Depression and Alzheimer’s Disease Biomarkers Predict Driving Decline - Babulal, Ganesh M. (J Alzheimers Dis, 2018)
BACKGROUND: Symptomatic Alzheimer’s disease (AD) and depression independently increase crash risk. Additionally, depression is both a risk factor for and a consequence of AD. OBJECTIVE: To examine whether a depression diagnosis, antidepressant use, and preclinical AD are associated with driving decline among cognitively normal older adults. METHODS: Cognitively normal participants, age ≥65, were enrolled. Cox proportional hazards models evaluated whether a depression diagnosis, depressive symptoms (Geriatric Depression Scale), antidepressant use, cerebrospinal fluid (amyloid-β(42)[A β(42)], tau, phosphorylated tau(181) [ptau(181)]), and amyloid imaging biomarkers (Pittsburgh Compound B and Florbetapir) were associated with time to receiving a rating of marginal/fail on a road test. Age was adjusted for in all models. RESULTS: Data were available from 131 participants with age ranging from 65.4 to 88.2 years and mean follow up of 2.4 years (SD = 1.0). A depression diagnosis was associated with a faster time to receiving a marginal/fail rating on a road test and antidepressant use (p = 0.024, HR = 2.62). Depression diagnosis and CSF and amyloid PET imaging biomarkers were associated with driving performance on the road test (p≤0.05, HR = 2.51–3.15). In the CSF ptau(181) model, depression diagnosis (p = 0.031, HR = 2.51) and antidepressant use (p = 0.037, HR = 2.50) were statistically significant predictors. There were no interaction effects between depression diagnosis, antidepressant use, and biomarker groups. Depressive symptomology was not a statistically significant predictor of driving performance. CONCLUSIONS: While, as previously shown, preclinical AD alone predicts a faster time to receiving a marginal/fail rating, these results suggest that also having a diagnosis of depression accelerates the onset of driving problems in cognitively normal older adults.