Florbetapir F 18 amyloid PET and 36-month cognitive decline: a prospective multicenter study.

This study was designed to evaluate whether subjects with amyloid beta (Aß) pathology, detected using florbetapir positron emission tomorgraphy (PET), demonstrated greater cognitive decline than subjects without Aß pathology. Sixty-nine cognitively normal (CN) controls, 52 with recently diagnosed mild cognitive impairment (MCI) and 31 with probable Alzheimer's disease (AD) dementia were included in the study. PET images obtained in these subjects were visually rated as positive (Aß+) or negative (Aß-), blind to diagnosis. Fourteen percent (10/69) of CN, 37% (19/52) of MCI and 68% (21/31) of AD were Aß+. The primary outcome was change in ADAS-Cog score in MCI subjects after 36 months; however, additional outcomes included change on measures of cognition, function and diagnostic status. Aß+ MCI subjects demonstrated greater worsening compared with Aß- subjects on the ADAS-Cog over 36 months (5.66 ± 1.47 vs -0.71 ± 1.09, P = 0.0014) as well as on the mini-mental state exam (MMSE), digit symbol substitution (DSS) test, and a verbal fluency test (P < 0.05). Similar to MCI subjects, Aß+ CN subjects showed greater decline on the ADAS-Cog, digit-symbol-substitution test and verbal fluency (P<0.05), whereas Aß+ AD patients showed greater declines in verbal fluency and the MMSE (P < 0.05). Aß+ subjects in all diagnostic groups also showed greater decline on the CDR-SB (P<0.04), a global clinical assessment. Aß+ subjects did not show significantly greater declines on the ADCS-ADL or Wechsler Memory Scale. Overall, these findings suggest that in CN, MCI and AD subjects, florbetapir PET Aß+ subjects show greater cognitive and global deterioration over a 3-year follow-up than Aß- subjects do.

Comparative mortality risks of antipsychotic medications in community-dwelling older adults.

BACKGROUND: All antipsychotic medications carry warnings of increased mortality for older adults, but little is known about comparative mortality risks between individual agents. AIMS: To estimate the comparative mortality risks of commonly prescribed antipsychotic agents in older people living in the community. METHOD: A retrospective, claims-based cohort study was conducted of people over 65 years old living in the community who had been newly prescribed risperidone, olanzapine, quetiapine, haloperidol, aripiprazole or ziprasidone (n = 136 393). Propensity score-adjusted Cox proportional hazards models assessed the 180-day mortality risk of each antipsychotic compared with risperidone. RESULTS: Risperidone, olanzapine and haloperidol showed a dose-response relation in mortality risk. After controlling for propensity score and dose, mortality risk was found to be increased for haloperidol (hazard ratio (HR) = 1.18, 95% CI 1.06-1.33) and decreased for quetiapine (HR = 0.81, 95% CI 0.73-0.89) and olanzapine (HR = 0.82, 95% CI 0.74-0.90). CONCLUSIONS: Significant variation in mortality risk across commonly prescribed antipsychotics suggests that antipsychotic selection and dosing may affect survival of older people living in the community.

Personalized Computational Causal Modeling of the Alzheimer Disease Biomarker Cascade.

