A major goal of animal research is to identify interventions that can promote successful aging and delay or reverse age-related cognitive decline in humans. Recent advances in standardizing cognitive assessment tools for humans have the potential to bring preclinical work closer to human research in aging and Alzheimer’s disease. The National Institute of Health (NIH) has led an initiative to develop a comprehensive Toolbox for Neurologic Behavioral Function (NIH Toolbox) to evaluate cognitive, motor, sensory and emotional function for use in epidemiologic and clinical studies spanning 3 to 85 years of age. This paper aims to analyze the strengths and limitations of animal behavioral tests that can be used to parallel those in the NIH Toolbox. We conclude that there are several paradigms available to define a preclinical battery that parallels the NIH Toolbox. We also suggest areas in which new tests may benefit the development of a comprehensive preclinical test battery for assessment of cognitive function in animal models of aging and Alzheimer’s disease.

Introduction

Leisure activities impact brain aging and may be prevention targets. We characterized how physical and cognitive activities relate to brain health for the first time in autosomal dominant frontotemporal lobar degeneration (FTLD).

Methods

A total of 105 mutation carriers (C9orf72/MAPT/GRN) and 69 non-carriers reported current physical and cognitive activities at baseline, and completed longitudinal neurobehavioral assessments and brain magnetic resonance imaging (MRI) scans.

Results

Greater physical and cognitive activities were each associated with an estimated >55% slower clinical decline per year among dominant gene carriers. There was also an interaction between leisure activities and frontotemporal atrophy on cognition in mutation carriers. High-activity carriers with frontotemporal atrophy (-1 standard deviation/year) demonstrated >two-fold better cognitive performances per year compared to their less active peers with comparable atrophy rates.

Discussion

Active lifestyles were associated with less functional decline and moderated brain-to-behavior relationships longitudinally. More active carriers "outperformed" brain volume, commensurate with a cognitive reserve hypothesis. Lifestyle may confer clinical resilience, even in autosomal dominant FTLD.

Introduction

Behavioral variant frontotemporal dementia (bvFTD) may present sporadically or due to an autosomal dominant mutation. Characterization of both forms will improve understanding of the generalizability of assessments and treatments.

Methods

A total of 135 sporadic (s-bvFTD; mean age 63.3 years; 34% female) and 99 familial (f-bvFTD; mean age 59.9; 48% female) bvFTD participants were identified. f-bvFTD cases included 43 with known or presumed chromosome 9 open reading frame 72 (C9orf72) gene expansions, 28 with known or presumed microtubule-associated protein tau (MAPT) mutations, 14 with known progranulin (GRN) mutations, and 14 with a strong family history of FTD but no identified mutation.

Results

Participants with f-bvFTD were younger and had earlier age at onset. s-bvFTD had higher total Neuropsychiatric Inventory Questionnaire (NPI-Q) scores due to more frequent endorsement of depression and irritability.

Discussion

f-bvFTD and s-bvFTD cases are clinically similar, suggesting the generalizability of novel biomarkers, therapies, and clinical tools developed in either form to the other.

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.

Introduction

There is conflicting evidence whether high-density lipoprotein cholesterol (HDL-C) is a risk factor for Alzheimer's disease (AD) and dementia. Genetic variation in the cholesteryl ester transfer protein (CETP) locus is associated with altered HDL-C. We aimed to assess AD risk by genetically predicted HDL-C.

Methods

Ten single nucleotide polymorphisms within the CETP locus predicting HDL-C were applied to the International Genomics of Alzheimer's Project (IGAP) exome chip stage 1 results in up 16,097 late onset AD cases and 18,077 cognitively normal elderly controls. We performed instrumental variables analysis using inverse variance weighting, weighted median, and MR-Egger.

Results

Based on 10 single nucleotide polymorphisms distinctly predicting HDL-C in the CETP locus, we found that HDL-C was not associated with risk of AD (P > .7).

Discussion

Our study does not support the role of HDL-C on risk of AD through HDL-C altered by CETP. This study does not rule out other mechanisms by which HDL-C affects risk of AD.