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Gain in brain immunity in the oldest-old differentiates cognitively normal from demented individuals.

ABSTRACT: BACKGROUND:Recent findings suggest that Alzheimer's disease (AD) neuropathological features (neuritic plaques and NFTs) are not strongly associated with dementia in extreme old (over 90 years of age) and compel a search for neurobiological indices of dementia in this rapidly growing segment of the elderly population. We sought to characterize transcriptional and protein profiles of dementia in the oldest-old. METHODS AND FINDINGS:Gene and protein expression changes relative to non-demented age-matched controls were assessed by two microarray platforms, qPCR and Western blot in different regions of the brains of oldest-old and younger old persons who died at mild or severe stages of dementia. Our results indicate that: i) consistent with recent neuropathological findings, gene expression changes associated with cognitive impairment in oldest-old persons are distinct from those in cognitively impaired youngest-old persons; ii) transcripts affected in young-old subjects with dementia participate in biological pathways related to synaptic function and neurotransmission while transcripts affected in oldest-old subjects with dementia are associated with immune/inflammatory function; iii) upregulation of immune response genes in cognitively intact oldest-old subjects and their subsequent downregulation in dementia suggests a potential protective role of the brain immune-associated system against dementia in the oldest-old; iv) consistent with gene expression profiles, protein expression of several selected genes associated with the inflammatory/immune system in inferior temporal cortex is significantly increased in cognitively intact oldest-old persons relative to cognitively intact young-old persons, but impaired in cognitively compromised oldest-old persons relative to cognitively intact oldest-old controls. CONCLUSIONS:These results suggest that disruption of the robust immune homeostasis that is characteristic of oldest-old individuals who avoided dementia may be directly associated with dementia in the oldest-old and contrast with the synaptic and neurotransmitter system failures that typify dementia in younger old persons.

SUBMITTER: Katsel P

PROVIDER: S-EPMC2764344 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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Gain in brain immunity in the oldest-old differentiates cognitively normal from demented individuals.

Katsel Pavel P Tan Weilun W Haroutunian Vahram V

PloS one 20091029 10

<h4>Background</h4>Recent findings suggest that Alzheimer's disease (AD) neuropathological features (neuritic plaques and NFTs) are not strongly associated with dementia in extreme old (over 90 years of age) and compel a search for neurobiological indices of dementia in this rapidly growing segment of the elderly population. We sought to characterize transcriptional and protein profiles of dementia in the oldest-old.<h4>Methods and findings</h4>Gene and protein expression changes relative to non ...[more]

PMID: 19865478

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Project description:PurposeConventional resting-state fMRI studies indicate that many cortical and subcortical regions have altered function in Alzheimer's disease (AD) but the nature of this alteration has remained unclear. Ultrafast fMRIs with sub-second acquisition times have the potential to improve signal contrast and enable advanced analyses to understand temporal interactions between brain regions as opposed to spatial interactions. In this work, we leverage such fast fMRI acquisitions from Alzheimer's disease Neuroimaging Initiative to understand temporal differences in the interactions between resting-state networks in 55 older adults with mild cognitive impairment (MCI) and 50 cognitively normal healthy controls.MethodsWe used a sliding window approach followed by k-means clustering. At each window, we computed connectivity i.e., correlations within and across the regions of the default mode, salience, dorsal attention, and frontoparietal network. Visual and somatosensory networks were excluded due to their lack of association with AD. Using the Davies-Bouldin index, we identified clusters of windows with distinct connectivity patterns, also referred to as brain states. The fMRI time courses were converted into time courses depicting brain state transition. From these state time course, we calculated the dwell time for each state i.e., how long a participant spent in each state. We determined how likely a participant transitioned between brain states. Both metrics were compared between MCI participants and controls using a false discovery rate correction of multiple comparisons at a threshold of. 0.05.ResultsWe identified 8 distinct brain states representing connectivity within and between the resting state networks. We identified three transitions that were different between controls and MCI, all involving transitions in connectivity between frontoparietal, dorsal attention, and default mode networks (p<0.04).ConclusionWe show that ultra-fast fMRI paired with dynamic functional connectivity analysis allows us to capture temporal transitions between brain states. Most changes were associated with transitions between the frontoparietal and dorsal attention networks connectivity and their interaction with the default mode network. Although future work needs to validate these findings, the brain networks identified in our work are known to interact with each other and play an important role in cognitive function and memory impairment in AD.

