Plaque and tangle imaging and cognition in normal aging and Alzheimer's disease

TXNIP contributes to induction of pro-inflammatory phenotype and caspase-3 activation in astrocytes during Alzheimer's diseases

Neuroinflammation and oxidative stress have been implicated in the pathogenesis of Alzheimer's disease (AD). Neuroinflammation and oxidative stress are associated with neuronal death in AD. Astrocytes are linked to neuroinflammation during AD. Astrocytes are important contributors to AD progression. Although the role of thioredoxin-interacting protein (TXNIP) has been identified in inflammation and oxidative stress, the mechanism by which TXNIP regulates inflammation and oxidative stress in astrocytes during AD remains unclear. In the present study, we found that TXNIP gene levels were elevated in cerebral cortex of patients with AD. The protein levels of TXNIP were elevated in GFAP-positive astrocytes of cerebral cortex from patients with AD and APP/PS1 double-transgenic mouse model of AD. Our results showed that TXNIP increased expression of genes related to pro-inflammatory reactive astrocytes and pro-inflammatory cytokines and chemokines in human astrocytes. Moreover, TXNIP increased production of pro-inflammatory cytokines and chemokines in human astrocytes. TXNIP induced activation of NK-kB signaling and over-production of mitochondrial reactive oxygen species (mtROS) in human astrocytes. TXNIP also induced mitochondrial oxidative stress by reduction of mitochondrial respiration and ATP production in human astrocytes. Furthermore, elevated TXNIP levels are correlated with caspase-3 activation of GFAP-positive astrocytes in patients with AD and mouse AD. TXNIP induced mitochondria-dependent apoptosis via caspase-9 and caspase-3 activation in human astrocytes. These results suggest that TXNIP contributes to induction of pro-inflammatory phenotype and caspase-3 activation in astrocytes during AD.

Resting-State Network Alterations Differ between Alzheimer's Disease Atrophy Subtypes

Several Alzheimer's disease (AD) atrophy subtypes were identified, but their brain network properties are unclear. We analyzed data from two independent datasets, including 166 participants (103 AD/63 controls) from the DZNE-longitudinal cognitive impairment and dementia study and 151 participants (121 AD/30 controls) from the AD neuroimaging initiative cohorts, aiming to identify differences between AD atrophy subtypes in resting-state functional magnetic resonance imaging intra-network connectivity (INC) and global and nodal network properties. Using a data-driven clustering approach, we identified four AD atrophy subtypes with differences in functional connectivity, accompanied by clinical and biomarker alterations, including a medio-temporal-predominant (S-MT), a limbic-predominant (S-L), a diffuse (S-D), and a mild-atrophy (S-MA) subtype. S-MT and S-D showed INC reduction in the default mode, dorsal attention, visual and limbic network, and a pronounced reduction of "global efficiency" and decrease of the "clustering coefficient" in parietal and temporal lobes. Despite severe atrophy in limbic areas, the S-L exhibited only marginal global network but substantial nodal network failure. S-MA, in contrast, showed limited impairment in clinical and cognitive scores but pronounced global network failure. Our results contribute toward a better understanding of heterogeneity in AD with the detection of distinct differences in functional connectivity networks accompanied by CSF biomarker and cognitive differences in AD subtypes.

Neuroimaging Biomarkers of Chronic Traumatic Encephalopathy: Targets for the Academic Memory Disorders Clinic

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts, such as those from contact sports. The pathognomonic lesion for CTE is the perivascular accumulation of hyper-phosphorylated tau in neurons and other cell process at the depths of sulci. CTE cannot be diagnosed during life at this time, limiting research on risk factors, mechanisms, epidemiology, and treatment. There is an urgent need for in vivo biomarkers that can accurately detect CTE and differentiate it from other neurological disorders. Neuroimaging is an integral component of the clinical evaluation of neurodegenerative diseases and will likely aid in diagnosing CTE during life. In this qualitative review, we present the current evidence on neuroimaging biomarkers for CTE with a focus on molecular, structural, and functional modalities routinely used as part of a dementia evaluation. Supporting imaging-pathological correlation studies are also presented. We targeted neuroimaging studies of living participants at high risk for CTE (e.g., aging former elite American football players, fighters). We conclude that an optimal tau PET radiotracer with high affinity for the 3R/4R neurofibrillary tangles in CTE has not yet been identified. Amyloid PET scans have tended to be negative. Converging structural and functional imaging evidence together with neuropathological evidence show frontotemporal and medial temporal lobe neurodegeneration, and increased likelihood for a cavum septum pellucidum. The literature offers promising neuroimaging biomarker targets of CTE, but it is limited by cross-sectional studies of small samples where the presence of underlying CTE is unknown. Imaging-pathological correlation studies will be important for the development and validation of neuroimaging biomarkers of CTE.

Neuroimaging Advances in Diagnosis and Differentiation of HIV, Comorbidities, and Aging in the cART Era

In the "cART era" of more widely available and accessible treatment, aging and HIV-related comorbidities, including symptoms of brain dysfunction, remain common among HIV-infected individuals on suppressive treatment. A better understanding of the neurobiological consequences of HIV infection is essential for developing thorough treatment guidelines and for optimizing long-term neuropsychological outcomes and overall brain health. In this chapter, we first summarize magnetic resonance imaging (MRI) methods used in over two decades of neuroHIV research. These methods evaluate brain volumetric differences and circuitry disruptions in adults living with HIV, and help map clinical correlations with brain function and tissue microstructure. We then introduce and discuss aging and associated neurological complications in people living with HIV, and processes by which infection may contribute to the risk for late-onset dementias. We describe how new technologies and large-scale international collaborations are helping to disentangle the effect of genetic and environmental risk factors on brain aging and neurodegenerative diseases. We provide insights into how these advances, which are now at the forefront of Alzheimer's disease research, may advance the field of neuroHIV. We conclude with a summary of how we see the field of neuroHIV research advancing in the decades to come and highlight potential clinical implications.

