Anxiety in late-life depression: Associations with brain volume, amyloid beta, white matter lesions, cognition, and functional ability.

OBJECTIVES: Late-life depression (LLD) is common and frequently co-occurs with neurodegenerative diseases of aging. Little is known about how heterogeneity within LLD relates to factors typically associated with neurodegeneration. Varying levels of anxiety are one source of heterogeneity in LLD. We examined associations between anxiety symptom severity and factors associated with neurodegeneration, including regional brain volumes, amyloid beta (Aß) deposition, white matter disease, cognitive dysfunction, and functional ability in LLD. PARTICIPANTS AND MEASUREMENTS: Older adults with major depression (N = 121, Ages 65-91) were evaluated for anxiety severity and the following: brain volume (orbitofrontal cortex [OFC], insula), cortical Aß standardized uptake value ratio (SUVR), white matter hyperintensity (WMH) volume, global cognition, and functional ability. Separate linear regression analyses adjusting for age, sex, and concurrent depression severity were conducted to examine associations between anxiety and each of these factors. A global regression analysis was then conducted to examine the relative associations of these variables with anxiety severity. RESULTS: Greater anxiety severity was associated with lower OFC volume (ß = -68.25, t = -2.18, p = .031) and greater cognitive dysfunction (ß = 0.23, t = 2.46, p = .016). Anxiety severity was not associated with insula volume, Aß SUVR, WMH, or functional ability. When examining the relative associations of cognitive functioning and OFC volume with anxiety in a global model, cognitive dysfunction (ß = 0.24, t = 2.62, p = .010), but not OFC volume, remained significantly associated with anxiety. CONCLUSIONS: Among multiple factors typically associated with neurodegeneration, cognitive dysfunction stands out as a key factor associated with anxiety severity in LLD which has implications for cognitive and psychiatric interventions.

Hoarding Symptoms in Late Life Depression are Associated With Greater Executive Dysfunction and Disability and Poorer Response to Depression Treatment.

OBJECTIVES: Late life depression (LLD) and hoarding disorder (HD) are common in older adults and characterized by executive dysfunction and disability. We aimed to determine the frequency of co-occurring HD in LLD and examine hoarding severity as an additional contributor to executive dysfunction, disability, and response to psychotherapy for LLD. DESIGN: Cross-sectional. SETTING: Outpatient psychiatry program. PARTICIPANTS: Eighty-three community-dwelling adults ages 65-90 with LLD. INTERVENTION: Problem-solving therapy. MEASUREMENTS: Measures of executive function, disability, depression, and hoarding severity were completed at post-treatment. Pearson's chi-squared tests evaluated group differences in rates of cognitive impairment, disability, and depression treatment response between participants with HD (LLD+HD) and LLD only. Separate linear regressions assessed associations between hoarding severity and executive function, disability, and psychotherapy response. Covariates included age, education, gender, and depression severity. RESULTS: 30.1% (25/83) of LLD participants met HD criteria. Relative to LLD, LLD+HD participants demonstrated greater impairment rates on measures of executive function (Letter-Number-Sequencing, X2(1)=4.0, p = 0.045; Stroop-Interference, X2(1) = 4.8, p = 0.028). Greater hoarding severity was associated with poorer executive functioning performance (Letter-Number-Sequencing (t[70] = -2.1, ß = -0.05, p = 0.044), Digit-Span (t[71] = -2.4, ß = -0.07, p = 0.019), Letter-Fluency (t[ 71] = -2.8, ß = -0.24, p = 0.006)). Rates of disability were significantly higher for LLD+HD (88.0%) than LLD (62.3%), (X2[1] = 5.41, p = 0.020) and higher hoarding severity was related to greater disability (t[72] = 2.97, ß = 0.13, p = 0.004). Depression treatment response rates were significantly lower for LLD+HD (24.0%) compared to LLD (48.3%), X2(1) = 4.26, p = 0.039, and HD status predicted psychotherapy response, t(67) = -2.15, ß = -15.6, p = 0.035. CONCLUSIONS: We found 30.1% co-occurrence of HD in LLD, which was accompanied by greater executive dysfunction, disability, and poorer response to depression treatment. Results underscore the need for increased screening of hoarding behaviors in LLD and tailored interventions for this LLD+HD group.

