NeuroImage (Aug 2022)

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

  • 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 P Salloway,
  • Igor Yakushev,
  • John C. Morris,
  • Beau M. Ances,
  • Sarah Adams, MS,
  • Ricardo Allegri, PhD,
  • Aki Araki,
  • Nicolas Barthelemy, PhD,
  • Randall Bateman, MD,
  • Jacob Bechara, BS,
  • Tammie Benzinger, MD, PhD,
  • Sarah Berman, MD, PhD,
  • Courtney Bodge, PhD,
  • Susan Brandon, BS,
  • William (Bill) Brooks, MBBS,MPH,
  • Jared Brosch, MD, PhD,
  • Jill Buck, BSN,
  • Virginia Buckles, PhD,
  • Kathleen Carter, PhD,
  • Lisa Cash, BFA,
  • Charlie Chen, BA,
  • Jasmeer Chhatwal, MD,PhD,
  • Patricio Chrem Mendez, MD,
  • Jasmin Chua, BS,
  • Helena Chui, MD,
  • Laura Courtney, BS,
  • Carlos Cruchaga, PhD,
  • Gregory S Day, MD,
  • Chrismary DeLaCruz, BA,
  • Darcy Denner, PhD,
  • Anna Diffenbacher, MS,
  • Aylin Dincer, BS,
  • Tamara Donahue, MS,
  • Jane Douglas, MPh,
  • Duc Duong, BS,
  • Noelia Egido, BS,
  • Bianca Esposito, BS,
  • Anne Fagan, PhD,
  • Marty Farlow, MD,
  • Becca Feldman, BS,BA,
  • Colleen Fitzpatrick, MS,
  • Shaney Flores, BS,
  • Nick Fox, MD,
  • Erin Franklin, MS,
  • Nelly Joseph-Mathurin, PhD,
  • Hisako Fujii, PhD,
  • Samantha Gardener, PhD,
  • Bernardino Ghetti, MD,
  • Alison Goate, PhD,
  • Sarah Goldberg, MS,LPC,NCC,
  • Jill Goldman, MS,MPhil,CGC,
  • Alyssa Gonzalez, BS,
  • Brian Gordon, PhD,
  • Susanne Gräber-Sultan, PhD,
  • Neill Graff-Radford, MD,
  • Morgan Graham, BA,
  • Julia Gray, MS,
  • Emily Gremminger, BA,
  • Miguel Grilo, MD,
  • Alex Groves,
  • Christian Haass, PhD,
  • Lisa Häsler, MSc,
  • Jason Hassenstab, PhD,
  • Cortaiga Hellm, BA,
  • Elizabeth Herries, BA,
  • Laura Hoechst-Swisher, MS,
  • Anna Hofmann, MD,
  • Anna Hofmann,
  • David Holtzman, MD,
  • Russ Hornbeck, MSCS, MPM,
  • Yakushev Igor, MD,
  • Ryoko Ihara, MD,
  • Takeshi Ikeuchi, MD,
  • Snezana Ikonomovic, MD,
  • Kenji Ishii, MD,
  • Clifford Jack, MD,
  • Gina Jerome, MS,
  • Erik Johnson, MD, PHD,
  • Mathias Jucker, PhD,
  • Celeste Karch, PhD,
  • Stephan Käser, PHD,
  • Kensaku Kasuga, MD,
  • Sarah Keefe, BS,
  • William Klunk, MD, PHD,
  • Robert Koeppe, PHD,
  • Deb Koudelis, MHS,RN,
  • Elke Kuder-Buletta, RN,
  • Christoph Laske, PhD,
  • Allan Levey, MD, PHD,
  • Johannes Levin, MD,
  • Yan Li, PHD,
  • Oscar Lopez, MD, MD,
  • Jacob Marsh, BA,
  • Ralph Martins, PhD,
  • Neal Scott Mason, PhD,
  • Colin Masters, MD,
  • Kwasi Mawuenyega, PhD,
  • Austin McCullough, PhD Candidate,
  • Eric McDade, DO,
  • Arlene Mejia, MD,
  • Estrella Morenas-Rodriguez, MD, PhD,
  • John Morris, MD,
  • James Mountz, MD,
  • Cath Mummery, PhD,
  • N eelesh Nadkarni, MD, PhD,
  • Akemi Nagamatsu, RN,
  • Katie Neimeyer, MS,
  • Yoshiki Niimi, MD,
  • James Noble, MD,
  • Joanne Norton, MSN, RN, PMHCNS-BC,
  • Brigitte Nuscher,
  • Ulricke Obermüller,
  • Antoinette O'Connor, MRCPI,
  • Riddhi Patira, MD,
  • Richard Perrin, MD, PhD,
  • Lingyan Ping, PhD,
  • Oliver Preische, MD,
  • Alan Renton, PhD,
  • John Ringman, MD,
  • Stephen Salloway, MD,
  • Peter Schofield, PhD,
  • Michio Senda, MD, PhD,
  • Nicholas T Seyfried, D.Phil,
  • Kristine Shady, BA, BS,
  • Hiroyuki Shimada, MD, PhD,
  • Wendy Sigurdson, RN,
  • Jennifer Smith, PhD,
  • Lori Smith, PA-C,
  • Beth Snitz, PhD,
  • Hamid Sohrabi, PhD,
  • Sochenda Stephens, BS, CCRP,
  • Kevin Taddei, BS,
  • Sarah Thompson, PA-C,
  • Jonathan Vöglein, MD,
  • Peter Wang, PhD,
  • Qing Wang, PhD,
  • Elise Weamer, MPH,
  • Chengjie Xiong, PhD,
  • Jinbin Xu, PhD,
  • Xiong Xu, BS, MS

Journal volume & issue
Vol. 256
p. 119228

Abstract

Read online

“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.

Keywords