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Downstream Biomarker Effects of Gantenerumab or Solanezumab in Dominantly Inherited Alzheimer Disease: The DIAN-TU-001 Randomized Clinical Trial. JAMA Neurol 2024:2817630. [PMID: 38683602 PMCID: PMC11059071 DOI: 10.1001/jamaneurol.2024.0991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 02/01/2024] [Indexed: 05/01/2024]
Abstract
Importance Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD). Objective To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment. Design, Setting, and Participants From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed. Interventions In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks. Main Outcomes and Measures Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3-like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL. Results Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] β = -242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] β = -0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] β = -0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] β = -0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] β = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] β = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] β = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo. Conclusions and Relevance This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification. Trial Registration ClinicalTrials.gov Identifier: NCT04623242.
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Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease. Brain Commun 2024; 6:fcae081. [PMID: 38505230 PMCID: PMC10950051 DOI: 10.1093/braincomms/fcae081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 02/01/2024] [Accepted: 03/14/2024] [Indexed: 03/21/2024] Open
Abstract
Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.
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Antecedents of mind wandering states in healthy aging and mild cognitive impairment. Neuropsychology 2024:2024-51315-001. [PMID: 38330359 DOI: 10.1037/neu0000941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024] Open
Abstract
OBJECTIVE Mind wandering refers to periods of internally directed attention and comprises up to 30% or more of our waking thoughts. Frequent mind wandering can be detrimental to ongoing task performance. We aim to determine whether rates of mind wandering change in healthy aging and mild cognitive impairment and how differences in mind wandering contribute to differences in attention and working memory. METHOD We administered a standard behavioral task, the Sustained Attention to Response Test, to measure mind wandering in healthy younger adults (N = 66), healthy older adults (N = 51), and adults with cognitive impairment (N = 38), that was completed daily for 3 weeks. The N-back test was also administered at a reduced frequency as a measure of working memory performance. RESULTS Generally speaking, averaged across 3 weeks of testing, relative to healthy older adults, mind wandering was higher in younger adults and in cognitive impairment, although the specific patterns varied across mind wandering states. Multiple states of mind wandering also predicted working memory performance; however, reaction time variability tended to be the best predictor based on model comparisons. Each state was also modestly associated with different dispositional factors including mood and Agreeableness. CONCLUSIONS Patterns of mind wandering change across healthy aging and cognitive impairment and are related to individual differences in multiple dispositional factors and also working memory performance. These results suggest that different states of mind wandering should be measured and accounted for when modeling cognitive change in healthy and pathological aging. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease. Mol Neurodegener 2023; 18:98. [PMID: 38111006 PMCID: PMC10729487 DOI: 10.1186/s13024-023-00688-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/28/2023] [Indexed: 12/20/2023] Open
Abstract
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.
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Location of pathogenic variants in PSEN1 impacts progression of cognitive, clinical, and neurodegenerative measures in autosomal-dominant Alzheimer's disease. Aging Cell 2023; 22:e13871. [PMID: 37291760 PMCID: PMC10410059 DOI: 10.1111/acel.13871] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/30/2023] [Accepted: 05/03/2023] [Indexed: 06/10/2023] Open
Abstract
Although pathogenic variants in PSEN1 leading to autosomal-dominant Alzheimer disease (ADAD) are highly penetrant, substantial interindividual variability in the rates of cognitive decline and biomarker change are observed in ADAD. We hypothesized that this interindividual variability may be associated with the location of the pathogenic variant within PSEN1. PSEN1 pathogenic variant carriers participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study were grouped based on whether the underlying variant affects a transmembrane (TM) or cytoplasmic (CY) protein domain within PSEN1. CY and TM carriers and variant non-carriers (NC) who completed clinical evaluation, multimodal neuroimaging, and lumbar puncture for collection of cerebrospinal fluid (CSF) as part of their participation in DIAN were included in this study. Linear mixed effects models were used to determine differences in clinical, cognitive, and biomarker measures between the NC, TM, and CY groups. While both the CY and TM groups were found to have similarly elevated Aβ compared to NC, TM carriers had greater cognitive impairment, smaller hippocampal volume, and elevated phosphorylated tau levels across the spectrum of pre-symptomatic and symptomatic phases of disease as compared to CY, using both cross-sectional and longitudinal data. As distinct portions of PSEN1 are differentially involved in APP processing by γ-secretase and the generation of toxic β-amyloid species, these results have important implications for understanding the pathobiology of ADAD and accounting for a substantial portion of the interindividual heterogeneity in ongoing ADAD clinical trials.