Olfactory Dysfunction and Depression Trajectories in Community-Dwelling Older Adults.

BACKGROUND: We examined the relationship between baseline olfactory performance and incident significant depressive symptoms and longitudinal depression trajectories in well-functioning older adults. Inflammation and cognitive status were examined as potential mediators. METHODS: Older adults (n = 2 125, 71-82 years, 51% female, 37% Black) completed an odor identification task at Year 3 (our study baseline) of the Health, Aging, and Body Composition study. Cognitive assessments, depressive symptoms, and inflammatory markers were ascertained across multiple visits over 8 years. Discrete-time complementary log-log models, group-based trajectory models, and multivariable-adjusted multinomial logistic regression were employed to assess the relationship between baseline olfaction and incident depression and longitudinal depression trajectories. Mediation analysis assessed the influence of cognitive status on these relationships. RESULTS: Individuals with lower olfaction had an increased risk of developing significant depressive symptoms at follow-up (hazard ratio = 1.04, 95% confidence interval [CI]: 1.00, 1.08). Of the 3 patterns of longitudinal depression scores identified (stable low, stable moderate, and stable high), poorer olfaction was associated with a 6% higher risk of membership in the stable moderate (relative risk ratio [RRR] = 1.06, 95% CI: 1.02, 1.10)/stable high (RRR = 1.06, 95% CI: 1.00, 1.12) groups, compared to the stable low group. Poor cognitive status, but not inflammation, partially mediated the relationship between olfactory performance and incident depression symptom severity. CONCLUSIONS: Suboptimal olfaction could serve as a prognostic indicator of vulnerability for the development of late-life depression. These findings underscore the need for a greater understanding of olfaction in late-life depression and the demographic, cognitive, and biological factors that influence these relationships over time.

Brain Health Registry Study Partner Portal: Novel infrastructure for digital, dyadic data collection.

BACKGROUND: In Alzheimer's disease (AD) research, subjective reports of cognitive and functional decline from participant-study partner dyads is an efficient method of assessing cognitive impairment and clinical progression. METHODS: Demographics and subjective cognitive/functional decline (Everyday Cognition Scale [ECog]) scores from dyads enrolled in the Brain Health Registry (BHR) Study Partner Portal were analyzed. Associations between dyad characteristics and both ECog scores and study engagement were investigated. RESULTS: A total of 10,494 BHR participants (mean age = 66.9 ± 12.16 standard deviations, 67.4% female) have enrolled study partners (mean age = 64.3 ± 14.3 standard deviations, 49.3% female), including 8987 dyads with a participant 55 years of age or older. Older and more educated study partners were more likely to complete tasks and return for follow-up. Twenty-five percent to 27% of older adult participants had self and study partner-report ECog scores indicating a possible cognitive impairment. DISCUSSION: The BHR Study Partner Portal is a unique digital tool for capturing dyadic data, with high impact applications in the clinical neuroscience and AD fields. Highlights The Brain Health Registry (BHR) Study Partner Portal is a novel, digital platform of >10,000 dyads. Collection of dyadic online subjective cognitive and functional data is feasible. The portal has good usability as evidenced by positive study partner feedback. The portal is a potential scalable strategy for cognitive impairment screening in older adults.

Evaluation of the Electronic Clinical Dementia Rating for Dementia Screening.

