White matter hyperintensities and the surrounding normal appearing white matter are associated with water channel disruption in the oldest old.

INTRODUCTION: Age-related magnetic resonance imaging (MRI) T2 white matter hyperintensities (WMHs) are common and associated with neurological decline. We investigated the histopathological underpinnings of MRI WMH and surrounding normal appearing white matter (NAWM), with a focus on astroglial phenotypes. METHODS: Brain samples from 51 oldest old Oregon Alzheimer's Disease Research Center participants who came to autopsy underwent post mortem (PM) 7 tesla MRI with targeted histopathological sampling of WMHs and NAWM. Stained slides were digitized and quantified. Mixed-effects models determined differences in molecular characteristics between WMHs and the NAWM and across NAWM. RESULTS: PM MRI-targeted WMHs are characterized by demyelination, microglial activation, and prominent astrocytic alterations, including disrupted aquaporin (AQP) expression. Similar changes occur within the surrounding NAWM in a pattern of decreasing severity with increased distance from WMHs. DISCUSSION: Decreased AQP expression within WMH and proximal NAWM suggest an overwhelmed system wherein water homeostasis is no longer maintained, contributing to WM damage in older individuals. HIGHLIGHTS: Post mortem magnetic resonance imaging (MRI) was used to characterize the pathology of white matter hyperintensities (WMHs) and surrounding normal appearing white matter (NAWM). Stained immunohistochemical (IHC) slides from targeted WMH and NAWM samples were digitized and quantified. WMHs and NAWM were associated with inflammation, demyelination, and gliosis. WMHs and NAWM astrocytic changes included decreased AQP1 and AQP4 expression. Abnormal NAWM pathology diminished in severity with increasing distance from WMH.

Decentralized clinical trials for medications to reduce the risk of dementia: Consensus report and guidance.

INTRODUCTION: Recent growth in the functionality and use of technology has prompted an increased interest in the potential for remote or decentralized clinical trials in dementia. There are many potential benefits associated with decentralized medication trials, but we currently lack specific recommendations for their delivery in the dementia field. METHODS: A modified Delphi method engaged an expert panel to develop recommendations for the conduct of decentralized medication trials in dementia prevention. A working group of researchers and clinicians with expertise in dementia trials further refined the recommendations. RESULTS: Overall, the recommendations support the delivery of decentralized trials in dementia prevention provided adequate safety checks and balances are included. A total of 40 recommendations are presented, spanning aspects of decentralized clinical trials, including safety, dispensing, outcome assessment, and data collection. DISCUSSION: These recommendations provide an accessible, pragmatic guide for the design and conduct of remote medication trials for dementia prevention. HIGHLIGHTS: Clinical trials of medication have begun adopting decentralized approaches. Researchers in the field lack guidance on what would be appropriate circumstances and frameworks for what would be appropriate circumstances and frameworks for the use of decentralized trial methods in dementia prevention. The present report provides consensus-based expert recommendations for decentralized clinical trials for dementia prevention.

Mild cognitive impairment detection from facial video interviews by applying spatial-to-temporal attention module.

Early detection of Mild Cognitive Impairment (MCI) leads to early interventions to slow the progression from MCI into dementia. Deep Learning (DL) algorithms could help achieve early non-invasive and low-cost detection of MCI. This paper presents the detection of MCI in older adults using DL models based only on facial features extracted from video-recorded conversations at home. We used the data collected from the I-CONECT behavioral intervention study (NCT02871921), where several sessions of semi-structured interviews between socially isolated older individuals and interviewers were video recorded. We develop a framework that extracts holistic spatial facial features using a convolutional autoencoder and temporal information using transformers. We proposed the Spatial-to-Temporal Attention Module (STAM) to detect the I-CONECT study participants' cognitive conditions (MCI vs. those with normal cognition (NC)) using facial and interaction features. The interaction features of the facial features improved the prediction performance compared with applying facial features solely. The detection accuracy using this combined method reached 88%, whereas the accuracy without applying the segments and sequences information of the facial features within a video on a certain theme was 84%. Overall, the results show that spatiotemporal facial features modeled using DL algorithms have a discriminating power for the detection of MCI.

