326 research outputs found

    Cerebral blood flow and Aβ-amyloid estimates by WARM analysis of [<sup>11</sup>C]PiB uptake distinguish among and between neurodegenerative disorders and aging

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    Background: We report results of the novel Washout Allometric Reference Method (WARM) that uses estimates of cerebral blood flow and amyloid load from the same [C]Pittsburgh Compound B ([C]PiB) retention maps in brain to distinguish between patients with different forms dementia, including Alzheimer's disease, and healthy volunteers. The method introduces two approaches to the identification of brain pathology related to amyloid accumulation, (1) a novel analysis of amyloid binding based on the late washout of the tracer from brain tissue, and (2) the simultaneous estimation of absolute cerebral blood flow indices (sCBF) from the early accumulation of the tracer in brain tissue. Objective: We tested the hypothesis that a change of cerebral blood flow is correlated with the degree of tracer [C]PiB retention, reflecting dendritic spine pathology and consequent inhibition of brain energy metabolism and reduction of blood flow by neurovascular coupling in neurodegenerative disorders, including Alzheimer's disease. Methods: Previously reported images of [C]PiB retention in brain of 29 subjects with cognitive impairment or dementia [16 Alzheimer's Disease (AD), eight subjects with dementia with Lewy bodies (DLB), five patients with frontotemporal lobar degeneration (FTLD), five patients with mild cognitive impairment, and 29 age-matched healthy control subjects (HC)], underwent analysis of PiB delivery and retention by means of WARM for quantitation of [C]PiB's binding potentials (BP) and correlated surrogate cerebral blood flow (sCBF) estimates, based on the [C]PiB images, compared to estimates by conventional Standard Uptake Value Ratio (SUVR) of [C]PiB retention with cerebellum gray matter as reference. Receiver Operating Characteristics (ROC) revealed the power of discrimination among estimates. Results: For AD, the discriminatory power of [C]PiB binding potential (BP) by WARM exceeded the power of SUVR that in turn exceeded the power of sCBF estimates. Differences of [C]PiB binding and sCBF measures between AD and HC both were highly significant (p < 0.001). For all the dementia groups as a whole, sCBF estimates revealed the greatest discrimination between the patient and HC groups. WARM resolves a major issue of amyloid load quantification with [C]PiB in human brain by determining absolute sCBF and amyloid load measures from the same images. The two parameter approach provides key discriminary information in AD for which [C]PiB traditionally is used, as well as for the distinct flow deficits in FTLD, and the marked parietal and occipital lobe flow deficits in DLB. Conclusion: We conclude that WARM yields estimates of two important variables that together discriminate among patients with dementia, including AD, and healthy volunteers, with ROC that are superior to conventional methods of analysis. The distinction between estimates of flow and amyloid load from the same dynamic emission tomograms provides valuable pathogenetic information

    Exploring discordant low amyloid beta and high neocortical tau positron emission tomography cases

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    Introduction: Neocortical 3R4R (3-repeat/4-repeat) tau aggregates are rarely observed in the absence of amyloid beta (Aβ). 18F-MK6240 binds specifically to the 3R4R form of tau that is characteristic of Alzheimer\u27s disease (AD). We report four cases with negative Aβ, but positive tau positron emission tomography (PET) findings. Methods: All Australian Imaging, Biomarkers and Lifestyle study of aging (AIBL) study participants with Aβ (18F-NAV4694) and tau (18F-MK6240) PET scans were included. Centiloid \u3c 25 defined negative Aβ PET (Aβ–). The presence of neocortical tau was defined quantitatively and visually. Results: Aβ– PET was observed in 276 participants. Four of these participants (one cognitively unimpaired [CU], two mild cognitive impairment [MCI], one AD) had tau tracer retention in a pattern consistent with Braak tau stages V to VI. Fluid biomarkers supported a diagnosis of AD. In silico analysis of APP, PSEN1, PSEN2, and MAPT genes did not identify relevant functional mutations. Discussion: Discordant cases were infrequent (1.4% of all Aβ– participants). In these cases, the Aβ PET ligand may not be detecting the Aβ that is present

    Supervised method to build an atlas database for multi-atlas segmentation-propagation

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    Multi-atlas based segmentation-propagation approaches have been shown to obtain accurate parcelation of brain structures. However, this approach requires a large number of manually delineated atlases, which are often not available. We propose a supervised method to build a population specific atlas database, using the publicly available Internet Brain Segmentation Repository (IBSR). The set of atlases grows iteratively as new atlases are added, so that its segmentation capability may be enhanced in the multi-atlas based approach. Using a dataset of 210 MR images of elderly subjects (170 elderly controls, 40 Alzheimer's disease) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, 40 MR images were segmented to build a population specific atlas database for the purpose of multi-atlas segmentation-propagation. The population specific atlases were used to segment the elderly population of 210 MR images, and were evaluated in terms of the agreement among the propagated labels. The agreement was measured by using the entropy H of the probability image produced when fused by voting rule and the partial moment mu(2) of the histogram. Compared with using IBSR atlases, the population specific atlases obtained a higher agreement when dealing with images of elderly subjects

