Exploring the Impact of The NEST Collaborative's Remote Social Intervention on Feelings of Depression and Isolation.

Early evidence of remote, volunteer-led social support interventions to reduce social isolation in older adults has been encouraging; however, evaluation data on outcomes related to social isolation associated from these interventions is scarce. Here, we share programmatic details of a novel, statewide initiative, called the NEST Collaborative, rolled out to meet immediate emotional, informational, and instrumental needs of older adults in Nevada during the COVID-19 pandemic. The evaluation included 31 older adults participating in weekly one-to-one empathy-based phone calls with multi-generational volunteers seeking to enhance participants' social networks through meaningful friendships. The calls were associated with programmatically meaningful, though not statistically significant, improvements in modified Hawthorne Friendship Scale and PHQ-2 Depression Scale scores over two waves of survey responses. These results suggest that social isolation and depression among older adults decreased among our sample over a period of increased isolation and mental health burden across the general population. With the potential for sustained impact in reducing social isolation over time, remote social support programs, such as the NEST Collaborative, may have persistent value long-term, beyond time-limited crisis response contexts.

Staging Alzheimer's Disease in the Brain and Retina of B6.APP/PS1 Mice by Transcriptional Profiling.

Alzheimer's disease (AD) is a common form of dementia characterized by amyloid plaque deposition, tau pathology, neuroinflammation, and neurodegeneration. Mouse models recapitulate some key features of AD. For instance, the B6.APP/PS1 model (carrying human transgenes for mutant forms of APP and PSEN1) shows plaque deposition and neuroinflammation involving both astrocytes and microglia beginning around 4-6 months of age. However, significant tau pathology and neurodegeneration are not apparent in this model even when assessed at old age. Therefore, this model is ideal for studying neuroinflammatory responses to amyloid deposition. Here, RNA sequencing of brain and retinal tissue, generalized linear modeling (GLM), functional annotation followed by validation by immunofluorescence was performed in B6.APP/PS1 mice to determine the earliest molecular changes prior to and around the onset of plaque deposition (2-6 months of age). Multiple pathways were shown to be activated in response to amyloid deposition including the JAK/STAT and NALFD pathways. Putative, cell-specific targets of STAT3, a central component of the JAK/STAT pathway, were identified that we propose provide more precise options for assessing the potential for targeting activation of the JAK/STAT pathway as a treatment for human AD. In the retina, GLM predicted activation of vascular-related pathways. However, many of the gene expression changes comparing B6 with B6.APP/PS1 retina samples occurred prior to plaque onset (2 months of age). This suggests retinal changes in B6.APP/PS1 mice may be an artefact of overexpression of mutant forms of APP and PSEN1 providing limited translatability to human AD. Therefore, caution should be taken when using this mouse model to assess the potential of using the eye as a window to the brain for AD.

Enhancing face validity of mouse models of Alzheimer's disease with natural genetic variation.

Classical laboratory strains show limited genetic diversity and do not harness natural genetic variation. Mouse models relevant to Alzheimer's disease (AD) have largely been developed using these classical laboratory strains, such as C57BL/6J (B6), and this has likely contributed to the failure of translation of findings from mice to the clinic. Therefore, here we test the potential for natural genetic variation to enhance the translatability of AD mouse models. Two widely used AD-relevant transgenes, APPswe and PS1de9 (APP/PS1), were backcrossed from B6 to three wild-derived strains CAST/EiJ, WSB/EiJ, PWK/PhJ, representative of three Mus musculus subspecies. These new AD strains were characterized using metabolic, functional, neuropathological and transcriptional assays. Strain-, sex- and genotype-specific differences were observed in cognitive ability, neurodegeneration, plaque load, cerebrovascular health and cerebral amyloid angiopathy. Analyses of brain transcriptional data showed strain was the greatest driver of variation. We identified significant variation in myeloid cell numbers in wild type mice of different strains as well as significant differences in plaque-associated myeloid responses in APP/PS1 mice between the strains. Collectively, these data support the use of wild-derived strains to better model the complexity of human AD.

A Bayesian Framework for Generalized Linear Mixed Modeling Identifies New Candidate Loci for Late-Onset Alzheimer's Disease.

Recent technical and methodological advances have greatly enhanced genome-wide association studies (GWAS). The advent of low-cost, whole-genome sequencing facilitates high-resolution variant identification, and the development of linear mixed models (LMM) allows improved identification of putatively causal variants. While essential for correcting false positive associations due to sample relatedness and population stratification, LMMs have commonly been restricted to quantitative variables. However, phenotypic traits in association studies are often categorical, coded as binary case-control or ordered variables describing disease stages. To address these issues, we have devised a method for genomic association studies that implements a generalized LMM (GLMM) in a Bayesian framework, called Bayes-GLMM Bayes-GLMM has four major features: (1) support of categorical, binary, and quantitative variables; (2) cohesive integration of previous GWAS results for related traits; (3) correction for sample relatedness by mixed modeling; and (4) model estimation by both Markov chain Monte Carlo sampling and maximal likelihood estimation. We applied Bayes-GLMM to the whole-genome sequencing cohort of the Alzheimer's Disease Sequencing Project. This study contains 570 individuals from 111 families, each with Alzheimer's disease diagnosed at one of four confidence levels. Using Bayes-GLMM we identified four variants in three loci significantly associated with Alzheimer's disease. Two variants, rs140233081 and rs149372995, lie between PRKAR1B and PDGFA The coded proteins are localized to the glial-vascular unit, and PDGFA transcript levels are associated with Alzheimer's disease-related neuropathology. In summary, this work provides implementation of a flexible, generalized mixed-model approach in a Bayesian framework for association studies.

Effects of natural enrichment materials on stress, memory and exploratory behavior in mice.

Environmental enrichment is an essential component of laboratory animal housing that allows animals to engage in natural behaviors in an otherwise artificial setting. Previous research by the authors suggested that, compared with synthetic enrichment materials, natural materials were associated with lower stress levels in mice. Here, the authors compare the effects of different enrichment materials on stress, memory and exploratory behavior in Swiss Webster mice. Mice that were provided with natural enrichment materials had lower stress levels, better memory and greater exploratory behavior than did mice provided with synthetic enrichment materials or with no enrichment materials. These findings suggest that provision of natural enrichment materials can improve well-being of laboratory mice.