BACKGROUND: Early identification of deficits in our ability to perceive odors is important as many normal (i.e., aging) and pathological (i.e., sinusitis, viral, neurodegeneration) processes can result in diminished olfactory function. To realistically enable population-level measurements of olfaction, validated olfaction tests must be capable of being administered outside the research laboratory and clinical setting. AIM: The purpose of this study was to determine the feasibility of remotely testing olfactory performance using a test that was developed with funding from the National Institutes of Health as part of a ready-to-use, non-proprietary set of measurements useful for epidemiologic studies (NIH Toolbox Odor ID Test). MATERIALS AND METHODS: Eligible participants older than 39 years and active (within 6 months) in the Brain Health Registry (BHR), an online cognitive assessment platform which connects participants with researchers, were recruited for this study. Interested participants were mailed the NIH Toolbox Odor ID Test along with instructions on accessing a website to record their responses. Data obtained from subjects who performed the test at home was compared to the normative data collected when the NIH Toolbox Odor ID Test was administered by a tester in a research setting and validated against the Smell Identification Test. The age-range and composition of the population ensured we had the ability to observe both age-related decline and gender-related deficits in olfactory ability, as shown in the experimental setting. RESULTS: We observed that age-associated olfactory decline and gender-associated performance was comparable to performance on the administered test. Self-administration of this test showed the age-related loss in olfactory acuity, F(4, 1156)=14.564, p<.0001 as well as higher accuracy for women compared to men after controlling for participants age, F(1, 1160) = 22.953, p <.0001. The effect size calculated as Hedges g, was 0.41. CONCLUSION: These results indicate that the NIH Toolbox Odor ID Test is an appropriate instrument for self-administered assessment of olfactory performance. The ability to self-administer an inexpensive olfactory test increases its utility for inclusion in longitudinal epidemiological studies and when in-person testing is not feasible.

OBJECTIVES: Dementia assessment includes cognitive and behavioral testing with informant verification. Conventional testing is resource-intensive, with uneven access. Online unsupervised assessments could reduce barriers to risk assessment. The aim of this study was to assess the relationship between informant-rated behavioral changes and participant-completed neuropsychological test performance in older adults, both measured remotely via an online unsupervised platform, the Brain Health Registry (BHR). DESIGN: Observational cohort study. SETTING: Community-dwelling older adults participating in the online BHR. Informant reports were obtained using the BHR Study Partner Portal. PARTICIPANTS: The final sample included 499 participant-informant dyads. MEASUREMENTS: Participants completed online unsupervised neuropsychological assessment including Forward Memory Span, Reverse Memory Span, Trail Making B, and Go/No-Go tests. Informants completed the Mild Behavioral Impairment Checklist (MBI-C) via the BHR Study Partner portal. Cognitive performance was evaluated in MBI+/- individuals, as was the association between cognitive scores and MBI symptom severity. RESULTS: Mean age of the 499 participants was 67, of which 308/499 were females (61%). MBI + status was associated with significantly lower memory and executive function test scores, measured using Forward and Reverse Memory Span, Trail Making Errors and Trail Making Speed. Further, significant associations were found between poorer objectively measured cognitive performance, in the domains of memory and executive function, and MBI symptom severity. CONCLUSION: These findings support the feasibility of remote, informant-reported behavioral assessment utilizing the MBI-C, supporting its validity by demonstrating a relationship to online unsupervised neuropsychological test performance, using a previously validated platform capable of assessing early dementia risk markers.

Hoarding behaviors are positively associated with medical morbidity, however, current prevalence estimates and types of medical conditions associated with hoarding vary. This analysis aims to quantify the medical morbidity of hoarding disorder (HD). Cross-sectional data were collected online using the Brain Health Registry (BHR). Among 20,745 participants who completed the Hoarding and Clutter and Medical History thematic modules, 1348 had HD (6.5%), 1268 had subclinical HD (6.1%), and 18,829 did not meet hoarding criteria (87.4%). Individuals with HD were more likely to report a lifetime history of cardiovascular/metabolic conditions: diabetes (HD adjusted odds ratio (AOR):1.51, 95% confidence interval (CI):[1.20, 1.91]; subclinical HD AOR:1.24, 95% CI:[0.95, 1.61]), and hypercholesterolemia (HD AOR:1.24, 95% CI:[1.06, 1.46]; subclinical HD AOR:1.11, 95% CI:[0.94, 1.31]). Those with HD and subclinical HD were also more to report chronic pain (HD AOR: 1.69, 95% CI:[1.44, 1.98]; subclinical HD AOR: 1.44, 95% CI:[1.22, 1.69]), and sleep apnea (HD AOR: 1.58, 95% CI:[1.31, 1.89]; subclinical HD AOR:1.30, 95% CI:[1.07, 1.58]) than non-HD participants. For most conditions, likelihood of diagnosis did not differ between HD and subclinical HD. Structural equation modeling revealed that more severe hoarding symptomatology was independently associated with increased cardiovascular/metabolic vulnerability. The assessment and management of medical complications in individuals with HD is a fundamental component in improving quality of life, longevity, and overall physical health outcomes.

