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Keator, David B.

0000-0001-5281-5576

Mayo Clinic

University of California, Irvine

Citations 3

Cross‐Sectional FDG in Down Syndrome and Autosomal Dominant Alzheimer's Disease
Abdelmoity, Omar , Wisch, Julie K. , Kennedy, James T. , Vlassenko, Andrei G. , Handen, Benjamin L. , Head, Elizabeth , Lai, Florence , Rosas, H. Diana , Hartley, Sigan L. , Tudorascu, Dana , Keefe, Sarah , Ikeuchi, Takeshi, Morris, John C., Roh, Jee Hoon , Day, Gregory S. , Xiong, Chengjie , Head, Elizabeth , Lao, Patrick , Keefe, Sarah , Roh, Jee Hoon , Day, Gregory S , Gordon, Brian A , Xiong, Chengjie , Wisch, Julie K , Goyal, Manu S. , Flores, Shaney , Keator, David B. , Rafii, Michael S. , Zaman, Shahid H. , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Fougère, Christian la , Llibre‐Guerra, Jorge J. , Ikeuchi, Takeshi , Morris, John C. , Schofield, Peter R. , Gordon, Brian A. , Benzinger, Tammie L.S. , Ances, Beau M.

Annals of Neurology | September 22, 2025 | Volume: 98 | Issue: 6 | Pages: 1237-1248

10.1002/ana.78002 Get It

Objectives Directly compare the brain glucose patterns seen with [F‐18] fluorodeoxyglucose (FDG) positron emission tomography (PET) between 2 genetically determined forms of Alzheimer's disease: Down syndrome (DS) and autosomal dominant Alzheimer's disease (ADAD). Methods Cross‐sectional analyses of FDG were performed in individuals with DS (n = 76) from the Alzheimer Biomarker Consortium‐Down Syndrome (ABC‐DS), ADAD (n = 297), and neurotypical familial controls (n = 188) from the Dominantly Inherited Alzheimer Network (DIAN). Within‐group linear regression models and generalized additive models were performed for select regional FDG uptake measures (isthmus cingulate and inferior parietal, precuneus, middle temporal gyrus, and precentral gyrus). Age, sex, apolipoprotein (APOE) ε4 carrier status, and cortical amyloid burden were included within these analyses. Results Even 20 years before expected onset of clinical symptoms, FDG uptake was lower for DS compared to neurotypical familial controls ( p < 0.01). ADAD baseline FDG was similar to neurotypical familial controls until 7 years before expected symptom onset. Both symptomatic individuals with DS and ADAD had lower FDG compared to neurotypical familial controls ( p < 0.01). A higher amyloid burden was associated with lower FDG for both genetic forms, with similar rates of decline in FDG uptake for DS and ADAD who were amyloid positive. Interpretation Brain glucose metabolism is substantially lower for people with DS, even in individuals who are cognitively stable. The patterns of FDG decline are distinct in these 2 genetically determined forms of AD. The diagnostic utility of FDG‐PET is specific to the genetic form of AD. ANN NEUROL 2025;98:1237–1248
The past, present, and future of the brain imaging data structure (BIDS)
Markiewicz, Christopher J. , Bansal, Shashank , Bénar, Christian , Bertazzoli, Giacomo , Bhogawar, Suyash , Blair, Ross , Brooks, Teon L , Calhoun, Vince D. , Castelli, Filippo Maria , D’Ambrosio, Sasha , Hollander, Gilles de , Vega, Alejandro de la , Delorme, Arnaud , Earl, Eric , Feingold, Franklin , Flandin, Guillaume, Galassi, Anthony , Gallitto, Giuseppe , Ganz, Melanie , Gholam, James , Ghosh, Satrajit , Guidali, Giacomo , Handwerker, Daniel A. , Hardcastle, Nell , Innis, Robert B. , Ioanas, Horea-Ioan , Jahn, Andrew , Karakuzu, Agâh , Kincses, Bálint , Lau, Jonathan C. , Li, Xiangrui , Meisler, Steven L. , Mikkelsen, Mark E. , Nichols, Thomas E. , Ort, Eduard , Park, Patrick J., Pawlik, Mateusz , Pestilli, Franco , Pollonini, Luca , Rizzo, Gaia , Robbins, Kay A. , Rockhill, Alexander P. , Rogers, Christine , Rokem, Ariel , Rorden, Chris , Routier, Alexandre , Saborit-Torres, Jose Manuel , Schirner, Michael , Smith, Robert E. , Sprenger, Julia , Szinte, Martin , Thomas, Adam G. , Torabian, Sajjad, Voytek, Bradley , Calhoun, Vince D. , Poldrack, Russell A. , Appelhoff, Stefan , Ashar, Yoni K. , Auer, Tibor , Baillet, Sylvain , Beltrachini, Leandro , Bortoletto, Marta , Boudreau, Mathieu , Clement, Patricia , Cohen, Alexander L. , Cohen-Adad, Julien , Iglesia-Vayá, María de la , Devinsky, Orrin , Draschkow, Dejan , Duff, Eugene Paul , DuPré, Elizabeth , Estéban, Oscar , Gau, Rémi , Ghosh, Satrajit S , Giacomel, Alessio , Gillman, Ashley , Gleeson, Padraig , Gramfort, Alexandre , Guay, Samuel , Halchenko, Yaroslav O. , Herholz, Peer , Hermes, Dora , Honey, Christopher John , Keator, David B. , Kiar, Gregory , Laird, Angela R. , Lazari, Alberto , Legarreta, Jon Haitz , Li, Adam , Love, Bradley C. , Lu, Hanzhang , Marcantoni, Eleonora , Maumet, Camille , Mazzamuto, Giacomo , Mutsaerts, Henk , Nikolaidis, Aki , Nilsonne, Gustav , Niso, Guiomar , Nørgaard, Martin Agge , Okell, Thomas W. , Oostenveld, Robert , Pernet, Cyril R , Petr, Jan , Phillips, Christophe L. M. , Poline, Jean‐Baptiste , Raamana, Pradeep Reddy , Ritter, Petra , Salo, Taylor , Spisák, Tamás , Swann, Nicole C. , Takerkart, Sylvain , Thirion, Bertrand , Varoquaux, Gaël , Welzel, Julius , Wilson, Martin , Yarkoni, Tal , Gorgolewski, Krzysztof J.