Importance: The Clinical Dementia Rating (CDR) is a well-validated instrument widely used to detect and stage dementia due to Alzheimer disease. The digital Electronic Clinical Dementia Rating (eCDR) can be remotely self-administered and automatically scored, with potential to facilitate efficient dementia screening and staging. Objective: To evaluate the association of the eCDR with the CDR and other in-clinic assessments for screening older adults for cognitive impairment. Design, Setting, and Participants: This multisite, cross-sectional study used baseline data from a longitudinal, observational study from 2020 to 2023, including up to 3 years of follow-up. Participants were enrolled from 3 Alzheimer Disease Research Centers and the Brain Health Registry. Participants (aged ≥55 years, with a study partner, and no acute or unstable major medical conditions) were recruited during in-clinic visits or by automated emails. Exposures: Participants completed the Uniform Data Set Version 3 (UDS; including the CDR) in supervised clinical research settings, and then completed the eCDR remotely, online and unsupervised, using their own device. Main Outcomes and Measures: The primary outcomes were eCDR scores (item; categorical box and global; continuous box and global), CDR scores (item; categorical box and global), and UDS assessment scores. Associations were evaluated using linear and logistic regressions. Results: A total of 3565 participants were contacted, and 288 were enrolled. Among 173 participants with item-level data (mean [SD] age, 70.84 [7.65] years; 76 women [43.9%]), eCDR to CDR concordance was 90% or higher for 33 items (63%) and 70% to 89% for 13 items (25%). Box (domain) level concordance ranged from 80% (memory) to 99% (personal care). The global score concordance rate was 81%. κ statistics were fair to moderate. Among 206 participants with box and global scores (mean [SD] age, 71.34 [7.68] years; 95 women [46.1%]), eCDR continuous global score was associated with CDR global (categorical) score with an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.70-0.87). Correlations between eCDR and in-clinic UDS assessments were similar to those between CDR sum of box scores and the same in-clinic assessments. Conclusions and Relevance: These findings suggest that the eCDR is valid and has potential use for screening and assessment of older adults for cognitive and functional decline related to Alzheimer disease. Instrument optimization and validation in diverse cohorts in remote settings are crucial for evaluating scalability and eCDR utility in clinical research, trials, and health care settings.

Brain health registry updates: An online longitudinal neuroscience platform.

INTRODUCTION: Remote, internet-based methods for recruitment, screening, and longitudinally assessing older adults have the potential to facilitate Alzheimer's disease (AD) clinical trials and observational studies. METHODS: The Brain Health Registry (BHR) is an online registry that includes longitudinal assessments including self- and study partner-report questionnaires and neuropsychological tests. New initiatives aim to increase inclusion and engagement of commonly underincluded communities using digital, community-engaged research strategies. New features include multilingual support and biofluid collection capabilities. RESULTS: BHR includes > 100,000 participants. BHR has made over 259,000 referrals resulting in 25,997 participants enrolled in 30 aging and AD studies. In addition, 28,278 participants are coenrolled in BHR and other studies with data linkage among studies. Data have been shared with 28 investigators. Recent efforts have facilitated the enrollment and engagement of underincluded ethnocultural communities. DISCUSSION: The major advantages of the BHR approach are scalability and accessibility. Challenges include compliance, retention, cohort diversity, and generalizability. HIGHLIGHTS: Brain Health Registry (BHR) is an online, longitudinal platform of > 100,000 members. BHR made > 259,000 referrals, which enrolled 25,997 participants in 32 studies. New efforts increased enrollment and engagement of underincluded communities in BHR. The major advantages of the BHR approach are scalability and accessibility. BHR provides a unique adjunct for clinical neuroscience research.

Item Response Analysis of the Financial Capacity Instrument-Short Form.

OBJECTIVE: The Financial Capacity Instrument-Short Form (FCI-SF) is a performance-based measure of everyday financial skills that takes 15 min to administer. Although the FCI-SF has demonstrated excellent psychometric properties, advanced psychometric methods such as item response theory (IRT) can provide important information on the performance of individual test items in measuring financial capacity and in distinguishing between healthy and cognitively impaired individuals. METHOD: Participants were 272 older adults diagnosed with mild cognitive impairment (MCI) and 1,344 cognitively healthy controls recruited from the Mayo Clinic Study of Aging at the Mayo Clinic in Rochester, Minnesota and also from the Cognitive Observations in Seniors study at the University of Alabama at Birmingham. Participants in each study were administered the FCI-SF, which evaluates coin/currency calculation, financial conceptual knowledge, use of a checkbook/register, and use of a bank statement. RESULTS: A unidimensional two-parameter logistic model best fit the 37 FCI-SF Test items, and most FCI-SF items fit the unidimensional two-parameter model well. The results indicated that all FCI-SF items robustly distinguished cognitively healthy controls from persons with MCI. CONCLUSIONS: The study results showed that the FCI-SF performed well under IRT analysis, further highlighted the psychometric properties of the FCI-SF as a valid and reliable measure of financial capacity, and demonstrated the clinical utility of the FCI-SF in distinguishing between cognitively normal and cognitively impaired individuals.