BACKGROUND: Mathematical models of complex diseases, such as Alzheimer's disease, have the potential to play a significant role in personalized medicine. Specifically, models can be personalized by fitting parameters with individual data for the purpose of discovering primary underlying disease drivers, predicting natural history, and assessing the effects of theoretical interventions. Previous work in causal/mechanistic modeling of Alzheimer's Disease progression has modeled the disease at the cellular level and on a short time scale, such as minutes to hours. No previous studies have addressed mechanistic modeling on a personalized level using clinically validated biomarkers in individual subjects. OBJECTIVES: This study aimed to investigate the feasibility of personalizing a causal model of Alzheimer's Disease progression using longitudinal biomarker data. DESIGN/SETTING/PARTICIPANTS/MEASUREMENTS: We chose the Alzheimer Disease Biomarker Cascade model, a widely-referenced hypothetical model of Alzheimer's Disease based on the amyloid cascade hypothesis, which we had previously implemented mathematically as a mechanistic model. We used available longitudinal demographic and serial biomarker data in over 800 subjects across the cognitive spectrum from the Alzheimer's Disease Neuroimaging Initiative. The data included participants that were cognitively normal, had mild cognitive impairment, or were diagnosed with dementia (probable Alzheimer's Disease). The model consisted of a sparse system of differential equations involving four measurable biomarkers based on cerebrospinal fluid proteins, imaging, and cognitive testing data. RESULTS: Personalization of the Alzheimer Disease Biomarker Cascade model with individual serial biomarker data yielded fourteen personalized parameters in each subject reflecting physiologically meaningful characteristics. These included growth rates, latency values, and carrying capacities of the various biomarkers, most of which demonstrated significant differences across clinical diagnostic groups. The model fits to training data across the entire cohort had a root mean squared error (RMSE) of 0.09 (SD 0.081) on a variable scale between zero and one, and were robust, with over 90% of subjects showing an RMSE of < 0.2. Similarly, in a subset of subjects with data on all four biomarkers in at least one test set, performance was high on the test sets, with a mean RMSE of 0.15 (SD 0.117), with 80% of subjects demonstrating an RMSE < 0.2 in the estimation of future biomarker points. Cluster analysis of parameters revealed two distinct endophenotypic groups, with distinct biomarker profiles and disease trajectories. CONCLUSION: Results support the feasibility of personalizing mechanistic models based on individual biomarker trajectories and suggest that this approach may be useful for reclassifying subjects on the Alzheimer's clinical spectrum. This computational modeling approach is not limited to the Alzheimer Disease Biomarker Cascade hypothesis, and can be applied to any mechanistic hypothesis of disease progression in the Alzheimer's field that can be monitored with biomarkers. Thus, it offers a computational platform to compare and validate various disease hypotheses, personalize individual biomarker trajectories and predict individual response to theoretical prevention and therapeutic intervention strategies.

Computerized Cognitive Training in Mild Cognitive Impairment: Findings in African Americans and Caucasians.

BACKGROUND: African Americans with MCI may be at increased risk for dementia compared to Caucasians. The effect of race on the efficacy of cognitive training in MCI is unclear. METHODS: We used data from a two-site, 78-week randomized trial of MCI comparing intensive, home-based, computerized training with Web-based cognitive games or Web-based crossword puzzles to examine the effect of race on outcomes. The study outcomes were changes from baseline in cognitive and functional scales as well as MRI-measured changes in hippocampal volume and cortical thickness. Analyses used linear models adjusted for baseline scores. This was an exploratory study. RESULTS: A total of 105 subjects were included comprising 81 whites (77.1%) and 24 African Americans (22.8%). The effect of race on the change from baseline in ADAS-Cog-11 was not significant. The effect of race on change from baseline to week 78 in the Functional Activities Questionnaire (FAQ) was significant with African American participants' FAQ scores showing greater improvements at weeks 52 and 78 (P = 0.009, P = 0.0002, respectively) than white subjects. Within the CCT cohort, FAQ scores for African American participants showed greater improvement between baseline and week 78, compared to white participants randomized to CCT (P = 0.006). There was no effect of race on the UPSA. There was no effect of race on hippocampal or cortical thickness outcomes. CONCLUSIONS: Our preliminary findings suggest that web-based cognitive training programs may benefit African Americans with MCI at least as much as Caucasians, and highlight the need to further study underrepresented minorities in AD prevention trials. (Supported by the National Institutes of Health, National Institute on Aging; ClinicalTrials.gov number, NCT03205709.).

Expectancy Does Not Predict 18-month Treatment Outcomes with Cognitive Training in Mild Cognitive Impairment.