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A flexible modeling approach for biomarker-based computation of absolute risk of Alzheimer's disease dementia. Alzheimers Dement 2023; 19:1452-1465. [PMID: 36178120 PMCID: PMC10060442 DOI: 10.1002/alz.12781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 06/15/2022] [Accepted: 07/21/2022] [Indexed: 01/19/2023]
Abstract
INTRODUCTION As Alzheimer's disease (AD) biomarkers rapidly develop, tools are needed that accurately and effectively communicate risk of AD dementia. METHODS We analyzed longitudinal data from >10,000 cognitively unimpaired older adults. Five-year risk of AD dementia was modeled using survival analysis. RESULTS A demographic model was developed and validated on independent data with area under the receiver operating characteristic curve (AUC) for 5-year prediction of AD dementia of 0.79. Clinical and cognitive variables (AUC = 0.79), and apolipoprotein E genotype (AUC = 0.76) were added to the demographic model. We then incorporated the risk computed from the demographic model with hazard ratios computed from independent data for amyloid positron emission tomography status and magnetic resonance imaging hippocampal volume (AUC = 0.84), and for plasma amyloid beta (Aβ)42/Aβ40 (AUC = 0.82). DISCUSSION An adaptive tool was developed and validated to compute absolute risks of AD dementia. This approach allows for improved accuracy and communication of AD risk among cognitively unimpaired older adults.
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Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study. eLife 2023; 12:e81869. [PMID: 36607335 PMCID: PMC9988262 DOI: 10.7554/elife.81869] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 12/30/2022] [Indexed: 01/07/2023] Open
Abstract
Background Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. Methods We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. Results All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. Conclusions Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. Funding This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer's Association (SG-20-690363-DIAN).
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Diagnostic accuracy of the Stricker Learning Span and Mayo Test Drive Composite for amnestic Mild Cognitive Impairment. Alzheimers Dement 2022. [DOI: 10.1002/alz.063190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Differential impact of APOE genetic variants on autosomal dominant‐ and sporadic‐ Alzheimer disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.068309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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SORTOUT‐AB: A Study of Race to Understand Alzheimer Biomarkers. Alzheimers Dement 2022. [DOI: 10.1002/alz.066301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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The COEQUAL Registry: Creating Opportunities to Increase Health Equity & Equality for Persons at Risk for AD/ADRD. Alzheimers Dement 2022. [DOI: 10.1002/alz.064300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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A More Efficient Outcome for Alzheimer Disease Research: the Item Response Theory Based Score for the Clinical Dementia Rating (CDR
®
). Alzheimers Dement 2022. [DOI: 10.1002/alz.062591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Progressive white matter injury in autosomal dominant Alzheimer’s disease is strongly associated with cerebral microbleeds and neurodegeneration. Alzheimers Dement 2022. [DOI: 10.1002/alz.066715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Convergent and criterion validity of a computer adaptive self‐administered word list memory test and the Mayo Test Drive composite: correlations with traditional measures and group difference by PET imaging biomarker status in persons without dementia. Alzheimers Dement 2022. [DOI: 10.1002/alz.063723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Baseline White Matter Neuroinflammation Predicts Cognitive Decline in Alzheimer Disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.063781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Comparison of amyloid accumulation between Down syndrome and autosomal‐dominant Alzheimer disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.064684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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AD‐causing variants that affect
PSEN1