Role of Insulin in Neurotrauma and Neurodegeneration: A Review

Insulin is a hormone typically associated with pancreatic release and blood sugar regulation. The brain was long thought to be “insulin-independent,” but research has shown that insulin receptors (IR) are expressed on neurons, microglia and astrocytes, among other cells. The effects of insulin on cells within the central nervous system are varied, and can include both metabolic and non-metabolic functions. Emerging data suggests that insulin can improve neuronal survival or recovery after trauma or during neurodegenerative diseases. Further, data suggests a strong anti-inflammatory component of insulin, which may also play a role in both neurotrauma and neurodegeneration. As a result, administration of exogenous insulin, either via systemic or intranasal routes, is an increasing area of focus in research in neurotrauma and neurodegenerative disorders. This review will explore the literature to date on the role of insulin in neurotrauma and neurodegeneration, with a focus on traumatic brain injury (TBI), spinal cord injury (SCI), Alzheimer’s disease (AD) and Parkinson’s disease (PD).

White matter hyperintensities and their relationship to cognition: Effects of segmentation algorithm

White matter hyperintensities (WMHs) are brain white matter lesions that are hyperintense on fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) scans. Larger WMH volumes have been associated with Alzheimer's disease (AD) and with cognitive decline. However, the relationship between WMH volumes and cross-sectional cognitive measures has been inconsistent. We hypothesize that this inconsistency may arise from 1) the presence of AD-specific neuropathology that may obscure any WMH effects on cognition, and 2) varying criteria for creating a WMH segmentation. Manual and automated programs are typically used to determine segmentation boundaries, but criteria for those boundaries can differ. It remains unclear whether WMH volumes are associated with cognitive deficits, and which segmentation criteria influence the relationships between WMH volumes and clinical outcomes. In a sample of 260 non-demented participants (ages 55-90, 141 males, 119 females) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we compared the performance of five WMH segmentation methods, by relating the WMH volumes derived using each method to both clinical diagnosis and composite measures of executive function and memory. To separate WMH effects on cognition from effects related to AD-specific processes, we performed analyses separately in people with and without abnormal cerebrospinal fluid amyloid levels. WMH volume estimates that excluded more diffuse, lower-intensity lesions were more strongly correlated with clinical diagnosis and cognitive performance, and only in those without abnormal amyloid levels. These findings may inform best practices for WMH segmentation, and suggest that AD neuropathology may mask WMH effects on clinical diagnosis and cognition.

Tau PET imaging in neurodegenerative tauopathies-still a challenge

The accumulation of pathological misfolded tau is a feature common to a collective of neurodegenerative disorders known as tauopathies, of which Alzheimer's disease (AD) is the most common. Related tauopathies include progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), Down's syndrome (DS), Parkinson's disease (PD), and dementia with Lewy bodies (DLB). Investigation of the role of tau pathology in the onset and progression of these disorders is now possible due the recent advent of tau-specific ligands for use with positron emission tomography (PET), including first- (e.g., [¹⁸F]THK5317, [¹⁸F]THK5351, [¹⁸F]AV1451, and [¹¹C]PBB3) and second-generation compounds [namely [¹⁸F]MK-6240, [¹⁸F]RO-948 (previously referred to as [¹⁸F]RO69558948), [¹⁸F]PI-2620, [¹⁸F]GTP1, [¹⁸F]PM-PBB3, and [¹⁸F]JNJ64349311 ([¹⁸F]JNJ311) and its derivative [¹⁸F]JNJ-067)]. In this review we describe and discuss findings from in vitro and in vivo studies using both initial and new tau ligands, including their relation to biomarkers for amyloid-β and neurodegeneration, and cognitive findings. Lastly, methodological considerations for the quantification of in vivo ligand binding are addressed, along with potential future applications of tau PET, including therapeutic trials.

The Full Spectrum of Alzheimer's Disease Is Rooted in Metabolic Derangements That Drive Type 3 Diabetes

The standard practice in neuropathology is to diagnose Alzheimer's disease (AD) based on the distribution and abundance of neurofibrillary tangles and Aβ deposits. However, other significant abnormalities including neuroinflammation, gliosis, white matter degeneration, non-Aβ microvascular disease, and insulin-related metabolic dysfunction require further study to understand how they could be targeted to more effectively remediate AD. This review addresses non-Aβ and non-pTau AD-associated pathologies, highlighting their major features, roles in neurodegeneration, and etiopathic links to deficits in brain insulin and insulin-like growth factor signaling and cognitive impairment. The discussion delineates why AD with its most characteristic clinical and pathological phenotypic profiles should be regarded as a brain form of diabetes, i.e., type 3 diabetes, and entertains the hypothesis that type 3 diabetes is just one of the categories of insulin resistance diseases that can occur independently or overlap with one or more of the others, including type 2 diabetes, metabolic syndrome, and nonalcoholic fatty liver disease.

Vestibular Function and Beta-Amyloid Deposition in the Baltimore Longitudinal Study of Aging

Beta-amyloid (Aβ) plaque deposition is a key feature of Alzheimer’s disease (AD), and occurs years before the onset of symptoms. Aβ plaque deposition has been shown to be present in ~30% of cognitively normal older adults using amyloid C-11 labeled Pittsburgh Compound B (¹¹C-PiB) Positron Emission Tomography (PET) imaging. Prior studies have reported a link between reduced vestibular function and poorer cognition in healthy older adults. It is unknown whether vestibular impairment occurs in association with AD pathology among individuals in the preclinical phase of AD, which could contribute to the observed association between vestibular and cognitive function in healthy older adults. Using the Baltimore Longitudinal Study of Aging (BLSA), we analyzed the association between a comprehensive set of vestibular function measures and PiB status in 98 healthy participants with a mean age of 77.3 (±8.26). We did not observe a significant relationship between any vestibular function measure and PiB status in cognitively-intact older adults in the BLSA. This finding suggests that Aβ deposition does not explain the observed association between reduced vestibular function and poorer cognition in healthy older adults.

