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000266753 1001_ $$00000-0003-4588-739X$$aMillar, Peter R$$b0
000266753 245__ $$aAdvanced structural brain aging in preclinical autosomal dominant Alzheimer disease.
000266753 260__ $$aLondon$$bBiomed Central$$c2023
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000266753 520__ $$a'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.
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000266753 650_7 $$2Other$$aAlzheimer disease
000266753 650_7 $$2Other$$aBrain aging
000266753 650_7 $$2Other$$aMachine learning
000266753 650_7 $$2Other$$aStructural MRI
000266753 650_7 $$2NLM Chemicals$$aAmyloid beta-Peptides
000266753 650_7 $$2NLM Chemicals$$aAmyloid
000266753 650_7 $$2NLM Chemicals$$aBiomarkers
000266753 650_7 $$2NLM Chemicals$$atau Proteins
000266753 650_2 $$2MeSH$$aHumans
000266753 650_2 $$2MeSH$$aAlzheimer Disease
000266753 650_2 $$2MeSH$$aAmyloid beta-Peptides: metabolism
000266753 650_2 $$2MeSH$$aBrain: metabolism
000266753 650_2 $$2MeSH$$aAmyloid
000266753 650_2 $$2MeSH$$aAging
000266753 650_2 $$2MeSH$$aBiomarkers
000266753 650_2 $$2MeSH$$aPositron-Emission Tomography
000266753 650_2 $$2MeSH$$atau Proteins: genetics
000266753 650_2 $$2MeSH$$atau Proteins: metabolism
000266753 7001_ $$aGordon, Brian A$$b1
000266753 7001_ $$aWisch, Julie K$$b2
000266753 7001_ $$aSchultz, Stephanie A$$b3
000266753 7001_ $$aBenzinger, Tammie Ls$$b4
000266753 7001_ $$aCruchaga, Carlos$$b5
000266753 7001_ $$aHassenstab, Jason J$$b6
000266753 7001_ $$aIbanez, Laura$$b7
000266753 7001_ $$aKarch, Celeste$$b8
000266753 7001_ $$aLlibre-Guerra, Jorge J$$b9
000266753 7001_ $$aMorris, John C$$b10
000266753 7001_ $$aPerrin, Richard J$$b11
000266753 7001_ $$aSupnet-Bell, Charlene$$b12
000266753 7001_ $$aXiong, Chengjie$$b13
000266753 7001_ $$aAllegri, Ricardo F$$b14
000266753 7001_ $$aBerman, Sarah B$$b15
000266753 7001_ $$aChhatwal, Jasmeer P$$b16
000266753 7001_ $$aChrem Mendez, Patricio A$$b17
000266753 7001_ $$aDay, Gregory S$$b18
000266753 7001_ $$0P:(DE-2719)2814244$$aHofmann, Anna$$b19
000266753 7001_ $$aIkeuchi, Takeshi$$b20
000266753 7001_ $$0P:(DE-2719)2000010$$aJucker, Mathias$$b21
000266753 7001_ $$0P:(DE-HGF)0$$aLee, Jae-Hong$$b22
000266753 7001_ $$0P:(DE-2719)2811659$$aLevin, Johannes$$b23
000266753 7001_ $$aLopera, Francisco$$b24
000266753 7001_ $$aNiimi, Yoshiki$$b25
000266753 7001_ $$aSánchez-González, Victor J$$b26
000266753 7001_ $$aSchofield, Peter R$$b27
000266753 7001_ $$aSosa-Ortiz, Ana Luisa$$b28
000266753 7001_ $$0P:(DE-2719)2811820$$aVöglein, Jonathan$$b29
000266753 7001_ $$aNetwork, Dominantly Inherited Alzheimer$$b30$$eCollaboration Author
000266753 7001_ $$aBateman, Randall J$$b31
000266753 7001_ $$aAnces, Beau M$$b32
000266753 7001_ $$aMcDade, Eric M$$b33
000266753 773__ $$0PERI:(DE-600)2244557-2$$a10.1186/s13024-023-00688-3$$gVol. 18, no. 1, p. 98$$n1$$p98$$tMolecular neurodegeneration$$v18$$x1750-1326$$y2023
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