Background: Emerging evidence shows that cognitively normal older adults with preclinical Alzheimer’s disease (AD) make more errors and are more likely to receive a marginal/fail rating on a standardized road test compared to older adults without preclinical AD, but the extent to which preclinical AD impacts everyday driving behavior is unknown. Objective: To examine self-reported and naturalistic longitudinal driving behavior among persons with and without preclinical AD. Method: We prospectively followed cognitively normal drivers (aged 65 + years) with ( n = 10) and without preclinical AD ( n = 10) for 2.5 years. Preclinical AD was assessed using amyloid positron emission tomography (PET) with Pittsburgh Compound B. The Driving Habits Questionnaire assessed self-reported driving outcomes. Naturalistic driving was captured using a commercial GPS data logger plugged into the on-board diagnostics II port of each participant’s vehicle. Data were sampled every 30 seconds and all instances of speeding, hard braking, and sudden acceleration were recorded. Results: Preclinical AD participants went to fewer places/unique destinations, traveled fewer days, and took fewer trips than participants without preclinical AD. The preclinical AD group reported a smaller driving space, greater dependence on other drivers, and more difficulty driving due to vision difficulties. Persons with preclinical AD had fewer trips with any aggression and showed a greater decline across the 2.5-year follow-up period in the number of days driving per month and the number of trips between 1–5 miles. Conclusion: Changes in driving occur even during the preclinical stage of AD.

Introduction: Links between preclinical Alzheimer's 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. Methods: One hundred four OAs (65+ years) with normal cognition took part in biomarker measurements, a road test, clinical and psychometric batteries, and self‐reported their driving habits. Results: Higher values of cerebrospinal fluid (CSF) tau/Aβ ₄₂ and phosphorylated tau (ptau ₁₈₁ )/Aβ ₄₂ ratios, but not uptake on Pittsburgh compound B amyloid imaging ( P = .12), predicted time to a rating of marginal or fail on the driving test using Cox proportional hazards models. Hazards ratios (95% confidence interval) were 5.75 (1.70–19.53), P = .005 for CSF tau/Aβ ₄₂ ; 6.19 (1.75–21.88), and P = .005 for CSF ptau ₁₈₁ /Aβ ₄₂ . Discussion: Preclinical AD predicted time to receiving a marginal or fail rating on an on‐road driving test. Driving performance shows promise as a functional outcome in AD prevention trials.

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.

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 DeviceTM 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.

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.

Purpose: Older adults experience impaired driving performance, and modify their driving habits, including limiting amount and spatial extent of travel. Alzheimer disease (AD)-related pathology, as well as spatial navigation difficulties, may influence driving performance and driving behaviors in clinically normal older adults. We examined whether AD biomarkers [cerebrospinal fluid (CSF) concentrations of Aβ₄₂, tau, and ptau₁₈₁] were associated with lower self-reported spatial navigation abilities, and whether navigation abilities mediated the relationship of AD biomarkers with driving performance and extent. Methods: Clinically normal older adults (n=112; aged 65+) completed an on-road driving test, the Santa Barbara Sense of Direction scale (self-report measure of spatial navigation ability), and the Driving Habits Questionnaire for an estimate of driving extent (composite of driving exposure and driving space). All participants had a lumbar puncture to obtain CSF. Results: CSF Aβ₄₂, but not tau or ptau₁₈₁, was associated with self-reported navigation ability. Lower self-reported navigation was associated with reduced driving extent, but not driving errors. Self-reported navigation mediated the relationship between CSF Aβ₄₂ and driving extent. Conclusions: Findings suggest that cerebral amyloid deposition is associated with lower perceived ability to navigate the environment, which may lead older adults with AD pathology to limit their driving extent.