Systemic inflammation as a predictor of brain aging: Contributions of physical activity, metabolic risk, and genetic risk

Inflammatory processes may contribute to risk for Alzheimer's disease (AD) and age-related brain degeneration. Metabolic and genetic risk factors, and physical activity may, in turn, influence these inflammatory processes. Some of these risk factors are modifiable, and interact with each other. Understanding how these processes together relate to brain aging will help to inform future interventions to treat or prevent cognitive decline. We used brain magnetic resonance imaging (MRI) to scan 335 older adult humans (mean age 77.3 ± 3.4 years) who remained non-demented for the duration of the 9-year longitudinal study. We used structural equation modeling (SEM) in a subset of 226 adults to evaluate whether measures of baseline peripheral inflammation (serum C-reactive protein levels; CRP), mediated the baseline contributions of genetic and metabolic risk, and physical activity, to regional cortical thickness in AD-relevant brain regions at study year 9. We found that both baseline metabolic risk and AD risk variant apolipoprotein E ε4 (APOE4), modulated baseline serum CRP. Higher baseline CRP levels, in turn, predicted thinner regional cortex at year 9, and mediated an effect between higher metabolic risk and thinner cortex in those regions. A higher polygenic risk score composed of variants in immune-associated AD risk genes (other than APOE) was associated with thinner regional cortex. However, CRP levels did not mediate this effect, suggesting that other mechanisms may be responsible for the elevated AD risk. We found interactions between genetic and environmental factors and structural brain health. Our findings support the role of metabolic risk and peripheral inflammation in age-related brain decline.

Religious Orders Study and Rush Memory and Aging Project

BACKGROUND

The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD).

OBJECTIVES

To summarize progress over the past five years and its implications for understanding neurodegenerative diseases.

METHODS

Participants in both studies are older adults who enroll without dementia and agree to detailed longitudinal clinical evaluations and organ donation. The last review summarized findings through the end of 2011. Here we summarize progress and study findings over the past five years and discuss new directions for how these studies can inform on aging and AD in the future.

RESULTS

We summarize 1) findings on the relation of neurobiology to clinical AD; 2) neurobiologic pathways linking risk factors to clinical AD; 3) non-cognitive AD phenotypes including motor function and decision making; 4) the development of a novel drug discovery platform.

CONCLUSION

Complexity at multiple levels needs to be understood and overcome to develop effective treatments and preventions for cognitive decline and AD dementia.

Development of tau PET Imaging Ligands and their Utility in Preclinical and Clinical Studies

The pathological features of Alzheimer's disease are senile plaques which are aggregates of β-amyloid peptides and neurofibrillary tangles in the brain. Neurofibrillary tangles are aggregates of hyperphosphorylated tau proteins, and these induce various other neurodegenerative diseases, such as progressive supranuclear palsy, corticobasal degeneration, frontotemporal lobar degeneration, frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17), and chronic traumatic encephalopathy. In the case of Alzheimer's disease, the measurement of neurofibrillary tangles associated with cognitive decline is suitable for differential diagnosis, disease progression assessment, and to monitor the effects of therapeutic treatment. This review discusses considerations for the development of tau ligands for imaging and summarizes the results of the first-in-human and preclinical studies of the tau tracers that have been developed thus far. The development of tau ligands for imaging studies will be helpful for differential diagnosis and for the development of therapeutic treatments for tauopathies including Alzheimer's disease.

Brain-predicted age in Down syndrome is associated with beta amyloid deposition and cognitive decline

Individuals with Down syndrome (DS) are more likely to experience earlier onset of multiple facets of physiological aging. This includes brain atrophy, beta amyloid deposition, cognitive decline, and Alzheimer's disease—factors indicative of brain aging. Here, we employed a machine learning approach, using structural neuroimaging data to predict age (i.e., brain-predicted age) in people with DS (N = 46) and typically developing controls (N = 30). Chronological age was then subtracted from brain-predicted age to generate a brain-predicted age difference (brain-PAD) score. DS participants also underwent [¹¹C]-PiB positron emission tomography (PET) scans to index the levels of cerebral beta amyloid deposition, and cognitive assessment. Mean brain-PAD in DS participants' was +2.49 years, significantly greater than controls (p < 0.001). The variability in brain-PAD was associated with the presence and the magnitude of PiB-binding and levels of cognitive performance. Our study indicates that DS is associated with premature structural brain aging, and that age-related alterations in brain structure are associated with individual differences in the rate of beta amyloid deposition and cognitive impairment.

Cognitive Domain Dispersion Association with Alzheimer's Disease Pathology

Within neuropsychology, the term dispersion refers to the degree of variation in performance between different cognitive domains for an individual. Previous studies have demonstrated that cognitively normal individuals with higher dispersion are at an increased risk for progressing to mild cognitive impairment (MCI) and Alzheimer's disease (AD). Therefore, we determined 1) whether increased dispersion in older adults was associated with amyloid plaques and neurofibrillary tangles (NFTs) and 2) whether increased cognitive dispersion accurately differentiated MCI and AD from non-cognitively impaired (NCI) individuals. The intra-subject standard deviation (ISD) was used to quantify cognitive dispersion, and receiver operator characteristic (ROC) analysis determined whether ISD differentiated MCI and AD from NCI. Neuropathological scores for diffuse plaques (DPs), neuritic plaques (NPs), and NFTs were used as outcome measures in a series of negative binomial regression models. Regression analyses found that increased ISD was associated with increased NFT pathology (β= 10.93, SE = 3.82, p = 0.004), but not with DPs (β= 1.33, SE = 8.85, p = 0.88) or NPs (β= 14.64, SE = 8.45, p = 0.08) after adjusting for age at death, gender, education, APOE ɛ4 status, and clinical diagnosis. An interaction term of ISD with age at death also showed a significant negative association (β= -0.13, SE = 0.04, p = 0.004), revealing an age-dependent association between ISD with NFTs. The ISD failed to show an acceptable level of diagnostic accuracy for MCI (AUC = 0.60). These findings suggest that increased cognitive dispersion is related to NFT pathology where age significantly affects this association.