Association of Major Depressive Disorder with remotely administered measures of cognition and subjective report of cognitive difficulties across the adult age spectrum.

BACKGROUND: Major depressive disorder (MDD) has increasing prevalence with age. Both objective measures of cognitive dysfunction and subjective report of cognitive difficulties related to MDD are often thought to worsen with increasing age. However, few studies have directly evaluated these characteristics across the adult lifespan. METHODS: Participants included 23,594 adults completing objective and subjective measures of cognition on an online research registry. Linear regression including interactions of age group with depression was used to evaluate the association of self-reported MDD with measures of cognition in three age groups: 21-40 years; 41-60 years; 61+ years. RESULTS: MDD (n = 2127) demonstrated poorer objective cognitive performance and greater subjective ratings of cognitive difficulties across all domains assessed compared to non-depressed individuals (ND; n = 21,467). Significant interactions of age group and MDD status with objective and subjective measures of cognition were observed for both middle age and older adults when compared to young adults but few significant differences between middle-aged and older adults were evident. LIMITATIONS: This study relied on self-report of MDD diagnosis, utilized remotely administered and unsupervised measures of cognition, and the sample was not diverse. CONCLUSIONS: The magnitude of association between MDD and cognitive correlates appears to plateau in middle age. Our results suggest that increased rates of dementia are not due to greater cognitive consequence of MDD in older adults and that age effects, and not greater effects of depression, may lead to increased diagnosis of MDD based on subjective report of cognitive symptoms.

Digital culturally tailored marketing for enrolling Latino participants in a web-based registry: Baseline metrics from the Brain Health Registry.

INTRODUCTION: This culturally tailored enrollment effort aims to determine the feasibility of enrolling 5000 older Latino adults from California into the Brain Health Registries (BHR) over 2.25 years. METHODS: This paper describes (1) the development and deployment of culturally tailored BHR websites and digital ads, in collaboration with a Latino community science partnership board and a marketing company; (2) an interim feasibility analysis of the enrollment efforts and numbers, and participant characteristics (primary aim); as well as (3) an exploration of module completion and a preliminary efficacy evaluation of the culturally tailored digital efforts compared to BHR's standard non-culturally tailored efforts (secondary aim). RESULTS: In 12.5 months, 3603 older Latino adults were enrolled (71% of the total California Latino BHR initiative enrollment goal). Completion of all BHR modules was low (6%). DISCUSSION: Targeted ad placement, culturally tailored enrollment messaging, and culturally tailored BHR websites increased enrollment of Latino participants in BHR, but did not translate to increased module completion. HIGHLIGHTS: Culturally tailored social marketing and website improvements were implemented. The efforts enrolled 5662 Latino individuals in 12.5 months. The number of Latino Brain Health Registry (BHR) participants increased by 122.7%. We failed to adequately enroll female Latinos and Latinos with lower education. Future work will evaluate effects of a newly released Spanish-language BHR website.

Poor Sleep Quality and Daytime Fatigue Are Associated With Subjective but Not Objective Cognitive Functioning in Clinically Relevant Hoarding.

Background: Hoarding disorder is a chronic psychiatric condition of increasing public health concern. Recent investigation suggests a positive association between hoarding severity and insomnia symptoms. However, these findings have yet to be replicated, and the prevalence and type of sleep impairment experienced by individuals with clinically relevant hoarding symptoms (CHSs) are not known. Methods: This analysis of 20,473 members of the internet-based Brain Health Registry uses multivariate logistic regression modeling and structural equation modeling to evaluate the relationship between hoarding symptoms, sleep impairment, adverse health, and cognitive functioning. Results: More than 12% of study participants endorsed CHSs or subclinical hoarding symptoms. After adjustment for demographic characteristics and psychiatric comorbidity, individuals with CHSs reported increased odds of sleep impairment in nearly all domains. The odds of poor sleep quality (adjusted odds ratio, 2.07; 95% CI, 1.83-2.34), sleep disturbances (adjusted odds ratio, 2.15; 95% CI, 1.91-2.43), and daytime dysfunction (adjusted odds ratio, 5.84; 95% CI, 5.12-6.65) were two- to fivefold higher for individuals with CHSs compared with those without. For all measures, the proportion of individuals reporting sleep impairment increased with hoarding severity. In our structural equation model, sleep impairment acted as a partial mediator on the indirect pathways from hoarding to subjective cognitive complaints and poorer quality of life. Conclusions: Identification of sleep problems among those with hoarding symptoms is a critical component of hoarding assessment. Additional research is needed to better understand the mechanisms underlying the observed relationships, including neurobiological underpinnings, and to examine the role of sleep management in treatment for hoarding behaviors.

