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Blood-based biomarkers are increasingly used to characterize Alzheimer's disease (AD)-related pathology, yet substantial heterogeneity exists in how biomarker burden relates to cognitive performance. Grip strength, a marker of frailty and functional reserve, may modify this relationship. We conducted a cross-sectional analysis of 348 participants from the Aging Adult Brain Connectome (AABC) study. Global cognition was assessed using the Preclinical Alzheimer Cognitive Composite (PACC). Plasma biomarkers included phosphorylated tau-217 (pTau Show less

Early identification of markers of cognitive decline in cognitively normal older adults is essential for dementia prevention strategies. Sensorimotor measures, such as gait speed, grip strength, and reaction time, may provide sensitive indicators of current and future impairment. This study examined associations between baseline sensorimotor function and cognitive decline in cognitively normal older adults. In this prospective cohort, 246 cognitively normal older adults from the DRIVES Project completed baseline assessments of grip strength, gait speed, simple reaction time, and the Preclinical Alzheimer Cognitive Composite (PACC). Participants were followed for a mean of 4 years. Linear mixed-effects models adjusted for demographics, APOE ε4 status, and neighborhood deprivation. Cross-sectional analyses evaluated the associations between sensorimotor measures and cerebrospinal fluid (CSF) biomarkers of amyloid, tau, and plasma neurofilament light chain (NfL). Participants (mean age: 74.9 ± 5.17 years; 48.8% female) had a mean baseline PACC score of 1.06 ± 0.50. Cross-sectionally, slower gait speed was associated with higher CSF tau/Aβ Show less

Early detection of preclinical Alzheimer's disease (AD) could expand preventative care. Current biomarkers are costly, invasive, or lack generalizability. Driving and sensorimotor performance may reveal prodromal changes. We tested whether features from high-frequency driving trips detect preclinical AD and whether demographic, genetic, or sensorimotor data improve accuracy. Drivers aged ≥ 65 (n = 254) from Driving Real-World In-Vehicle Evaluation System (DRIVES) completed cerebrospinal fluid Aβ The top-performing model (driving, age, A high-frequency trip's driving telemetry, combined with age and Show less

Driving integrates multiple cognitive, sensory, and motor systems and may serve as a real-world indicator of functional decline in aging. Older adults with mild cognitive impairment (MCI) often experience subtle driving changes before formal dementia diagnosis, but longitudinal, real-world evidence is limited. This study examined whether naturalistic driving data can differentiate older adults with MCI from those with normal cognition (NC) over time and evaluated the discriminative ability of driving features compared with conventional risk factors. We conducted a prospective, observational cohort study of community-dwelling older drivers enrolled in the Driving Real-World In-Vehicle Evaluation System Project at Washington University. Participants underwent annual Clinical Dementia Rating assessment, neuropsychological testing, and apolipoprotein ε4 (APOE ε4) genotyping. Driving behaviors were captured daily for up to 40 months using global positioning system-enabled in-vehicle dataloggers, recording trip frequency, duration, distance, time of day, speeding, hard braking, and spatial mobility (entropy, maximum distance, radius of gyration). Longitudinal changes were analyzed using linear mixed-effect models, adjusting for age, sex, race, education, and APOE ε4. Logistic regression with reciever operator curve analysis evaluated discrimination between older adults with MCI and those with NC, compared with conventional sociodemographic and genetic markers. Among 298 participants (MCI, n = 56; NC, n = 242; mean age 75.1 years; 45.6% female), the groups were similar in age, sex, race, and APOE ε4 status at baseline, as well as in most driving behaviors. Over time, drivers with MCI showed greater reductions in monthly trip count (MCI: -0.501, standard error [SE]: 0.21, 95% CI [-0.923 to -0.083] vs NC: -0.523, SE: 0.09, 95% CI [-0.709 to -0.337]; MCI was associated with progressive declines in driving frequency, complexity, and spatial range, supporting naturalistic driving data as a potential unobtrusive digital biomarker for early cognitive decline. Limitations of the study include a predominantly White, highly educated sample and a lack of external validation, warranting cautious interpretation. Continuous monitoring could augment clinical assessments, inform driving safety decisions, and guide interventions to preserve mobility in aging. Show less