Cognitive markers of preclinical and prodromal Alzheimer's disease in Down syndrome.
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ABSTRACT:
SUBMITTER: Startin CM
PROVIDER: S-EPMC6374283 | biostudies-literature | 2019 Feb
REPOSITORIES: biostudies-literature
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Cognitive markers of preclinical and prodromal Alzheimer's disease in Down syndrome.
Startin Carla M CM Hamburg Sarah S Hithersay Rosalyn R Al-Janabi Tamara T Mok Kin Y KY Hardy John J Strydom Andre A
Alzheimer's & dementia : the journal of the Alzheimer's Association 20181128 2
<h4>Introduction</h4>Down syndrome (DS) is associated with an almost universal development of Alzheimer's disease. Individuals with DS are therefore an important population for randomized controlled trials to prevent or delay cognitive decline, though it is essential to understand the time course of early cognitive changes.<h4>Methods</h4>We conducted the largest cognitive study to date with 312 adults with DS to assess age-related and Alzheimer's disease-related cognitive changes during progres ...[more]
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Project description:Accurate identification of the prodromal stage of Alzheimer's disease (AD), known as mild cognitive impairment (MCI), in adults with Down syndrome (MCI-DS) has been challenging because there are no established diagnostic criteria that can be applied for people with lifelong intellectual disabilities (ID). As such, the sequence of cognitive decline in adults with DS has been difficult to ascertain, and it is possible that domain constructs characterizing cognitive function in neurotypical adults do not generalize to this high-risk population. The present study examined associations among multiple measures of cognitive function in adults with DS, either prior to or during the prodromal stage of AD to determine, through multiple statistical techniques, the measures that reflected the same underlying domains of processing. Participants included 144 adults with DS 40-82 years of age, all enrolled in a larger, multidisciplinary study examining biomarkers of AD in adults with DS. All participants had mild or moderate lifelong intellectual disabilities. Overall AD-related clinical status was rated for each individual during a personalized consensus conference that considered performance as well as health status, with 103 participants considered cognitively stable (CS) and 41 to have MCI-DS. Analyses of 17 variables derived from 10 tests of cognition indicated that performance reflected three underlying factors: language/executive function, memory, and visuomotor. All three domain composite scores significantly predicted MCI-DS status. Based upon path modeling, the language/executive function composite score was the most affected by prodromal AD. However, based upon structural equation modeling, tests assessing the latent construct of memory were the most impacted, followed by those assessing visuomotor, and then those assessing language/executive function. Our study provides clear evidence that cognitive functioning in older adults with DS can be characterized at the cognitive domain level, but the statistical methods selected and the inclusion or exclusion of certain covariates may lead to different conclusions. Best practice requires investigators to understand the internal structure of their variables and to provide evidence that their variables assess their intended constructs.
| S-EPMC8471085 | biostudies-literature
Project description:BackgroundNeuropathological studies have suggested the tau pathology observed in Alzheimer's disease (AD) originates in brainstem nuclei, but no studies to date have quantified brainstem volumes in clinical populations with biomarker-confirmed mild cognitive impairment (MCI) or dementia due to AD or determined the value of brainstem volumetrics in predicting dementia.ObjectiveThe present study examined whether MRI-based brainstem volumes differ among cognitively normal older adults and those with MCI or dementia due to AD and whether preclinical brainstem volumes predict future progression to dementia.MethodsAlzheimer's Disease Neuroimaging Initiative participants (N = 1,629) underwent baseline MRI scanning with variable clinical follow-up (6-120 months). Region of interest and voxel-based morphometric methods assessed brainstem volume differences among cognitively normal (n = 814), MCI (n = 542), and AD (n = 273) participants, as well as subsets of cerebrospinal fluid biomarker-confirmed MCI (n = 203) and AD (n = 160) participants.ResultsMCI and AD cases showed smaller midbrain volumes relative to cognitively normal participants when normalizing to whole brainstem volume, and showed smaller midbrain, locus coeruleus, pons, and whole brainstem volumes when normalizing to total intracranial volume. Cognitively normal individuals who later progressed to AD dementia diagnosis exhibited smaller baseline midbrain volumes than individuals who did not develop dementia, and voxel-wise analyses revealed specific volumetric reduction of the locus coeruleus.ConclusionFindings are consistent with neuropathological observations of early AD-related pathology in brainstem nuclei and further suggest the clinical relevance of brainstem substructural volumes in preclinical and prodromal AD.