    Cross-sectional and Longitudinal Analysis of the Relationship Between A beta Deposition, Cortical Thickness, and Memory in Cognitively Unimpaired Individuals and in Alzheimer Disease

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    IMPORTANCE beta-amyloid (A beta) deposition is one of the hallmarks of Alzheimer disease. A beta deposition accelerates gray matter atrophy at early stages of the disease even before objective cognitive impairment is manifested. Identification of at-risk individuals at the presymptomatic stage has become a major research interest because it will allow early therapeutic interventions before irreversible synaptic and neuronal loss occur. We aimed to further characterize the cross-sectional and longitudinal relationship between A beta deposition, gray matter atrophy, and cognitive impairment

    Cerebrospinal fluid levels of fatty acid–binding protein 3 are associated with likelihood of amyloidopathy in cognitively healthy individuals

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    Introduction: Fatty acid–binding protein 3 (FABP3) is a biomarker of neuronal membrane disruption, associated with lipid dyshomeostasis—a notable Alzheimer\u27s disease (AD) pathophysiological change. We assessed the association of cerebrospinal fluid (CSF) FABP3 levels with brain amyloidosis and the likelihood/risk of developing amyloidopathy in cognitively healthy individuals. Methods: FABP3 levels were measured in CSF samples of cognitively healthy participants, \u3e 60 years of age (n = 142), from the Australian Imaging, Biomarkers & Lifestyle Flagship Study of Ageing (AIBL). Results: FABP3 levels were positively associated with baseline brain amyloid beta (Aβ) load as measured by standardized uptake value ratio (SUVR, standardized β = 0.22, P =.009) and predicted the change in brain Aβ load (standardized β = 0.32, P =.004). Higher levels of CSF FABP3 (above median) were associated with a likelihood of amyloidopathy (odds ratio [OR] 2.28, 95% confidence interval [CI] 1.12 to 4.65, P =.023). Discussion: These results support inclusion of CSF FABP3 as a biomarker in risk-prediction models of AD

    Sensitivity of composite scores to amyloid burden in preclinical Alzheimer\u27s disease: Introducing the Z-scores of Attention, Verbal fluency, and Episodic memory for Nondemented older adults composite score

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    Introduction: Cognitive composite scores developed for preclinical Alzheimer\u27s disease (AD) often consist of multiple cognitive domains as they may provide greater sensitivity to detect β-amyloid (Aβ)-related cognitive decline than episodic memory (EM) composite scores alone. However, this has never been empirically tested. We compared the rate of cognitive decline associated with high Aβ (Aβ+) and very high Aβ (Aβ++) in cognitively normal (CN) older adults on three multidomain cognitive composite scores and one single-domain (EM) composite score. Methods: CN older adults (n = 423) underwent Aβ neuroimaging and completed neuropsychological assessments at baseline, and at 18-, 36-, 54-, and 72-month follow-ups. Four cognitive composite scores were computed: the ADCS-PACC (ADCS-Preclinical Alzheimer Cognitive Composite), ADCS-PACC without the inclusion of the mini-mental state examination (MMSE), an EM composite, and the Z-scores of Attention, Verbal fluency, and Episodic memory for Nondemented older adults (ZAVEN) composite. Results: Compared with Aβ+ CN older adults, Aβ++ CN older adults showed faster rates of decline across all cognitive composites, with the largest decline observed for ZAVEN composite (d = 1.07). Similarly, compared with Aβ- CN older adults, Aβ+ CN older adults also showed faster rates of cognitive decline, but only for the ADCS-PACC no MMSE (d = 0.43), EM (d = 0.53), and ZAVEN (d = 0.50) composites. Discussion: Aβ-related cognitive decline is best detected using validated neuropsychological instruments. Removal of the MMSE from the ADCS-PACC and replacing it with a test of executive function (verbal fluency; i.e., the ZAVEN) rendered this composite more sensitive even in detecting Aβ-related cognitive decline between Aβ+ and Aβ++ CN older adults

    Assessment of a polygenic hazard score for the onset of pre-clinical Alzheimer’s disease

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    Background: With a growing number of loci associated with late-onset (sporadic) Alzheimer’s disease (AD), the polygenic contribution to AD is now well established. The development of polygenic risk score approaches have shown promising results for identifying individuals at higher risk of developing AD, thereby facilitating the development of preventative and therapeutic strategies. A polygenic hazard score (PHS) has been proposed to quantify age-specific genetic risk for AD. In this study, we assessed the predictive power and transferability of this PHS in an independent cohort, to support its clinical utility. Results: Using genotype and imaging data from 780 individuals enrolled in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, we investigated associations between the PHS and several AD-related traits, including 1) cross-sectional Aβ-amyloid (Aβ) deposition, 2) longitudinal brain atrophy, 3) longitudinal cognitive decline, 4) age of onset. Except in the cognitive domain, we obtained results that were consistent with previously published findings. The PHS was associated with increased Aβ burden, faster regional brain atrophy and an earlier age of onset. Conclusion: Overall, the results support the predictive power of a PHS, however, with only marginal improvement compared to apolipoprotein E alone