BACKGROUND: Computerized cognitive training (CCT) has emerged as a potential treatment option for mild cognitive impairment (MCI). It remains unclear whether CCT's effect is driven in part by expectancy of improvement. OBJECTIVES: This study aimed to determine factors associated with therapeutic expectancy and the influence of therapeutic expectancy on treatment effects in a randomized clinical trial of CCT versus crossword puzzle training (CPT) for older adults with MCI. DESIGN: Randomized clinical trial of CCT vs CPT with 78-week follow-up. SETTING: Two-site study - New York State Psychiatric Institute and Duke University Medical Center. PARTICIPANTS: 107 patients with MCI. INTERVENTION: 12 weeks of intensive training with CCT or CPT with follow-up booster training over 78 weeks. MEASUREMENTS: Patients rated their expectancies for CCT and CPT prior to randomization. RESULTS: Patients reported greater expectancy for CCT than CPT. Lower patient expectancy was associated with lower global cognition at baseline and older age. Expectancy did not differ by sex or race. There was no association between expectancy and measures of everyday functioning, hippocampus volume, or apolipoprotein E genotype. Expectancy was not associated with change in measures of global cognition, everyday functioning, and hippocampus volume from baseline to week 78, nor did expectancy interact with treatment condition. CONCLUSIONS: While greater cognitive impairment and increased age was associated with low expectancy of improvement, expectancy was not associated with the likelihood of response to treatment with CPT or CCT.

ElliQ, an AI-Driven Social Robot to Alleviate Loneliness: Progress and Lessons Learned.

Background: Loneliness is a significant issue in older adults and can increase the risk of morbidity and mortality. Objective: To present the development of ElliQ, a proactive, AI-driven social robot with multiple social and health coaching functions specifically designed to address loneliness and support older people. Development/Implementation: ElliQ, a consumer robot with a friendly appearance, uses voice, sounds, light, and buttons through a touch screen to facilitate conversation, music, video calls, well-being assessments, stress reduction, cognitive games, and health reminders. The robot was deployed by 15 government agencies in the USA. Initial experience suggests it is not only highly engaging for older people but may be able to improve their quality of life and reduce loneliness. In addition, the development of a weekly report that patients can share with their clinicians to allow better integration into routine care is described. Conclusion: This paper describes the development and real-world implementation of this product innovation and discusses challenges encountered and future directions.

Blueberry Supplementation Effects on Neuronal and Pathological Biomarkers in Subjects at Risk for Alzheimer's Disease: A Pilot Study.

Background: There is a need to develop non-invasive practical lifestyle interventions for preventing Alzheimer's disease (AD) in people at risk, such as those with mild cognitive impairment (MCI). Blueberry consumption has been associated with reduced risk of dementia in some epidemiologic studies and with improvements in cognition in healthy aging adults. Blood-based biomarkers have emerged at the forefront of AD therapeutics research spurred by the development of reliable ultra-sensitive "single-molecule array" assays with 100-1000-fold greater sensitivity over traditional platforms. Objective: The purpose of this study was to examine the effect of blueberry supplementation in MCI on six blood biomarkers: amyloid-beta 40 (Aß40), amyloid-beta 42 (Aß42), phosphorylated Tau181 (ptau181), neurofilament light (NfL), Glial Fibrillary acidic protein (GFAP), and Brain-Derived Neurotrophic Factor (BDNF). Methods: This was a 12-week, open-label, pilot trial of 10 participants with MCI (mean age 80.2 years + 5.16). Subjects consumed 36 grams per day of lyophilized blueberry powder in a split dose consumed with breakfast and dinner. Baseline and endpoint venous blood was analyzed using an ultrasensitive SIMOA assay. Our aim was to test if blueberry supplementation would particularly impact p-tau181, NfL, and GFAP elevations associated with the neurodegenerative process. Results: There were no statistically significant (p < 0.05) changes from baseline to endpoint for any of the biomarker values or in the ratios of Aß42 / Aß40 and ptau181/ Aß42. Adverse effects were mild and transient; supplementation was relatively well tolerated with all subjects completing the study. Conclusion: To our knowledge, this is the first study to prospectively examine the effects of blueberry supplementation on a panel of blood biomarkers reflecting the neurodegenerative process. Our findings raise two possibilities - a potential stabilization of the neurodegenerative process or a lack of a direct and acute effect on beta-amyloid/tau/glial markers. A larger controlled study is warranted.

Erratum to: Blueberry Supplementation Effects on Neuronal and Pathological Biomarkers in Subjects at Risk for Alzheimer's Disease: A Pilot Study.

[This corrects the article DOI: 10.14283/jarlife.2023.13.].

Reproductive Markers in Alzheimer's Disease Progression: The Framingham Heart Study.