Hoarding symptoms are associated with higher rates of disability than other medical and psychiatric disorders across multiple domains of functioning.

BACKGROUND: Hoarding symptoms are associated with functional impairment, though investigation of disability among individuals with hoarding disorder has largely focused on clutter-related impairment to home management activities and difficulties using space because of clutter. This analysis assesses disability among individuals with hoarding symptoms in multiple domains of everyday functioning, including cognition, mobility, self-care, interpersonal and community-level interactions, and home management. The magnitude of the association between hoarding and disability was compared to that of medical and psychiatric disorders with documented high disability burden, including major depressive disorder (MDD), diabetes, and chronic pain. METHODS: Data were cross-sectionally collected from 16,312 adult participants enrolled in an internet-based research registry, the Brain Health Registry. Pearson's chi-square tests and multivariable logistic regression models were used to quantify the relationship between hoarding and functional ability relative to MDD, diabetes, and chronic pain. RESULTS: More than one in ten participants endorsed clinical (5.7%) or subclinical (5.7%) hoarding symptoms (CHS and SCHS, respectively). After adjusting for participant demographic characteristics and psychiatric and medical comorbidity, CHS and SCHS were associated with increased odds of impairment in all domains of functioning. Moderate to extreme impairment was endorsed more frequently by those with CHS or SCHS compared to those with self-reported MDD, diabetes, and/or chronic pain in nearly all domains (e.g., difficulty with day-to-day work or school: CHS: 18.7% vs. MDD: 11.8%, p < 0.0001) except mobility and self-care. While those with current depressive symptoms endorsed higher rates of impairment than those with hoarding symptoms, disability was most prevalent among those endorsing both hoarding and comorbid depressive symptoms. CONCLUSIONS: Hoarding symptoms are associated with profound disability in all domains of functioning. The burden of hoarding is comparable to that of other medical and psychiatric illnesses with known high rates of functional impairment. Future studies should examine the directionality and underlying causality of the observed associations, and possibly identify target interventions to minimize impairment associated with hoarding symptomatology.

Identifying psychiatric and neurological comorbidities associated with hoarding disorder through network analysis.

BACKGROUND: The relationships between hoarding disorder (HD) and other neurological and psychiatric disorders remain largely unknown. Although psychiatric burden in those with HD is high, less is known about neurological disorders. Furthermore, which disorders are primarily associated with HD vs which can be better explained via a relationship with another disorder has not been determined. To address these questions, we examined comorbidity patterns of psychiatric and neurological disorders in a large online registry of adults using network analyses. METHODS: We first examined psychiatric comorbidity among 252 participants completing clinician administered psychiatric assessments. Using the Brain Health Registry (BHR) (N = 15,978), we next analyzed prevalence of self-reported neurological and psychiatric disorders among participants with no/minimal hoarding, subclinical hoarding, and clinically significant hoarding and used network analyses to identify direct and indirect relationships between HD and the assessed psychiatric and neurological disorders. RESULTS: The most prevalent comorbidity in clinically assessed participants with HD was major depressive disorder (MDD, 62%), followed by generalized anxiety disorder (GAD, 32%). Network analyses in the BHR indicated that the strongest direct relationships with HD were attention-deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and obsessive-compulsive disorder (OCD). The relationships between HD and neurological disorders, including mild cognitive impairment, were weak or non-existent after controlling for other disorders. CONCLUSIONS: ADHD, MDD, and OCD form a triad of psychiatric disorders directly associated with HD. Despite their high comorbidity rates, the associations among anxiety disorders and HD were weak or indirect.

Cognitive outcomes are differentially associated with depression severity trajectories during psychotherapy treatment for late life major depressive disorder.

