Browsing by Author "Jasodanand, Varuna"

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    Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging
    (bioRxiv, 2023-05-18) Archer, Derek B.; Schilling, Kurt; Shashikumar, Niranjana; Jasodanand, Varuna; Moore, Elizabeth E.; Pechman, Kimberly R.; Bilgel, Murat; Beason-Held, Lori L.; An, Yang; Shafer, Andrea; Ferrucci, Luigi; Risacher, Shannon L.; Gifford, Katherine A.; Landman, Bennett A.; Jefferson, Angela L.; Saykin, Andrew J.; Resnick, Susan M.; Hohman, Timothy J.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    Introduction: It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging. Methods: Diffusion MRI data from several well-established longitudinal cohorts of aging [Alzheimer's Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory & Aging Project (VMAP)] was free-water corrected and harmonized. This dataset included 1,723 participants (age at baseline: 72.8±8.87 years, 49.5% male) and 4,605 imaging sessions (follow-up time: 2.97±2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42±1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed. Results: While we found global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging. Conclusions: There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes. Highlights: Longitudinal data was free-water corrected and harmonizedGlobal effects of white matter decline were seen in normal and abnormal agingThe free-water metric was most vulnerable to abnormal agingCingulum free-water was the most vulnerable to abnormal aging.
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    White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease
    (Wiley, 2023-05-17) Yang, Yisu; Schilling, Kurt; Shashikumar, Niranjana; Jasodanand, Varuna; Moore, Elizabeth E.; Pechman, Kimberly R.; Bilgel, Murat; Beason-Held, Lori L.; An, Yang; Shafer, Andrea; Risacher, Shannon L.; Landman, Bennett A.; Jefferson, Angela L.; Saykin, Andrew J.; Resnick, Susan M.; Hohman, Timothy J.; Archer, Derek B.; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    Introduction: White matter microstructure may be abnormal along the Alzheimer's disease (AD) continuum. Methods: Diffusion 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. Results: Conventional 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. Discussion: White 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.