Sarah Holtz Stout

Preclinical Alzheimer's disease and longitudinal driving decline

Links between preclinical Alzheimers disease (AD) and driving difficulty onset would support the use of driving performance as an outcome in primary and secondary prevention trials among older adults (OAs). We examined whether AD biomarkers predicted the onset of driving difficulties among OAs.

Development and interval testing of a naturalistic driving methodology to evaluate driving behavior in clinical research.

Background: The number of older adults in the United States will double by 2056. Additionally, the number of licensed drivers will increase along with extended driving-life expectancy. Motor vehicle crashes are a leading cause of injury and death in older adults. Alzheimer’s disease (AD) also negatively impacts driving ability and increases crash risk. Conventional methods to evaluate driving ability are limited in predicting decline among older adults. Innovations in GPS hardware and software can monitor driving behavior in the actual environments people drive in. Commercial off-the-shelf (COTS) devices are affordable, easy to install and capture large volumes of data in real-time. However, adapting these methodologies for research can be challenging. This study sought to adapt a COTS device and determine an interval that produced accurate data on the actual route driven for use in future studies involving older adults with and without AD. Methods: Three subjects drove a single course in different vehicles at different intervals (30, 60 and 120 seconds), at different times of day, morning (9:00-11:59AM), afternoon (2:00-5:00PM) and night (7:00-10pm). The nine datasets were examined to determine the optimal collection interval. Results: Compared to the 120-second and 60-second intervals, the 30-second interval was optimal in capturing the actual route driven along with the lowest number of incorrect paths and affordability weighing considerations for data storage and curation. Discussion: Use of COTS devices offers minimal installation efforts, unobtrusive monitoring and discreet data extraction. However, these devices require strict protocols and controlled testing for adoption into research paradigms. After reliability and validity testing, these devices may provide valuable insight into daily driving behaviors and intraindividual change over time for populations of older adults with and without AD. Data can be aggregated over time to look at changes or adverse events and ascertain if decline in performance is occurring.

A Naturalistic Study of Driving Behavior in Older Adults and Preclinical Alzheimer Disease: A Pilot Study

A clinical consequence of symptomatic Alzheimer’s disease (AD) is impaired driving performance. However, decline in driving performance may begin in the preclinical stage of AD. We used a naturalistic driving methodology to examine differences in driving behavior over one year in a small sample of cognitively normal older adults with (n = 10) and without (n = 10) preclinical AD. As expected with a small sample size, there were no statistically significant differences between the two groups, but older adults with preclinical AD drove less often, were less likely to drive at night, and had fewer aggressive behaviors such as hard braking, speeding, and sudden acceleration. The sample size required to power a larger study to determine differences was calculated.

Association of Functional Impairments and Co-Morbid Conditions with Driving Performance among Cognitively Normal Older Adults

Objectives To examine the relationship between key functional impairments, co-morbid conditions and driving performance in a sample of cognitively normal older adults. Design Prospective observational study Setting The Knight Alzheimer’s Disease Research Center, Washington University at St. Louis Participants Individuals with normal cognition, 64.9 to 88.2 years old (N = 129), with a valid driver’s license, who were currently driving at least once per week, and who had participated in longitudinal studies at the Knight Alzheimer’s Disease Research Center Measurements Static visual acuity, contrast sensitivity, physical frailty measures, motor skills, total medical conditions, and the modified Washington University Road Test. Results When controlling for age, race, gender, APOE, and education the total number of medical conditions was unassociated with both road test scores (pass vs. marginal + fail) and the total driver error count. There were marginal associations of our measure of physical frailty (p = 0.06) and contrast sensitivity score (p = 0.06) with total driving error count. Conclusion Future research that focuses on older adults and driving should consider adopting measures of physical frailty and contrast sensitivity, especially in samples that may have a propensity for disease impacting visual and/or physical function (e.g. osteoarthritis, Parkinson’s, eye disorders, advanced age >80 years, etc.).

Creating a driving profile for older adults using GPS devices and naturalistic driving methodology

Background/Objectives: Road tests and driving simulators are most commonly used in research studies and clinical evaluations of older drivers. Our objective was to describe the process and associated challenges in adapting an existing, commercial, off-the-shelf (COTS), in-vehicle device for naturalistic, longitudinal research to better understand daily driving behavior in older drivers. Design: The Azuga G2 Tracking Device TM was installed in each participant’s vehicle, and we collected data over 5 months (speed, latitude/longitude) every 30-seconds when the vehicle was driven. Setting: The Knight Alzheimer’s Disease Research Center at Washington University School of Medicine. Participants: Five individuals enrolled in a larger, longitudinal study assessing preclinical Alzheimer disease and driving performance. Participants were aged 65+ years and had normal cognition. Measurements: Spatial components included Primary Location(s), Driving Areas, Mean Centers and Unique Destinations. Temporal components included number of trips taken during different times of the day. Behavioral components included number of hard braking, speeding and sudden acceleration events. Methods: Individual 30-second observations, each comprising one breadcrumb, and trip-level data were collected and analyzed in R and ArcGIS. Results: Primary locations were confirmed to be 100% accurate when compared to known addresses. Based on the locations of the breadcrumbs, we were able to successfully identify frequently visited locations and general travel patterns. Based on the reported time from the breadcrumbs, we could assess number of trips driven in daylight vs. night. Data on additional events while driving allowed us to compute the number of adverse driving alerts over the course of the 5-month period. Conclusions: Compared to cameras and highly instrumented vehicle in other naturalistic studies, the compact COTS device was quickly installed and transmitted high volumes of data. Driving Profiles for older adults can be created and compared month-to-month or year-to-year, allowing researchers to identify changes in driving patterns that are unavailable in controlled conditions.

