Basic Science and Pathogenesis.

Background: The glymphatic system has been suggested as an important clearance mechanism for amyloid-β (Aβ) during sleep. Animal and cellular models have suggested this clearance mechanism involves the water-channel protein, Aquaporin-4 (encoded by the AQP4 gene), located primarily in the astrocytic end-feet. We have previously reported on the interaction between genetic variants within AQP4, sleep and cross-sectional cortical amyloid-β (Aβ) burden.

Basic Science and Pathogenesis.

Background: Genome-wide association studies (GWAS) have identified numerous genetic variants associated with Alzheimer's disease (AD) risk, but genetic variation in the onset and progression of AD pathology is less understood. Accumulation of amyloid-β (Aβ) in the brain is a key pathological hallmark of AD beginning 10 - 20 years prior to cognitive symptoms. We investigated the genetic basis of variation in age at onset (AAO) of brain Aβ by comparing the performance of polygenic scores (PGSs) based on AD risk and resilience with a Aβ-AAO trait-specific PGS.

Clinical Manifestations.

Background: Cognitive dysfunction is central to clinicopathological models of Alzheimer's disease (AD). While AD prospective studies assess similar cognitive domains, the neuropsychological tests used vary between studies, limiting potential for aggregation. We examined a machine learning (ML) data harmonisation method for neuropsychological test data to develop a harmonised PACC score for the Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) consortium.

A Machine Learning Model to Harmonize Volumetric Brain MRI Data for Quantitative Neuroradiological Assessment of Alzheimer Disease.

Purpose To extend a previously developed machine learning algorithm for harmonizing brain volumetric data of individuals undergoing neuroradiological assessment of Alzheimer disease not encountered during model training. Materials and Methods Neuroharmony is a recently developed method that uses image quality metrics (IQM) as predictors to remove scanner-related effects in brain-volumetric data using random forest regression. To account for the interactions between Alzheimer disease pathology and IQM during harmonization, the authors developed a multiclass extension of Neuroharmony for individuals with and without cognitive impairment.

The interplay of age, gender and amyloid on brain and cognition in mid-life and older adults.

Deficits in memory are seen as a canonical sign of aging and a prodrome to dementia in older adults. However, our understanding of age-related cognition and brain morphology occurring throughout a broader spectrum of adulthood remains limited. We quantified the relationship between cognitive function and brain morphology (sulcal width, SW) using three cross-sectional observational datasets (PISA, AIBL, ADNI) from mid-life to older adulthood, assessing the influence of age, sex, amyloid (Aβ) and genetic risk for dementia.