Neuritic and Diffuse Plaque Associations with Memory in Non-Cognitively Impaired Elderly

The presence of Alzheimer's disease (AD)-related neuropathology among cognitively normal individuals has been well documented. It has been proposed that these individuals may represent a pre-clinical AD population. Previous studies have demonstrated a negative association between the presence of both amyloid-β (Aβ) plaques and neurofibrillary tangles with ante-mortem cognitive performance, a relationship which is likely influenced by a number of factors including age and APOE ɛ4 carrier status. The present study determined whether the presence of neuritic plaques (NPs) and diffuse plaques (DPs) are associated with performance in a number of cognitive domains after accounting for APOE ɛ4 carrier status and neurofibrillary tangle presence in a cohort of 123 older participants from the Rush Religious Order Study who died with a premortem clinical diagnosis of no cognitive impairment (NCI). After adjusting for age at death, education, gender, Braak stage, and APOE ɛ4 carrier status, the presence of NPs was associated with lower performance in the cognitive domains of Global Cognition (p = 0.002), Episodic Memory (p = 0.03), Semantic Memory (p = 0.009), and Visuospatial performance (p = 0.006), while DPs showed no association with any cognitive domain examined. These results suggest that decreases in cognition in elderly NCI individuals are associated with an increase in NPs and not DPs when age at death, education, gender, APOE ɛ4 status, and Braak stage are taken into consideration.

First magenetic resonance imaging studies on aluminium maltolate-treated aged New Zealand rabbits: an Alzheimer's animal model

BACKGROUND

Alzheimer's disease is a devastative neurodegenerative disorder. To date, there has been no animal model that could unravel the complete disease pathology. Magnetic resonance imaging has played a pivotal role in the quantitative assessment of brain tissue atrophy for a few decades. In particular, temporal lobe atrophy and ventricular dilatation have been found to be sensitive in Alzheimer's disease.

METHODS

The present study focused on the replication of these crucial pathological events to enable disease progression to be diagnosed at an early stage and stopped through the use of potential therapeutic strategies.

RESULT

The objective of this study was to show temporal lobe atrophy and ventricular dilatation in aluminium maltolate-treated aged New Zealand rabbit, and our study was able to demonstrate this for the first time.

CONCLUSION

The present study makes this animal model a substantial one for further molecular level studies and opens up new targets for potential therapeutic strategies.

Myelin basic protein associates with AβPP, Aβ1-42, and amyloid plaques in cortex of Alzheimer's disease brain

The goal of this study was to show that myelin and axons in cortical gray matter are damaged in Alzheimer's disease (AD) brain. Superior temporal gyrus gray matter of AD patients (9 male, 14 female) was compared to cognitively normal controls (8 male, 7 female). Myelin basic protein (MBP) and a degraded myelin basic protein complex (dMBP) were quantified by Western blot. Brain sections were immunostained for MBP, dMBP, axonal neurofilament protein (NF), autophagy marker microtubule-associated proteins 1A/B light chain 3B precursor (LC3B), amyloid-β protein precursor (AβPP), and amyloid markers amyloid β1-42 (Aβ1-42) and FSB. Co-immunoprecipitation and mass spectroscopy evaluated interaction of AβPP/Aβ1-42 with MBP/dMBP. Evidence of axonal injury in AD cortex included appearance of AβPP in NF stained axons, and NF at margins of amyloid plaques. Evidence of myelin injury in AD cortex included (1) increased dMBP in AD gray matter compared to control (p < 0.001); (2) dMBP in AD neurons; and (3) increased LC3B that co-localized with MBP. Evidence of interaction of AβPP/Aβ1-42 with myelin or axonal components included (1) greater binding of dMBP with AβPP in AD brain; (2) MBP at the margins of amyloid plaques; (3) dMBP co-localized with Aβ1-42 in the core of amyloid plaques in AD brains; and (4) interactions between Aβ1-42 and MBP/dMBP by co-immunoprecipitation and mass spectrometry. We conclude that damaged axons may be a source of AβPP. dMBP, MBP, and NF associate with amyloid plaques and dMBP associates with AβPP and Aβ1-42. These molecules could be involved in formation of amyloid plaques.

Opposite effects of two estrogen receptors on tau phosphorylation through disparate effects on the miR-218/PTPA pathway

The two estrogen receptors (ERs), ERα and ERβ, mediate the diverse biological functions of estradiol. Opposite effects of ERα and ERβ have been found in estrogen-induced cancer cell proliferation and differentiation as well as in memory-related tasks. However, whether these opposite effects are implicated in the pathogenesis of Alzheimer’s disease (AD) remains unclear. Here, we find that ERα and ERβ play contrasting roles in regulating tau phosphorylation, which is a pathological hallmark of AD. ERα increases the expression of miR-218 to suppress the protein levels of its specific target, protein tyrosine phosphatase α (PTPα). The downregulation of PTPα results in the abnormal tyrosine hyperphosphorylation of glycogen synthase kinase-3β (resulting in activation) and protein phosphatase 2A (resulting in inactivation), the major tau kinase and phosphatase. Suppressing the increased expression of miR-218 inhibits the ERα-induced tau hyperphosphorylation as well as the PTPα decline. In contrast, ERβ inhibits tau phosphorylation by limiting miR-218 levels and restoring the miR-218 levels antagonized the attenuation of tau phosphorylation by ERβ. These data reveal for the first time opposing roles for ERα and ERβ in AD pathogenesis and suggest potential therapeutic targets for AD.

Nuclear medicine imaging and therapy: gender biases in disease

Gender-based medicine is medical research and care conducted with conscious consideration of the sex and gender differences of subjects and patients. This issue of Seminars is focused on diseases for which nuclear medicine is part of routine management and for which the diseases have sex- or gender-based differences that affect incidence or pathophysiology and that thus have differences that can potentially affect the results of the relevant nuclear medicine studies. In this first article, we discuss neurologic diseases, certain gastrointestinal conditions, and thyroid conditions. The discussion is in the context of those sex- or gender-based aspects of these diseases that should be considered in the performance, interpretation, and reporting of the relevant nuclear medicine studies. Cardiovascular diseases, gynecologic diseases, bone conditions such as osteoporosis, pediatric occurrences of some diseases, human immunodeficiency virus-related conditions, and the radiation dose considerations of nuclear medicine studies are discussed in the other articles in this issue.

