Trends in Neurosciences
ReviewNeuroimaging markers for the prediction and early diagnosis of Alzheimer's disease dementia
Introduction
An estimated 35.6 million people are affected worldwide today by a mild to severe clinical dementia syndrome, associated with costs of approximately US$ 604 billion (World Alzheimer Report 2010, http://www.alz.org). The number of affected people is predicted to dramatically increase to 115 million by 2050 (World Alzheimer Report 2010, http://www.alz.org). Dementia of the Alzheimer's disease (AD) (see Glossary) type is the most frequent form of age-related dementia 1, 2.
Clinically, initial progressive memory deficits that are eventually accompanied by more global cognitive and attention deficits are typical in AD dementia. Major pathologies in the brain associated with AD dementia have been identified, but the causes of such pathological changes are largely unknown. Causative factors include autosomal dominant inheritable mutations in the genes of presenilin 1 (PS1) and presenilin 2 (PS2) and the amyloid precursor protein (APP). Such an inheritable form of AD (familial AD) is associated with early onset of the disease, typically before the age of 65 years, but accounts for approximately only 1% of all AD cases [3]. For AD without the presence of such known genetic causes (sporadic AD), a late onset of dementia (age>65 years) is typical. The most important risk factor for sporadic late onset AD is age, with the annual incidence of clinically-diagnosed AD dementia being <1% of adults between 65 and 69 years old, but >8% in adults 85 years and older [4]. Presence of the apolipoprotein E (ApoE) É4 allele is the strongest genetic risk factor of sporadic AD [3]. Presence of at least one ApoE É4 allele advances the age of clinical onset of AD dementia significantly (from age 84 to 68 years) and increases the risk of AD dementia by a factor of four (for regularly updated meta-analyses, see http://www.alzgene.org/).
Core neuropathologies in AD include abnormalities such as the accumulation of the protein amyloid-beta (AĪ²) and the development of neurofibrillary tangles, which have been associated with neuronal degeneration and clinical symptoms of dementia [5]. Such brain changes occur decades before the onset of dementia. The detection of AĪ² in the brain of living subjects has been made possible by recent developments in positron emission tomography (PET) using radiotracers such as 11C-labeled Pittsburgh Compound-B (PiB), which label AĪ² deposits [6]. Such studies have confirmed that substantial levels of AĪ² deposits are present in subjects before the onset of dementia or even before any overt signs of cognitive impairment (as discussed later in the review). Other early brain changes include a decline in synaptic function, as assessed by [18F]fluorodeoxyglucose positron emission tomography (FDG-PET), gross neuronal loss causing atrophy, as measured by volumetric magnetic resonance imaging (MRI), and white matter changes within axonal projections, as detected by diffusion tensor imaging (DTI) (Box 1). These different types of changes might evolve sequentially and relate to the development of cognitive impairment within the clinical course of AD [7].
Mild cognitive impairment (MCI) is a well-defined clinical syndrome, which includes deficits in memory or other cognitive abilities [8]. Subjects with MCI have a higher risk to progress to AD dementia [9], but a substantial proportion of MCI subjects remain stable for years or revert to normal, indicating that clinical MCI symptoms can also stem from non-AD related etiologies. This notion is substantiated by the finding that only a subset of patients with MCI display measurable amounts of AĪ² on PiB-PET scans (for a review, see [10]). To increase the detection of MCI due to underlying AD pathology, the combination of cognitive deficits (as present at the MCI stage) with abnormal values for biomarkers indicative of AD pathology (e.g. AĪ² levels as measured by PiB-PET) has been proposed as research diagnostic criteria of predementia AD, called āMCI due to ADā or āprodromal ADā 11, 12, 13. A revision of the clinical diagnostic criteria of AD by the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) and the Alzheimer's Disease and Related Disorders Association (ADRDA) [14] has recently been proposed 11, 13, 15. For clinical use, the National Institute of Aging (NIA) and Alzheimer's Association (AA) work group has recommended purely clinical and neuropsychological criteria for the diagnosis of AD dementia and MCI 13, 15. For the use as research diagnostic criteria of AD and MCI, however, the dual clinico-pathological definition based on clinical testing and biomarker measurements has been adopted 13, 15, and awaits further validation before use in clinical routine diagnostics. It should be mentioned that MCI due to AD is a diagnostic label in view of clinical and biomarker evidence, but this diagnosis does not mean that AD pathology has necessarily caused the clinical symptoms or that subjects with MCI due to AD necessarily progress to AD dementia. Rather, it is a research concept that has not yet been fully validated.
