GPS driving: a digital biomarker for preclinical Alzheimer disease

Abstract Background Alzheimer disease (AD) is the most common cause of dementia. Preclinical AD is the period during which early AD brain changes are present but cognitive symptoms have not yet manifest. The presence of AD brain changes can be ascertained by molecular biomarkers obtained via imaging and lumbar puncture. However, the use of these methods is limited by cost, acceptability, and availability. The preclinical stage of AD may have a subtle functional signature, which can impact complex behaviours such as driving. The objective of the present study was to evaluate the ability of in-vehicle GPS data loggers to distinguish cognitively normal older drivers with preclinical AD from those without preclinical AD using machine learning methods. Methods We followed naturalistic driving in cognitively normal older drivers for 1 year with a commercial in-vehicle GPS data logger. The cohort included n = 64 individuals with and n = 75 without preclinical AD, as determined by cerebrospinal fluid biomarkers. Four Random Forest (RF) models were trained to detect preclinical AD. RF Gini index was used to identify the strongest predictors of preclinical AD. Results The F1 score of the RF models for identifying preclinical AD was 0.85 using APOE ε4 status and age only, 0.82 using GPS-based driving indicators only, 0.88 using age and driving indicators, and 0.91 using age, APOE ε4 status, and driving. The area under the receiver operating curve for the final model was 0.96. Conclusion The findings suggest that GPS driving may serve as an effective and accurate digital biomarker for identifying preclinical AD among older adults.

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NATURALISTIC DRIVING BEHAVIOR AS A NEUROBEHAVIORAL MARKER OF PRECLINICAL ALZHEIMER’S DISEASE

Innovation in Aging ◽

10.1093/geroni/igz038.3243 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

pp. S886-S886

Author(s):

Ganesh Babulal

Keyword(s):

Driving Behavior ◽

Receiver Operating Curve ◽

Stepwise Logistic Regression ◽

Prospective Longitudinal Study ◽

Cognitively Normal ◽

Preclinical Ad ◽

Ε4 Allele ◽

Naturalistic Driving ◽

Prospective Longitudinal ◽

Apolipoprotein Ε4

Abstract Decline in driving skills begins in preclinical AD, when an older adult remains cognitively normal, but the underlying disease process has begun. Preclinical AD is detectable among cognitively normal individuals using molecular biomarkers: positron emission tomography (PET) imaging and cerebrospinal fluid (CSF). The aim of this prospective, longitudinal study is to determine whether naturalistic driving behavior using in-vehicle dataloggers can distinguish older adults with (n=36) and without preclinical AD (n=134). Driving data was calculated as mean/month for several variables (number of trips/day, trip length, trip time, speeding, and hard-braking) for participants followed between one to 46 months. Using stepwise logistic regression, the area under the receiver operating curve (AUC) and 95% confidence interval for these five variables was 0.73 (0.63-0.79) in distinguishing those with and without preclinical AD via amyloid imaging. When age, gender, race, and education were added, the model improved: 0.80 (0.72-0.88). Finally, when apolipoprotein ε4 allele (APOε4), obtained via blood or saliva, was added to the model, accuracy improved: 0.84 (0.77-0.89). Similar results were found using CSF biomarker tau/Aβ42: AUCs (95% CI) were 0.68 (0.58-0.79) for driving variables alone, 0.77 (0.69-0.86) for driving variables and demographics, and 0.87 (0.80-0.94) driving variables, demographics, and apolipoprotein ε4 allele. These promising findings suggest that naturalistic driving behavior can predict those with and without preclinical AD. The AUC is further improved with demographics and APOε4, an easily obtainable genetic biomarker. This model may be used in clinical/research settings as a screen or adjunct for diagnostics and prognostics purposes.

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Sequence of Alzheimer disease biomarker changes in cognitively normal adults

Neurology ◽

10.1212/wnl.0000000000010747 ◽

2020 ◽

Vol 95 (23) ◽

pp. e3104-e3116

Author(s):

Jingqin Luo ◽

Folasade Agboola ◽

Elizabeth Grant ◽

Colin L. Masters ◽

Marilyn S. Albert ◽

...

Keyword(s):