| S-EPMC7868064 | biostudies-literature
Project description:Introduction:We aimed to define prodromal Alzheimer's disease (AD) and AD dementia using normative neuropsychological data in a large population-based cohort of adults with Down syndrome (DS). Methods:Cross-sectional study. DS participants were classified into asymptomatic, prodromal AD and AD dementia, based on neurologist's judgment blinded to neuropsychological data (Cambridge Cognitive Examination for Older Adults with Down's syndrome [CAMCOG-DS] and modified Cued Recall Test [mCRT]). We compared the cutoffs derived from the normative data in young adults with DS to those from receiver-operating characteristic curve (ROC) analysis. Results:Diagnostic performance of the CAMCOG-DS and modified Cued Recall Test (mCRT) in subjects with mild and moderate levels of intellectual disability (ID) was high, both for diagnosing prodromal AD and AD dementia (area under the curve [AUC] 0.73-0.83 and 0.90-1, respectively). The cutoffs derived from the normative data were similar to those derived from the ROC analyses. Discussion:Diagnosing prodromal AD and AD dementia in DS with mild and moderate ID using population norms for neuropsychological tests is possible with high diagnostic accuracy.
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Project description:Down syndrome (DS) is now viewed as a genetic type of Alzheimer's disease (AD), given the near-universal presence of AD pathology in middle adulthood and the elevated risk for developing clinical AD in DS. As the field of DS prepares for AD clinical intervention trials, there is a strong need to identify cognitive measures that are specific and sensitive to the transition from being cognitively stable to the prodromal (e.g., Mild Cognitive Impairment-Down syndrome) and clinical AD (e.g., Dementia) stages of the disease in DS. It is also important to determine cognitive measures that map onto biomarkers of early AD pathology during the transition from the preclinical to the prodromal stage of the disease, as this transition period is likely to be targeted and tracked in AD clinical trials. The present chapter discusses the current state of research on cognitive measures that could be used to screen/select study participants and as potential outcome measures in future AD clinical trials with adults with DS. In this chapter, we also identify key challenges that need to be overcome and questions that need to be addressed by the DS field as it prepares for AD clinical trials in the coming years.
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Project description:Biomarkers useful for the predementia stages of Alzheimer's disease are needed. Electroencephalography and magnetoencephalography (MEG) are expected to provide potential biomarker candidates for evaluating the predementia stages of Alzheimer's disease. However, the physiological relevance of EEG/MEG signal changes and their role in pathophysiological processes such as amyloid-β deposition and neurodegeneration need to be elucidated. We evaluated 28 individuals with mild cognitive impairment and 38 cognitively normal individuals, all of whom were further classified into amyloid-β-positive mild cognitive impairment (n = 17, mean age 74.7 ± 5.4 years, nine males), amyloid-β-negative mild cognitive impairment (n = 11, mean age 73.8 ± 8.8 years, eight males), amyloid-β-positive cognitively normal (n = 13, mean age 71.8 ± 4.4 years, seven males), and amyloid-β-negative cognitively normal (n = 25, mean age 72.5 ± 3.4 years, 11 males) individuals using Pittsburgh compound B-PET. We measured resting state MEG for 5 min with the eyes closed, and investigated regional spectral patterns of MEG signals using atlas-based region of interest analysis. Then, the relevance of the regional spectral patterns and their associations with pathophysiological backgrounds were analysed by integrating information from Pittsburgh compound B-PET, fluorodeoxyglucose-PET, structural MRI, and cognitive tests. The results demonstrated that regional spectral patterns of resting state activity could be separated into several types of MEG signatures as follows: (i) the effects of amyloid-β deposition were expressed as the alpha band power augmentation in medial frontal areas; (ii) the delta band power increase in the same region was associated with disease progression within the Alzheimer's disease continuum and was correlated with entorhinal atrophy and an Alzheimer's disease-like regional decrease in glucose metabolism; and (iii) the global theta power augmentation, which was previously considered to be an Alzheimer's disease-related EEG/MEG signature, was associated with general cognitive decline and hippocampal atrophy, but was not specific to Alzheimer's disease because these changes could be observed in the absence of amyloid-β deposition. The results suggest that these MEG signatures may be useful as unique biomarkers for the predementia stages of Alzheimer's disease.