BACKGROUND: Reproductive status, such as the age of menarche or menopause, may be linked to cognitive abilities and risk for incident Alzheimer's disease (AD) but the evidence is conflicting. It is also not fully known if these factors interact with cortical beta-amyloid deposition. OBJECTIVES: To study the relationship between reproductive risks, sex hormone markers and risk for decline in specific cognitive domains in women. DESIGN, SETTING AND PARTICIPANTS: We analyzed the association of reproductive markers (age at menarche, number of births, age at menopause, sex hormone-binding globulin, estradiol, estrone, total testosterone, free testosterone) with incident AD and annualized cognitive decline in the community-based longitudinal Framingham Heart Study (FHS) Offspring women 60 years and older (n=772, mean age 68 years, mean follow-up 10.7 ± 3 years). We used the Cox proportional hazards regression model and linear regression model, adjusting for covariates. OUTCOME MEASURES: Incident AD dementia as well as the annualized change in memory, language, attention and executive functions. RESULTS: Older age at menopause was associated with a lower risk of incident AD dementia (p = 0.047, 6% lower risk per older year) after adjusting for baseline age, education, hormone therapy status, and MMSE score. Older age at menopause was significantly associated with a slower annualized decline in memory (beta = 0.085, p = 0.00059). The lower level of plasma Aß42 was also associated with a higher risk of incident AD (HR = 0.97, 95% CI = 0.95, 0.99; p = 0.0039) but there was no significant interaction effect with age at menarche, age at menopause or plasma sex hormone levels. CONCLUSION: Younger age at menopause is a risk factor for late-life memory decline and incident AD. This risk appears to be independent of Aß42 pathology. Further studies to understand the biological and social mechanisms underlying the differential effects of reproductive risks are warranted.

Early Detection of Mild Cognitive Impairment (MCI) in an At-Home Setting.

Emerging digital tools have the potential to enable a new generation of qualitative and quantitative assessment of cognitive performance. Moreover, the ubiquity of consumer electronics, such as smartphones and tablets, can be harnessed to support large-scale self-assessed cognitive screening with benefit to healthcare systems and consumers. A wide variety of apps, wearables, and new digital technologies are either available or in development for the detection of mild cognitive impairment (MCI), a risk factor for dementia. Two categories of novel methodologies may be considered: passive technologies (which monitor a user's behavior without active user input) and interactive assessments (which require active user input). Such examinations can be self-administered, supervised by a caregiver, or conducted by an informant at home or outside of a clinical setting. These direct-to-consumer tools have the potential to sidestep barriers associated with cognitive evaluation in primary care, thus improving access to cognitive assessments. Although direct-to-consumer cognitive assessment is associated with its own barriers, including test validation, user experience, and technological concerns, it is conceivable that these issues can be addressed so that a large-scale, self-assessed cognitive evaluation that would represent an initial cognitive screen may be feasible in the future.

Rationale for Early Diagnosis of Mild Cognitive Impairment (MCI) Supported by Emerging Digital Technologies.

Disease-modifying pharmacotherapies for Alzheimer's Disease (AD) are currently in late-stage clinical development; once approved, new healthcare infrastructures and services, including primary healthcare, will be necessary to accommodate a huge demand for early and large-scale detection of AD. The increasing global accessibility of digital consumer electronics has opened up new prospects for early diagnosis and management of mild cognitive impairment (MCI) with particular regard to AD. This new wave of innovation has spurred research in both academia and industry, aimed at developing and validating a new "digital generation" of tools for the assessment of the cognitive performance. In light of this paradigm shift, an international working group (the Global Advisory Group on Future MCI Care Pathways) convened to elaborate on how digital tools may be optimally integrated in screening-diagnostic pathways of AD The working group developed consensus perspectives on new algorithms for large-scale screening, detection, and diagnosis of individuals with MCI within primary medical care delivery. In addition, the expert panel addressed operational aspects concerning the implementation of unsupervised at-home testing of cognitive performance. The ultimate intent of the working group's consensus perspectives is to provide guidance to developers of cognitive tests and tools to facilitate the transition toward globally accessible cognitive screening aimed at the early detection, diagnosis, and management of MCI due to AD.

Hippocampal atrophy confounds template-based functional MR imaging measures of hippocampal activation in patients with mild cognitive impairment.