transmembrane domains are associated with faster neurodegeneration and cognitive decline compared to those affecting cytoplasmic domains. Alzheimers Dement 2022. [DOI: 10.1002/alz.068221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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AD‐causing variants that affect
PSEN1
transmembrane domains are associated with faster neurodegeneration and cognitive decline compared to those affecting cytoplasmic domains. Alzheimers Dement 2022. [DOI: 10.1002/alz.067186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Comparison of amyloid accumulation between Down syndrome and autosomal‐dominant Alzheimer disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.063959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Baseline White Matter Neuroinflammation Predicts Cognitive Decline in Alzheimer Disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.063755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Resilience and Reserve mechanisms underlying clinical‐cognitive progression in Dominant Inherited Alzheimer’s Disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.068763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Modeling functional and structural brain‐predicted age in relation to Alzheimer disease and cognition. Alzheimers Dement 2022. [DOI: 10.1002/alz.060606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Neurofilament Light Predicts Decline in Attention but Not Episodic Memory in Preclinical Alzheimer's Disease. J Alzheimers Dis 2020; 74:1119-1129. [PMID: 32144992 PMCID: PMC7183899 DOI: 10.3233/jad-200018] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Cerebrospinal fluid tau and neurofilament light (NfL) are two biomarkers of neurodegeneration in Alzheimer's disease. Previous reports have shown that the influence of tau on cognitive decline depends on levels of amyloid burden whereas NfL predicts decline independently of amyloid. Most studies use a global cognitive composite as the primary outcome, and it is unknown if critical cognitive domain scores are similarly sensitive to rates of decline due to neurodegeneration. OBJECTIVE To examine the unique contribution of amyloid, tau, and NfL to rates of cognitive decline in multiple cognitive composites in a cognitively healthy, middle-aged to older adult cohort. METHODS A total of 255 participants (55% female; mean age = 66.2 years, range = 42.5-86.7 years) completed CSF studies and serial cognitive assessments to measure global cognition, episodic memory, and attentional control. Linear mixed effects models were used to examine rates of change on each composite score as a function of baseline biomarker levels. RESULTS Total tau predicted decline in attention regardless of amyloid status, but the relationship to global cognition and episodic memory was dependent on amyloid, replicating prior literature. NfL predicted decline in attention and global cognition, but not memory, and this effect was independent of amyloid status. CONCLUSIONS These findings suggest that NfL can be used to monitor cognitive decline in aging and Alzheimer's disease and that an attentional control composite may be a better outcome for tracking general neurodegenerative effects on cognition.
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Two-period linear mixed effects models to analyze clinical trials with run-in data when the primary outcome is continuous: Applications to Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2019; 5:450-457. [PMID: 31517032 PMCID: PMC6732759 DOI: 10.1016/j.trci.2019.07.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Introduction Study outcomes can be measured repeatedly based on the clinical trial protocol before randomization during what is known as the “run-in” period. However, it has not been established how best to incorporate run-in data into the primary analysis of the trial. Methods We proposed two-period (run-in period and randomization period) linear mixed effects models to simultaneously model the run-in data and the postrandomization data. Results Compared with the traditional models, the two-period linear mixed effects models can increase the power up to 15% and yield similar power for both unequal randomization and equal randomization. Discussion Given that analysis of run-in data using the two-period linear mixed effects models allows more participants (unequal randomization) to be on the active treatment with similar power to that of the equal-randomization trials, it may reduce the dropout by assigning more participants to the active treatment and thus improve the efficiency of AD clinical trials.
