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Alzheimer's Disease Biomarkers and Future Decline in Cognitive Normal Older Adults.

ABSTRACT: Identifying older adults at risk of cognitive decline represents a challenge as Alzheimer's disease (AD) modifying therapies move toward preclinical stages.To investigate the relationship between AD biomarkers and subsequent change in cognition in a cohort of cognitively intact older adults.84 cognitively normal subjects (mean age 72.0 years, 59% women) were recruited through the Massachusetts Alzheimer's Disease Research Center and the Harvard Aging Brain Study and followed over 3 years. Measurements of amyloid-? 1-42 (A?42), total Tau (t-Tau), and Tau phosphorylated at threonine 181 (p-Tau181) in the cerebrospinal fluid (CSF) at study entry were available in all cases. Baseline brain MRI, FDG-PET, and PiB-PET data were available in the majority of participants. Relationship between baseline AD biomarkers and longitudinal change in cognition was assessed using Cox proportional hazard regression and linear mixed models.14% participants increased their global Clinical Dementia Rating (CDR) score from 0 to 0.5 during follow-up. A CDR score increase was associated with higher baseline CSF t-Tau and p-Tau181, higher global cortical PiB retention, and lower hippocampal volume. The combination of high CSF t-Tau and low A?42 or low hippocampal volume was more strongly related to cognitive outcome than each single biomarker. Higher CSF t-Tau was the only biomarker associated with subsequent decline in MMSE score.Baseline CSF t-Tau and p-Tau181, in vivo amyloid load, and hippocampal volume were all independently associated with future decline in cognition. The discriminatory ability of these biomarkers to predict risk of cognitive decline, however, was only modest.

SUBMITTER: Dumurgier J

PROVIDER: S-EPMC5773095 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Alzheimer's Disease Biomarkers and Future Decline in Cognitive Normal Older Adults.

Dumurgier Julien J Hanseeuw Bernard J BJ Hatling Frances B FB Judge Kelly A KA Schultz Aaron P AP Chhatwal Jasmeer P JP Blacker Deborah D Sperling Reisa A RA Johnson Keith A KA Hyman Bradley T BT Gómez-Isla Teresa T

Journal of Alzheimer's disease : JAD 20170101 4

<h4>Background</h4>Identifying older adults at risk of cognitive decline represents a challenge as Alzheimer's disease (AD) modifying therapies move toward preclinical stages.<h4>Objective</h4>To investigate the relationship between AD biomarkers and subsequent change in cognition in a cohort of cognitively intact older adults.<h4>Methods</h4>84 cognitively normal subjects (mean age 72.0 years, 59% women) were recruited through the Massachusetts Alzheimer's Disease Research Center and the Harvar ...[more]

PMID: 29036824

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Project description:In this paper, we explore the utility of resting-state EEG measures as potential biomarkers for the detection and assessment of cognitive decline in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Neurophysiological biomarkers of AD derived from EEG and FDG-PET, once characterized and validated, would expand the set of existing diagnostic molecular biomarkers of AD pathology with associated biomarkers of disease progression and neural dysfunction. Since symptoms of AD often begin to appear later in life, successful identification of EEG-based biomarkers must account for age-related neurophysiological changes that occur even in healthy individuals. To this end, we collected EEG data from individuals with AD (n = 26), MCI (n = 53), and cognitively normal healthy controls stratified by age into three groups: 18-40 (n = 129), 40-60 (n = 62) and 60-90 (= 55) years old. For each participant, we computed power spectral density at each channel and spectral coherence between pairs of channels. Compared to age matched controls, in the AD group, we found increases in both spectral power and coherence at the slower frequencies (Delta, Theta). A smaller but significant increase in power of slow frequencies was observed for the MCI group, localized to temporal areas. These effects on slow frequency spectral power opposed that of normal aging observed by a decrease in the power of slow frequencies in our control groups. The AD group showed a significant decrease in the spectral power and coherence in the Alpha band consistent with the same effect in normal aging. However, the MCI group did not show any significant change in the Alpha band. Overall, Theta to Alpha ratio (TAR) provided the largest and most significant differences between the AD group and controls. However, differences in the MCI group remained small and localized. We proposed a novel method to quantify these small differences between Theta and Alpha bands' power using empirically derived distributions of spectral power across the time domain as opposed to averaging power across time. We defined Power Distribution Distance Measure (PDDM) as a distance measure between probability distribution functions (pdf) of Theta and Alpha power. Compared to average TAR, using PDDF enhanced the statistical significance, the effect size, and the spatial distribution of significant effects in the MCI group. We designed classifiers for differentiating individual MCI and AD participants from age-matched controls. The classification performance measured by the area under ROC curve after cross-validation were AUC = 0.85 and AUC = 0.6, for AD and MCI classifiers, respectively. Posterior probability of AD, TAR, and the proposed PDDM measure were all significantly correlated with MMSE score and neuropsychological tests in the AD group.

Dataset Information

Alzheimer's Disease Biomarkers and Future Decline in Cognitive Normal Older Adults.

Publications

Alzheimer's Disease Biomarkers and Future Decline in Cognitive Normal Older Adults.

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