Mild Cognitive Impairment Subtype Performance in Comparison to Healthy Older Controls on the NIH Toolbox and Cogstate.

BACKGROUND: Early detection is necessary for the treatment of dementia. Computerized testing has become more widely used in clinical trials; however, it is unclear how sensitive these measures are to early signs of neurodegeneration. We investigated the use of the NIH Toolbox-Cognition (NIHTB-CB) and Cogstate-Brief computerized neuropsychological batteries in the identification of mild cognitive impairment (MCI) versus healthy older adults [healthy control (HC)] and amnestic (aMCI) versus nonamnestic MCI (naMCI). Exploratory analyses include investigating potential racial differences. METHODS: Two hundred six older adults were diagnosed as aMCI (n = 58), naMCI (n = 15), or cognitively healthy (HC; n = 133). RESULTS: The NIH Toolbox-CB subtests of Flanker, Picture Sequence Memory, and Picture Vocabulary significantly differentiated MCI from HC. Further, subtests from both computerized batteries differentiated patients with aMCI from those with naMCI. Although the main effect of race differences was noted on tests and in diagnostic groups was significant, there were no significant race-by-test interactions. CONCLUSIONS: Computer-based subtests vary in their ability to help distinguish MCI subtypes, though these tests provide less expensive and easier-to-administer clinical screeners to help identify patients early who may qualify for more comprehensive evaluations. Further work is needed, however, to refine computerized tests to achieve better precision in distinguishing impairment subtypes.

Committee on High-quality Alzheimer's Disease Studies (CHADS) consensus report.

BACKGROUND: Consensus guidance for the development and identification of high-quality Alzheimer's disease clinical trials is needed for protocol development and conduct of clinical trials. METHODS: An ad hoc consensus committee was convened in conjunction with the Alzheimer's Association to develop consensus recommendations. RESULTS: Consensus was readily reached for the need to provide scientific justification, registration of trials, institutional review board oversight, conflict of interest disclosure, funding source disclosure, defined trial population, recruitment resources, definition of the intervention, specification of trial duration, appropriate payment for participant engagement, risk-benefit disclosure as part of the consent process, and the requirement to disseminate and/or publish trial results even if the study is negative. CONCLUSIONS: This consensus guidance should prove useful for the protocol development and conduct of clinical trials, and may further provide a platform for the development of education materials that may help guide appropriate clinical trial participation decisions for potential trial participants and the general public.

ARMADA: Assessing reliable measurement in Alzheimer's disease and cognitive aging project methods.

INTRODUCTION: Early detection of cognitive decline in older adults is a public health priority. Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA), a multisite study, is validating cognition, emotion, motor, and sensory modules of the National Institutes of Health Toolbox for Assessment of Neurological and Behavioral Function (NIHTB) in the aging spectrum from cognitively normal to dementia of the Alzheimer's type (DAT). METHODS: Participants 65 to 85 years old, in demographic groups racially proportional to the general US population, are recruited in one of three groups to validate the NIHTB: cognitively normal, amnestic mild cognitive impairment (aMCI), or mild DAT. Additional special emphasis cohorts include (1) Blacks in the three clinical groups; (2) Spanish-speakers in the three clinical groups; (3) cognitively normal, population-proportional, over age 85. DISCUSSION: Longitudinal study will determine whether NIHTB can predict cognitive decline and is associated with Alzheimer's disease biomarkers. Here, we detail the methods for the ARMADA study.

The epidemiology is promising, but the trial evidence is weak. Why pharmacological dementia risk reduction trials haven't lived up to expectations, and where do we go from here?

There is an urgent need for interventions that can prevent or delay cognitive decline and dementia. Decades of epidemiological research have identified potential pharmacological strategies for risk factor modification to prevent these serious conditions, but clinical trials have failed to confirm the potential efficacy for such interventions. Our multidisciplinary international group reviewed seven high-potential intervention strategies in an attempt to identify potential reasons for the mismatch between the observational and trial results. In considering our findings, we offer constructive recommendations for the next steps. Overall, we observed some differences in the observational evidence base for the seven strategies, but several common methodological themes that emerged. These themes included the appropriateness of trial populations and intervention strategies, including the timing of interventions and other aspects of trials methodology. To inform the design of future clinical trials, we provide recommendations for the next steps in finding strategies for effective dementia risk reduction.

