Robert X Smith1, Jeremy F Strain1, Aaron Tanenbaum1, Anne M Fagan1,2, Jason Hassenstab1, Eric McDade1, Suzanne E Schindler1, Brian A Gordon3,2, Chengjie Xiong4, Jasmeer Chhatwal5, Clifford Jack6, Celeste Karch2,7, Sarah Berman8, Jared R Brosch9, James J Lah10, Adam M Brickman11, David M Cash12, Nick C Fox12, Neill R Graff-Radford13, Johannes Levin14, James Noble11, David M Holtzman1,2, Colin L Masters15, Martin R Farlow9, Christoph Laske16, Peter R Schofield17, Daniel S Marcus3, John C Morris1,2, Tammie L S Benzinger3,2, Randall J Bateman1,2, Beau M Ances1,2. 1. Department of Neurology, Washington University in Saint Louis, St. Louis, Missouri, USA. 2. Hope Center for Neurological Disorders, Knight ADRC, Washington University, St. Louis, Missouri, USA. 3. Department of Radiology, Washington University in Saint Louis, St. Louis, Missouri, USA. 4. Department of Biostatistics, Washington University in Saint Louis, St. Louis, Missouri, USA. 5. Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA. 6. Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA. 7. Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA. 8. Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. 9. Department of Neurology, Indiana University, Indianapolis, Indiana, USA. 10. Department of Neurology, Emory University, Atlanta, Georgia, USA. 11. Department of Neurology, Columbia University, New York, New York, USA. 12. Department of Neurodegenerative Disease, Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom. 13. Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA. 14. German Center for Neurodegenerative Disease (DZNE) Munich, Munich, Germany. 15. The Florey Institute, University of Melbourne, Parkvile, Australia. 16. Eberhard Karls University of Tubingen, Tubingen, Germany. 17. Neuroscience Research Australia and School of Medical Sciences, The University of New South Wales (UNSW) Sydney, Sydney, Australia.
Abstract
Aim: Identify a global resting-state functional connectivity (gFC) signature in mutation carriers (MC) from the Dominantly Inherited Alzheimer Network (DIAN). Assess the gFC with regard to amyloid (A), tau (T), and neurodegeneration (N) biomarkers, and estimated years to symptom onset (EYO). Introduction: Cross-sectional measures were assessed in MC (n = 171) and mutation noncarrier (NC) (n = 70) participants. A functional connectivity (FC) matrix that encompassed multiple resting-state networks was computed for each participant. Methods: A global FC was compiled as a single index indicating FC strength. The gFC signature was modeled as a nonlinear function of EYO. The gFC was linearly associated with other biomarkers used for assessing the AT(N) framework, including cerebrospinal fluid (CSF), positron emission tomography (PET) molecular biomarkers, and structural magnetic resonance imaging. Results: The gFC was reduced in MC compared with NC participants. When MC participants were differentiated by clinical dementia rating (CDR), the gFC was significantly decreased in MC CDR >0 (demented) compared with either MC CDR 0 (cognitively normal) or NC participants. The gFC varied nonlinearly with EYO and initially decreased at EYO = -24 years, followed by a stable period followed by a further decline near EYO = 0 years. Irrespective of EYO, a lower gFC associated with values of amyloid PET, CSF Aβ1-42, CSF p-tau, CSF t-tau, 18F-fluorodeoxyglucose, and hippocampal volume. Conclusions: The gFC correlated with biomarkers used for defining the AT(N) framework. A biphasic change in the gFC suggested early changes associated with CSF amyloid and later changes associated with hippocampal volume.
Aim: Identify a global resting-state functional connectivity (gFC) signature in mutation carriers (MC) from the Dominantly Inherited Alzheimer Network (DIAN). Assess the gFC with regard to amyloid (A), tau (T), and neurodegeneration (N) biomarkers, and estimated years to symptom onset (EYO). Introduction: Cross-sectional measures were assessed in MC (n = 171) and mutation noncarrier (NC) (n = 70) participants. A functional connectivity (FC) matrix that encompassed multiple resting-state networks was computed for each participant. Methods: A global FC was compiled as a single index indicating FC strength. The gFC signature was modeled as a nonlinear function of EYO. The gFC was linearly associated with other biomarkers used for assessing the AT(N) framework, including cerebrospinal fluid (CSF), positron emission tomography (PET) molecular biomarkers, and structural magnetic resonance imaging. Results: The gFC was reduced in MC compared with NC participants. When MC participants were differentiated by clinical dementia rating (CDR), the gFC was significantly decreased in MC CDR >0 (demented) compared with either MC CDR 0 (cognitively normal) or NC participants. The gFC varied nonlinearly with EYO and initially decreased at EYO = -24 years, followed by a stable period followed by a further decline near EYO = 0 years. Irrespective of EYO, a lower gFC associated with values of amyloid PET, CSF Aβ1-42, CSF p-tau, CSF t-tau, 18F-fluorodeoxyglucose, and hippocampal volume. Conclusions: The gFC correlated with biomarkers used for defining the AT(N) framework. A biphasic change in the gFC suggested early changes associated with CSF amyloid and later changes associated with hippocampal volume.
Entities:
Keywords:
18F-fluorodeoxyglucose (FDG); amyloid; autosomal dominant Alzheimer disease; cerebrospinal fluid (CSF); estimated years to onset (EYO); hippocampus; positron emission tomography (PET); resting-state functional connectivity; tau
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