Mapping ventricular expansion onto cortical gray matter in older adults

Dynamic changes in the brain's lateral ventricles on magnetic resonance imaging are powerful biomarkers of disease progression in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Ventricular measures can represent accumulation of diffuse brain atrophy with very high effect sizes. Despite having no direct role in cognition, ventricular expansion co-occurs with volumetric loss in gray and white matter structures. To better understand relationships between ventricular and cortical changes over time, we related ventricular expansion to atrophy in cognitively relevant cortical gray matter surfaces, which are more challenging to segment. In ADNI participants, percent change in ventricular volumes at 1-year (N = 677) and 2-year (N = 536) intervals was significantly associated with baseline cortical thickness and volume in the full sample controlling for age, sex, and diagnosis, and in MCI separately. Ventricular expansion in MCI was associated with thinner gray matter in frontal, temporal, and parietal regions affected by AD. Ventricular expansion reflects cortical atrophy in early AD, offering a useful biomarker for clinical trials of interventions to slow AD progression.

In vivo parahippocampal white matter pathology as a biomarker of disease progression to Alzheimer's disease

Noninvasive diagnostic tests for Alzheimer's disease (AD) are limited. Postmortem diagnosis is based on density and distribution of neurofibrillary tangles (NFTs) and amyloid-rich neuritic plaques. In preclinical stages of AD, the cells of origin for the perforant pathway within the entorhinal cortex are among the first to display NFTs, indicating its compromise in early stages of AD. We used diffusion tensor imaging (DTI) to assess the integrity of the parahippocampal white matter in mild cognitive impairment (MCI) and AD, as a first step in developing a noninvasive tool for early diagnosis. Subjects with AD (N = 9), MCI (N = 8), or no cognitive impairment (NCI; N = 20) underwent DTI-MRI. Fractional anisotropy (FA) and mean (MD) and radial (RD) diffusivity measured from the parahippocampal white matter in AD and NCI subjects differed greatly. Discriminant analysis in the MCI cases assigned statistical membership of 38% of MCI subjects to the AD group. Preliminary data 1 year later showed that all MCI cases assigned to the AD group either met the diagnostic criteria for probable AD or showed significant cognitive decline. Voxelwise analysis in the parahippocampal white matter revealed a progressive change in the DTI patterns in MCI and AD subjects: whereas converted MCI cases showed structural changes restricted to the anterior portions of this region, in AD the pathology was generalized along the entire anterior-posterior axis. The use of DTI for in vivo assessment of the parahippocampal white matter may be useful for identifying individuals with MCI at highest risk for conversion to AD and for assessing disease progression.

The link between cardiovascular risk, Alzheimer's disease, and mild cognitive impairment: support from recent functional neuroimaging studies

OBJECTIVE

To review functional neuroimaging studies about the relationship between cardiovascular risk factors (CVRFs), Alzheimer's disease (AD), and mild cognitive impairment (MCI).

METHODS

We performed a comprehensive literature search to identify articles in the neuroimaging field addressing CVRF in AD and MCI. We included studies that used positron emission tomography (PET), single photon emission computerized tomography (SPECT), or functional magnetic resonance imaging (fMRI).

RESULTS

CVRFs have been considered risk factors for cognitive decline, MCI, and AD. Patterns of AD-like changes in brain function have been found in association with several CVRFs (both regarding individual risk factors and also composite CVRF measures). In vivo assessment of AD-related pathology with amyloid imaging techniques provided further evidence linking CVRFs and AD, but there is still limited information resulting from this new technology.

CONCLUSION

There is a large body of evidence from functional neuroimaging studies supporting the hypothesis that CVRFs may play a causal role in the pathophysiology of AD. A major limitation of most studies is their cross-sectional design; future longitudinal studies using multiple imaging modalities are expected to better document changes in CVRF-related brain function patterns and provide a clearer picture of the complex relationship between aging, CVRFs, and AD.

Using neuroimaging to inform clinical practice for the diagnosis and treatment of mild cognitive impairment

Advances in structural and functional neuroimaging techniques have unquestionably improved understanding of the development and progression of Alzheimer disease (AD), with evidence supporting regional (and network) change that underlies cognitive decline across the "healthy" aging/mild cognitive impairment (MCI)/AD spectrum. This review focuses on visual rating scales and volumetric analyses that could be easily integrated into clinical practice, followed by a review of functional neuroimaging findings suggesting that widespread cerebral dysfunction underlies the learning and memory deficits in MCI. Evidence of preserved neuroplasticity in this population and that cognitive rehabilitation techniques may capitalize on this plasticity to improve cognition in those with MCI is also discussed.

Brain region's relative proximity as marker for Alzheimer's disease based on structural MRI

BACKGROUND

Alzheimer's disease (AD) is a progressive, incurable neurodegenerative disease and the most common type of dementia. It cannot be prevented, cured or drastically slowed, even though AD research has increased in the past 5-10 years. Instead of focusing on the brain volume or on the single brain structures like hippocampus, this paper investigates the relationship and proximity between regions in the brain and uses this information as a novel way of classifying normal control (NC), mild cognitive impaired (MCI), and AD subjects.

METHODS

A longitudinal cohort of 528 subjects (170 NC, 240 MCI, and 114 AD) from ADNI at baseline and month 12 was studied. We investigated a marker based on Procrustes aligned center of masses and the percentile surface connectivity between regions. These markers were classified using a linear discriminant analysis in a cross validation setting and compared to whole brain and hippocampus volume.

RESULTS

We found that both our markers was able to significantly classify the subjects. The surface connectivity marker showed the best results with an area under the curve (AUC) at 0.877 (p<0.001), 0.784 (p<0.001), 0,766 (p<0.001) for NC-AD, NC-MCI, and MCI-AD, respectively, for the functional regions in the brain. The surface connectivity marker was able to classify MCI-converters with an AUC of 0.599 (p<0.05) for the 1-year period.

CONCLUSION

Our results show that our relative proximity markers include more information than whole brain and hippocampus volume. Our results demonstrate that our proximity markers have the potential to assist in early diagnosis of AD.

Neuroimaging and genetic risk for Alzheimer's disease and addiction-related degenerative brain disorders

Neuroimaging offers a powerful means to assess the trajectory of brain degeneration in a variety of disorders, including Alzheimer's disease (AD). Here we describe how multi-modal imaging can be used to study the changing brain during the different stages of AD. We integrate findings from a range of studies using magnetic resonance imaging (MRI), positron emission tomography (PET), functional MRI (fMRI) and diffusion weighted imaging (DWI). Neuroimaging reveals how risk genes for degenerative disorders affect the brain, including several recently discovered genetic variants that may disrupt brain connectivity. We review some recent neuroimaging studies of genetic polymorphisms associated with increased risk for late-onset Alzheimer's disease (LOAD). Some genetic variants that increase risk for drug addiction may overlap with those associated with degenerative brain disorders. These common associations offer new insight into mechanisms underlying neurodegeneration and addictive behaviors, and may offer new leads for treating them before severe and irreversible neurological symptoms appear.

