bioRxiv ScienceSearch

bioRxiv · 10.1101/2020.04.07.029553

Physical and mental health characteristics of adults with subjective cognitive decline: A study of 3,407 people aged 18-81 years from an MTurk-based U.S. national sample

Abstract

Subjective cognitive decline (SCD), or internal feelings of reduced mental capacity, is of increasing interest in the scientific, clinical, and lay community. Much of the extant literature is focused on SCD as a risk factor for Alzheimers disease in older adults, while less attention has been paid to non-cognitive health correlates of SCD across adulthood. Consequently, we investigated physical and mental health correlates of SCD in younger, middle-aged, and older adults. We recruited 3,407 U.S. residents through Amazons Mechanical Turk, an online labor market. Participants completed a 90-item self-report survey questionnaire assessing sociodemographic characteristics, physical health, sleep, depression, anxiety, loneliness, wisdom, self-efficacy, and happiness. Overall, 493/1930 (25.5%) of younger adults (18-49) and 278/1032 (26.9%) of older adults (50 or older) endorsed the SCD item. Multivariate analysis of variance and follow-up t-tests revealed worse physical and mental health characteristics in people endorsing SCD compared to those who did not, with effect sizes primarily in the medium to large range. Additionally, age did not moderate relationships between SCD and physical and mental health. Results suggest that SCD is associated with a diverse set of negative health characteristics such as poor sleep and high body mass index, and lower levels of positive factors including happiness and wisdom. Effect sizes of psychological correlates of SCD were as large as (or larger than) those of physical correlates, indicating that mental health and affective symptoms may be critical to consider when evaluating SCD. Overall, findings from this large, national U.S. sample suggest the presence of relationships between SCD and multiple psychological and perceived health factors; our results also show that SCD may be highly prevalent in both younger and older adults, suggesting that it be assessed across the adult lifespan.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Van Patten, R., Nguyen, T., Mahmood, Z., Lee, E., Daly, R., Palmer, B., Wu, T.-C., Tu, X., Jeste, D. V., Twamley, E.. 2020-04-07. Physical and mental health characteristics of adults with subjective cognitive decline: A study of 3,407 people aged 18-81 years from an MTurk-based U.S. national sample. https://doi.org/10.1101/2020.04.07.029553

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience