White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease

Author:

Yang Yisu1,Schilling Kurt23,Shashikumar Niranjana1,Jasodanand Varuna1,Moore Elizabeth E.1,Pechman Kimberly R.1,Bilgel Murat4,Beason‐Held Lori L.4,An Yang4,Shafer Andrea4,Risacher Shannon L.56,Landman Bennett A.12378,Jefferson Angela L.1910,Saykin Andrew J.56,Resnick Susan M.4,Hohman Timothy J.19,Archer Derek B.19,

Affiliation:

1. Vanderbilt Memory and Alzheimer's Center Vanderbilt University School of Medicine Nashville Tennessee USA

2. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville Tennessee USA

3. Department of Radiology & Radiological Sciences Vanderbilt University Medical Center Nashville Tennessee USA

4. Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health Baltimore Maryland USA

5. Indiana University School of Medicine Indianapolis Indiana USA

6. Indiana Alzheimer's Disease Research Center Indianapolis Indiana USA

7. Department of Biomedical Engineering Vanderbilt University Nashville Tennessee USA

8. Department of Electrical and Computer Engineering Vanderbilt University Nashville Tennessee USA

9. Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville Tennessee USA

10. Department of Medicine Vanderbilt University Medical Center Nashville Tennessee USA

Abstract

AbstractIntroductionWhite matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum.MethodsDiffusion magnetic resonance imaging (dMRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 627), Baltimore Longitudinal Study of Aging (BLSA, n = 684), and Vanderbilt Memory & Aging Project (VMAP, n = 296) cohorts were free‐water (FW) corrected and conventional, and FW‐corrected microstructural metrics were quantified within 48 white matter tracts. Microstructural values were subsequently harmonized using the Longitudinal ComBat technique and inputted as independent variables to predict diagnosis (cognitively unimpaired [CU], mild cognitive impairment [MCI], AD). Models were adjusted for age, sex, race/ethnicity, education, apolipoprotein E (APOE) ε4 carrier status, and APOE ε2 carrier status.ResultsConventional dMRI metrics were associated globally with diagnostic status; following FW correction, the FW metric itself exhibited global associations with diagnostic status, but intracellular metric associations were diminished.DiscussionWhite matter microstructure is altered along the AD continuum. FW correction may provide further understanding of the white matter neurodegenerative process in AD.Highlights Longitudinal ComBat successfully harmonized large‐scale diffusion magnetic resonance imaging (dMRI) metrics. Conventional dMRI metrics were globally sensitive to diagnostic status. Free‐water (FW) correction mitigated intracellular associations with diagnostic status. The FW metric itself was globally sensitive to diagnostic status. Multivariate conventional and FW‐corrected models may provide complementary information.

Funder

National Institute on Aging

Alzheimer's Association

National Institutes of Health

U.S. Department of Defense

National Institute of Biomedical Imaging and Bioengineering

National Institute of General Medical Sciences

National Center for Advancing Translational Sciences

NIH Office of the Director

Publisher

Wiley

Subject

Psychiatry and Mental health,Neurology (clinical)

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