BACKGROUND AND PURPOSE: Functional MR imaging has been used to study patterns of hippocampal activation that distinguish pathologic from normal memory loss in the elderly population. Our objective was to assess whether hippocampal atrophy confounds measurements of hippocampal activation in subjects with mild cognitive impairment (MCI). METHODS: Twenty subjects with MCI and 20 elderly control subjects with objectively normal memory were studied at 4T during a face-name paradigm designed to activate the hippocampus. Hippocampal activation was measured using 2 separate approaches: applying a preset region of interest (ROI) in standardized template space and applying a manually drawn ROI in native subject space. Pearson correlation coefficients were calculated to compare group-dependent relationships between hippocampal volume and activation. Analysis of covariance (ANCOVA) was performed to assess group differences in hippocampal activation during encoding and retrieval. Age and hippocampal volume were included as covariates, as was a term for the interaction between hippocampal volume and group. RESULTS: When hippocampal activation was measured by the template-based method, the correlation coefficient in the right hippocampus of subjects with MCI but not control subjects during retrieval differed significantly from zero. There was a significant (P < .05) group-by-volume interaction in the ANCOVA model. No significant correlations or interactions were demonstrated when activation was measured in native subject space with manually drawn ROIs. CONCLUSION: Our findings suggest a potential confounding relationship between hippocampal volume and activation for subjects with MCI in template-based analyses. Template-based measures of hippocampal activation that do not adequately account for hippocampal atrophy should be used with caution in patients with MCI.

Magnetic resonance imaging of the caudate nuclei in depression. Preliminary observations.

A role of the caudate nucleus in depression has been suggested from relevant clinical conditions, such as patients with Huntington's disease or caudate infarcts, as well as animal studies. Correlations of caudate nucleus disease with depressive symptoms have been limited to autopsy studies and cases of gross pathological disorder, such as large infarcts. We used serial axial high-field magnetic resonance images and an unbiased stereological technique to estimate the volumes of the caudate nuclei in 50 patients who met DSM-III criteria for major depression (23 men, 48.3 +/- 17 years old) in comparison with 50 age- and gender-matched normal controls free of major neurological and psychiatric disorders. Depressed patients had smaller caudate nucleus volumes (5.2 +/- 1.6 cm3) compared with controls (6.2 +/- 1.7 cm3). Right and left caudate nucleus volumes were smaller in depressed patients compared with controls. Age was negatively correlated with caudate nucleus volumes in depressed patients as well as in controls. Caudate nucleus volumes in depressed patients were inversely correlated with the bicaudate and bifrontal indices. These results may be the first demonstration of diminished caudate nucleus volumes in depression and suggest a role for the caudate nucleus in the pathogenesis of major depression.

Effects of exercise training on older patients with major depression.

BACKGROUND: Previous observational and interventional studies have suggested that regular physical exercise may be associated with reduced symptoms of depression. However, the extent to which exercise training may reduce depressive symptoms in older patients with major depressive disorder (MDD) has not been systematically evaluated. OBJECTIVE: To assess the effectiveness of an aerobic exercise program compared with standard medication (ie, antidepressants) for treatment of MDD in older patients, we conducted a 16-week randomized controlled trial. METHODS: One hundred fifty-six men and women with MDD (age, > or = 50 years) were assigned randomly to a program of aerobic exercise, antidepressants (sertraline hydrochloride), or combined exercise and medication. Subjects underwent comprehensive evaluations of depression, including the presence and severity of MDD using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria and Hamilton Rating Scale for Depression (HAM-D) and Beck Depression Inventory (BDI) scores before and after treatment. Secondary outcome measures included aerobic capacity, life satisfaction, self-esteem, anxiety, and dysfunctional cognitions. RESULTS: After 16 weeks of treatment, the groups did not differ statistically on HAM-D or BDI scores (P = .67); adjustment for baseline levels of depression yielded an essentially identical result. Growth curve models revealed that all groups exhibited statistically and clinically significant reductions on HAM-D and BDI scores. However, patients receiving medication alone exhibited the fastest initial response; among patients receiving combination therapy, those with less severe depressive symptoms initially showed a more rapid response than those with initially more severe depressive symptoms. CONCLUSIONS: An exercise training program may be considered an alternative to antidepressants for treatment of depression in older persons. Although antidepressants may facilitate a more rapid initial therapeutic response than exercise, after 16 weeks of treatment exercise was equally effective in reducing depression among patients with MDD.

