Stefan J Teipel1,2, Enrica Cavedo3,4,5,6,7, Simone Lista3,4,5,6, Marie-Odile Habert8,9, Marie-Claude Potier10, Michel J Grothe1,2, Stephane Epelbaum4, Luisa Sambati4, Geoffroy Gagliardi4, Nicola Toschi11,12,13, Michael D Greicius14, Bruno Dubois4, Harald Hampel3,4,5,6. 1. German Center for Neurodegenerative Diseases (DZNE)-Rostock/Greifswald, Rostock, Germany. 2. Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany. 3. AXA Research Fund & Sorbonne Université Chair, Paris, France. 4. Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France. 5. Institut du Cerveau et de la Moelle Épiniére (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France. 6. Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France. 7. IRCCS Centro San Giovanni di Dio-Fatebenefratelli, Brescia, Italy. 8. Département de Médecine Nucléaire, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France. 9. Laboratoire d'Imagerie Biomédicale, Sorbonne Universités, UPMC Univ Paris 06, Inserm U 1146, CNRS UMR 7371, Paris, France. 10. ICM Institut du Cerveau et de la Moelle épinière, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France. 11. Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy. 12. Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA. 13. Harvard Medical School, Boston, MA, USA. 14. Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
Abstract
INTRODUCTION: Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals. METHODS: We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes. RESULTS: Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories. DISCUSSION: Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials.
INTRODUCTION: Cognitive change in people at risk of Alzheimer's disease (AD) such as subjective memory complainers is highly variable across individuals. METHODS: We used latent class growth modeling to identify distinct classes of nonlinear trajectories of cognitive change over 2 years follow-up from 265 subjective memory complainers individuals (age 70 years and older) of the INSIGHT-preAD cohort. We determined the effect of cortical amyloid load, hippocampus and basal forebrain volumes, and education on the cognitive trajectory classes. RESULTS: Latent class growth modeling identified distinct nonlinear cognitive trajectories. Education was associated with higher performing trajectories, whereas global amyloid load and basal forebrain atrophy were associated with lower performing trajectories. DISCUSSION: Distinct classes of cognitive trajectories were associated with risk and protective factors of AD. These associations support the notion that the identified cognitive trajectories reflect different risk for AD that may be useful for selecting high-risk individuals for intervention trials.
Authors: Rosalinde E R Slot; Sietske A M Sikkes; Johannes Berkhof; Henry Brodaty; Rachel Buckley; Enrica Cavedo; Efthimios Dardiotis; Francoise Guillo-Benarous; Harald Hampel; Nicole A Kochan; Simone Lista; Tobias Luck; Paul Maruff; José Luis Molinuevo; Johannes Kornhuber; Barry Reisberg; Steffi G Riedel-Heller; Shannon L Risacher; Susanne Roehr; Perminder S Sachdev; Nikolaos Scarmeas; Philip Scheltens; Melanie B Shulman; Andrew J Saykin; Sander C J Verfaillie; Pieter Jelle Visser; Stephanie J B Vos; Michael Wagner; Steffen Wolfsgruber; Frank Jessen; Wiesje M van der Flier Journal: Alzheimers Dement Date: 2018-12-13 Impact factor: 21.566
Authors: Frank Jessen; Rebecca E Amariglio; Rachel F Buckley; Wiesje M van der Flier; Ying Han; José Luis Molinuevo; Laura Rabin; Dorene M Rentz; Octavio Rodriguez-Gomez; Andrew J Saykin; Sietske A M Sikkes; Colette M Smart; Steffen Wolfsgruber; Michael Wagner Journal: Lancet Neurol Date: 2020-01-17 Impact factor: 44.182
Authors: Elena Lobo; Patricia Gracia-García; Antonio Lobo; Pedro Saz; Concepción De-la-Cámara Journal: Int J Environ Res Public Health Date: 2021-07-02 Impact factor: 3.390
Authors: Zimu Wu; Robyn L Woods; Rory Wolfe; Elsdon Storey; Trevor T J Chong; Raj C Shah; Suzanne G Orchard; John J McNeil; Anne M Murray; Joanne Ryan Journal: Alzheimers Dement (Amst) Date: 2021-05-02