OBJECTIVES: Late Life Depression (LLD) is associated with persistent cognitive dysfunction even after depression symptoms improve. The present study was designed to examine cognitive outcomes associated with the pattern of depression severity change during psychotherapy intervention for LLD. METHODS: 96 community-dwelling adults ages 65-91 with major depressive disorder completed 12 sessions of Problem-Solving Therapy at the University of California, San Francisco. Nonlinear trajectories of depression severity ratings using the Hamilton Depression Rating Scale were computed from multiple time points collected throughout the weekly psychotherapy intervention. Performance on measures of cognition (information processing speed, executive functioning, verbal learning, memory) was assessed at baseline and post-treatment. Linear mixed-effects models examined associations between nonlinear depression severity trajectories and post-treatment change in cognitive performance. RESULTS: Broadly, different patterns of depression change during treatment were associated with improved cognition post-treatment. Greater and more consistent interval improvements in depression ratings were differentially associated with improvements in aspects of verbal learning, memory, and executive function post-treatment, while no associations were found with information processing speed. CONCLUSIONS: The heterogeneity of depression trajectories associated with improved cognitive outcomes suggests that the temporal pattern of depression response may impact specific cognitive processes distinctly. Results suggest that use of nonlinear depression severity trajectories may help to elucidate complex associations between the time course of depression response and cognitive outcomes of psychotherapy in LLD. These findings have important implications for identifying treatment targets to enhance clinical and cognitive outcomes of psychotherapy in LLD.

Self-reporting of psychiatric illness in an online patient registry is a good indicator of the existence of psychiatric illness.

Online registries offer many advantages for research, including the ability to efficiently assess large numbers of individuals and identify potential participants for clinical trials and genetic studies. Of particular interest is the validity and utility of self-endorsement of psychiatric disorders in online registries, which, while increasingly more common, remain understudied. We thus assessed the comparability of prevalence estimated from self-endorsement of psychiatric disorders in one such registry, the Brain Health Registry (BHR) to prevalence computed from large US-based epidemiological studies and the degree to which BHR participants report psychiatric disorders consistently. We also examined the concordance between self-report and clinically determined diagnoses of various DSM-5 psychiatric disorders in a subset of participants who underwent direct assessments and identified possible reasons for discordance. Rates of self-reported psychiatric disorders were closest to previously reported population prevalence rates when endorsed at multiple timepoints, and accuracy was at least 70% for all except Hoarding Disorder as compared to the clinical diagnoses. Clinical data suggested that self-endorsement of a given psychiatric diagnosis was indicative of the presence of a closely related condition, although not necessarily for the specific disorder, with the exception of major depressive disorder, panic disorder, and hoarding disorder, which had high positive predictive values (85%, 73%, 100%, respectively). We conclude that self-reporting of psychiatric conditions in an online setting is a fair indicator of psychopathology, but should be accompanied by more in-depth interviews if using data from a participant for a specific disorder.

Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression.

Importance: Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological mechanisms and support precision and individualized medicine. Objective: To cross-sectionally and longitudinally delineate disease-related heterogeneity in LLD associated with neuroanatomy, cognitive functioning, clinical symptoms, and genetic profiles. Design, Setting, and Participants: The Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) study is an international multicenter consortium investigating brain aging in pooled and harmonized data from 13 studies with more than 35 000 participants, including a subset of individuals with major depressive disorder. Multimodal data from a multicenter sample (N = 996), including neuroimaging, neurocognitive assessments, and genetics, were analyzed in this study. A semisupervised clustering method (heterogeneity through discriminative analysis) was applied to regional gray matter (GM) brain volumes to derive dimensional representations. Data were collected from July 2017 to July 2020 and analyzed from July 2020 to December 2021. Main Outcomes and Measures: Two dimensions were identified to delineate LLD-associated heterogeneity in voxelwise GM maps, white matter (WM) fractional anisotropy, neurocognitive functioning, clinical phenotype, and genetics. Results: A total of 501 participants with LLD (mean [SD] age, 67.39 [5.56] years; 332 women) and 495 healthy control individuals (mean [SD] age, 66.53 [5.16] years; 333 women) were included. Patients in dimension 1 demonstrated relatively preserved brain anatomy without WM disruptions relative to healthy control individuals. In contrast, patients in dimension 2 showed widespread brain atrophy and WM integrity disruptions, along with cognitive impairment and higher depression severity. Moreover, 1 de novo independent genetic variant (rs13120336; chromosome: 4, 186387714; minor allele, G) was significantly associated with dimension 1 (odds ratio, 2.35; SE, 0.15; P = 3.14 ×108) but not with dimension 2. The 2 dimensions demonstrated significant single-nucleotide variant-based heritability of 18% to 27% within the general population (N = 12 518 in UK Biobank). In a subset of individuals having longitudinal measurements, those in dimension 2 experienced a more rapid longitudinal change in GM and brain age (Cohen f2 = 0.03; P = .02) and were more likely to progress to Alzheimer disease (Cohen f2 = 0.03; P = .03) compared with those in dimension 1 (N = 1431 participants and 7224 scans from the Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], and Biomarkers for Older Controls at Risk for Dementia [BIOCARD] data sets). Conclusions and Relevance: This study characterized heterogeneity in LLD into 2 dimensions with distinct neuroanatomical, cognitive, clinical, and genetic profiles. This dimensional approach provides a potential mechanism for investigating the heterogeneity of LLD and the relevance of the latent dimensions to possible disease mechanisms, clinical outcomes, and responses to interventions.