The aim of the study was to evaluate the value of assessing white matter integrity using diffusion tensor imaging (DTI) for classification of mild cognitive impairment (MCI) and prediction of cognitive impairments in comparison to brain atrophy measurements using structural MRI. Fifty-one patients with MCI and 66 cognitive normal controls (CN) underwent DTI and T1-weighted structural MRI. DTI measures included fractional anisotropy (FA) and radial diffusivity (DR) from 20 predetermined regions-of-interest (ROIs) in the commissural, limbic and association tracts, which are thought to be involved in Alzheimers disease; measures of regional gray matter (GM) volume included 21 ROIs in medial temporal lobe, parietal cortex, and subcortical regions. Significant group differences between MCI and CN were detected by each MRI modality: In particular, reduced FA was found in splenium, left isthmus cingulum and fornix; increased DR was found in splenium, left isthmus cingulum and bilateral uncinate fasciculi; reduced GM volume was found in bilateral hippocampi, left entorhinal cortex, right amygdala and bilateral thalamus; and thinner cortex was found in the left entorhinal cortex. Group classifications based on FA or DR was significant and better than classifications based on GM volume. Using either DR or FA together with GM volume improved classification accuracy. Furthermore, all three measures, FA, DR and GM volume were similarly accurate in predicting cognitive performance in MCI patients. Taken together, the results imply that DTI measures are as accurate as measures of GM volume in detecting brain alterations that are associated with cognitive impairment. Furthermore, a combination of DTI and structural MRI measurements improves classification accuracy.

Introduction

This study aimed to predict brain amyloid beta (Aβ) status in older adults using collected information from an online registry focused on cognitive aging.

Methods

Aβ positron emission tomography (PET) was obtained from multiple in-clinic studies. Using logistic regression, we predicted Aβ using self-report variables collected in the Brain Health Registry in 634 participants, as well as a subsample (N = 533) identified as either cognitively unimpaired (CU) or mild cognitive impairment (MCI). Cross-validated area under the curve (cAUC) evaluated the predictive performance.

Results

The best prediction model included age, sex, education, subjective memory concern, family history of Alzheimer's disease, Geriatric Depression Scale Short-Form, self-reported Everyday Cognition, and self-reported cognitive impairment. The cross-validated AUCs ranged from 0.62 to 0.66. This online model could help reduce between 15.2% and 23.7% of unnecessary Aβ PET scans in CU and MCI populations.

Disucssion

The findings suggest that a novel, online approach could aid in Aβ prediction.

Introduction

This study aimed to identify the relationship of sociodemographic variables with older adults participation in an online registry for recruitment and longitudinal assessment in cognitive aging.

Methods

Using Brain Health Registry (BHR) data, associations between sociodemographic variables (sex, race, ethnicity, education) and registry participation outcomes (task completion, willingness to participate in future studies, referral/enrollment in other studies) were examined in adults aged 55+ (N = 35,919) using logistic regression. All models included sex, race, ethnicity, education, age, and subjective memory concern.

Results

Non-white race, being Latino, and lower educational attainment were associated with decreased task completion and enrollment in additional studies. Results for sex were mixed.

Discussion

The findings provide novel information about engagement in online aging-related registries, and highlight a need to develop improved engagement strategies targeting underrepresented sociodemographic groups. Increasing registry diversity will allow researchers to refer more representative populations to Alzheimer's and related dementias prevention and treatment trials.

Introduction

Recruitment, assessment, and longitudinal monitoring of participants for neuroscience studies and clinical trials limit the development of new treatments. Widespread Internet use allows data capture from participants in an unsupervised setting. The Brain Health Registry, a website and online registry, collects data from participants and their study partners.

Methods

The Brain Health Registry obtains self and study partner report questionnaires and neuropsychological data, including the Cogstate Brief Battery, Lumos Labs Neurocognitive Performance Test, and MemTrax Memory Test. Participants provide informed consent before participation.

Results

Baseline and longitudinal data were obtained from nearly 57,000 and 28,000 participants, respectively. Over 18,800 participants were referred to, and nearly 1800 were enrolled in, clinical Alzheimer's disease and aging studies, including five observational studies and seven intervention trials.