Pituitary size in depression.

Magnetic resonance images centered at the pituitary stalk were used to measure pituitary gland size in 19 patients with major depression compared with that in age- and sex-matched controls. Depressed patients had significantly greater pituitary cross-sectional area (P = 0.0009) and volume (P = 0.007) than the controls. This difference was particularly prominent in elderly depressed patients compared to elderly controls. These results provide the first demonstration of structural alterations in the pituitary gland in major depression.

In vivo assessment of pituitary gland volume with magnetic resonance imaging: the effect of age.

We used sagittal and coronal T1 weighted magnetic resonance images, at 1.5 Tesla, to measure the height, width, length, and cross-sectional area and to generate two estimates of pituitary gland volume in 35 normal volunteers aged 26-79 yr (19 females and 16 males). Subjects over 50 yr of age had significantly smaller pituitary gland height (P = 0.03), area (P = 0.04), and volume (P = 0.04) than those under 50 yr (by two-tailed t test). Overall, age was negatively correlated with pituitary volume (V1: r = -0.51; P = 0.003; V2: r = -0.47; P = 0.008), area (r = -0.43; P = 0.009), and height (r = -0.46; P = 0.005), but not with pituitary length or width. There were no statistically significant differences in pituitary size between men and women (by two-tailed t test). These findings suggest that pituitary gland height provides a good single measure for the assessment of pituitary gland size and that age must be controlled for in studies of pituitary gland size.

Magnetic resonance spectroscopy in Alzheimer's disease: focus on N-acetylaspartate.

This paper reviews published post-mortem brain and in-vivo proton magnetic resonance spectroscopy (1H-MRS) studies in Alzheimer's disease (AD) and focuses on the emerging role of N-acetylaspartate (NAA) as a prognostic marker of neuronal function. Post-mortem brain studies have reported significantly lower NAA levels in AD brains than in control brains, and some have correlated the low levels with neuropathological findings (i.e. amyloid plaques and neurofibrillary tangles). Similarly, almost all published in-vivo studies have reported lower NAA levels in AD patients compared to elderly controls. While some studies have found changes in metabolite levels that were considered useful for the diagnosis of AD, most have found that 1H-MRS provided little or no advantages over other, more common diagnostic tools. Instead, recent studies in AD and other neuropsychiatric disorders suggest that NAA may be more useful as a prognostic marker for monitoring neurodegeneration, stabilization, or improvement, and for evaluating therapeutic response to novel drugs.

Magnetic resonance findings in patients with early-onset Alzheimer's disease.

The magnetic resonance scans of 22 patients with early-onset Alzheimer's disease (AD) were compared to 16 age-matched neurologically normal controls for the presence of white matter subcortical hyperintensities (SCH) and periventricular hyperintensities (PVH). Patients with AD were significantly more likely to have evidence of PVH (p less than 0.01) than age-matched controls. There was no significant difference between the two groups in either the frequency of SCH or the size of the largest lesion. Within the AD group, there was no difference demonstrated in the location of the SCH, either in the anterior-posterior plane or between the two hemispheres. Patients with AD more frequently demonstrated ventriculomegaly (p less than 0.001) and sulcal widening (p less than 0.05) compared with controls. This study suggests that the SCH seen in early-onset AD patients on MRI are related more to the aging process than to the AD process and that the increased frequency of PVH may have a relationship to the disease process.

A brain magnetic resonance imaging study of pituitary gland morphology in anorexia nervosa and bulimia.

Magnetic resonance imaging (MRI) of the brain was used to examine the morphology and dimensions of the pituitary gland in 18 patients with eating disorders (8 anorectics and 10 bulimics), in comparison with 13 healthy volunteers. None of the 18 patients with anorexia or bulimia had any radiological evidence suggestive of pituitary macroadenoma, cyst, or empty sella. Measurements revealed that the anorectics and bulimics had smaller pituitary gland cross-sectional areas (p less than 0.05) and smaller pituitary gland heights, compared with healthy controls. These preliminary findings in anorectics and bulimics are suggestive of pituitary atrophy secondary to nutritional or endocrine alterations, rather than a primary pituitary pathology.