Health-related quality of life in hoarding: A comparison to chronic conditions with high disease burden.

Hoarding disorder often results in debilitating functional impairment and may also compromise health-related quality of life (QoL). This study investigated the association between hoarding behavior and QoL relative to six highly impairing medical and psychiatric disorders in a sample of 20,722 participants enrolled in the internet-based Brain Health Registry. Nearly 1 in 8 participants (12.2%) endorsed clinically relevant hoarding symptoms (CHS). In separate multivariable linear regression models, hoarding was more strongly associated with mental QoL than diabetes (Standardizedß = -0.21, 95% CI: [-0.22, -0.20] vs. -0.01 [-0.02, 0.0]), heart disease (-0.22 [-0.23, -0.20] vs. 0.00 [-0.02, 0.01]), chronic pain (-0.18 [-0.19, -0.16] vs. -0.12 [-0.13, -0.10]), post-traumatic stress disorder (PTSD; -0.20 [-0.22, -0.19] vs. -0.07 [-0.09, -0.06]), and substance use disorder (SUD; -0.21 [-0.23, -0.20] vs. -0.04 [-0.05, -0.03]). Similarly, CHS was more strongly negatively associated with physical QoL than diabetes (-0.11 [-0.10, -0.12] vs. -0.08 [-0.06, -0.09]), major depressive disorder (-0.09 [-0.10, -0.08] vs. -0.05 [-0.06, 0.03]), PTSD (-0.11 [-0.12, -0.10] vs. -0.08 [-0.09, -0.07]), and SUD (-0.12 [-0.13, -0.09] vs. -0.01 [-0.02, 0.00]). Higher hoarding severity was associated with reductions in both mental (Standardizedß = -0.28, ΔR2 = 0.08, p < 0.0001) and physical (ß = -0.12, ΔR2 = 0.02, p < 0.0001) QoL, though the strength of the relationship between hoarding symptoms and QoL varied with depression severity. Efforts to improve the overall QoL and well-being of those with CHS are needed.

Remote blood collection from older adults in the Brain Health Registry for plasma biomarker and genetic analysis.

INTRODUCTION: Use of online registries to efficiently identify older adults with cognitive decline and Alzheimer's disease (AD) is an approach with growing evidence for feasibility and validity. Linked biomarker and registry data can facilitate AD clinical research. METHODS: We collected blood for plasma biomarker and genetic analysis from older adult Brain Health Registry (BHR) participants, evaluated feasibility, and estimated associations between demographic variables and study participation. RESULTS: Of 7150 participants invited to the study, 864 (12%) enrolled and 629 (73%) completed remote blood draws. Participants reported high study acceptability. Those from underrepresented ethnocultural and educational groups were less likely to participate. DISCUSSION: This study demonstrates the challenges of remote blood collection from a large representative sample of older adults. Remote blood collection from > 600 participants within a short timeframe demonstrates the feasibility of our approach, which can be expanded for efficient collection of plasma AD biomarker and genetic data.

Reliability and Validity of a Home-Based Self-Administered Computerized Test of Learning and Memory Using Speech Recognition.