Project description:BackgroundTo systematically examine the clinical utility of tau-PET and Braak-staging as prognostic markers of future cognitive decline in older adults with and without cognitive impairment.MethodsIn this longitudinal study, we included 396 cognitively normal to dementia subjects with 18F-Florbetapir/18F-Florbetaben-amyloid-PET, 18F-Flortaucipir-tau-PET and ~ 2-year cognitive follow-up. Annual change rates in global cognition (i.e., MMSE, ADAS13) and episodic memory were calculated via linear-mixed models. We determined global amyloid-PET (Centiloid) plus global and Braak-stage-specific tau-PET SUVRs, which were stratified as positive(+)/negative(-) at pre-established cut-offs, classifying subjects as Braak0/BraakI+/BraakI-IV+/BraakI-VI+/Braakatypical+. In bootstrapped linear regression, we assessed the predictive accuracy of global tau-PET SUVRs vs. Centiloid on subsequent cognitive decline. To test for independent tau vs. amyloid effects, analyses were further controlled for the contrary PET-tracer. Using ANCOVAs, we tested whether more advanced Braak-stage predicted accelerated future cognitive decline. All models were controlled for age, sex, education, diagnosis, and baseline cognition. Lastly, we determined Braak-stage-specific conversion risk to mild cognitive impairment (MCI) or dementia.ResultsBaseline global tau-PET SUVRs explained more variance (partial R2) in future cognitive decline than Centiloid across all cognitive tests (Cohen's d ~ 2, all tests p < 0.001) and diagnostic groups. Associations between tau-PET and cognitive decline remained consistent when controlling for Centiloid, while associations between amyloid-PET and cognitive decline were non-significant when controlling for tau-PET. More advanced Braak-stage was associated with gradually worsening future cognitive decline, independent of Centiloid or diagnostic group (p < 0.001), and elevated conversion risk to MCI/dementia.ConclusionTau-PET and Braak-staging are highly predictive markers of future cognitive decline and may be promising single-modality estimates for prognostication of patient-specific progression risk in clinical settings.

Project description:ObjectivesEpidemiological evidence linking diet, one of the most important modifiable lifestyle factors, and risk of Alzheimer's disease (AD) is rapidly increasing. However, there is little or no evidence for a direct association between dietary nutrients and brain biomarkers of AD. This study identifies nutrient patterns associated with major brain AD biomarkers in a cohort of clinically and cognitively normal (NL) individuals at risk for AD.DesignCross-sectional study.SettingManhattan (broader area).ParticipantsFifty-two NL individuals (age 54+12 y, 70% women, Clinical Dementia Rating=0, MMSE>27, neuropsychological test performance within norms by age and education) with complete dietary information and cross-sectional, 3D T1-weighted Magnetic Resonance Imaging (MRI; gray matter volumes, GMV, a marker of brain atrophy), 11C-Pittsburgh compound-B (PiB; a marker of fibrillar amyloid-β, Aβ) and 18F-fluorodeoxyglucose (FDG; a marker of glucose metabolism, METglc) Positron Emission Tomography (PET) scans were examined.MeasurementsDietary intake of 35 nutrients associated with cognitive function and AD was assessed using the Harvard/Willet Food Frequency Questionnaire. Principal component analysis was used to generate nutrient patterns (NP) from the full nutrient panel. Statistical parametric mapping and voxel based morphometry were used to assess the associations of the identified NPs with AD biomarkers.ResultsNone of the participants were diabetics, smokers, or met criteria for obesity. Five NPs were identified: NP1 was characterized by most B-vitamins and several minerals [VitB and Minerals]; NP2 by monounsaturated and polyunsaturated fats, including ω-3 and ω-6 PUFA, and vitamin E [VitE and PUFA]; NP3 by vitamin A, vitamin C, carotenoids and dietary fibers [Anti-oxidants and Fibers]; NP4 by vitamin B12, vitamin D and zinc [VitB12 and D]; NP5 by saturated, trans-saturated fats, cholesterol and sodium [Fats]. Voxel-based analysis showed that NP4 scores [VitB12 and D] were positively associated with METglc and GMV, and negatively associated with PiB retention in AD-vulnerable regions (p<0.001). In addition, both METglc and GMV were positively associated with NP2 scores [VitE and PUFA], and negatively associated with NP5 scores [Fats] (p<0.001), and METglc was positively associated with higher NP3 scores [Anti-oxidants and Fibers] (p<0.001). Adjusting for age, gender, ethnicity, education, caloric intake, BMI, alcohol consumption, family history and Apolipoprotein E (APOE) status did not attenuate these relationships. The identified 'AD-protective' nutrient combination was associated with higher intake of fresh fruit and vegetables, whole grains, fish and low-fat dairies, and lower intake of sweets, fried potatoes, high-fat dairies, processed meat and butter.ConclusionSpecific dietary NPs are associated with brain biomarkers of AD in NL individuals, suggesting that dietary interventions may play a role in the prevention of AD by modulating AD-risk through its effects on Aβ and associated neuronal impairment.