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Emerging cerebrospinal fluid biomarkers in autosomal dominant Alzheimer's disease. Alzheimers Dement 2019; 15:655-665. [PMID: 30846386 PMCID: PMC6511459 DOI: 10.1016/j.jalz.2018.12.019] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 12/17/2018] [Accepted: 12/29/2018] [Indexed: 01/21/2023]
Abstract
INTRODUCTION Four less well-studied but promising "emerging" cerebrospinal fluid (CSF) biomarkers are elevated in late-onset Alzheimer disease (AD): neurogranin, synaptosomal-associated protein-25 (SNAP-25), visinin-like protein 1 (VILIP-1), and chitinase-3-like protein 1 (YKL-40). METHODS CSF neurogranin, SNAP-25, VILIP-1, and YKL-40 were measured in families carrying autosomal-dominant AD mutations. RESULTS The four emerging CSF biomarkers were significantly elevated in the mutation carriers (n = 235) versus noncarriers (n = 145). CSF SNAP-25, VILIP-1, and YKL-40 were altered very early in the AD time course, approximately 15-19 years before estimated symptom onset. All CSF biomarkers predicted important AD-related outcomes including performance on a cognitive composite, brain amyloid burden as measured by amyloid positron emission tomography, and the estimated years from symptom onset. DISCUSSION Early abnormalities in CSF tTau, pTau, SNAP-25, VILIP-1, and YKL-40 suggest that synaptic damage, neuronal injury, and neuroinflammation begin shortly after the commencement of brain amyloid accumulation.
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Relative neuron loss in hippocampal sclerosis of aging and Alzheimer's disease. Ann Neurol 2018; 84:741-753. [PMID: 30246887 DOI: 10.1002/ana.25344] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 09/19/2018] [Accepted: 09/19/2018] [Indexed: 12/26/2022]
Abstract
OBJECTIVE To characterize the pattern of neuron loss in hippocampal sclerosis of aging (HS-Aging) and age-related diseases and to evaluate its contribution to cognitive impairment in the elderly. METHODS Participants (n = 1,361) came from longitudinal observational studies of aging at the Knight Alzheimer Disease Research Center, Washington University (St. Louis, MO). Relative neuron loss in the hippocampus of HS-Aging was measured using unbiased stereological methods. Transactive response DNA-binding protein of 43 kDa (TDP-43) proteinopathy, a putative marker of HS-Aging, was assessed. Clinical and cognitive data were analyzed using parametric statistical methods. RESULTS Ninety-three cases had HS-Aging (6.8%), 8 cases had "pure" HS-Aging, and 37 cases had comorbid intermediate or high Alzheimer's disease neuropathological change (i/h ADNC). Relative neuron loss (ratio of neuron number in hippocampal subfield CA1 to the neuron number in parahippocampal gyrus) was 0.15 for HS-Aging; this was significantly lower than 0.64 for i/h ADNC and 0.66 for control cases (Kruskal-Wallis test, p < 0.0001; p = 0.0003, respectively). TDP-43 proteinopathy was present in 92.4% of HS-Aging cases, higher than that in i/h ADNC (52%) and control (25%) cases. Pure HS-Aging cases were more likely to have cognitive impairment in the memory domain. INTERPRETATION Relative neuron loss in the hippocampus compared to the parahippocampus gyrus may be useful in distinguishing HS-Aging in the context of comorbid ADNC. HS-Aging contributes to cognitive impairment, which phenotypically resembles AD dementia. TDP proteinopathy is a frequent comorbidity in HS-Aging and may contribute to cognitive impairment to a modest degree. Ann Neurol 2018;84:749-761.