    Higher coffee consumption is associated with slower cognitive decline and less cerebral Aβ-amyloid accumulation over 126 months: Data from the Australian imaging, biomarkers, and lifestyle study

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    Background: Worldwide, coffee is one of the most popular beverages consumed. Several studies have suggested a protective role of coffee, including reduced risk of Alzheimer’s disease (AD). However, there is limited longitudinal data from cohorts of older adults reporting associations of coffee intake with cognitive decline, in distinct domains, and investigating the neuropathological mechanisms underpinning any such associations. Methods: The aim of the current study was to investigate the relationship between self-reported habitual coffee intake, and cognitive decline assessed using a comprehensive neuropsychological battery in 227 cognitively normal older adults from the Australian Imaging, Biomarkers, and Lifestyle (AIBL) study, over 126 months. In a subset of individuals, we also investigated the relationship between habitual coffee intake and cerebral Aβ-amyloid accumulation (n = 60) and brain volumes (n = 51) over 126 months. Results: Higher baseline coffee consumption was associated with slower cognitive decline in executive function, attention, and the AIBL Preclinical AD Cognitive Composite (PACC; shown reliably to measure the first signs of cognitive decline in at-risk cognitively normal populations), and lower likelihood of transitioning to mild cognitive impairment or AD status, over 126 months. Higher baseline coffee consumption was also associated with slower Aβ-amyloid accumulation over 126 months, and lower risk of progressing to “moderate,” “high,” or “very high” Aβ-amyloid burden status over the same time-period. There were no associations between coffee intake and atrophy in total gray matter, white matter, or hippocampal volume. Discussion: Our results further support the hypothesis that coffee intake may be a protective factor against AD, with increased coffee consumption potentially reducing cognitive decline by slowing cerebral Aβ-amyloid accumulation, and thus attenuating the associated neurotoxicity from Aβ-amyloid-mediated oxidative stress and inflammatory processes. Further investigation is required to evaluate whether coffee intake could be incorporated as a modifiable lifestyle factor aimed at delaying AD onset

    A blood-based biomarker panel indicates IL-10 and IL-12/23p40 are jointly associated as predictors of β-amyloid load in an AD cohort

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    Alzheimer’s Disease (AD) is the most common form of dementia, characterised by extracellular amyloid deposition as plaques and intracellular neurofibrillary tangles of tau protein. As no current clinical test can diagnose individuals at risk of developing AD, the aim of this project is to evaluate a blood-based biomarker panel to identify individuals who carry this risk. We analysed the levels of 22 biomarkers in clinically classified healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer’s participants from the well characterised Australian Imaging, Biomarker and Lifestyle (AIBL) study of aging. High levels of IL-10 and IL-12/23p40 were significantly associated with amyloid deposition in HC, suggesting that these two biomarkers might be used to detect at risk individuals. Additionally, other biomarkers (Eotaxin-3, Leptin, PYY) exhibited altered levels in AD participants possessing the APOE ε4 allele. This suggests that the physiology of some potential biomarkers may be altered in AD due to the APOE ε4 allele, a major risk factor for AD. Taken together, these data highlight several potential biomarkers that can be used in a blood-based panel to allow earlier identification of individuals at risk of developing AD and/or early stage AD for which current therapies may be more beneficial

    A blood-based biomarker panel indicates IL-10 and IL-12/23p40 are jointly associated as predictors of β-amyloid load in an AD cohort

    Get PDF
    Alzheimer’s Disease (AD) is the most common form of dementia, characterised by extracellular amyloid deposition as plaques and intracellular neurofibrillary tangles of tau protein. As no current clinical test can diagnose individuals at risk of developing AD, the aim of this project is to evaluate a blood-based biomarker panel to identify individuals who carry this risk. We analysed the levels of 22 biomarkers in clinically classified healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer’s participants from the well characterised Australian Imaging, Biomarker and Lifestyle (AIBL) study of aging. High levels of IL-10 and IL-12/23p40 were significantly associated with amyloid deposition in HC, suggesting that these two biomarkers might be used to detect at risk individuals. Additionally, other biomarkers (Eotaxin-3, Leptin, PYY) exhibited altered levels in AD participants possessing the APOE ε4 allele. This suggests that the physiology of some potential biomarkers may be altered in AD due to the APOE ε4 allele, a major risk factor for AD. Taken together, these data highlight several potential biomarkers that can be used in a blood-based panel to allow earlier identification of individuals at risk of developing AD and/or early stage AD for which current therapies may be more beneficial
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