Project description:BackgroundIndividuals on the preclinical Alzheimer's continuum, particularly those with both amyloid and tau positivity (A + T +), display a rapid cognitive decline and elevated disease progression risk. However, limited studies exist on brain atrophy trajectories within this continuum over extended periods.MethodsThis study involved 367 ADNI participants grouped based on combinations of amyloid and tau statuses determined through cerebrospinal fluid tests. Using longitudinal MRI scans, brain atrophy was determined according to the whole brain, lateral ventricle, and hippocampal volumes and cortical thickness in AD-signature regions. Cognitive performance was evaluated with the Preclinical Alzheimer's Cognitive Composite (PACC). A generalized linear mixed-effects model was used to examine group × time interactions for these measures. In addition, progression risks to mild cognitive impairment (MCI) or dementia were compared among the groups using Cox proportional hazards models.ResultsA total of 367 participants (48 A + T + , 86 A + T - , 63 A - T + , and 170 A - T - ; mean age 73.8 years, mean follow-up 5.1 years, and 47.4% men) were included. For the lateral ventricle and PACC score, the A + T - and A + T + groups demonstrated statistically significantly greater volume expansion and cognitive decline over time than the A - T - group (lateral ventricle: β = 0.757 cm3/year [95% confidence interval 0.463 to 1.050], P < .001 for A + T - , and β = 0.889 cm3/year [0.523 to 1.255], P < .001 for A + T + ; PACC: β = - 0.19 /year [- 0.36 to - 0.02], P = .029 for A + T - , and β = - 0.59 /year [- 0.80 to - 0.37], P < .001 for A + T +). Notably, the A + T + group exhibited additional brain atrophy including the whole brain (β = - 2.782 cm3/year [- 4.060 to - 1.504], P < .001), hippocampus (β = - 0.057 cm3/year [- 0.085 to - 0.029], P < .001), and AD-signature regions (β = - 0.02 mm/year [- 0.03 to - 0.01], P < .001). Cox proportional hazards models suggested an increased risk of progressing to MCI or dementia in the A + T + group versus the A - T - group (adjusted hazard ratio = 3.35 [1.76 to 6.39]).ConclusionsIn cognitively normal individuals, A + T + compounds brain atrophy and cognitive deterioration, amplifying the likelihood of disease progression. Therapeutic interventions targeting A + T + individuals could be pivotal in curbing brain atrophy, cognitive decline, and disease progression.

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Gain in brain immunity in the oldest-old differentiates cognitively normal from demented individuals.

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Gain in brain immunity in the oldest-old differentiates cognitively normal from demented individuals.

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