Discussion

Online assessments of participants and study partners provide useful information at relatively low cost for neuroscience studies and clinical trials and may ultimately be used in routine clinical practice.

The Hoarding Rating Scale, Self Report (HRS-SR) is a 5-item assessment developed to ascertain the presence and severity of hoarding symptoms. This study aimed to evaluate the validity of an online adaptation of the HRS-SR in a remote, unsupervised internet sample of 23,214 members of the Brain Health Registry (BHR), an online research registry that evaluates and longitudinally monitors cognition, medical and psychiatric health status. Convergent validity was assessed among a sub-sample of 1,183 participants who completed additional, remote measures of self-reported hoarding behaviors. Structured clinical interviews conducted in-clinic and via video conferencing tools were conducted among 230 BHR participants; ROC curves were plotted to assess the diagnostic performance of the internet-based HRS-SR using best estimate hoarding disorder (HD) diagnoses as the gold standard. The area under the curve indicated near-perfect model accuracy, and was confirmed with 10-fold cross validation. Sensitivity and specificity for distinguishing clinically relevant hoarding were optimized using an HRS-SR total score cut-off of 5. Longitudinal analyses indicated stability of HRS-SR scores over time. Findings indicate that the internet-based HRS-SR is a useful and valid assessment of hoarding symptoms, though additional research using samples with more diverse hoarding behavior is needed to validate optimal cut-off values.

The aim of the study was to evaluate the value of assessing white matter integrity using diffusion tensor imaging (DTI) for classification of mild cognitive impairment (MCI) and prediction of cognitive impairments in comparison to brain atrophy measurements using structural MRI. Fifty-one patients with MCI and 66 cognitive normal controls (CN) underwent DTI and T1-weighted structural MRI. DTI measures included fractional anisotropy (FA) and radial diffusivity (DR) from 20 predetermined regions-of-interest (ROIs) in the commissural, limbic and association tracts, which are thought to be involved in Alzheimer's disease; measures of regional gray matter (GM) volume included 21 ROIs in medial temporal lobe, parietal cortex, and subcortical regions. Significant group differences between MCI and CN were detected by each MRI modality: In particular, reduced FA was found in splenium, left isthmus cingulum and fornix; increased DR was found in splenium, left isthmus cingulum and bilateral uncinate fasciculi; reduced GM volume was found in bilateral hippocampi, left entorhinal cortex, right amygdala and bilateral thalamus; and thinner cortex was found in the left entorhinal cortex. Group classifications based on FA or DR was significant and better than classifications based on GM volume. Using either DR or FA together with GM volume improved classification accuracy. Furthermore, all three measures, FA, DR and GM volume were similarly accurate in predicting cognitive performance in MCI patients. Taken together, the results imply that DTI measures are as accurate as measures of GM volume in detecting brain alterations that are associated with cognitive impairment. Furthermore, a combination of DTI and structural MRI measurements improves classification accuracy.

Introduction

This study aimed to understand whether older adults' longitudinal completion of assessments in an online Alzheimer's disease and related dementias (ADRD)-related registry is influenced by self-reported medical conditions.

Methods

Brain Health Registry (BHR) is an online cognitive aging and ADRD-related research registry that includes longitudinal health and cognitive assessments. Using logistic regressions, we examined associations between longitudinal registry completion outcomes and self-reported (1) number of medical conditions and (2) eight defined medical condition groups (cardiovascular, metabolic, immune system, ADRD, current psychiatric, substance use/abuse, acquired, other specified conditions) in adults aged 55+ (N = 23,888). Longitudinal registry completion outcomes were assessed by the completion of the BHR initial questionnaire (first questionnaire participants see at each visit) at least twice and completion of a cognitive assessment (Cogstate Brief Battery) at least twice. Models included ethnocultural identity, education, age, and subjective memory concern as covariates.

Results

We found that the likelihood of longitudinally completing the initial questionnaire was negatively associated with reporting a diagnosis of ADRD and current psychiatric conditions but was positively associated with reporting substance use/abuse and acquired medical conditions. The likelihood of longitudinally completing the cognitive assessment task was negatively associated with number of reported medical conditions, as well as with reporting cardiovascular conditions, ADRD, and current psychiatric conditions. Previously identified associations between ethnocultural identity and longitudinal assessment completion in BHR remained after accounting for the presence of medical conditions.

Discussion

This post hoc analysis provides novel, initial evidence that older adults' completion of longitudinal assessments in an online registry is associated with the number and types of participant-reported medical conditions. Our findings can inform future efforts to make online studies with longitudinal health and cognitive assessments more usable for older adults with medical conditions. The results need to be interpreted with caution due to selection biases, and the under-inclusion of minoritized communities.