INTRODUCTION: The objective of this study is to evaluate the reliability and validity of the ReVeReTM word list recall test (RWLRT), which uses speech recognition, when administered remotely and unsupervised. METHODS: Prospective cohort study. Participants included 249 cognitively intact community dwelling older adults. Measures included clinician administered neuropsychological assessments at baseline and unsupervised remotely administered tests of cognition from six time-points over six months. RESULTS: The RWLRT showed acceptable validity. Reliability coefficients varied across time points, with poor reliability between times 1 and 2 and fair-to-good reliability across the remaining five testing sessions. Practice effects were observed with repeated administration as expected. DISCUSSION: Unsupervised computerized tests of cognition, particularly word list learning and memory tests that use speech recognition, have significant potential for large scale early detection and long-term tracking of cognitive decline due to AD.

Association of Sleep and ß-Amyloid Pathology Among Older Cognitively Unimpaired Adults.

Importance: Disrupted sleep commonly occurs with progressing neurodegenerative disease. Large, well-characterized neuroimaging studies of cognitively unimpaired adults are warranted to clarify the magnitude and onset of the association between sleep and emerging ß-amyloid (Aß) pathology. Objective: To evaluate the associations between daytime and nighttime sleep duration with regional Aß pathology in older cognitively unimpaired adults. Design, Setting, and Participants: In this cross-sectional study, screening data were collected between April 1, 2014, and December 31, 2017, from healthy, cognitively unimpaired adults 65 to 85 years of age who underwent florbetapir F 18 positron emission tomography (PET), had APOE genotype information, scored between 25 and 30 on the Mini-Mental State Examination, and had a Clinical Dementia Rating of 0 for the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study. Data analysis was performed from December 1, 2019, to May 10, 2021. Exposures: Self-reported daytime and nighttime sleep duration. Main Outcomes and Measures: Regional Aß pathology, measured by florbetapir PET standardized uptake value ratio. Results: Amyloid PET and sleep duration information was acquired on 4425 cognitively unimpaired participants (mean [SD] age, 71.3 [4.7] years; 2628 [59.4%] female; 1509 [34.1%] tested Aß positive). Each additional hour of nighttime sleep was associated with a 0.005 reduction of global Aß standardized uptake value ratio (F1, 4419 = 5.0; P = .03), a 0.009 reduction of medial orbitofrontal Aß (F1, 4419 = 17.4; P < .001), and a 0.011 reduction of anterior cingulate Aß (F1, 4419 = 15.9; P < .001). When restricting analyses to participants who tested Aß negative, nighttime sleep was associated with a 0.006 reduction of medial orbitofrontal Aß (F1,2910 = 16.9; P < .001) and a 0.005 reduction of anterior cingulate Aß (F1,2910 = 7.6; P = .03). Daytime sleep was associated with a 0.013 increase of precuneus Aß (F1,2910 = 7.3; P = .03) and a 0.024 increase of posterior cingulate Aß (F1,2910 = 14.2; P = .001) in participants who tested Aß negative. Conclusions and Relevance: In this cross-sectional study, the increased risk of Aß deposition with reduced nighttime sleep duration occurred early, before cognitive impairment or significant Aß deposition. Daytime sleep may be associated with an increase in risk for early Aß accumulation and did not appear to be corrective for loss of nighttime sleep, demonstrating a circadian rhythm dependence of sleep in preventing Aß accumulation. Treatments that improve sleep may reduce early Aß accumulation and aid in delaying the onset of cognitive dysfunction associated with early Alzheimer disease.

Machine learning approaches to predicting amyloid status using data from an online research and recruitment registry: The Brain Health Registry.

INTRODUCTION: This study investigated the extent to which subjective and objective data from an online registry can be analyzed using machine learning methodologies to predict the current brain amyloid beta (Aß) status of registry participants. METHODS: We developed and optimized machine learning models using data from up to 664 registry participants. Models were assessed on their ability to predict Aß positivity using the results of positron emission tomography as ground truth. RESULTS: Study partner-assessed Everyday Cognition score was preferentially selected for inclusion in the models by a feature selection algorithm during optimization. DISCUSSION: Our results suggest that inclusion of study partner assessments would increase the ability of machine learning models to predict Aß positivity.