyloid PET and MRI, but not tau PET imaging. Findings The numbers of participants in each profile group were 165 A−T−N−, 35 A−T+N−, 63 A−T−N+, 19 A−T+N+, 44 A+T−N−, 25 A+T+N−, 35 A+T−N+, and 49 A+T+N+. Age differed by ATN group (p<0·0001), ranging from a median 58 years (IQR 55–64) in A–T–N– and 57 years (54–64) in A–T+N– to a median 80 years (75–84) in A+T–N+ and 79 years (73–87) in A+T+N+. The number of APOE ε4 carriers differed by ATN group (p=0·04), with carriers roughly twice as frequent in each A+ group versus the corresponding A– group. White matter hyperintensity volume (p<0·0001) and cognitive performance (p<0·0001) also differed by ATN group. Tau PET and neurodegeneration biomarkers were discordant in most individuals who would be categorised as stage 2 or 3 preclinical Alzheimer's disease (A+T+N−, A+T−N+, and A+T+N+; 86% at age 65 years and 51% at age 80 years) or with suspected non-Alzheimer's pathophysiology (A−T+N−, A−T−N+, and A−T+N+; 92% at age 65 years and 78% at age 80 years). From age 50 years, A−T−N− prevalence declined and A+T+N+ and A−T+N+ prevalence increased. In both men and women, A−T−N− was the most prevalent until age late 70s. After about age 80 years, A+T+N+ was most prevalent. By age 85 years, more than 90% of men and women had one or more biomarker abnormalities. Interpretation Biomarkers of fibrillar tau deposition can be included with those of β-amyloidosis and neurodegeneration or neuronal injury to more fully characterise the heterogeneous pathological profiles in the population. Both amyloid- dependent and amyloid-independent pathological profiles can be identified in the cognitively unimpaired population. The prevalence of each ATN group changed substantially with age, with progression towards more biomarker abnormalities among individuals who remained cognitively unimpaired. Funding National Institute on Aging (part of the US National Institutes of Health), the Alexander Family Professorship of Alzheimer's Disease Research, the Mayo Clinic, and the GHR Foundation.

Brain iron elevation is implicated in Alzheimer's disease (AD) pathogenesis, but the impact of iron on disease outcomes has not been previously explored in a longitudinal study. Ferritin is the major iron storage protein of the body; by using cerebrospinal fluid (CSF) levels of ferritin as an index, we explored whether brain iron status impacts longitudinal outcomes in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We show that baseline CSF ferritin levels were negatively associated with cognitive performance over 7 years in 91 cognitively normal, 144 mild cognitive impairment (MCI) and 67 AD subjects, and predicted MCI conversion to AD. Ferritin was strongly associated with CSF apolipoprotein E levels and was elevated by the Alzheimer's risk allele, APOE-ɛ4. These findings reveal that elevated brain iron adversely impacts on AD progression, and introduce brain iron elevation as a possible mechanism for APOE-ɛ4 being the major genetic risk factor for AD.

Abstract There is considerable debate whether Alzheimer’s disease (AD) originates in basal forebrain or entorhinal cortex. Here we examined whether longitudinal decreases in basal forebrain and entorhinal cortex grey matter volume were interdependent and sequential. In a large cohort of age-matched older adults ranging from cognitively normal to AD, we demonstrate that basal forebrain volume predicts longitudinal entorhinal degeneration. Models of parallel degeneration or entorhinal origin received negligible support. We then integrated volumetric measures with an amyloid biomarker sensitive to pre-symptomatic AD pathology. Comparison between cognitively matched normal adult subgroups, delineated according to the amyloid biomarker, revealed abnormal degeneration in basal forebrain, but not entorhinal cortex. Abnormal degeneration in both basal forebrain and entorhinal cortex was only observed among prodromal (mildly amnestic) individuals. We provide evidence that basal forebrain pathology precedes and predicts both entorhinal pathology and memory impairment, challenging the widely held belief that AD has a cortical origin.

Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.

Suspected non-Alzheimer disease pathophysiology (SNAP) is a biomarker-based concept that applies to individuals with normal levels of amyloid-β biomarkers in the brain, but in whom biomarkers of neurodegeneration are abnormal. Clinically normal and mildly impaired individuals with SNAP are at increased risk of poor clinical and cognitive outcomes. In this Perspectives article, Clifford Jack and colleagues describe the available data on SNAP and address topical controversies in the field. Suspected non-Alzheimer disease pathophysiology (SNAP) is a biomarker-based concept that applies to individuals with normal levels of amyloid-β biomarkers in the brain, but in whom biomarkers of neurodegeneration are abnormal. The term SNAP has been applied to clinically normal individuals (who do not meet criteria for either mild cognitive impairment or dementia) and to individuals with mild cognitive impairment, but is applicable to any amyloid-negative, neurodegeneration-positive individual regardless of clinical status, except when the pathology underlying neurodegeneration can be reliably inferred from the clinical presentation. SNAP is present in ∼23% of clinically normal individuals aged >65 years and in ∼25% of mildly cognitively impaired individuals. APOE*ε4 is underrepresented in individuals with SNAP compared with amyloid-positive individuals. Clinically normal and mildly impaired individuals with SNAP have worse clinical and/or cognitive outcomes than individuals with normal levels of neurodegeneration and amyloid-β biomarkers. In this Perspectives article, we describe the available data on SNAP and address topical controversies in the field.

To assess the correlations of both MRI and CSF biomarkers with clinical diagnosis and with cognitive performance in cognitively normal (CN) subjects and patients with amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD).This is a cross-sectional study with data from the Alzheimer's Disease Neuroimaging Initiative, which consists of CN subjects, subjects with aMCI, and subjects with AD with both CSF and MRI. Baseline CSF (t-tau, Abeta(1-42), and p-tau(181P)) and MRI scans were obtained in 399 subjects (109 CN, 192 aMCI, 98 AD). Structural Abnormality Index (STAND) scores, which reflect the degree of AD-like anatomic features on MRI, were computed for each subject.We found no significant correlation between CSF biomarkers and cognitive scores in any of the 3 clinical groups individually. Conversely, STAND scores correlated with both Clinical Dementia Rating-sum of boxes and Mini-Mental State Examination in aMCI and AD (p < or = 0.01). While STAND and all CSF biomarkers were predictors of clinical group membership (CN, aMCI, or AD) univariately (p < 0.001), STAND was more predictive than CSF both univariately and in combined models.CSF and MRI biomarkers independently contribute to intergroup diagnostic discrimination and the combination of CSF and MRI provides better prediction than either source of data alone. However, MRI provides greater power to effect cross-sectional groupwise discrimination and better correlation with general cognition and functional status cross-sectionally. We therefore conclude that although MRI and CSF provide complementary information, MRI reflects clinically defined disease stage better than the CSF biomarkers tested.