The Tele-STELLA protocol: Telehealth-based support for families living with later-stage Alzheimer's disease.

AIMS: We aim to establish the feasibility and acceptability of the Tele-STELLA (Support via Telehealth: Living and Learning with Advancing Alzheimer's Disease and Related Dementias) intervention. We will also assess the efficacy of the intervention in reducing the frequency of behavioural symptoms of dementia as well as family Care Partner reactivity to the symptoms. DESIGN: This is a multi-component, quasi-experimental study that focuses on facilitating effective management of behavioural symptoms that occur in the later stages of dementia. METHODS: Family Care Partners (n = 124) for persons with Alzheimer's disease will participate in two 8-week videoconferencing components that address behavioural symptoms-in both the persons with Alzheimer's disease and their Care Partners. In the first component ('Nova'), Care Partners work with one nurse for an hour/week for 4 weeks, then they join a small group for another 4 weeks. In the second component ('Constellation'), Care Partners work in a larger group to hone skills and knit supportive relationships. Behavioural symptom frequency and Care Partner reactivity to the behaviours will be measured prior to, during and after the intervention. The study is funded by the United States National Institute on Aging (R01AG067546); funding was initiated as on February, 2021. DISCUSSION: Tele-STELLA fills a gap in current videoconference-based psychoeducational interventions in that it offers real-time interaction with nurses and peers. The intervention was designed with feedback by pilot participants. This study will assess Tele-STELLA in its current, novel format; thus, preparing it for a larger, future randomized controlled trial. IMPACT: Tele-STELLA addresses symptoms that occur in the later stages of dementia, providing families with tools to facilitate effective behavioural management. Because Tele-STELLA is implemented via videoconferencing, it targets Care Partners who face barriers to support, such as cost and transportation. TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov (#NCT04627662).

Type and frequency of social contacts associated with low mood before and during the COVID-19 pandemic in older adults: I-CONECT project.

BACKGROUND: Social isolation is a risk factor for dementia, but the underlying mechanism is not well understood. It is possible that lack of social contacts negatively affects emotional well-being, which leads to cognitive decline. To shed light on this potential mediation mechanism, we examined changes in type and frequency of social contacts and their effects on mood using data collected before and during the COVID-19 pandemic among socially isolated older adults aged 75 and older. METHOD: The data come from an ongoing randomized controlled trial, the Internet-Based Conversational Engagement Clinical Trial (I-CONECT, ClinicalTirals.gov: NCT02871921). One hundred forty-six participants (age=81.0±4.5, 71.9% women) who were in the trial both before and during the pandemic and whose data were available as of November of 2020 were included in the current analysis. Weekly health questionnaires administered on all participants regardless of treatment assignments were collected before and during the COVID-19 pandemic. Low mood ("Blueness") was self-reported as feeling downhearted or blue for three or more days in the past week (YES/NO). Social contacts were self-reported by amount of time they had interacted, with whom (family; friends; others), and via which modalities (in-person; phone/video call; text/email). RESULT: A total of 4,774 weeks of survey data were analyzed (3,047 before COVID 19). The weekly average time spent in-person, on phone/video call, and via text/email were 282, 113, and 44 minutes, respectively. During the COVID-19 pandemic, participants on average spent 82 minutes less in total social contact per week (in-person: reduced 123 minutes, video/call: increased 28 minutes, text/email: increased 13 minutes per week). Generalized estimating equation model revealed that in-person family contact was associated with less blueness regardless of the pandemic (OR=0.91, p=0.04). There was a COVID*text/email time with friends interaction (OR=0.68, p=0.03), suggesting that during the COVID-19 pandemic, an increase of 1 hour of texting/emailing with friends per week was associated with 32% decrease in experiencing blueness three or more days per week. CONCLUSION: In-person family time is beneficial for mental health. While in-person contacts become less frequent during the COVID-19 pandemic, increased text/email time with friends becomes an alternative to maintain mental health for socially isolated older adults.