Functional brain connectivity using fMRI in aging and Alzheimer's disease

Normal aging and Alzheimer's disease (AD) cause profound changes in the brain's structure and function. AD in particular is accompanied by widespread cortical neuronal loss, and loss of connections between brain systems. This degeneration of neural pathways disrupts the functional coherence of brain activation. Recent innovations in brain imaging have detected characteristic disruptions in functional networks. Here we review studies examining changes in functional connectivity, measured through fMRI (functional magnetic resonance imaging), starting with healthy aging and then Alzheimer's disease. We cover studies that employ the three primary methods to analyze functional connectivity--seed-based, ICA (independent components analysis), and graph theory. At the end we include a brief discussion of other methodologies, such as EEG (electroencephalography), MEG (magnetoencephalography), and PET (positron emission tomography). We also describe multi-modal studies that combine rsfMRI (resting state fMRI) with PET imaging, as well as studies examining the effects of medications. Overall, connectivity and network integrity appear to decrease in healthy aging, but this decrease is accelerated in AD, with specific systems hit hardest, such as the default mode network (DMN). Functional connectivity is a relatively new topic of research, but it holds great promise in revealing how brain network dynamics change across the lifespan and in disease.

Vascular risk and FDDNP-PET influence cognitive performance

The relationship of cerebrovascular risk and Alzheimer's disease (AD) pathology to cognition in pre-dementia has been extensively investigated and is well-established. Cerebrovascular risk can be measured using a Framingham Stroke Risk Profile (FSRP) score, while positron emission tomography (PET) scans with 2-(1-{6-[(2-[F-18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile (FDDNP) measure AD neuropathology (i.e., amyloid-β plaques and tau tangles). Here we report results of 75 healthy non-demented subjects (mean age, 63 years) who underwent neuropsychological testing, physical assessments, and FDDNP-PET scans. Controlling for AD family history, education, and APOE4 status in a general linear model, higher FSRP risk and global FDDNP-PET binding were each associated with poorer cognitive functioning. The interaction of FSRP and global FDDNP-PET binding was not significant in the model, indicating that stroke risk and plaque and tangle burden each contributed to worse cognitive performance. Within our healthy volunteers, age, blood pressure, and antihypertensive medication use were vascular risks that contributed significantly to the above findings. These findings suggest that even mild cerebrovascular risk may influence the extent of cognitive dysfunction in pre-dementia, along with amyloid-β and tau burden.

Understanding cognitive deficits in Alzheimer's disease based on neuroimaging findings

Brain amyloid can be measured using positron emission tomography (PET). There are mixed reports regarding whether amyloid measures are correlated with measures of cognition (in particular memory), depending on the cohorts and cognitive domains assessed. In Alzheimer's disease (AD) patients and those at heightened risk for AD, cognitive performance may be related to the level and extent of classical AD pathology (amyloid plaques and neurofibrillary angles), but it is also influenced by neurodegeneration, neurocognitive reserve, and vascular health. We discuss what recent neuroimaging research has discovered about cognitive deficits in AD and offer suggestions for future research.

Recent advances in imaging Alzheimer's disease

Advances in brain imaging technology in the past five years have contributed greatly to the understanding of Alzheimer's disease (AD). Here, we review recent research related to amyloid imaging, new methods for magnetic resonance imaging analyses, and statistical methods. We also review research that evaluates AD risk factors and brain imaging, in the context of AD prediction and progression. We selected a variety of illustrative studies, describing how they advanced the field and are leading AD research in promising new directions.

Design, synthesis and biological evaluation of trimethine cyanine dyes as fluorescent probes for the detection of tau fibrils in Alzheimer's disease brain and olfactory epithelium

Shedding light on grey matter: Fluorescent trimethine cyanines were evaluated as imaging probes for neurofibrillary tangles in post-mortem brain sections of Alzheimer's disease patients. These probes bind to neurofibrillary tangles with high contrast and selectivity over amyloid β plaques.

Mapping Dynamic Changes in Ventricular Volume onto Baseline Cortical Surfaces in Normal Aging, MCI, and Alzheimer's Disease

Ventricular volume (VV) is a powerful global indicator of brain tissue loss on MRI in normal aging and dementia. VV is used by radiologists in clinical practice and has one of the highest obtainable effect sizes for tracking brain change in clinical trials, but it is crucial to relate VV to structural alterations underlying clinical symptoms. Here we identify patterns of thinner cortical gray matter (GM) associated with dynamic changes in lateral VV at 1-year (N=677) and 2-year (N=536) intervals, in the ADNI cohort. People with faster VV loss had thinner baseline cortical GM in temporal, inferior frontal, inferior parietal, and occipital regions (controlling for age, sex, diagnosis). These findings show the patterns of relative cortical atrophy that predict later ventricular enlargement, further validating the use of ventricular segmentations as biomarkers. We may also infer specific patterns of regional cortical degeneration (and perhaps functional changes) that relate to VV expansion.

Anterior cingulate activation relates to local cortical thickness

Few studies have examined the relationship between local anatomic thickness of the cortex and the activation signals arising from it. Using structural and functional MRI, we examined whether a relationship exists between cortical thickness and brain activation. Twenty-eight participants were asked to perform the Go/NoGo response inhibition task known to activate the anterior cingulate and the prefrontal cortex. Structural data of the same regions were simultaneously collected. We hypothesized that cortical thickness in these brain regions would positively correlate with brain activation. Data from the structural MRI were aligned with those of functional MRI activation. There was a positive linear correlation between cortical thickness and activation during response inhibition in the right anterior cingulate cortex (Brodmann's Area 24). No significant thickness-activation correlations were found in the prefrontal cortex. Correlations between cortical thickness and activation may occur only in certain brain regions.