Imaging Neuroscience | February 20, 2024 | Volume: 2 | Issue: No issue available | Pages: No page available

10.1162/imag_a_00103 Get It

Abstract The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.
Cross‐sectional comparison of the role of tau burden among Down Syndrome Alzheimer disease and autosomal‐dominant Alzheimer disease
Boerwinkle, Anna H. , Henson, Rachel L. , Thippabhotla, Sharmila, Kennedy, James Tyler, Butt, Omar H. , Chen, Charles D., Christian, Bradley T. , Mapstone, Mark , Tudorascu, Dana , Cohen, Annie , Fagan, Anne M. , Price, Julie C. , Schupf, Nicole , Laymon, Charles M. , Krinsky‐McHale, Sharon J. , Lai, Florence , Rosas, H. Diana , Lott, Ira T. , Silverman, Wayne , Chhatwal, Jasmeer P. , Chui, Helena C., Farlow, Martin R. , Graff‐Radford, Neill R. , Mori, Hiroshi , Perrin, Richard J. , Salloway, Stephen , Xiong, Chengjie , Wisch, Julie K. , Gordon, Brian A. , Flores, Shaney , McKay, Nicole S. , Handen, Benjamin L. , Head, Elizabeth , Zammit, Matthew D. , Johnson, Sterling C. , Klunk, William E. , Rafii, Michael S. , O’Bryant, Sid E. , Yassa, Michael A. , Keator, David B. , Hartley, Sigan L. , Zaman, Shahid H. , Lao, Patrick , Brickman, Adam M. , Lee, Joseph H. , Allegri, Ricardo , Berman, Sarah , Chui, Helena C. , Cruchaga, Carlos , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Jucker, Mathias , Lee, Jae‐Hong , Xiong, Chengjie , Martins, Ralph N. , Sánchez‐Valle, Raquel , Schofield, Peter William , Xiong, Chengjie , Schindler, Suzanne E. , Morris, John C. , Karch, Celeste M. , Hassenstab, Jason , Benzinger, Tammie L.S. , McDade, Eric , Bateman, Randall J. , Ances, Beau M.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S14 | Pages: No page available

10.1002/alz.079102 Get It

AbstractBackgroundAdults with Down Syndrome (DS) develop Alzheimer disease (AD)‐like pathology and dementia as they age. This is attributed to triplication of the amyloid precursor protein gene. Recent work demonstrated that amyloid is elevated in DS and accumulates in a similar topography to autosomal dominant AD (ADAD). Tau accumulation is the second hallmark of AD and may be measured using tau positron emission tomography (PET) imaging. The pattern of tau accumulation remains unknown in DS.MethodIn a cross‐sectional analysis we evaluated amyloid and tau positron emission tomography (PET) in 124 participants with DS (109 cognitively stable, 8 symptomatic, 7 no consensus), 29 ADAD mutation carriers (26 asymptomatic, 3 symptomatic), and 201 cognitively normal non‐mutation carriers (CN). Regional cortical standard uptake value ratios (SUVR) for tau imaging were obtained and compared by cognitive status. Similarly, regional cortical amyloid SUVR were obtained and converted to centiloids. We then compared the magnitude of tau burden as well as spatial spread of tau across groups relative to amyloid burden.ResultCompared to CN, tau PET binding was elevated in participants with (µDS = 2.12 ± 0.22 SUVR, µADAD = 2.52 ± 0.37 SUVR) and without (µDS = 1.24 ± 0.15 SUVR, µADAD = 1.16 ± 0.19 SUVR) cognitive changes. For both groups, tau increased with increasing amyloid (centiloids). In some regions, DS had greater tau burden for a given amyloid level (centiloids) (Figure 1). There was increased spatial distribution of tau throughout the brain for participants with DS compared to CN. In contrast, tau burden was more focal in participants with ADAD with tau primarily elevated in posterior regions (Figure 2).ConclusionWhile tau burden was higher with symptomatic disease for both groups, significant differences existed in the overall amount and spatial spread. Tau spread was greatest in participants with DS and more diffuse compared to ADAD. These results indicate a substantial tau burden is present in DS, and suggest not only anti‐amyloid but also tau‐reducing agents should be considered for treating cognitive decline in adults with DS.