TY - JOUR
T1 - Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease
AU - Millar, Peter R.
AU - Gordon, Brian A.
AU - Wisch, Julie K.
AU - Schultz, Stephanie A.
AU - Benzinger, Tammie Ls
AU - Cruchaga, Carlos
AU - Hassenstab, Jason J.
AU - Ibanez, Laura
AU - Karch, Celeste
AU - Llibre-Guerra, Jorge J.
AU - Morris, John C.
AU - Perrin, Richard J.
AU - Supnet-Bell, Charlene
AU - Xiong, Chengjie
AU - Allegri, Ricardo F.
AU - Berman, Sarah B.
AU - Chhatwal, Jasmeer P.
AU - Chrem Mendez, Patricio A.
AU - Day, Gregory S.
AU - Hofmann, Anna
AU - Ikeuchi, Takeshi
AU - Jucker, Mathias
AU - Lee, Jae Hong
AU - Levin, Johannes
AU - Lopera, Francisco
AU - Niimi, Yoshiki
AU - Sánchez-González, Victor J.
AU - Schofield, Peter R.
AU - Sosa-Ortiz, Ana Luisa
AU - Vöglein, Jonathan
AU - Bateman, Randall J.
AU - Ances, Beau M.
AU - McDade, Eric M.
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - Background: “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. Methods: 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. Results: 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. Conclusions: 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.
AB - Background: “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. Methods: 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. Results: 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. Conclusions: 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.
KW - Alzheimer disease
KW - Brain aging
KW - Machine learning
KW - Structural MRI
UR - http://www.scopus.com/inward/record.url?scp=85180172035&partnerID=8YFLogxK
U2 - 10.1186/s13024-023-00688-3
DO - 10.1186/s13024-023-00688-3
M3 - Article
C2 - 38111006
AN - SCOPUS:85180172035
SN - 1750-1326
VL - 18
JO - Molecular neurodegeneration
JF - Molecular neurodegeneration
IS - 1
M1 - 98
ER -