Adverse driving behaviors increase over time as a function of preclinical Alzheimer's disease biomarkers

Jason M Doherty; Samantha A Murphy; Sayeh Bayat; Julie K Wisch; Ann M Johnson; Alexis Walker; Suzanne E Schindler; Beau M Ances; John C Morris; Ganesh M Babulal

doi:10.1002/alz.12852

Adverse driving behaviors increase over time as a function of preclinical Alzheimer's disease biomarkers

Alzheimers Dement. 2023 May;19(5):2014-2023. doi: 10.1002/alz.12852. Epub 2022 Nov 23.

Authors

Jason M Doherty¹, Samantha A Murphy¹, Sayeh Bayat^{2

3

4}, Julie K Wisch¹, Ann M Johnson⁵, Alexis Walker¹, Suzanne E Schindler^{1

6

7}, Beau M Ances^{1

8

6

7}, John C Morris^{1

8

6

7}, Ganesh M Babulal^{1

7

9

10

11}

Affiliations

¹ Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.
² Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada.
³ Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, Canada.
⁴ Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
⁵ Center for Clinical Studies, Washington University in St. Louis, St. Louis, Missouri, USA.
⁶ Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, Missouri, USA.
⁷ Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.
⁸ Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
⁹ Institute of Public Health, Washington University in St. Louis, St. Louis, Missouri, USA.
¹⁰ Department of Psychology, Faculty of Humanities, University of Johannesburg, Johannesburg, South Africa.
¹¹ Department of Clinical Research and Leadership, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA.

Abstract

Introduction: We investigated the relationship between preclinical Alzheimer's disease (AD) biomarkers and adverse driving behaviors in a longitudinal analysis of naturalistic driving data.

Methods: Naturalistic driving data collected using in-vehicle dataloggers from 137 community-dwelling older adults (65+) were used to model driving behavior over time. Cerebrospinal fluid (CSF) biomarkers were used to identify individuals with preclinical AD. Additionally, hippocampal volume and cognitive biomarkers for AD were investigated in exploratory analyses.

Results: CSF biomarkers predicted the longitudinal trajectory of the incidence of adverse driving behavior. Abnormal amyloid beta (Aβ₄₂ /Aβ₄₀ ) ratio was associated with an increase in adverse driving behaviors over time compared to ratios in the normal/lower range.

Discussion: Preclinical AD is associated with increased adverse driving behavior over time that cannot be explained by cognitive changes. Driving behavior as a functional, neurobehavioral marker may serve as an early detection for decline in preclinical AD. Screening may also help prolong safe driving as older drivers age.

Keywords: Alzheimer's disease; cerebrospinal fluid biomarkers; driving; older adults.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Aged
Alzheimer Disease* / epidemiology
Amyloid beta-Peptides / cerebrospinal fluid
Biomarkers / cerebrospinal fluid
Cognitive Dysfunction* / cerebrospinal fluid
Humans
Peptide Fragments / cerebrospinal fluid
tau Proteins / cerebrospinal fluid

Substances

Amyloid beta-Peptides
tau Proteins
Biomarkers
Peptide Fragments

Abstract

Publication types

MeSH terms

Substances

Grants and funding