The question of the clinical fate of subjects with AD-like brain changes becomes even more urgent at an earlier time point, i.e. the preclinical phase of AD [16], when such brain changes are present without any overt cognitive deficits. The extent to which subjects with preclinical AD progress to dementia is currently not known. Of note, it has not been established that all subjects with AD-like brain changes inevitably progress to AD dementia, and many subjects with preclinical AD die of natural age-related causes before any signs of dementia are ever observed.
In the current article, we review recent imaging studies that have examined brain changes in both the preclinical and MCI phase, and evaluate the utility of neuroimaging markers for the prediction of clinical progression in these two distinct phases. The association between different imaging modalities is shown for each of the stages, and stage-specific changes in neuroimaging markers are discussed with respect to the predictive value for cognitive decline and the progression from MCI to AD dementia.
Section snippets
Multimodal neuroimaging changes in AD dementia
Before discussing neuroimaging changes of relevance for the preclinical and MCI due to AD stages, it is helpful to begin by briefly overviewing the typical neuroimaging findings that have been observed over the past several years in patients with clinically manifest AD dementia. Multiple studies have determined that the pattern of AĪ² deposits detected in the brains of living subjects diagnosed with AD dementia using [11C]PiB-PET closely matches the pattern predicted by the histochemical
Multimodal neuroimaging in preclinical AD
In this section, we will provide an overview of neuroimaging studies that have assessed changes in subjects with preclinical AD, i.e. in elderly subjects who show normal cognitive abilities but have already AD-like brain abnormalities such as discussed above. Findings from amyloid PET studies will be discussed first and compared to findings on amyloid PET in AD dementia. Functional and structural brain changes (as assessed by FDG-PET and MRI methods) will be discussed subsequently, especially
Multimodal neuroimaging changes in MCI
In the following section, we review neuroimaging findings in subjects with clinically manifest MCI without full-blown dementia. The same imaging modalities as discussed previously are reviewed to allow for a direct comparison with findings in the preclinical AD and AD dementia stages discussed above.
Combining neuroimaging markers for the prediction of clinical progression from MCI to AD dementia
There is now accumulating evidence that a combination of neuroimaging markers show additive effects of different modalities for the prediction of progression to AD dementia. Cross-sectional studies suggest that PiB-PET and hippocampus volume provide complementary information for the diagnostic classification of AD dementia [35]. Within MCI subjects, the combination of structural MRI to assess hippocampus volume and DTI in the posterior parietal lobe contributes to the prediction of the severity
Concluding remarks
Neuroimaging methods are capable of detecting substantial brain changes, not only in subjects with AD dementia, but also in subjects in the mildly symptomatic MCI due to AD stage and even in cognitively normal subjects who might be in the preclinical stage of AD (Box 2). There are imaging modality-specific changes within these clinical/preclinical stages. In the preclinical stage, AĪ² deposits are already present in a substantial number of subjects. Such changes are associated with increased
Disclaimer statement
GE Healthcare holds a license agreement with the University of Pittsburgh based on the PiB-PET imaging technology described in this manuscript. W.E.K. is a co-inventor of PiB and, as such, has a financial interest in this license agreement. GE Healthcare did not provide grant support for this study and did not have a role in the design or interpretation of results or preparation of this manuscript. R.A.S. has served as a consultant for Elan, Janssen, Pfizer, Link and Bristol-Myers Squibb (BMS),
Acknowledgments
This work was supported by National Institutes of Health (NIH) grants R01AG10897, P41RR023953 and U01AG024904 (to M.W.), which were administered by the Northern California Institute for Research and Education, and with resources of the Veterans Affairs (VA) Medical Center, San Francisco, California. Additional support came from NIH grants P50 AG005133, R37 AG025516, P01 AG025204 (to B.K.), NIA: P01 AG036694, R01AG027435 (to R.S.), the Science Foundation Ireland (SFI) investigator neuroimaging
References (124)
Operationalizing diagnostic criteria for Alzheimer's disease and other age-related cognitive impairment: Part 2
Alzheimers Dement.
(2011)Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Lancet Neurol.
(2010)Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria
Lancet Neurol.
(2007)Revising the definition of Alzheimer's disease: a new lexicon
Lancet Neurol.
