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Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease

2022; Elsevier BV; Volume: 256; Linguagem: Inglês

10.1016/j.neuroimage.2022.119228

1095-9572

Peter R Millar, Patrick H. Luckett, Brian A. Gordon, Tammie L.S. Benzinger, Suzanne E. Schindler, Anne M. Fagan, Carlos Cruchaga, Randall J. Bateman, Ricardo Allegri, Mathias Jucker, Jae‐Hong Lee, Hiroshi Mori, Stephen Salloway, Igor Yakushev, John C. Morris, Beau M. Ances, Sarah Adams, Ricardo Allegri, Aki Araki, Nicolas R. Barthélemy, Randall J. Bateman, Jacob Bechara, Tammie L.S. Benzinger, Sarah Berman, Courtney Bodge, Susan Brandon, William S. Brooks, Jared R. Brosch, Jill Buck, Virginia Buckles, Kathleen Carter, Lisa Cash, Charlie Chen, Jasmeer P. Chhatwal, Patricio Chrem Méndez, Jasmin Chua, Helena Chui, Laura Courtney, Carlos Cruchaga, Gregory S. Day, Chrismary DeLaCruz, Darcy Denner, Anna Diffenbacher, Aylin Dincer, Tamara Donahue, Jane Douglas, Duc M. Duong, Noelia Egido, Bianca Esposito, Anne M. Fagan, Marty Farlow, Becca Feldman, Colleen Fitzpatrick, Shaney Flores, Nick C. Fox, Erin Franklin, Nelly Joseph‐Mathurin, Hisako Fujii, Samantha L. Gardener, Bernardino Ghetti, Alison Goate, Sarah B. Goldberg, Jill Goldman, Alyssa Gonzalez, Brian A. Gordon, Susanne Gräber‐Sultan, Neill R. Graff‐Radford, Morgan Graham, Julia Gray, Emily Gremminger, Miguel L. Grilo, Alex Groves, Christian Haass, Lisa M. Häsler, Jason Hassenstab, Cortaiga Hellm, Elizabeth Herries, Laura Hoechst-Swisher, Anna Hofmann, Anna Hofmann, David M. Holtzman, Russ C. Hornbeck, Yakushev Igor, Ryoko Ihara, Takeshi Ikeuchi, Snežana Ikonomović, Kenji Ishii, Clifford R. Jack, Gina Jerome, Erik C. B. Johnson, Mathias Jucker, Celeste M. Karch, Stephan Käser, Kensaku Kasuga, Sarah Keefe, William E. Klunk, Robert A. Koeppe, Deb Koudelis, Elke Kuder-Buletta, Christoph Laske, Allan I. Levey, Johannes Levin, Yan Li, Oscar L. López, Jacob I. Marsh, Ralph N. Martins, Neal Scott Mason, Colin L. Masters, Kwasi G. Mawuenyega, Austin McCullough, Eric McDade, Arlene Mejia, Estrella Morenas‐Rodríguez, John C. Morris, James M. Mountz, Cath Mummery, Neelesh Nadkarni, Akemi Nagamatsu, Katie Neimeyer, Yoshiki Niimi, James M. Noble, Joanne Norton, Brigitte Nuscher, Ulricke Obermüller, Antoinette O’Connor, Riddhi Patira, Richard J. Perrin, Lingyan Ping, Oliver Preische, Alan E. Renton, John M. Ringman, Stephen Salloway, Peter R. Schofield, Michio Senda, Nicholas T. Seyfried, Kristine Shady, Hiroyuki Shimada, Wendy Sigurdson, Jennifer A. Smith, Lori Smith, Beth E. Snitz, Hamid R. Sohrabi, Sochenda Stephens, Kevin Taddei, Sarah Thompson, Jonathan Vöglein, Peter Wang, Qing Wang, Elise A. Weamer, Chengjie Xiong, Jinbin Xu, Xu Xiong,

Advanced MRI Techniques and Applications

"Brain-predicted age" quantifies apparent brain age compared to normative neuroimaging trajectories. Advanced brain-predicted age has been well established in symptomatic Alzheimer disease (AD), but is underexplored in preclinical AD. Prior brain-predicted age studies have typically used structural MRI, but resting-state functional connectivity (FC) remains underexplored. Our model predicted age from FC in 391 cognitively normal, amyloid-negative controls (ages 18-89). We applied the trained model to 145 amyloid-negative, 151 preclinical AD, and 156 symptomatic AD participants to test group differences. The model accurately predicted age in the training set. FC-predicted brain age gaps (FC-BAG) were significantly older in symptomatic AD and significantly younger in preclinical AD compared to controls. There was minimal correspondence between networks predictive of age and AD. Elevated FC-BAG may reflect network disruption during symptomatic AD. Reduced FC-BAG in preclinical AD was opposite to the expected direction, and may reflect a biphasic response to preclinical AD pathology or may be driven by inconsistency between age-related vs. AD-related networks. Overall, FC-predicted brain age may be a sensitive AD biomarker.