| S-EPMC5920328 | biostudies-literature
Project description:BackgroundCognitive decline is a key outcome of clinical studies in Alzheimer's disease (AD).ObjectiveTo determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts.MethodsWe included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis.ResultsWe found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases.ConclusionsWe found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid.
| S-EPMC10578328 | biostudies-literature
Project description:ObjectiveIndividuals with Down syndrome (DS) have an extremely high genetic risk for Alzheimer's disease (AD), however, the course of cognitive decline associated with progression to dementia is ill-defined. Data-driven methods can estimate long-term trends from cross-sectional data while adjusting for variability in baseline ability, which complicates dementia assessment in those with DS.MethodsWe applied an event-based model to cognitive test data and informant-rated questionnaire data from 283 adults with DS (the largest study of cognitive functioning in DS to date) to estimate the sequence of cognitive decline and individuals' disease stage.ResultsDecline in tests of memory, sustained attention/motor coordination, and verbal fluency occurred early, demonstrating that AD in DS follows a similar pattern of change to other forms of AD. Later decline was found for informant measures. Using the resulting staging model, we showed that adults with a clinical diagnosis of dementia and those with APOE 3:4 or 4:4 genotype were significantly more likely to be staged later, suggesting that the model is valid.InterpretationOur results identify tests of memory and sustained attention may be particularly useful measures to track decline in the preclinical/prodromal stages of AD in DS whereas informant-measures may be useful in later stages (i.e. during conversion into dementia, or postdiagnosis). These results have implications for the selection of outcome measures of treatment trials to delay or prevent cognitive decline due to AD in DS. As clinical diagnoses are generally made late into AD progression, early assessment is essential.
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Project description:Alzheimer's Disease-resemblance atrophy index (AD-RAI) is an MRI-based machine learning derived biomarker that was developed to reflect the characteristic brain atrophy associated with AD. Recent study showed that AD-RAI (≥0.5) had the best performance in predicting conversion from mild cognitive impairment (MCI) to dementia and from cognitively unimpaired (CU) to MCI. We aimed to validate the performance of AD-RAI in detecting preclinical and prodromal AD. We recruited 128 subjects (MCI=50, CU=78) from two cohorts: CU-SEEDS and ADNI. Amyloid (A+) and tau (T+) status were confirmed by PET (11C-PIB, 18F-T807) or CSF analysis. We investigated the performance of AD-RAI in detecting preclinical and prodromal AD (i.e. A+T+) among MCI and CU subjects and compared its performance with that of hippocampal measures. AD-RAI achieved the best metrics among all subjects (sensitivity 0.74, specificity 0.91, accuracy 85.94%) and among MCI subjects (sensitivity 0.92, specificity 0.81, accuracy 86.00%) in detecting A+T+ subjects over other measures. Among CU subjects, AD-RAI yielded the best specificity (0.95) and accuracy (85.90%) over other measures, while hippocampal volume achieved a higher sensitivity (0.73) than AD-RAI (0.47) in detecting preclinical AD. These results showed the potential of AD-RAI in the detection of early AD, in particular at the prodromal stage.
