Subjective Cognitive Decline in a Registry Sample: Relation to Psychiatric History, Loneliness, and Personality.

BACKGROUND: With the increasing focus on prevention of Alzheimer's disease, there is need for characterization of preclinical populations. Local participant registries offer an opportunity to facilitate research engagement via remote data collection, inform recruitment, and characterize preclinical samples, including individuals with subjective cognitive decline. OBJECTIVES: We sought to characterize subjective cognitive decline in a registry sample, as related to psychiatric history and related variables, including personality and loneliness, quality of life, and factors related to dementia risk (e.g., family history of dementia). DESIGN, SETTING, PARTICIPANTS: Participants were 366 individuals (mean age=67.2 (range 50-88), 65% female, 94% white, 97% non-Hispanic or Latino, 82% with at least a bachelor's degree) with no reported history of mild cognitive impairment or dementia. All participants had expressed interest in research, primarily via community outreach events and prior research involvement. Data was collected via electronic surveys, distributed using REDCap. Electronic questionnaires included questions on demographic variables, subjective cognitive decline, quality of life, loneliness, and personality. RESULTS: There was a high prevalence of risk factors for dementia in the registry sample (68% with family history of dementia, 31% with subjective cognitive decline). Subjective cognitive decline was more common in women and associated with history of depression, but not with family history of dementia. Subjective cognitive decline was also associated with lower conscientiousness and lower emotional stability, as well as higher loneliness and lower quality of life. Among participants who endorsed a psychiatric history, most reported onset more than 10 years prior, rather than within the last 10 years. CONCLUSIONS: Subjective cognitive decline in a registry sample may be more strongly associated with longstanding psychiatric and personality variables, rather than family history of dementia, adding to the literature on characterization of subjective cognitive decline across different settings. These findings highlight the acceptability of remote data collection and the potential of registries to inform recruitment by characterizing registrants, which may help to stratify dementia risk and match participants to eligible trials.

Brain connectomics predict response to treatment in social anxiety disorder.

We asked whether brain connectomics can predict response to treatment for a neuropsychiatric disorder better than conventional clinical measures. Pre-treatment resting-state brain functional connectivity and diffusion-weighted structural connectivity were measured in 38 patients with social anxiety disorder (SAD) to predict subsequent treatment response to cognitive behavioral therapy (CBT). We used a priori bilateral anatomical amygdala seed-driven resting connectivity and probabilistic tractography of the right inferior longitudinal fasciculus together with a data-driven multivoxel pattern analysis of whole-brain resting-state connectivity before treatment to predict improvement in social anxiety after CBT. Each connectomic measure improved the prediction of individuals' treatment outcomes significantly better than a clinical measure of initial severity, and combining the multimodal connectomics yielded a fivefold improvement in predicting treatment response. Generalization of the findings was supported by leave-one-out cross-validation. After dividing patients into better or worse responders, logistic regression of connectomic predictors and initial severity combined with leave-one-out cross-validation yielded a categorical prediction of clinical improvement with 81% accuracy, 84% sensitivity and 78% specificity. Connectomics of the human brain, measured by widely available imaging methods, may provide brain-based biomarkers (neuromarkers) supporting precision medicine that better guide patients with neuropsychiatric diseases to optimal available treatments, and thus translate basic neuroimaging into medical practice.

Experimental demonstration of coherence effects and linearity in microdensitometry.

Microdensitometer measurements of photographic film transmittance made at high spatial frequencies demonstrate that the basic instrument is nonlinear in that its response is a function of the spatial frequency and the mode of illumination. A method developed for measuring the spatial coherence, making use of a Wollaston prism shearing interferometer, has been applied to typical microdensitometers, documenting the existence of the partial coherence. The trace of a phase edge was found to be a graphical means of demonstrating one of the consequences of the partial coherence. Since partial coherence is present in all image-forming instruments, a linear instrument that avoids the imaging step and collects all the transmitted light has been developed. This linear instrument is limited in spatial frequency only by the size of the scanning spot. The system transfer function is the Fourier transform of the scanning spot irradiance. A linear microdensitometer was assembled on an optical bench using a cw laser source and standard microscope objectives, and it was used to trace a series of samples to test its response at high spatial frequencies. The linearity is demonstrated with both edge width measurements and flat response to a phase edge.