Alzheimer Disease ◽

Change Point ◽

Standardized Uptake Value ◽

Brain Structures ◽

Hippocampal Volume ◽

Cognitive Outcomes ◽

Cross Sectional ◽

Cognitively Normal ◽

Preclinical Ad ◽

Normal Individuals

ObjectiveTo determine the ordering of changes in Alzheimer disease (AD) biomarkers among cognitively normal individuals.MethodsCross-sectional data, including CSF analytes, molecular imaging of cerebral fibrillar β-amyloid (Aβ) with PET using the [11C] benzothiazole tracer Pittsburgh compound B (PiB), MRI-based brain structures, and clinical/cognitive outcomes harmonized from 8 studies, collectively involving 3,284 cognitively normal individuals 18 to 101 years of age, were analyzed. The age at which each marker exhibited an accelerated change (called the change point) was estimated and compared across the markers.ResultsAccelerated changes in CSF Aβ1-42 (Aβ42) occurred at 48.28 years of age and in Aβ42/Aβ40 ratio at 46.02 years, followed by PiB mean cortical standardized uptake value ratio (SUVR) with a change point at 54.47 years. CSF total tau (Tau) and tau phosphorylated at threonine 181 (Ptau) had a change point at ≈60 years, similar to those for MRI hippocampal volume and cortical thickness. The change point for a cognitive composite occurred at 62.41 years. The change points for CSF Aβ42 and Aβ42/Aβ40 ratio, albeit not significantly different from that for PiB SUVR, occurred significantly earlier than that for CSF Tau, Ptau, MRI markers, and the cognitive composite. Adjusted analyses confirmed that accelerated changes in CSF Tau, Ptau, MRI markers, and the cognitive composite occurred at ages not significantly different from each other.ConclusionsOur findings support the hypothesized early changes of amyloid in preclinical AD and suggest that changes in neuronal injury and neurodegeneration markers occur close in time to cognitive decline.

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Neuropsychiatric symptoms predict hypometabolism in preclinical Alzheimer disease

Neurology ◽

10.1212/wnl.0000000000003916 ◽

2017 ◽

Vol 88 (19) ◽

pp. 1814-1821 ◽

Cited By ~ 28

Author(s):

Kok Pin Ng ◽

Tharick A. Pascoal ◽

Sulantha Mathotaarachchi ◽

Chang-Oh Chung ◽

Andréa L. Benedet ◽

...

Keyword(s):

Alzheimer Disease ◽

Neuropsychiatric Symptoms ◽

Posterior Cingulate Cortex ◽

Metabolic Dysfunction ◽

Tau Pathology ◽

Sleep Behavior ◽

Cognitively Normal ◽

Preclinical Ad ◽

Normal Individuals ◽

Metabolic Dysfunctions

Objective:To identify regional brain metabolic dysfunctions associated with neuropsychiatric symptoms (NPS) in preclinical Alzheimer disease (AD).Methods:We stratified 115 cognitively normal individuals into preclinical AD (both amyloid and tau pathologies present), asymptomatic at risk for AD (either amyloid or tau pathology present), or healthy controls (no amyloid or tau pathology present) using [18F]florbetapir PET and CSF phosphorylated tau biomarkers. Regression and voxel-based regression models evaluated the relationships between baseline NPS measured by the Neuropsychiatric Inventory (NPI) and baseline and 2-year change in metabolism measured by [18F]fluorodeoxyglucose (FDG) PET.Results:Individuals with preclinical AD with higher NPI scores had higher [18F]FDG uptake in the posterior cingulate cortex (PCC), ventromedial prefrontal cortex, and right anterior insula at baseline. High NPI scores predicted subsequent hypometabolism in the PCC over 2 years only in individuals with preclinical AD. Sleep/nighttime behavior disorders and irritability and lability were the components of the NPI that drove this metabolic dysfunction.Conclusions:The magnitude of NPS in preclinical cases, driven by sleep behavior and irritability domains, is linked to transitory metabolic dysfunctions within limbic networks vulnerable to the AD process and predicts subsequent PCC hypometabolism. These findings support an emerging conceptual framework in which NPS constitute an early clinical manifestation of AD pathophysiology.

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Resistance vs resilience to Alzheimer disease

Neurology ◽

10.1212/wnl.0000000000005303 ◽

2018 ◽

Vol 90 (15) ◽

pp. 695-703 ◽

Cited By ~ 74

Author(s):

Eider M. Arenaza-Urquijo ◽

Prashanthi Vemuri

Keyword(s):

Alzheimer Disease ◽

Cognitive Reserve ◽

Significant Proportion ◽

Lifestyle Interventions ◽

Cognitively Normal ◽

Elderly Individuals ◽

Preclinical Ad ◽

Brain Maintenance ◽

Neuro Protection ◽

Study Designs

Preventing or delaying Alzheimer disease (AD) through lifestyle interventions will come from a better understanding of the mechanistic underpinnings of (1) why a significant proportion of elderly remain cognitively normal with AD pathologies (ADP), i.e., amyloid or tau; and (2) why some elderly individuals do not have significant ADP. In the last decades, concepts such as brain reserve, cognitive reserve, and more recently brain maintenance have been proposed along with more general notions such as (neuro)protection and compensation. It is currently unclear how to effectively apply these concepts in the new field of preclinical AD specifically separating the 2 distinct mechanisms of coping with pathology vs avoiding pathology. We propose a simplistic conceptual framework that builds on existing concepts using the nomenclature of resistance in the context of avoiding pathology, i.e., remaining cognitively normal without significant ADP, and resilience in the context of coping with pathology, i.e., remaining cognitively normal despite significant ADP. In the context of preclinical AD studies, we (1) define these concepts and provide recommendations (and common scenarios) for their use; (2) discuss how to employ this terminology in the context of investigating mechanisms and factors; (3) highlight the complementarity and clarity they provide to existing concepts; and (4) discuss different study designs and methodologies. The application of the proposed framework for framing hypotheses, study design, and interpretation of results and mechanisms can provide a consistent framework and nomenclature for researchers to reach consensus on identifying factors that may prevent ADP or delay the onset of cognitive impairment.

