Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease

Springer Science and Business Media LLC - Tập 18 - Trang 1-17 - 2023
Peter R Millar1, Brian A Gordon2, Julie K Wisch1, Stephanie A Schultz3,4, Tammie LS Benzinger2, Carlos Cruchaga5, Jason J Hassenstab1, Laura Ibanez1,5,6, Celeste Karch5, Jorge J Llibre-Guerra1, John C Morris1, Richard J Perrin1,7, Charlene Supnet-Bell1, Chengjie Xiong8, Ricardo F Allegri9, Sarah B Berman10, Jasmeer P Chhatwal3,4, Patricio A Chrem Mendez9, Gregory S Day11, Anna Hofmann12,13, Takeshi Ikeuchi14, Mathias Jucker12,13, Jae-Hong Lee15, Johannes Levin16,17,18, Francisco Lopera19, Yoshiki Niimi20, Victor J Sánchez-González21, Peter R Schofield22,23, Ana Luisa Sosa-Ortiz24, Jonathan Vöglein16,17, Randall J Bateman1, Beau M Ances1,2, Eric M McDade1
1Department of Neurology, Washington University in St. Louis, St. Louis, USA
2Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, USA
3Department of Neurology, Harvard Medical School, Boston, USA
4 Department of Neurology, Massachusetts General Hospital, Boston, USA
5Department of Psychiatry, Washington University in St. Louis, St. Louis, USA
6NeuroGenomics & Informatics Center, Washington University in St. Louis, St. Louis, USA
7Department of Pathology & Immunology, Washington University in St. Louis, St. Louis, USA
8Department of Biostatistics, Washington University in St. Louis, St. Louis, USA
9Instituto Neurológico Fleni, Buenos Aires, Argentina
10Department of Neurology, University of Pittsburgh, Pittsburgh, USA
11Department of Neurology, Mayo Clinic, Jacksonville, USA
12German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
13Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
14Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
15Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
16Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
17German Center for Neurodegenerative Diseases, Munich, Germany
18Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
19Universidad de Antioquia. Medellín, Colombia
20Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Tokyo, Japan
21Departamento de Clínicas, CUALTOS, Universidad de Guadalajara, Tepatitlán de Morelos, Jalisco, México
22Neuroscience Research Australia, Sydney, Australia
23School of Biomedical Sciences, University of New South Wales, Sydney, Australia
24Instituto Nacional de Neurologia y Neurocirugía MVS, CDMX, Ciudad de México, Mexico

Tóm tắt

“Brain-predicted age” estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology. We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-β-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE ε4 carrier status, sex, and education. Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG. We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI.

Tài liệu tham khảo

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