Depression Symptoms Declining Among Older Adults: Birth Cohort Analyses From the Rust Belt.

OBJECTIVES: To investigate potential birth cohort effects in depression symptoms in older adults. DESIGN: Population-based prospective cohort. SETTING: Small-town communities in Pennsylvania. PARTICIPANTS: Three thousand two hundred and twenty seven older adults (average baseline age = 71.6) born between 1902 and 1941. MEASUREMENTS: Four decade-long birth cohorts were the primary predictors in this study: 1902-1911, 1912-1921, 1922-1931, and 1932-1941. The outcome was symptoms of depression assessed at baseline and follow-up study visits using a modified Center for Epidemiologic Studies Depression Scale (mCES-D). The depression outcome was operationalized as: 1). A binary outcome of having greater than equal to 5 depression symptoms on the total mCES-D at any study visit, and 2). A continuous outcome of four factor-analyzed component scores of the mCES-D including depressed mood, anergia/hopelessness, withdrawal, and poor self-esteem. All analyses were jointly modeled with attrition and adjusted for age, sex, education, Mini Mental State Examination score, antidepressant medications, and total prescription medications. RESULTS: Participants from more recently born cohorts were significantly less likely to have a study visit in which they reported greater than or equal to 5 depression symptoms, controlling for attrition. Specifically, in comparison to the 1902-1911 referent cohort, the 1912-1921 birth cohort was 43% less likely (odds ratio [OR] = 0.566, 95% confidence interval [CI]: 0.341-0.939), the 1922-1931 birth cohort was 63% less likely (OR = 0.0369, 95% CI: 0.215-0.632), and the 1932-1941 cohort was 79% less likely (OR = 0.205, 95% CI: 0.106-0.399). The cohort effect was most evident in the depressed mood and anergia/hopelessness symptom composites. CONCLUSION: Reduced rates of depression symptoms observed in successive birth cohorts of older adults may reflect compression of morbidity or other secular trends.

Expanded Demographic Norms for Version 3 of the Alzheimer Disease Centers' Neuropsychological Test Battery in the Uniform Data Set.

BACKGROUND: Norms for the Uniform Data Set Version 3 Neuropsychological Battery are available for cognitively normal individuals based on age, education, and sex; however, these norms do not include race. We provide expanded norms for African Americans and whites. METHODS: Data from 32 Alzheimer's Disease Centers (ADCs) and ADC affiliated cohorts with global Clinical Dementia Rating Scale (CDR) Dementia Staging Instrument scores of 0 were included. Descriptive statistics for each test were calculated by age, sex, race, and education. Multiple linear regressions were conducted to estimate the effect of each demographic variable; squared semipartial correlation coefficients measured the relative importance of variables. RESULTS: There were 8313 participants (16% African American) with complete demographic information, ranging from 6600 to 7885 depending on the test. Lower scores were found for older and less educated groups, and African Americans versus whites. Education was the strongest predictor for most tests, followed in order by age, race, and sex. Quadratic terms were significant for age and education, indicating some nonlinearity, but did not substantially increase R. CONCLUSIONS: Although race-based norms represent incomplete proxies for other sociocultural variables, the appropriate application of these norms is important given the potential to improve diagnostic accuracy and to reduce misclassification bias in cognitive disorders of aging such as Alzheimer disease.

Perspectives on ethnic and racial disparities in Alzheimer's disease and related dementias: Update and areas of immediate need.

Alzheimer's disease and related dementias (ADRDs) are a global crisis facing the aging population and society as a whole. With the numbers of people with ADRDs predicted to rise dramatically across the world, the scientific community can no longer neglect the need for research focusing on ADRDs among underrepresented ethnoracial diverse groups. The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART; alz.org/ISTAART) comprises a number of professional interest areas (PIAs), each focusing on a major scientific area associated with ADRDs. We leverage the expertise of the existing international cadre of ISTAART scientists and experts to synthesize a cross-PIA white paper that provides both a concise "state-of-the-science" report of ethnoracial factors across PIA foci and updated recommendations to address immediate needs to advance ADRD science across ethnoracial populations.