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Lipid Peroxidation Assessment in Preclinical Alzheimer Disease Diagnosis

Antioxidants ◽

10.3390/antiox10071043 ◽

2021 ◽

Vol 10 (7) ◽

pp. 1043

Author(s):

Carmen Peña-Bautista ◽

Lourdes Álvarez-Sánchez ◽

Inés Ferrer ◽

Marina López-Nogueroles ◽

Antonio José Cañada-Martínez ◽

...

Keyword(s):

Alzheimer Disease ◽

Area Under Curve ◽

Disease Diagnosis ◽

Csf Biomarkers ◽

Preclinical Ad ◽

Aging Populations ◽

Advanced Stages ◽

Preclinical Diagnosis ◽

T Tau ◽

And Oxidative Stress

Background: Alzheimer disease (AD) is an increasingly common neurodegenerative disease, especially in countries with aging populations. Its diagnosis is complex and is usually carried out in advanced stages of the disease. In addition, lipids and oxidative stress have been related to AD since the earliest stages. A diagnosis in the initial or preclinical stages of the disease could help in a more effective action of the treatments. Methods: Isoprostanoid biomarkers were determined in plasma samples from preclinical AD participants (n = 12) and healthy controls (n = 31) by chromatography and mass spectrometry (UPLC-MS/MS). Participants were accurately classified according to cerebrospinal fluid (CSF) biomarkers and neuropsychological examination. Results: Isoprostanoid levels did not show differences between groups. However, some of them correlated with CSF biomarkers (t-tau, p-tau) and with cognitive decline. In addition, a panel including 10 biomarkers showed an area under curve (AUC) of 0.96 (0.903–1) and a validation AUC of 0.90 in preclinical AD prediction. Conclusions: Plasma isoprostanoids could be useful biomarkers in preclinical diagnosis for AD. However, these results would require a further validation with an external cohort.

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Cerebrospinal Fluid Hypocretin and Nightmares in Dementia Syndromes

Dementia and Geriatric Cognitive Disorders Extra ◽

10.1159/000509585 ◽

2021 ◽

pp. 19-25

Author(s):

Lynn Marie Trotti ◽

Donald L. Bliwise ◽

Glenda L. Keating ◽

David B. Rye ◽

William T. Hu

Keyword(s):

Cerebrospinal Fluid ◽

Alzheimer Disease ◽

Cholinesterase Inhibitor ◽

Dementia With Lewy Bodies ◽

Lewy Bodies ◽

Cognitively Normal ◽

Dementia Patients ◽

Sleep Questionnaires ◽

Sleep Alterations ◽

Normal Controls

Background/Aims: Hypocretin promotes wakefulness and modulates REM sleep. Alterations in the hypocretin system are increasingly implicated in dementia. We evaluated relationships among hypocretin, dementia biomarkers, and sleep symptoms in elderly participants, most of whom had dementia. Methods: One-hundred twenty-six adults (mean age 66.2 ± 8.4 years) were recruited from the Emory Cognitive Clinic. Diagnoses were Alzheimer disease (AD; n = 60), frontotemporal dementia (FTD; n = 21), and dementia with Lewy bodies (DLB; n = 20). We also included cognitively normal controls (n = 25). Participants and/or caregivers completed sleep questionnaires and lumbar puncture was performed for cerebrospinal fluid (CSF) assessments. Results: Except for sleepiness (worst in DLB) and nocturia (worse in DLB and FTD) sleep symptoms did not differ by diagnosis. CSF hypocretin concentrations were available for 87 participants and normal in 70, intermediate in 16, and low in 1. Hypocretin levels did not differ by diagnosis. Hypocretin levels correlated with CSF total τ levels only in men (r = 0.34; p = 0.02). Lower hypocretin levels were related to frequency of nightmares (203.9 ± 29.8 pg/mL in those with frequent nightmares vs. 240.4 ± 46.1 pg/mL in those without; p = 0.05) and vivid dreams (209.1 ± 28.3 vs. 239.5 ± 47.8 pg/mL; p = 0.014). Cholinesterase inhibitor use was not associated with nightmares or vivid dreaming. Conclusion: Hypocretin levels did not distinguish between dementia syndromes. Disturbing dreams in dementia patients may be related to lower hypocretin concentrations in CSF.

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