DigiCog Primary Care (NIH K23)
The early detection of cognitive impairment is one of
the most important challenges in Alzheimer’s research. Cost-efficient, scalable screening strategies for primary care will greatly enhance early diagnosis and treatment. Cognitive assessment is non-invasive and covered by most insurance. Cognitive screening is a required part of the Medicare Annual Wellness Visit typically done by PCPs. However, current tools are insensitive to subtle cognitive changes and have poor specificity in underrepresented populations. Digital cognitive tools overcome many limitations of current paper-and-pencil based approaches. In this project, we are partnering with local primary care practices to enroll a diverse sample (25% identifying as a racial/ethnic minority, Spanish or English speaking) of 100 older adults without prior dementia diagnosis. Participants complete phone screening and consent and do 5 days of brief remote assessments on a smartphone. At their PCP follow-up visit, participants complete brief tablet- and paper-and-pencil-based screening measures. We will obtain feedback from participants and PCPs on the use of the novel digital screening tools. Participants will complete a brief visit to the Butler Memory and Aging Program to do a blood draw for AD plasma biomarker analysis. This last step of the study is aimed at understanding how combining digital cognitive screening and AD plasma biomarkers for early disease detection and monitoring might improve early access to treatment and support for patients and their families. Currently recruiting primary care physicians and their patients!
before clinical symptoms emerge is important to maximize benefits from
treatment. However, current methods to detect amyloid and tau protein build up
are invasive and expensive which limits wide scale accessibility. Novel blood plasma tests have the potential to reduce the cost and increase accessibility to Alzheimer’s disease diagnostic testing. BioFINDER-Brown is a five-year
observational study that aims to validate plasma biomarkers against gold
standard measures for detecting and monitoring Alzheimer’s disease in a diverse
sample of 200 cognitively normal adults aged 50-80 (25% identifying as being under-represented in research based on race/ethnicity, education, socioeconomic status, and/or rural geographic location). Participants complete both phone- and in-person screening
measures (e.g., blood draw and cheek swab) to determine eligibility. As part of
their baseline visit, participants complete questionnaires, paper-and-pencil
cognitive tests, PET, magnetic resonance imaging (MRI), and retinal (eye) imaging
scans. An optional sub study that aims to investigate the relationship between
plasma biomarkers and novel digital cognitive assessments is also available.
Digital cognitive assessments will evaluate how early speech changes and day-to-day
changes in thinking are associated with plasma biomarkers. Currently recruiting new participants!
Detecting early cognitive and daily functioning changes is seen as increasingly important to accelerate thepathway to intervention for Alzheimer’s disease and related dementias (ADRD). However, current paper-and-pencil tools often have poor sensitivity to early changes and lack ecological validity. Further, while there have been rapid advances in the development and validation of novel digital cognitive assessments, the development of novel methods to detect changes in daily functioning have lagged behind. In this pilot
project, we aim to evaluate the acceptability and feasibility of using unobtrusive sensors in participants’smartphones and smartwatches to detect and monitor ADRD through online surveys and small (8-10people) focus groups. Feedback gained from participants in this study will help us understand whichactivities (e.g., physical activity, social media use) and in what context (e.g., for early detection, tomonitor symptoms in dementia) passive monitoring is acceptable to older adults. We also aim to learnabout facilitators (e.g., experience with technology) and barriers (e.g., privacy concerns) of using these devices for early detection of ADRD. Recruitment starting soon!
DigiCog AD Pilot Project (Alzheimer’s Association AACSF)
This project explored
a novel approach to detecting cognitive changes that occur prior to the onset of the major clinical symptoms of Alzheimer’s disease (AD), using digital cognitive tests. Specifically, we evaluated the feasibility of use and accuracy of smartphone-based cognitive testing in cognitively normal older adults at risk for AD from our AD Prevention Registry. In addition to doing smartphone testing on their own for 8 days, participants will completed an in-person assessment involving novel digital cognitive tools (tablets and digital pens), as well as traditional paper and pencil tests, including standard measures and experimental measures that have demonstrated the greatest sensitivity to detect memory changes in the preclinical stage of AD. The accuracy of each digital cognitive measure to distinguish between participants with and without elevated brain amyloid levels was evaluated in comparison to the traditional paper and pencil tests. We are currently in the analysis stage of this project. Please check our publications and presentations pages for the latest results
Effect of baseline and intercurrent medical factors on 6-year cognitive trajectory: Secondary analysis of the SAGES Study (R03AG075434-01)
Intercurrent medical factors occurring while following a cohort study are common, and areoften considered to be a source of bias. In studies of cognition, medical events such as a stroke can occur months or years after following a cohort, and may influence rates of cognitive aging. Although the Successful Aging after Elective Surgery (SAGES) study has examined the effect of postoperative complications and adverse outcomes (i.e., length of stay >5 days, institutional discharge, 30-day rehospitalization), the SAGES cohort has yet to explore the effect of intercurrent medical factors throughout the entire follow-up period. Said intercurrent medical factors could result in an altered cognitive trajectory, thus leading to biased estimates of cognitive aging. As such, the purpose of this study will be to document intercurrent medical factors throughout the SAGES follow-up period, and explore the effect of intercurrent medical factors on cognition and cognitive aging. We will use latent growth curve modeling and random effects modeling, incorporating intercurrent medical factors as time-varying covariates, to refine our estimates of cognitive aging from project one. It may well be that experiencing specific intercurrent medical factors leads to quicker cognitive aging, which would meet the criteria for differential preservation.
Identifying rates of normative cognitive aging using the Children of Depression Age (CODA) cohort
It is well established that cognitive ability declines with age, declining more rapidly later in life.The speed of cognitive aging is influenced byneurocognitive disorders such as ADRD, MCI/CIND and delirium. Whereas it is known that neurocognitive disorders quicken cognitive aging, the pace of normative cognitive aging, or the pace of cognitive aging due to aging without any neurocognitive disorder, is understudied and relatively unknown. This is a major issue in cognition research since there is no general base rate of aging which can be compared to aging in clinical populations. Indeed, a study on cognitive aging in a sample of persons with ADRD, MCI/CIND, or those who have experienced delirium can certainly provide a trajectory of cognitive aging, but knowing just how much quicker said trajectory is compared to a sample of cognitively normal persons is a difficult endeavor. The inability to compare trajectories of cognitive aging among clinical and non-clinical samples creates difficulty for clinicians and researchers alike, since there is no way to determine if the pace of aging in an individual or in a sample is significantly different from normative aging. Using the Children of the Depression Age (CODA) cohort of the Health and Retirement Study (HRS), who were all ages 65 or older at baseline, we track cognitive trajectories from 1998 until the most recent wave of available data (2020), accounting for 22 years of cognitive change.