For the Alzheimers Disease Neuroimaging Initiative (ADNI), Germany
University of Cologne Nuclear MedicineAuthor Of 1 Presentation
BIOMARKERS AND COGNITIVE PHENOTYPE IN ALZHEIMER’S DISEASE: MODELING THE CONTRIBUTION OF FRAILTY IN THE ALZHEIMER’S DISEASE NEUROIMAGING INITIATIVE
Abstract
Aims
Our goal was to investigate if classical biomarkers of Alzheimer’s disease (AD) neuropathology and their association with cognitive phenotype and dementia are affected by the individual’s frailty status.
Methods
We analyzed cross-sectional analysis data extracted from the Alzheimer’s Disease Neuroimaging Initiative 2 (ADNI2) study, including subjects with normal cognition level, mild cognitive impairment (MCI), and AD dementia. Frailty was quantified by the Frailty Index (FI), based on a 40-items health deficit accumulation model. We analyzed classical AD biomarkers and cognitive status, following participants stratification according to frailty level: CSF Abeta1-42, 181P-tau, and T-tau; MRI-based hippocampal volume; cortical glucose metabolism by FDG-PET; amyloid deposition by 18F-AV-45 PET. Logistic regression models, adjusted for age, sex, and education, allowed to explore the association of biomarkers with cognitive phenotype at two different FI levels. We assessed the diagnostic potential of deficits and biomarkers by Machine Learning.
Results
Subjects with higher FI scores had lower CSF Abeta1-42, lower glucose metabolism by FDG-PET, smaller hippocampus, and a higher amyloid deposition by 18F-AV-45 PET. No significant differences were observed among the frailty groups for ApoE genotype, CSF T-tau, and P-Tau. Increasing frailty levels were associated with a weaker relationship between AD and 18F-AV-45 uptake and hippocampus volume and with a stronger relationship of AD with FDG-PET.
Conclusions
Frailty partially explains discrepancies between AD neuropathology and clinical phenotype and affects the association of AD pathological modifications with cognitive status.
AD and dementia should be conceived as ageing trajectories, determined by a network of interacting pathophysiological processes.