Prediction of cognitive decline by positron emission tomography of brain amyloid and tau

OBJECTIVE

To determine whether 2-(1-{6-[(2-fluorine 18-labeled fluoroethyl)methylamino]-2-napthyl}ethylidene) malononitrile ([(18)F]FDDNP) brain regional values in individuals without dementia predict and correlate with future cognitive change.

DESIGN

Two-year, longitudinal follow-up study.

SETTING

A university research institute.

PARTICIPANTS

Volunteer sample of 43 middle-aged and older persons (median age, 64 years), including 21 with mild cognitive impairment (MCI) and 22 with normal aging.

MAIN OUTCOME MEASURES

Longitudinal [(18)F]FDDNP positron emission tomography (PET) binding values in the medial and lateral temporal, posterior cingulate, parietal, frontal, and global (mean) regions of interest; neuropsychological test battery measuring 5 cognitive domains, including memory, language, attention (and information-processing speed), executive functioning, and visuospatial ability.

RESULTS

For the entire study group (MCI and normal aging), increases in frontal, posterior cingulate, and global binding at follow-up correlated with progression of memory decline (r = -0.32 to -0.37, P = .03 to .01) after 2 years. Moreover, higher baseline [(18)F]FDDNP binding was associated with future decline in most cognitive domains, including language, attention, executive, and visuospatial abilities (r = -0.31 to -0.56, P = .05 to .002). For the MCI group, frontal and parietal [(18)F]FDDNP binding yielded the greatest diagnostic accuracy in identifying converters to Alzheimer disease vs nonconverters after 2 years, with an area under the receiver operating characteristic curve of 0.88 (95% CI, 0.72-1.00) compared with 0.68 (95% CI, 0.45-0.91) for medial temporal binding.

CONCLUSIONS

[(18)F]FDDNP PET regional binding patterns are consistent with known neuropathologic patterns of plaque and tangle brain accumulation, spreading from the medial temporal to other neocortical regions as disease progresses. Because binding patterns predict future cognitive decline and increase over time along with clinical decline, [(18)F]FDDNP PET scanning may have practical utility in identifying people at risk for future cognitive decline and in tracking the effectiveness of novel interventions designed to prevent or delay neurodegeneration and cognitive decline.

Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data

Analysis of incomplete data is a big challenge when integrating large-scale brain imaging datasets from different imaging modalities. In the Alzheimer's Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. In this paper, we address this problem by proposing an incomplete Multi-Source Feature (iMSF) learning method where all the samples (with at least one available data source) can be used. To illustrate the proposed approach, we classify patients from the ADNI study into groups with Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI's 780 participants (172AD, 397 MCI, 211 NC), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithm. Depending on the problem being solved, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. To build a practical and robust system, we construct a classifier ensemble by combining our method with four other methods for missing value estimation. Comprehensive experiments with various parameters show that our proposed iMSF method and the ensemble model yield stable and promising results.

Structural imaging in early pre-states of dementia

In this review focus is on structural imaging in the Alzheimer's disease (AD) pre-states, particularly cognitively normal (CN) persons at future dementia risk. Findings in mild cognitive impairment (MCI) are described here only for comparison with CN. Cited literature evidence and commentary address issues of structural imaging alterations in CN that precede MCI and AD, regional patterns of such alterations, and the time relationship between structural imaging alterations and the appearance of symptoms of AD, issues relevant to the conduct of future AD prevention trials. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

Prediction of cognitive decline based on hemispheric cortical surface maps of FDDNP PET

OBJECTIVES

A cross-sectional study to establish whether a subject's cognitive state can be predicted based on regional values obtained from brain cortical maps of FDDNP Distribution Volume Ratio (DVR), which shows the pattern of beta amyloid and neurofibrillary binding, along with those of early summed FDDNP PET images (reflecting the pattern of perfusion) was performed.

METHODS

Dynamic FDDNP PET studies were performed in a group of 23 subjects (8 control (NL), 8 Mild Cognitive Impairment (MCI) and 7 Alzheimer's Disease (AD) subjects). FDDNP DVR images were mapped to the MR derived hemispheric cortical surface map warped into a common space. A set of Regions of Interest (ROI) values of FDDNP DVR and early summed FDDNP PET (0-6 min post tracer injection), were thus calculated for each subject which along with the MMSE score were used to construct a linear mathematical model relating ROI values to MMSE. After the MMSE prediction models were developed, the models' predictive ability was tested in a non-overlapping set of 8 additional individuals, whose cognitive status was unknown to the investigators who constructed the predictive models.

RESULTS

Among all possible subsets of ROIs, we found that the standard deviation of the predicted MMSE was 1.8 by using only DVR values from medial and lateral temporal and prefrontal regions plus the early summed FDDNP value in the posterior cingulate gyrus. The root mean square prediction error for the eight new subjects was 1.6.

CONCLUSION

FDDNP scans reflect progressive neuropathology accumulation and can potentially be used to predict the cognitive state of an individual.

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer's Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI's 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results.

Pathologic lesions in neurodegenerative diseases

This chapter will discuss two of the most widely used approaches to assessing brain structure: neuroimaging and neuropathology. Whereas neuropathologic approaches to studying the central nervous system have been utilized for many decades and have provided insights into morphologic correlates of dementia for over 100 years, accurate structural imaging techniques "blossomed" with the development and refinement of computerized tomographic scanning and magnetic resonance imaging (MRI), beginning in the late 1970s. As Alzheimer disease progresses over time, there is progressive atrophy of the hippocampus and neocortex--this can be quantified and regional accentuation of the atrophy can be evaluated using quantitative MRI scanning. Furthermore, ligands for amyloid proteins have recently been developed--these can be used in positron emission tomography studies to localize amyloid proteins, and (in theory) study the dynamics of their deposition (and clearance) within the brain over time. Neuropathologic studies of the brain, using highly specific antibodies, can demonstrate synapse loss and the deposition of proteins important in AD progression--specifically ABeta and phosphor-tau. Finally, neuropathologic assessment of (autopsy) brain specimens can provide important correlation with sophisticated neuroimaging techniques.