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Project description:Alzheimer's disease is a heterogeneous disorder. Understanding the biological basis for this heterogeneity is key for developing personalized medicine. We identified atrophy subtypes in Alzheimer's disease dementia and tested whether these subtypes are already present in prodromal Alzheimer's disease and could explain interindividual differences in cognitive decline. First we retrospectively identified atrophy subtypes from structural MRI with a data-driven cluster analysis in three datasets of patients with Alzheimer's disease dementia: discovery data (dataset 1: n = 299, age = 67 ± 8, 50% female), and two independent external validation datasets (dataset 2: n = 181, age = 66 ± 7, 52% female; dataset 3: n = 227, age = 74 ± 8, 44% female). Subtypes were compared on clinical, cognitive and biological characteristics. Next, we classified prodromal Alzheimer's disease participants (n = 603, age = 72 ± 8, 43% female) according to the best matching subtype to their atrophy pattern, and we tested whether subtypes showed cognitive decline in specific domains. In all Alzheimer's disease dementia datasets we consistently identified four atrophy subtypes: (i) medial-temporal predominant atrophy with worst memory and language function, older age, lowest CSF tau levels and highest amount of vascular lesions; (ii) parieto-occipital atrophy with poor executive/attention and visuospatial functioning and high CSF tau; (iii) mild atrophy with best cognitive performance, young age, but highest CSF tau levels; and (iv) diffuse cortical atrophy with intermediate clinical, cognitive and biological features. Prodromal Alzheimer's disease participants classified into one of these subtypes showed similar subtype characteristics at baseline as Alzheimer's disease dementia subtypes. Compared across subtypes in prodromal Alzheimer's disease, the medial-temporal subtype showed fastest decline in memory and language over time; the parieto-occipital subtype declined fastest on executive/attention domain; the diffuse subtype in visuospatial functioning; and the mild subtype showed intermediate decline in all domains. Robust atrophy subtypes exist in Alzheimer's disease with distinct clinical and biological disease expression. Here we observe that these subtypes can already be detected in prodromal Alzheimer's disease, and that these may inform on expected trajectories of cognitive decline.
| S-EPMC6669409 | biostudies-literature
Project description:BACKGROUND:Metabolic syndrome, the development of which is associated with high-caloric Western diet (HCD) intake, represent a risk factor for mild cognitive impairment (MCI) and dementia including Alzheimer's disease (AD) later in life. This study aimed to investigate the effect of diet-induced metabolic disturbances on white matter neuroinflammation and cognitive function in a transgenic (TG) Fischer 344 rat carrying a human ?-amyloid precursor protein (APP) gene with Swedish and Indiana mutations (APP21 TG), a model of pre-AD and MCI. METHODS:TG and wildtype (WT) rats received either a HCD with 40% kJ from fat supplemented with 20% corn syrup drink or a standard diet for 12 weeks. Body weight, caloric intake, and blood pressure were measured repeatedly. End-point changes in glucose and lipid metabolism were also assessed. Open field task was used for assessment of activity; Morris water maze was used to assess spatial learning and memory. Cerebral white matter microglia and astrocytes, hippocampal neurons, and neuronal synapses were examined using immunohistochemistry. RESULTS:Rats maintained on the HCD developed significant obesity, visceral adiposity, dyslipidemia, and hyperinsulinemia, but did not become hypertensive. Impaired glucose tolerance was observed only in WT rats on the HCD. Total microglia number, activated OX-6+ microglia, as well as GFAP+ astrocytes located predominantly in the white matter were greater in the APP21 TG rat model in comparison to WT rats. HCD-driven metabolic perturbations further exacerbated white matter microgliosis and microglia cell activation in the APP21 TG rats and led to detectable changes in spatial reference memory in the comorbid prodromal AD and metabolic syndrome group compared to WT control rats. Neuronal density in the CA1 subregion of the hippocampus was not different between the experimental groups. Synaptic density in the CA1 and CA3 hippocampal subregions was lower in the TG rats compared to WT rats; however, there was no additional effect of the co-morbidity on this measure. CONCLUSIONS:These results suggest that white matter neuroinflammation might be one of the possible processes of early interaction of metabolic syndrome with MCI and pre-AD and could be one of the early brain pathologies contributing to cognitive deficits observed in mild cognitive impairment and dementia, including AD cases.
| S-EPMC6975033 | biostudies-literature