Cerebral Microbleeds in Different Brain Regions and Their Associations With the Digital Clock-Drawing Test: Secondary Analysis of the Framingham Heart Study.

BACKGROUND: Cerebral microbleeds (CMB) increase the risk for Alzheimer disease. Current neuroimaging methods that are used to detect CMB are costly and not always accessible. OBJECTIVE: This study aimed to explore whether the digital clock-drawing test (DCT) may provide a behavioral indicator of CMB. METHODS: In this study, we analyzed data from participants in the Framingham Heart Study offspring cohort who underwent both brain magnetic resonance imaging scans (Siemens 1.5T, Siemens Healthcare Private Limited; T2*-GRE weighted sequences) for CMB diagnosis and the DCT as a predictor. Additionally, paper-based clock-drawing tests were also collected during the DCT. Individuals with a history of dementia or stroke were excluded. Robust multivariable linear regression models were used to examine the association between DCT facet scores with CMB prevalence, adjusting for relevant covariates. Receiver operating characteristic (ROC) curve analyses were used to evaluate DCT facet scores as predictors of CMB prevalence. Sensitivity analyses were conducted by further including participants with stroke and dementia. RESULTS: The study sample consisted of 1020 (n=585, 57.35% female) individuals aged 45 years and older (mean 72, SD 7.9 years). Among them, 64 (6.27%) participants exhibited CMB, comprising 46 with lobar-only, 11 with deep-only, and 7 with mixed (lobar+deep) CMB. Individuals with CMB tended to be older and had a higher prevalence of mild cognitive impairment and higher white matter hyperintensities compared to those without CMB (P<.05). While CMB were not associated with the paper-based clock-drawing test, participants with CMB had a lower overall DCT score (CMB: mean 68, SD 23 vs non-CMB: mean 76, SD 20; P=.009) in the univariate comparison. In the robust multiple regression model adjusted for covariates, deep CMB were significantly associated with lower scores on the drawing efficiency (ß=-0.65, 95% CI -1.15 to -0.15; P=.01) and simple motor (ß=-0.86, 95% CI -1.43 to -0.30; P=.003) domains of the command DCT. In the ROC curve analysis, DCT facets discriminated between no CMB and the CMB subtypes. The area under the ROC curve was 0.76 (95% CI 0.69-0.83) for lobar CMB, 0.88 (95% CI 0.78-0.98) for deep CMB, and 0.98 (95% CI 0.96-1.00) for mixed CMB, where the area under the ROC curve value nearing 1 indicated an accurate model. CONCLUSIONS: The study indicates a significant association between CMB, especially deep and mixed types, and reduced performance in drawing efficiency and motor skills as assessed by the DCT. This highlights the potential of the DCT for early detection of CMB and their subtypes, providing a reliable alternative for cognitive assessment and making it a valuable tool for primary care screening before neuroimaging referral.

Associations of loneliness with risk of Alzheimer's disease dementia in the Framingham Heart Study.

INTRODUCTION: The relationship between persistent loneliness and Alzheimer's disease (AD) is unclear. We examined the relationship between different types of mid-life loneliness and the development of dementia and AD. METHODS: Loneliness was assessed in cognitively normal adults using one item from the Center for Epidemiologic Studies Depression Scale. We defined loneliness as no loneliness, transient loneliness, incident loneliness,or persistent loneliness, and applied Cox regression models and Kaplan-Meier plots with dementia and AD as outcomes (n = 2880). RESULTS: After adjusting for demographics, social network, physical health, and apolipoprotein E ε4, persistent loneliness was associated with higher (hazard ratio [HR], 1.91; 95% confidence interval [CI] 1.25-2.90; P < .01), and transient loneliness with lower (HR, 0.34; 95% CI 0.14-0.84; P < .05), risk of dementia onset, compared to no loneliness. Results were similar for AD risk. DISCUSSION: Persistent loneliness in mid-life is an independent risk factor for dementia and AD, whereas recovery from loneliness suggests resilience to dementia risk.

Different loneliness types, cognitive function, and brain structure in midlife: Findings from the Framingham Heart Study.

Background: It remains unclear whether persistent loneliness is related to brain structures that are associated with cognitive decline and development of Alzheimer's disease (AD). This study aimed to investigate the relationships between different loneliness types, cognitive functioning, and regional brain volumes. Methods: Loneliness was measured longitudinally, using the item from the Center for Epidemiologic Studies Depression Scale in the Framingham Heart Study, Generation 3, with participants' average age of 46·3 ± 8·6 years. Robust regression models tested the association between different loneliness types with longitudinal neuropsychological performance (n = 2,609) and regional magnetic resonance imaging brain data (n = 1,829) (2002-2019). Results were stratified for sex, depression, and Apolipoprotein E4 (ApoE4). Findings: Persistent loneliness, but not transient loneliness, was strongly associated with cognitive decline, especially memory and executive function. Persistent loneliness was negatively associated with temporal lobe volume (ß = -0.18, 95%CI [-0.32, -0.04], P = 0·01). Among women, persistent loneliness was associated with smaller frontal lobe (ß = -0.19, 95%CI [-0.38, -0.01], P = 0·04), temporal lobe (ß = -0.20, 95%CI [-0.37, -0.03], P = 0·02), and hippocampus volumes (ß = -0.23, 95%CI [-0.40, -0.06], P = 0·007), and larger lateral ventricle volume (ß = 0.15, 95%CI [0.02, 0.28], P = 0·03). The higher cumulative loneliness scores across three exams, the smaller parietal, temporal, and hippocampus volumes and larger lateral ventricle were evident, especially in the presence of ApoE4. Interpretation: Persistent loneliness in midlife was associated with atrophy in brain regions responsible for memory and executive dysfunction. Interventions to reduce the chronicity of loneliness may mitigate the risk of age-related cognitive decline and AD. Funding: US National Institute on Aging.