Driving Outcomes among Older Adults: A Systematic Review on Racial and Ethnic Differences over 20 Years

The population of older adults (aged 65 years and older) in the United States will become more racially and ethnically diverse in the next three decades. Additionally, the growth of the aging population will come with an expansion in the number of older drivers and an increased prevalence of chronic neurological conditions. A major gap in the aging literature is an almost exclusive focus on homogenous, non-Hispanic white samples of older adults. It is unclear if this extends to the driving literature. A systematic review of SCOPUS, PubMed, CINAHL Plus, and Web of Science examined articles on driving and racial/ethnic differences among older adults. Eighteen studies met inclusion criteria and their results indicate that racial and ethnic minorities face a greater risk for driving reduction, mobility restriction, and driving cessation. The majority of studies compared African Americans to non-Hispanic whites but only examined race as a covariate. Only four studies explicitly examined racial/ethnic differences. Future research in aging and driving research needs to be more inclusive and actively involve different racial/ethnic groups in study design and analysis.

Driving cessation over a 24-year period: Dementia severity and cerebrospinal fluid biomarkers

With 36 million older adult U.S. drivers, safety is a critical concern, particularly among those with dementia. It is unclear at what stage of Alzheimers disease (AD) older adults stop driving and whether preclinical AD affects driving cessation.

Tau and Amyloid Positron Emission Tomography Imaging Predict Driving Performance Among Older Adults with and without Preclinical Alzheimer’s Disease

Abnormal levels of Alzheimers disease (AD) biomarkers, measured by positron emission tomography imaging using amyloid-based radiotracers and cerebrospinal fluid, are associated with impaired driving performance in older adults. We examined whether preclinical AD staging, defined using amyloid imaging and tau imaging using the radiotracer T807 (AKA flortaucipir or AV-1451), was associated with receiving a marginal/fail rating on a standardized road test (n = 42). Participants at Stage 2 (positive amyloid and tau scans) of preclinical AD were more likely to receive a marginal/fail rating compared to participants at Stage 0 or 1. Stage 2 preclinical AD may manifest in worse driving performance.

Using the A/T/N Framework to Examine Driving in Preclinical Alzheimer’s Disease

The A/T/N classification system is the foundation of the 2018 NIA-AA Research Framework and is intended to guide the Alzheimer disease (AD) research agenda for the next 5–10 years. Driving is a widespread functional activity that may be particularly useful in investigation of functional changes in pathological AD before onset of cognitive symptoms. We examined driving in preclinical AD using the A/T/N framework and found that the onset of driving difficulties is most associated with abnormality of both amyloid and tau pathology, rather than amyloid alone. These results have implications for participant selection into clinical trials and for the application time of interventions aimed at prolonging the time of safe driving among older adults with preclinical AD.

Incident cognitive impairment: longitudinal changes in molecular, structural and cognitive biomarkers

Longer periods are needed to examine how biomarker changes occur relative to incident sporadic cognitive impairment. We evaluated molecular (CSF and imaging), structural, and cognitive biomarkers to predict incident cognitive impairment and examined longitudinal biomarker changes before and after symptomatic onset. Data from participants who were cognitively normal, underwent amyloid imaging using Pittsburgh compound B and/or CSF studies, and at least two clinical assessments were used. Stepwise Cox proportional hazards models tested associations of molecular (Pittsburgh compound B; CSF amyloid-β42, tau, ptau181, tau/amyloid-β42, ptau181/amyloid-β42), structural (normalized hippocampal volume, normalized whole brain volume), and cognitive (Animal Naming, Trail Making A, Trail Making B, Selective Reminding Test - Free Recall) biomarkers with time to Clinical Dementia Rating (CDR) > 0. Cognitively normal participants (n = 664), aged 42 to 90 years (mean ± standard deviation = 71.4 ± 9.2) were followed for up to 16.9 years (mean ± standard deviation = 6.2 ± 3.5 years). Of these, 145 (21.8%) participants developed a CDR > 0. At time of incident cognitive impairment, molecular, structural, and cognitive markers were abnormal for CDR > 0 compared to CDR = 0. Linear mixed models indicated rates of change in molecular biomarkers were similar for CDR = 0 and CDR > 0, suggesting that the separation in values between CDR = 0 and CDR > 0 must have occurred prior to the observation period. Rate of decline for structural and cognitive biomarkers was faster for CDR > 0 compared to CDR = 0 (P < 0.0001). Structural and cognitive biomarkers for CDR > 0 diverged from CDR 0 at 9 and 12 years before incident cognitive impairment, respectively. Within those who developed CDR > 0, a natural separation occurred for Pittsburgh compound B values. In particular, CDR > 0 who had at least one APOE ɛ4 allele had higher, and more rapid increase in Pittsburgh compound B, while APOE ɛ2 was observed to have slower increases in Pittsburgh compound B. Of molecular biomarker-positive participants followed for at least 10 years (n = 16-23), ∼70% remained CDR = 0 over the follow-up period. In conclusion, conversion from cognitively normal to CDR > 0 is characterized by not only the magnitude of molecular biomarkers but also rate of change in cognitive and structural biomarkers. Findings support theoretical models of biomarker changes seen during transition to cognitive impairment using longitudinal data and provide a potential time for changes seen during this transition. These findings support the use of molecular biomarkers for trial inclusion and cognitive/structural biomarkers for evaluating trial outcomes. Finally, results support a potential role for APOE ɛ in modulating amyloid accumulation in CDR > 0 with APOE ɛ4 being deleterious and APOE ɛ2 protective.