Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Dincer, Aylin; Gordon, Brian A.; Hari-Raj, Amrita; Keefe, Sarah; Flores, Shaney; McKay, Nicole S.; Paulick, Angela M.; Lewis, Kristine E Shady; Feldman, Rebecca L.; Hornbeck, Russ C.; Allegri, Ricardo; Ances, Beau M.; Berman, Sarah B.; Brickman, Adam M.; Brooks, William S.; Cash, David M.; Chhatwal, Jasmeer P.; Farlow, Martin R.; Fougère, Christian la; Fox, Nick C.; Fulham, Michael; Jack, Clifford R.; Joseph‐Mathurin, Nelly; Karch, Celeste M.; Lee, Athene; Levin, Johannes; Masters, Colin L.; McDade, Eric; Oh, Hwamee; Perrin, Richard J.; Raji, Cyrus A.; Salloway, Stephen; Schofield, Peter R.; Su, Yi; Villemagne, Victor L.; Wang, Qing; Weiner, Michael W.; Xiong, Chengjie; Yakushev, Igor; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S.

doi:10.1016/j.nicl.2020.102491

Cited by 26 publications

(35 citation statements)

References 72 publications

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“…Total hippocampal volumes were obtained on a T1-weighted image with the use of automated FreeSurfer 5.3. segmentation as previously described [ 24 ]. AD cortical signature thickness was also obtained from the T1-weighted image through an ROI cortical map representing the specific brain regions most susceptible to AD-related cortical atrophy as described previously [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

Intracranial internal carotid artery calcification is not predictive of future cognitive decline

et al. 2022

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Background Intracranial internal carotid artery (ICA) calcification is a common incidental finding in non-contrast head CT. We evaluated the predictive value of ICAC (ICAC) for future risk of cognitive decline and compared the results with conventional imaging biomarkers of dementia. Methods In a retrospective observational cohort, we included 230 participants with a PET-CT scan within 18 months of a baseline clinical assessment and longitudinal imaging assessments. Intracranial ICAC was quantified on baseline CT scans using the Agatson calcium score, and the association between baseline ICA calcium scores and the risk of conversion from a CDR of zero in baseline to a persistent CDR > 0 at any follow-up visit, as well as longitudinal changes in cognitive scores, were evaluated through linear and mixed regression models. We also evaluated the association of conventional imaging biomarkers of dementia with longitudinal changes in cognitive scores and a potential indirect effect of ICAC on cognition through these biomarkers. Results Baseline ICA calcium score could not distinguish participants who converted to CDR > 0. ICA calcium score was also unable to predict longitudinal changes in cognitive scores, imaging biomarkers of small vessel disease such as white matter hyperintensities (WMH) volume, or AD such as hippocampal volume, AD cortical signature thickness, and amyloid burden. Severity of intracranial ICAC increased with age and in men. Higher WMH volume and amyloid burden as well as lower hippocampal volume and AD cortical signature thickness at baseline predicted lower Mini-Mental State Exam scores at longitudinal follow-up. Baseline ICAC was indirectly associated with longitudinal cognitive decline, fully mediated through WMH volume. Conclusions In elderly and preclinical AD populations, atherosclerosis of large intracranial vessels as demonstrated through ICAC is not directly associated with a future risk of cognitive impairment, or progression of imaging biomarkers of AD or small vessel disease.

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Section: Methodsmentioning

confidence: 99%

Intracranial internal carotid artery calcification is not predictive of future cognitive decline

et al. 2022

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“…Previous work has identi ed that cortical thickness decreases with the onset of AD (28-30). We calculated the average cortical thickness (30).…”

Section: Structural Mrimentioning

confidence: 99%

Proteomic Clusters Underlie Heterogeneity in Preclinical AD Progression

Wisch

Butt

Gordon

et al. 2022

Preprint

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Background: Heterogeneity in progression to AD poses challenges for both clinical prognosis and clinical trial implementation. In the absence of a well-defined understanding of future disease trajectory, participants may receive unnecessary treatment or true effects of pharmacological intervention may be obscured. We identified early differences in preclinical Alzheimer Disease (AD) biomarkers, assessed patterns for developing preclinical AD across the Amyloid-Tau-(Neurodegeneration) (AT(N)) framework, and considered potential sources of difference by analyzing the CSF proteome.Methods: 108 participants enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center (ADRC) who completed four or more lumbar punctures and were cognitively normal at baseline were included. Cerebrospinal fluid (CSF) measures of Aβ42, pTau181, and Neurofilament Light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including positron emission tomography (PET) amyloid and tau and structural magnetic resonance imaging (MRI) were repeatedly obtained when available. This allowed for staging individuals according to the AT(N) framework.Results and Conclusion: Growth mixture modeling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and CSF Aβ42. Two groups (AD Biomarker Positive and AD Biomarker Intermediate) had distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were successfully re-classified using only proteomic profiles (AUCAD Biomarker Positive vs AD Biomarker Negatives = 0.970, AUCAD Biomarker Positive vs. Intermediate AD Biomarkers = 0.750, AUCIntermediate AD Biomarkers vs. AD Biomarker Negative = 0.698). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified individuals who became AD Biomarker Positive before age 50. A second group, AD Biomarker Intermediate, developed elevated CSF ptau181 in their mid-60’s before becoming amyloid positive in their mid-70’s. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing vs. other agents) in clinical trials. CSF proteome analysis highlighted additional potential opportunities for non-AT(N) focused therapies, including blood brain barrier-, liver-, and neuroinflammatory-related targets.