(2010)The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging and Alzheimer's Association workgroup
Alzheimers Dement.
(2011)The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging and the Alzheimer's Association workgroup
Alzheimers Dement.
(2011)Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging and the Alzheimer's Association workgroup
Alzheimers Dement.
(2011)Microglia, amyloid, and cognition in Alzheimer's disease: an [11C](R)PK11195-PET and [11C]PIB-PET study
Neurobiol. Disease
(2008)The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core
Alzheimers Dement.
(2010)Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging
Neurobiol. Aging
(2010)
Neuropathology of nondemented aging: presumptive evidence for preclinical Alzheimer disease
Neurobiol. Aging
Progression of cerebral amyloid load is associated with the apolipoprotein E epsilon4 genotype in Alzheimer's disease
Biol. Psychiatry
Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET
Neuroimage
Verbal episodic memory impairment in Alzheimer's disease: a combined structural and functional MRI study
Neuroimage
Neural correlates of Alzheimer's disease and mild cognitive impairment: a systematic and quantitative meta-analysis involving 1351 patients
Neuroimage
Amyloid deposition is associated with impaired default network function in older persons without dementia
Neuron
Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly
Biol. Psychiatry
beta-Amyloid affects frontal and posterior brain networks in normal aging
Neuroimage
Dendritic function of tau mediates amyloid-beta toxicity in Alzheimer's disease mouse models
Cell
Effects of ApoE-epsilon4 allele load and age on the rates of grey matter and hippocampal volumes loss in a longitudinal cohort of 1186 healthy elderly persons
Neuroimage
PET imaging of amyloid deposition in patients with mild cognitive impairment
Neurobiol. Aging
Aberrant excitatory neuronal activity and compensatory remodeling of inhibitory hippocampal circuits in mouse models of Alzheimer's disease
Neuron
Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline
Neuroimage
Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI
Neuroimage
Diffusion tensor imaging of the posterior cingulate is a useful biomarker of mild cognitive impairment
Am. J. Geriatr. Psychiatry
Incidence and risk of dementia. The Rotterdam Study
Am. J. Epidemiol.
Molecular genetics of Alzheimer's disease
Curr. Psych. Rep.
Age-specific incidence of Alzheimer's disease in a community population
J. Am. Med. Assoc.
Alzheimer's disease
N. Engl. J. Med.
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B
Ann. Neurol.
Mild cognitive impairment: ten years later
Arch. Neurol.
Outcome in subgroups of mild cognitive impairment (MCI) is highly predictable using a simple algorithm
J. Neurol.
PET imaging of brain amyloid in dementia: a review
Int. J. Geriatr. Psychiatry
Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease
Neurology
Use of florbetapir-PET for imaging beta-amyloid pathology
J. Am. Med. Assoc.
Phases of A beta-deposition in the human brain and its relevance for the development of AD
Neurology
Frequent amyloid deposition without significant cognitive impairment among the elderly
Arch. Neurol.
Amyloid imaging in mild cognitive impairment subtypes
Ann. Neurol.
Effect of APOE genotype on amyloid plaque load and gray matter volume in Alzheimer disease
Neurology
Disruption of functional connectivity in clinically normal older adults harboring amyloid burden
J. Neurosci.
High PIB retention in Alzheimer's disease is an early event with complex relationship with CSF biomarkers and functional parameters
Curr. Alzheimer Res.
Increased metabolic vulnerability in early-onset Alzheimer's disease is not related to amyloid burden
Brain
Alzheimer disease identification using amyloid imaging and reserve variables: proof of concept
Neurology
Follow-up of [11C]PIB uptake and brain volume in patients with Alzheimer disease and controls
Neurology
Two-year follow-up of amyloid deposition in patients with Alzheimer's disease
Brain
Dynamic changes in PET amyloid and FDG imaging at different stages of Alzheimer's disease
Neurobiol. Aging
Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease
Brain
11C PiB and structural MRI provide complementary information in imaging of Alzheimer's disease and amnestic mild cognitive impairment
Brain
Brain 18F-FDG PET in the diagnosis of neurodegenerative dementias: comparison with perfusion SPECT and with clinical evaluations lacking nuclear imaging
J. Nucl. Med.
Amyloid, hypometabolism, and cognition in Alzheimer disease. An [11C]PIB and [18F]FDG PET study
Neurology
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