AD is a public health epidemic, which seriously impacts cognition, mood and daily activities; however, one type of activity, exercise, has been shown to alter these states. Accordingly, we sought to investigate the relationship between exercise and mood, in early-stage AD patients (N=104) from California, over a 1-year period. Patients completed the Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and Blessed-Roth Dementia Rating Scale (BRDRS), while their caregivers completed the Yale Physical Activity Survey (YALE), Profile of Mood States (POMS), the Neuropsychiatric Inventory (NPI) and Functional Abilities Questionnaire (FAQ). Approximately half of the participants were female, from a variety of ethnic groups (Caucasian=69.8%; Latino/Hispanic Americans=20.1%). Our results demonstrated that the patients spent little time engaged in physical activity in general, their overall activity levels decreased over time, and this was paired with a change in global cognition (e.g., MMSE total score) and affect/mood (e.g., POMS score). Patients were parsed into Active and Sedentary groups based on their Yale profiles, with Active participants engaged in walking activities, weekly, over 1 year. Here, Sedentary patients had a significant decline in MMSE scores, while the Active patients had an attenuation in global cognitive decline. Importantly, among the Active AD patients, those individuals who engaged in walking for more than 2 h/week had a significant improvement in MMSE scores. Structured clinical trials which seek to increase the amount of time AD patients were engaged in walking activities and evaluate the nature and scope of beneficial effects in the brain are warranted.

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.