Outcomes after diagnosis of mild cognitive impairment in a large autopsy series.

OBJECTIVE: To determine clinical and neuropathological outcomes following a clinical diagnosis of mild cognitive impairment (MCI). METHODS: Data were drawn from a large autopsy series (N = 1,337) of individuals followed longitudinally from normal or MCI status to death, derived from 4 Alzheimer Disease (AD) Centers in the United States. RESULTS: Mean follow-up was 7.9 years. Of the 874 individuals ever diagnosed with MCI, final clinical diagnoses were varied: 39.2% died with an MCI diagnosis, 46.8% with a dementia diagnosis, and 13.9% with a diagnosis of intact cognition. The latter group had pathological features resembling those with a final clinical diagnosis of MCI. In terms of non-AD pathologies, both primary age-related tauopathy (p < 0.05) and brain arteriolosclerosis pathology (p < 0.001) were more severe in MCI than cognitively intact controls. Among the group that remained MCI until death, mixed AD neuropathologic changes (ADNC; ≥1 comorbid pathology) were more frequent than "pure" ADNC pathology (55% vs 22%); suspected non-Alzheimer pathology comprised the remaining 22% of cases. A majority (74%) of subjects who died with MCI were without "high"-level ADNC, Lewy body disease, or hippocampal sclerosis pathologies; this group was enriched in cerebrovascular pathologies. Subjects who died with dementia and were without severe neurodegenerative pathologies tended to have cerebrovascular pathology and carry the MCI diagnosis for a longer interval. INTERPRETATION: MCI diagnosis usually was associated with comorbid neuropathologies; less than one-quarter of MCI cases showed "pure" AD at autopsy. Ann Neurol 2017;81:549-559.

Big Data Analytical Approaches to the NACC Dataset: Aiding Preclinical Trial Enrichment.

BACKGROUND: Clinical trials increasingly aim to retard disease progression during presymptomatic phases of Mild Cognitive Impairment (MCI) and thus recruiting study participants at high risk for developing MCI is critical for cost-effective prevention trials. However, accurately identifying those who are destined to develop MCI is difficult. Collecting biomarkers is often expensive. METHODS: We used only noninvasive clinical variables collected in the National Alzheimer's Coordinating Center (NACC) Uniform Data Sets version 2.0 and applied machine learning techniques to build a low-cost and accurate Mild Cognitive Impairment (MCI) conversion prediction calculator. Cross-validation and bootstrap were used to select as few variables as possible accurately predicting MCI conversion within 4 years. RESULTS: A total of 31,872 unique subjects, 748 clinical variables, and additional 128 derived variables in NACC data sets were used. About 15 noninvasive clinical variables are identified for predicting MCI/aMCI/naMCI converters, respectively. Over 75% Receiver Operating Characteristic Area Under the Curves (ROC AUC) was achieved. By bootstrap we created a simple spreadsheet calculator which estimates the probability of developing MCI within 4 years with a 95% confidence interval. CONCLUSIONS: We achieved reasonably high prediction accuracy using only clinical variables. The approach used here could be useful for study enrichment in preclinical trials where enrolling participants at risk of cognitive decline is critical for proving study efficacy, and also for developing a shorter assessment battery.

Version 3 of the Alzheimer Disease Centers' Neuropsychological Test Battery in the Uniform Data Set (UDS).

INTRODUCTION: The neuropsychological battery of the Uniform Data Set (UDSNB) was implemented in 2005 by the National Institute on Aging (NIA) Alzheimer Disease Centers program to measure cognitive performance in dementia and mild cognitive impairment due to Alzheimer Disease. This paper describes a revision, the UDSNB 3.0. METHODS: The Neuropsychology Work Group of the NIA Clinical Task Force recommended revisions through a process of due diligence to address shortcomings of the original battery. The UDSNB 3.0 covers episodic memory, processing speed, executive function, language, and constructional ability. Data from 3602 cognitively normal participants in the National Alzheimer Coordinating Center database were analyzed. RESULTS: Descriptive statistics are presented. Multivariable linear regression analyses demonstrated score differences by age, sex, and education and were also used to create a normative calculator available online. DISCUSSION: The UDSNB 3.0 neuropsychological battery provides a valuable non proprietary resource for conducting research on cognitive aging and dementia.

