Browsing by Author "Doran, Eric"

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    A pathway linking pulse pressure to dementia in adults with Down syndrome
    (Oxford University Press, 2024-05-09) Rizvi, Batool; Lao, Patrick J.; Sathishkumar, Mithra; Taylor, Lisa; Queder, Nazek; McMillan, Liv; Edwards, Natalie C.; Keator, David B.; Doran, Eric; Hom, Christy; Nguyen, Dana; Rosas, H. Diana; Lai, Florence; Schupf, Nicole; Gutierrez, Jose; Silverman, Wayne; Lott, Ira T.; Mapstone, Mark; Wilcock, Donna M.; Head, Elizabeth; Yassa, Michael A.; Brickman, Adam M.; Neurology, School of Medicine
    Adults with Down syndrome are less likely to have hypertension than neurotypical adults. However, whether blood pressure measures are associated with brain health and clinical outcomes in this population has not been studied in detail. Here, we assessed whether pulse pressure is associated with markers of cerebrovascular disease and is linked to a diagnosis of dementia in adults with Down syndrome via structural imaging markers of cerebrovascular disease and atrophy. The study included participants with Down syndrome from the Alzheimer’s Disease - Down Syndrome study (n = 195, age = 50.6 ± 7.2 years, 44% women, 18% diagnosed with dementia). Higher pulse pressure was associated with greater global, parietal and occipital white matter hyperintensity volume but not with enlarged perivascular spaces, microbleeds or infarcts. Using a structural equation model, we found that pulse pressure was associated with greater white matter hyperintensity volume, which in turn was related to increased neurodegeneration, and subsequent dementia diagnosis. Pulse pressure is an important determinant of brain health and clinical outcomes in individuals with Down syndrome despite the low likelihood of frank hypertension.
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    Cross-Sectional Exploration of Plasma Biomarkers of Alzheimer's Disease in Down Syndrome: Early Data from the Longitudinal Investigation for Enhancing Down Syndrome Research (LIFE-DSR) Study
    (MDPI, 2021-04-28) Hendrix, James A.; Airey, David C.; Britton, Angela; Burke, Anna D.; Capone, George T.; Chavez, Ronelyn; Chen, Jacqueline; Chicoine, Brian; Costa, Alberto C.S.; Dage, Jeffrey L.; Doran, Eric; Esbensen, Anna; Evans, Casey L.; Faber, Kelley M.; Foroud, Tatiana M.; Hart, Sarah; Haugen, Kelsey; Head, Elizabeth; Hendrix, Suzanne; Hillerstrom, Hampus; Kishnani, Priya S.; Krell, Kavita; Ledesma, Duvia Lara; Lai, Florence; Lott, Ira; Ochoa-Lubinoff, Cesar; Mason, Jennifer; Nicodemus-Johnson, Jessie; Proctor, Nicholas Kyle; Pulsifer, Margaret B.; Revta, Carolyn; Rosas, H. Diana; Rosser, Tracie C.; Santoro, Stephanie; Schafer, Kim; Scheidemantel, Thomas; Schmitt, Frederick; Skotko, Brian G.; Stasko, Melissa R.; Talboy, Amy; Torres, Amy; Wilmes, Kristi; Woodward, Jason; Zimmer, Jennifer A.; Feldman, Howard H.; Mobley, William; Medical and Molecular Genetics, School of Medicine
    With improved healthcare, the Down syndrome (DS) population is both growing and aging rapidly. However, with longevity comes a very high risk of Alzheimer's disease (AD). The LIFE-DSR study (NCT04149197) is a longitudinal natural history study recruiting 270 adults with DS over the age of 25. The study is designed to characterize trajectories of change in DS-associated AD (DS-AD). The current study reports its cross-sectional analysis of the first 90 subjects enrolled. Plasma biomarkers phosphorylated tau protein (p-tau), neurofilament light chain (NfL), amyloid β peptides (Aβ1-40, Aβ1-42), and glial fibrillary acidic protein (GFAP) were undertaken with previously published methods. The clinical data from the baseline visit include demographics as well as the cognitive measures under the Severe Impairment Battery (SIB) and Down Syndrome Mental Status Examination (DS-MSE). Biomarker distributions are described with strong statistical associations observed with participant age. The biomarker data contributes to understanding DS-AD across the spectrum of disease. Collectively, the biomarker data show evidence of DS-AD progression beginning at approximately 40 years of age. Exploring these data across the full LIFE-DSR longitudinal study population will be an important resource in understanding the onset, progression, and clinical profiles of DS-AD pathophysiology.
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    Joint-label fusion brain atlases for dementia research in Down syndrome
    (Wiley, 2022-05-25) Queder, Nazek; Phelan, Michael J.; Taylor, Lisa; Tustison, Nicholas; Doran, Eric; Hom, Christy; Nguyen, Dana; Lai, Florence; Pulsifer, Margaret; Price, Julie; Kreisl, William C.; Rosas, Herminia D.; Krinsky-McHale, Sharon; Brickman, Adam M.; Yassa, Michael A.; Schupf, Nicole; Silverman, Wayne; Lott, Ira T.; Head, Elizabeth; Mapstone, Mark; Keator, David B.; Alzheimer’s Biomarkers Consortium; Neurology, School of Medicine
    Research suggests a link between Alzheimer's Disease in Down Syndrome (DS) and the overproduction of amyloid plaques. Using Positron Emission Tomography (PET) we can assess the in-vivo regional amyloid load using several available ligands. To measure amyloid distributions in specific brain regions, a brain atlas is used. A popular method of creating a brain atlas is to segment a participant's structural Magnetic Resonance Imaging (MRI) scan. Acquiring an MRI is often challenging in intellectually-imparied populations because of contraindications or data exclusion due to significant motion artifacts or incomplete sequences related to general discomfort. When an MRI cannot be acquired, it is typically replaced with a standardized brain atlas derived from neurotypical populations (i.e. healthy individuals without DS) which may be inappropriate for use in DS. In this project, we create a series of disease and diagnosis-specific (cognitively stable (CS-DS), mild cognitive impairment (MCI-DS), and dementia (DEM-DS)) probabilistic group atlases of participants with DS and evaluate their accuracy of quantifying regional amyloid load compared to the individually-based MRI segmentations. Further, we compare the diagnostic-specific atlases with a probabilistic atlas constructed from similar-aged cognitively-stable neurotypical participants. We hypothesized that regional PET signals will best match the individually-based MRI segmentations by using DS group atlases that aligns with a participant's disorder and disease status (e.g. DS and MCI-DS). Our results vary by brain region but generally show that using a disorder-specific atlas in DS better matches the individually-based MRI segmentations than using an atlas constructed from cognitively-stable neurotypical participants. We found no additional benefit of using diagnose-specific atlases matching disease status. All atlases are made publicly available for the research community.