Jewell B Thomas1, Matthew R Brier1, Randall J Bateman1, Abraham Z Snyder2, Tammie L Benzinger2, Chengjie Xiong3, Marcus Raichle4, David M Holtzman1, Reisa A Sperling5, Richard Mayeux6, Bernardino Ghetti7, John M Ringman8, Stephen Salloway9, Eric McDade10, Martin N Rossor11, Sebastien Ourselin11, Peter R Schofield12, Colin L Masters13, Ralph N Martins14, Michael W Weiner15, Paul M Thompson16, Nick C Fox17, Robert A Koeppe18, Clifford R Jack19, Chester A Mathis20, Angela Oliver1, Tyler M Blazey2, Krista Moulder21, Virginia Buckles1, Russ Hornbeck2, Jasmeer Chhatwal22, Aaron P Schultz22, Alison M Goate23, Anne M Fagan1, Nigel J Cairns1, Daniel S Marcus2, John C Morris1, Beau M Ances1. 1. Department of Neurology, Washington University in St Louis, St Louis, Missouri. 2. Department of Radiology, Washington University in St Louis, St Louis, Missouri. 3. Division of Biostatistics, Washington University in St Louis, St Louis, Missouri. 4. Department of Neurology, Washington University in St Louis, St Louis, Missouri2Department of Radiology, Washington University in St Louis, St Louis, Missouri4Department of Anatomy and Neurobiology, Washington University in St Louis, St Louis, Missouri. 5. Department of Neurology, Brigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston. 6. Department of Neurology, Columbia University Medical Center, New York, New York. 7. Department of Pathology and Laboratory Medicine, Indiana University, Bloomington. 8. Department of Neurology, Easton Center for Alzheimer's Disease Research, David Geffen School of Medicine, University of California, Los Angeles. 9. Departments of Neurology and Psychiatry, Warren Alpert Medical School, Brown University, Providence, Rhode Island. 10. Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania. 11. Dementia Research Centre, Institute of Neurology, University College London, London, England. 12. Neuroscience Research Australia, Sydney, Australia13School of Medical Sciences, University of New South Wales, Sydney, Australia. 13. Mental Health Research Institute, University of Melbourne, Melbourne, Australia. 14. School of Medical Sciences, Edith Cowan University, Joondalup, Australia. 15. Department of Medicine, University of California, San Francisco17Department of Radiology, University of California, San Francisco18Department of Psychiatry, University of California, San Francisco. 16. Departments of Neurology and Psychiatry, Imaging Genetics Center, Laboratory of Neuroimaging, David Geffen School of Medicine at University of California, Los Angeles. 17. Dementia Research Centre, Department of Neurodegeneration, Institute of Neurology, University College of London, London, England. 18. Department of Radiology, University of Michigan, Ann Arbor. 19. Department of Radiology, Mayo Clinic, Rochester, Minnesota. 20. Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania. 21. Department of Psychiatry, Washington University in St Louis, St Louis, Missouri. 22. Department of Neurology, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston. 23. Department of Psychiatry, University of California, San Francisco.
Abstract
IMPORTANCE: Autosomal dominant Alzheimer disease (ADAD) is caused by rare genetic mutations in 3 specific genes in contrast to late-onset Alzheimer disease (LOAD), which has a more polygenetic risk profile. OBJECTIVE: To assess the similarities and differences in functional connectivity changes owing to ADAD and LOAD. DESIGN, SETTING, AND PARTICIPANTS: We analyzed functional connectivity in multiple brain resting state networks (RSNs) in a cross-sectional cohort of participants with ADAD (n = 79) and LOAD (n = 444), using resting-state functional connectivity magnetic resonance imaging at multiple international academic sites. MAIN OUTCOMES AND MEASURES: For both types of AD, we quantified and compared functional connectivity changes in RSNs as a function of dementia severity measured by the Clinical Dementia Rating Scale. In ADAD, we qualitatively investigated functional connectivity changes with respect to estimated years from onset of symptoms within 5 RSNs. RESULTS: A decrease in functional connectivity with increasing Clinical Dementia Rating scores were similar for both LOAD and ADAD in multiple RSNs. Ordinal logistic regression models constructed in one type of Alzheimer disease accurately predicted clinical dementia rating scores in the other, further demonstrating the similarity of functional connectivity loss in each disease type. Among participants with ADAD, functional connectivity in multiple RSNs appeared qualitatively lower in asymptomatic mutation carriers near their anticipated age of symptom onset compared with asymptomatic mutation noncarriers. CONCLUSIONS AND RELEVANCE: Resting-state functional connectivity magnetic resonance imaging changes with progressing AD severity are similar between ADAD and LOAD. Resting-state functional connectivity magnetic resonance imaging may be a useful end point for LOAD and ADAD therapy trials. Moreover, the disease process of ADAD may be an effective model for the LOAD disease process.
IMPORTANCE: Autosomal dominant Alzheimer disease (ADAD) is caused by rare genetic mutations in 3 specific genes in contrast to late-onset Alzheimer disease (LOAD), which has a more polygenetic risk profile. OBJECTIVE: To assess the similarities and differences in functional connectivity changes owing to ADAD and LOAD. DESIGN, SETTING, AND PARTICIPANTS: We analyzed functional connectivity in multiple brain resting state networks (RSNs) in a cross-sectional cohort of participants with ADAD (n = 79) and LOAD (n = 444), using resting-state functional connectivity magnetic resonance imaging at multiple international academic sites. MAIN OUTCOMES AND MEASURES: For both types of AD, we quantified and compared functional connectivity changes in RSNs as a function of dementia severity measured by the Clinical Dementia Rating Scale. In ADAD, we qualitatively investigated functional connectivity changes with respect to estimated years from onset of symptoms within 5 RSNs. RESULTS: A decrease in functional connectivity with increasing Clinical Dementia Rating scores were similar for both LOAD and ADAD in multiple RSNs. Ordinal logistic regression models constructed in one type of Alzheimer disease accurately predicted clinical dementia rating scores in the other, further demonstrating the similarity of functional connectivity loss in each disease type. Among participants with ADAD, functional connectivity in multiple RSNs appeared qualitatively lower in asymptomatic mutation carriers near their anticipated age of symptom onset compared with asymptomatic mutation noncarriers. CONCLUSIONS AND RELEVANCE: Resting-state functional connectivity magnetic resonance imaging changes with progressing AD severity are similar between ADAD and LOAD. Resting-state functional connectivity magnetic resonance imaging may be a useful end point for LOAD and ADAD therapy trials. Moreover, the disease process of ADAD may be an effective model for the LOAD disease process.
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