Staging Alzheimer's disease progression with multimodality neuroimaging

Rapid developments in medical neuroimaging have made it possible to reconstruct the trajectory of Alzheimer's disease (AD) as it spreads through the living brain. The current review focuses on the progressive signature of brain changes throughout the different stages of AD. We integrate recent findings on changes in cortical gray matter volume, white matter fiber tracts, neuropathological alterations, and brain metabolism assessed with molecular positron emission tomography (PET). Neurofibrillary tangles accumulate first in transentorhinal and cholinergic brain areas, and 4-D maps of cortical volume changes show early progressive temporo-parietal cortical thinning. Findings from diffusion tensor imaging (DTI) for assessment fiber tract integrity show cortical disconnection in corresponding brain networks. Importantly, the developmental trajectory of brain changes is not uniform and may be modulated by several factors such as onset of disease mechanisms, risk-associated and protective genes, converging comorbidity, and individual brain reserve. There is a general agreement between in vivo brain maps of cortical atrophy and amyloid pathology assessed through PET, reminiscent of post mortem histopathology studies that paved the way in the staging of AD. The association between in vivo and post mortem findings will clarify the temporal dynamics of pathophysiological alterations in the development of preclinical AD. This will be important in designing effective treatments that target specific underlying disease AD mechanisms.

Prediction of preclinical Alzheimer's disease: longitudinal rates of change in cognition

Preclinical Alzheimer's disease (pAD) reflects neuropathological findings of AD in cognitively normal subjects. The present study represents an effort to determine if differences could be identified in the longitudinal patterns of cognitive performance in persons classified as pAD compared to those who did not meet criteria for AD at autopsy. We included 121 subjects who were cognitively normal from baseline through their last assessment before death and who underwent autopsy. Participants were classified into two groups: pathologically normal (PN; NIA-Reagan low or no-likelihood of AD, n = 89) and preclinical AD (pAD; NIA-Reagan criteria of intermediate or high-likelihood of AD in the absence of clinical dementia symptoms, n = 32) followed for a mean 7.5 years prior to death. Longitudinal rates and patterns of change in scores on a standard cognitive battery were compared between these two groups. While cognitive results at baseline and last evaluations revealed no clear cross sectional group differences after adjustment for age, ApoE status, education, and gender, statistically significant differences between the pAD and PN groups in slope of decline were seen on a composite score of cognitive function. Further analyses showed three components of this score reached significance: constructional praxis, delayed recall of a word list, and category verbal fluency. Despite being clinically viewed as normal at enrollment and at the final exam, there are significant differences in rates of cognitive decline in participants classified as pAD compared to those without this pathology. Longitudinal changes in slope of decline in specific cognitive test measures can serve as non-invasive methods for the detection of pAD.

The Center for Computational Biology: resources, achievements, and challenges

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

Positron emission tomography of brain β-amyloid and τ levels in adults with Down syndrome

OBJECTIVES

To determine the neuropathological load in the living brain of nondemented adults with Down syndrome using positron emission tomography with 2-(1-{6-[(2-fluorine 18-labeled fluoroethyl)methylamino]-2-napthyl}ethylidene) malononitrile ([(18)F]FDDNP) and to assess the influence of age and cognitive and behavioral functioning. For reference, [(18)F]FDDNP binding values and patterns were compared with those from patients with Alzheimer disease and cognitively intact control participants.

DESIGN

Cross-sectional clinical study.

PARTICIPANTS

Volunteer sample of 19 persons with Down syndrome without dementia (mean age, 36.7 years), 10 patients with Alzheimer disease (mean age, 66.5 years), and 10 controls (mean age, 43.8 years).

MAIN OUTCOME MEASURES

Binding of [(18)F]FDDNP in brain regions of interest, including the parietal, medial temporal, lateral temporal, and frontal lobes and posterior cingulate gyrus, and the average of all regions (global binding).

RESULTS

The [(18)F]FDDNP binding values were higher in all brain regions in the Down syndrome group than in controls. Compared with the Alzheimer disease group, the Down syndrome group had higher [(18)F]FDDNP binding values in the parietal and frontal regions, whereas binding levels in other regions were comparable. Within the Down syndrome group, age correlated with [(18)F]FDDNP binding values in all regions except the posterior cingulate, and several measures of behavioral dysfunction showed positive correlations with global, frontal, parietal, and posterior cingulate [(18)F]FDDNP binding.

CONCLUSIONS

Consistent with neuropathological findings from postmortem studies, [(18)F]FDDNP positron emission tomography shows high binding levels in Down syndrome comparable to Alzheimer disease and greater levels than in members of a control group. The positive associations between [(18)F]FDDNP binding levels and age as well as behavioral dysfunction in Down syndrome are consistent with the age-related progression of Alzheimer-type neuropathological findings in this population.

[F-18]FDDNP microPET imaging correlates with brain Aβ burden in a transgenic rat model of Alzheimer disease: effects of aging, in vivo blockade, and anti-Aβ antibody treatment

In vivo detection of Alzheimer's disease (AD) neuropathology in living patients using positron emission tomography (PET) in conjunction with high affinity molecular imaging probes for β-amyloid (Aβ) and tau has the potential to assist with early diagnosis, evaluation of disease progression, and assessment of therapeutic interventions. Animal models of AD are valuable for exploring the in vivo binding of these probes, particularly their selectivity for specific neuropathologies, but prior PET experiments in transgenic mice have yielded conflicting results. In this work, we utilized microPET imaging in a transgenic rat model of brain Aβ deposition to assess [F-18]FDDNP binding profiles in relation to age-associated accumulation of neuropathology. Cross-sectional and longitudinal imaging demonstrated that [F-18]FDDNP binding in the hippocampus and frontal cortex progressively increases from 9 to 18months of age and parallels age-associated Aβ accumulation. Specificity of in vivo [F-18]FDDNP binding was assessed by naproxen pretreatment, which reversibly blocked [F-18]FDDNP binding to Aβ aggregrates. Both [F-18]FDDNP microPET imaging and neuropathological analyses revealed decreased Aβ burden after intracranial anti-Aβ antibody administration. The combination of this non-invasive imaging method and robust animal model of brain Aβ accumulation allows for future longitudinal in vivo assessments of potential therapeutics for AD that target Aβ production, aggregation, and/or clearance. These results corroborate previous analyses of [F-18]FDDNP PET imaging in clinical populations.