Weekly observations of online survey metadata obtained through home computer use allow for detection of changes in everyday cognition before transition to mild cognitive impairment.

INTRODUCTION: Subtle changes in instrumental activities of daily living often accompany the onset of mild cognitive impairment (MCI) but are difficult to measure using conventional tests. METHODS: Weekly online survey metadata metrics, annual neuropsychological tests, and an instrumental activity of daily living questionnaire were examined in 110 healthy older adults with intact cognition (mean age = 85 years) followed up for up to 3.6 years; 29 transitioned to MCI during study follow-up. RESULTS: In the baseline period, incident MCI participants completed their weekly surveys 1.4 hours later in the day than stable cognitively intact participants, P = .03, d = 0.47. Significant associations were found between earlier survey start time of day and higher memory (r = -0.34; P < .001) and visuospatial test scores (r = -0.37; P < .0001). Longitudinally, incident MCI participants showed an increase in survey completion time by 3 seconds per month for more than the year before diagnosis compared with stable cognitively intact participants (ß = 0.12, SE = 0.04, t = 2.8; P = .006). DISCUSSION: Weekly online survey metadata allowed for detection of changes in everyday cognition before transition to MCI.

Joining forces to prevent dementia: The International Research Network On Dementia Prevention (IRNDP).

Dementia is a neurodegenerative disorder with global impact, with the largest proportion of cases occurring in low- and middle-income countries. It is estimated that there are 46.8 million cases globally with approximately 10 million new cases each year or a new case occurring every 3 sec (Prince et al., 2015). For comparison there are 36.7 million HIV cases with an estimated 2 million new cases each year (WHO, 2017). The rise in dementia prevalence is largely due to population ageing, with the oldest being at highest risk. To date there are no diseases modifying medications for Alzheimer's disease or the other causes of dementia. Academics and research groups are increasingly focused on prevention or delay of dementia (Brayne and Miller, 2017) and a number of organizations now prioritize dementia, indicating a strong and coherent international effort to address this problem. Examples include the World Health Organisation (WHO), which has established a Global Dementia Observatory; the World Dementia Council; the Organisation for Economic Co-operation and Development (OECD); the U.S. National Alzheimer's Project Act (NAPA); and the Global Council on Brain Health.

Cohort effects in verbal memory function and practice effects: a population-based study.

BACKGROUND: In many developed countries, cognitive functioning (as measured by neuropsychological tests) appears to be improving over time in the population at large, in parallel with the declining age-specific incidence of dementia. Here, we investigated cohort effects in the age-associated trajectories of verbal memory function in older adults. We sought to determine whether they varied by decade of birth and, if so, whether the change would be explained by increasing educational attainment. METHODS: Pooling data from two prospective US population-based studies between 1987 and 2015, we identified four birth cohorts born 1902-1911, 1912-1921, 1922-1931, and 1932-1943. Among these cohorts, we compared age-associated trajectories both of performance and of practice effects on immediate and delayed recall of a 10-item Word List. We used mixed effects models, first including birth cohorts and cohort X age interaction terms, and then controlling for education and education X age interaction. RESULTS: We observed significant cohort effects in performance (baseline and age-associated trajectories) in both immediate recall and delayed recall, with function improving between the earliest- and latest-born cohorts. For both tests, we also observed cohort effects on practice effects with the highest levels in the latest-born cohorts. Including education in the models did not attenuate these effects. CONCLUSIONS: In this longitudinal population study, across four decade-long birth cohorts, there were significant improvements in test performance and practice effects in verbal memory tests, not explained by education. Whether this reflects declining disease incidence or other secular trends awaits further investigation.