Impact of C-Reactive Protein on Cognition and Alzheimer Disease Biomarkers in Homozygous Apolipoprotein E ɛ4 Carriers.

OBJECTIVE: Previous research has shown that elevated blood C-reactive protein (CRP) is associated with increased Alzheimer's disease (AD) risk only in apoliprotein E4 genotype (APOE ε4) allele carriers. The objective of this study was to examine the interactive effects of plasma CRP and apoliprotein E (APOE) genotype on cognition and AD biomarkers. METHODS: Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study was analyzed, including APOE genotype; plasma CRP concentrations; diagnostic status (i.e., MCI and dementia due to AD); Mini-Mental State Exam (MMSE) and Clinical Dementia Rating (CDR) Dementia Staging Instrument; cerebral spinal fluid (CSF) concentrations of amyloid-ß peptide (Aß42), total tau (t-Tau) and phosphorylated tau (p-Tau); and amyloid (AV45) PET imaging. Multivariable regression analyses tested the associations between plasma CRP and APOE on cognitive and biomarker outcomes. RESULTS: Among 566 ADNI participants, 274 (48.4%) had no, 222 (39.2%) had one, and 70 (12.4%) had two APOE ε4 alleles. Only among participants who had two APOE ε4 alleles, elevated CRP was associated with lower MMSE at baseline [ß (95%CI): -0.52 ( -1.01, -0.12)] and 12-month follow-up [ß (95%CI): -1.09 (-1.88, -0.17)] after adjusting for sex, age and education. The interaction of two APOE ε4 alleles and elevated plasma CRP was associated with increased CSF levels of t-Tau (ß = +11.21, SE = 3.37, p < 0.001) and p-Tau (ß = +2.74, SE = 1.14, p < 0.01). Among those who had no APOE ε4 allele, elevated CRP was associated with decreased CSF t-Tau and p-Tau. These effects were stronger at 12-month follow-up. CONCLUSIONS: CRP released during peripheral inflammation could be a mediator in APOE ε4 related AD neurodegeneration and serve as a drug target for AD.

Rapid Cycle Evaluation and Adaptation of an Inpatient Tobacco Treatment Service at a U.S. Safety-Net Hospital.

Background: To address disparities in smoking rates, our safety-net hospital implemented an inpatient tobacco treatment intervention: an "opt-out" electronic health record (EHR)-based Best Practice Alert + order-set, which triggers consultation to a Tobacco Treatment Consult (TTC) service for all hospitalized patients who smoke cigarettes. We report on development, implementation, and adaptation of the intervention, informed by a pre-implementation needs assessment and two rapid-cycle evaluations guided by the Consolidated Framework for Implementation Research (CFIR) and Expert Recommendations for Implementing Change (ERIC) compilation. Methods: We identified stakeholders affected by implementation and conducted a local needs assessment starting 6 months-pre-launch. We then conducted two rapid-cycle evaluations during the first 6 months post-implementation. The CFIR informed survey and interview guide development, data collection, assessment of barriers and facilitators, and selection of ERIC strategies to implement and adapt the intervention. Results: Key themes were: (1) Understanding the hospital's priority to improving tobacco performance metrics was critical in gaining leadership buy-in (CFIR Domain: Outer setting; Construct: External Policy and Incentives). (2) CFIR-based rapid-cycle evaluations allowed us to recognize implementation challenges early and select ERIC strategies clustering into 3 broad categories (conducting needs assessment; developing stakeholder relationships; training and educating stakeholders) to make real-time adaptations, creating an acceptable clinical workflow. (3) Minimizing clinician burden allowed the successful implementation of the TTC service. (4) Demonstrating improved 6-month quit rates and tobacco performance metrics were key to sustaining the program. Conclusions: Rapid-cycle evaluations to gather pre-implementation and early-implementation data, focusing on modifiable barriers and facilitators, allowed us to develop and refine the intervention to improve acceptability, adoption, and sustainability, enabling us to improve tobacco performance metrics in a short timeline. Future directions include spreading rapid-cycle evaluations to promote implementation of inpatient tobacco treatment programs to other settings and assessing long-term sustainability and return on investment of these programs.