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“…b) Total hippocampal volume and AD cortical signature thickness Total hippocampal volumes were obtained on a T1-weighted image with the use of automated FreeSurfer segmentation as previously described (23). AD cortical signature thickness was also obtained from the T1-weighted image through an ROI cortical map representing the speci c brain regions most susceptible to AD-related cortical atrophy as described previously (24).…”

Section: Mri Acquisition and Processingmentioning

confidence: 99%

“…volume: white matter hyperintensities volume; AA: African-American; C: Caucasian; Nat: Native American; U: unknown race; Centiloid: measure of global amyloid disposition based on conversion of PIB or AV45 PET SUVRs to a standardized scale; AD cortical signature thickness: cortical thickness in signature regions affected in Alzheimer disease (seeDincer et al 2020). Where variables did not have a normal distribution median ± interquartile range (IQR) or minimum and maximum values were reported.…”

mentioning

confidence: 99%

“…Control: participants with CDR = 0 throughout all visits; Converter: participants converting from CDR = 0 to CDR > 0 in any of the follow-up visits; Impaired: participants with CDR > 0 in the baseline visit; MMSE: Mini Mental-State Examination; CDR: Clinical Dementia Rating Scale; CDR-SB: Clinical Dementia Rating Scale Sum of Boxes; PACC: Preclinical Alzheimer Cognitive Composite; WMH volume: white matter hyperintensities volume; AA: African-American; C: Caucasian; Nat: Native American; U: unknown race; Centiloid: measure of global amyloid disposition based on conversion of PIB or AV45 PET SUVRs to a standardized scale; AD cortical signature thickness: cortical thickness in signature regions affected in Alzheimer disease (seeDincer et al 2020). Where variables did not have a normal distribution median ± interquartile range (IQR) or minimum and maximum values were reported.…”

mentioning

confidence: 99%

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Intracranial Internal Carotid Artery Calcification Is Not Predictive of Future Cognitive Decline

Rahmani

Nguyen

Chen

et al. 2021

Preprint

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BackgroundIntracranial internal carotid artery (ICA) calcification is a common incidental finding in non-contrast head CT. We evaluated the predictive value of ICA calcification for future risk of dementia and compared the results with conventional imaging biomarkers of dementia.MethodsIn a retrospective observational cohort, we included 230 participants with a PET-CT scan within 18 months of a baseline clinical assessment and longitudinal imaging assessments. Intracranial ICA calcification was quantified on baseline CT scans using the Agatson calcium score. The ability of baseline ICA calcification to discriminate between a control group (participants who maintained a Clinical Dementia Rating (CDR™) score of zero over all follow-up visits) and a converter group (participants who had a baseline CDR of zero but received a persistent CDR>0 at any follow-up visit) was evaluated along with the predictive value of baseline ICA calcification for longitudinal clinical and imaging biomarkers. ResultsBaseline ICA calcium score could not distinguish participants who converted to CDR>0. ICA calcium score was also unable to predict longitudinal changes in cognitive scores, imaging biomarkers of small vessel disease such as white matter hyperintensities (WMH) volume, or AD such as hippocampal volume, AD cortical signature thickness, and amyloid burden. Severity of intracranial ICA calcification increased with age, male sex, and higher WMH volumes at baseline visit. Higher WMH volume and amyloid burden as well as lower hippocampal volume and AD cortical signature thickness at baseline predicted lower Mini-Mental State Exam scores at longitudinal follow-up. Baseline ICA calcification was indirectly associated with longitudinal cognitive decline, fully mediated through WMH volume.ConclusionsIn elderly and preclinical AD populations, atherosclerosis of large intracranial vessels as demonstrated through ICA calcification is not directly associated with a future risk of dementia, cognitive impairment, or progression of imaging biomarkers of AD or small vessel disease.

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Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease

Cited by 26 publications

References 72 publications

Intracranial internal carotid artery calcification is not predictive of future cognitive decline

Intracranial internal carotid artery calcification is not predictive of future cognitive decline

Proteomic Clusters Underlie Heterogeneity in Preclinical AD Progression

Intracranial Internal Carotid Artery Calcification Is Not Predictive of Future Cognitive Decline

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