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Influence of tau PET, amyloid PET, and hippocampal volume on cognition in Alzheimer disease. Neurology 2018; 91:e859-e866. [PMID: 30068637 DOI: 10.1212/wnl.0000000000006075] [Citation(s) in RCA: 164] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 05/25/2018] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To examine the independent and interactive influences of neuroimaging biomarkers on retrospective cognitive decline. METHODS A total of 152 middle-aged and older adult participants with at least 2 clinical and cognitive assessments, a Clinical Dementia Rating score of 0 or 0.5, and a flortaucipir (18F-AV-1451) tau PET scan, a florbetapir (18F-AV-45) amyloid PET scan, and a structural MRI scan were recruited from the Knight Alzheimer Disease Research Center at Washington University in St. Louis. Cognition was assessed with standard measures reflecting episodic memory, executive functioning, semantic fluency, and processing speed. RESULTS Results from retrospective longitudinal analyses showed that each biomarker had a univariate association with the global cognitive composite; however, when each marker was analyzed in a single statistical model, only tau was a significant predictor of global cognitive decline. There was an interaction between tau and amyloid such that tau-related cognitive decline was worse in individuals with high amyloid. There was also an interaction with hippocampal volume indicating that individuals with high levels of all 3 pathologies exhibited the greatest declines in cognition. Additional analyses within each cognitive domain indicated that tau had the largest negative influence on tests of episodic memory and executive functioning. CONCLUSIONS Together, these results suggest that increasing levels of tau most consistently relate to declines in cognition preceding biomarker collection. These findings support models of Alzheimer disease (AD) staging that suggest that elevated β-amyloid alone may be insufficient to produce cognitive change in individuals at risk for AD and support the use of multiple biomarkers to stage AD progression.
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A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 8:147-155. [PMID: 28653035 PMCID: PMC5476965 DOI: 10.1016/j.dadm.2017.05.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
INTRODUCTION We established a method for diagnostic harmonization across multiple studies of preclinical Alzheimer's disease and validated the method by examining its relationship with clinical status and cognition. METHODS Cognitive and clinical data were used from five studies (N = 1746). Consensus diagnoses established in each study used criteria to identify progressors from normal cognition to mild cognitive impairment. Correspondence was evaluated between these consensus diagnoses and three algorithmic classifications based on (1) objective cognitive impairment in 2+ tests only; (2) a Clinical Dementia Rating (CDR) of ≥0.5 only; and (3) both. Associations between baseline cognitive performance and cognitive change were each tested in relation to progression to algorithm-based classifications. RESULTS In each study, an algorithmic classification based on both cognitive testing cutoff scores and a CDR ≥0.5 provided optimal balance of sensitivity and specificity (areas under the curve: 0.85-0.95). Over an average 6.6 years of follow-up (up to 28 years), N = 186 initially cognitively normal participants aged on average 64 years at baseline progressed (incidence rate: 15.3 people/1000 person-years). Baseline cognitive scores and cognitive change were associated with future diagnostic status using this algorithmic classification. DISCUSSION Both cognitive tests and CDR ratings can be combined across multiple studies to obtain a reliable algorithmic classification with high specificity and sensitivity. This approach may be applicable to large cohort studies and to clinical trials focused on preclinical Alzheimer's disease because it provides an alternative to implementation of a time-consuming adjudication panel.
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Neuropsychological measures that detect early impairment and decline in preclinical Alzheimer disease. Neurobiol Aging 2017; 56:25-32. [PMID: 28482211 DOI: 10.1016/j.neurobiolaging.2017.04.004] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Revised: 04/03/2017] [Accepted: 04/07/2017] [Indexed: 10/19/2022]
Abstract
Identifying which neuropsychological measures detect early cognitive changes associated with Alzheimer disease (AD), brain pathology would be helpful clinically for the diagnosis of early AD and for the design of clinical trials. We evaluated which neuropsychological measures in our cognitive battery are most strongly associated with cerebrospinal fluid (CSF) biomarkers of AD brain pathology. We studied a large cohort (n = 233) of middle-to older-aged community-dwelling individuals (mean age 61 years) who had no clinical symptoms of dementia and underwent baseline CSF collection at baseline. Participants completed a battery of 9 neuropsychological measures at baseline and then every 1 to 3 years. CSF tau/Aβ42 was associated with baseline performance on 5/9 neuropsychological measures, especially measures of episodic memory, and longitudinal performance on 7/9 neuropsychological measures, especially measures of global cognition. The free recall portion of the Free and Cued Selective Reminding Task (FCSRT-free) detected declining cognition in the high CSF tau/Aβ42 group the earliest, followed by another measure of episodic memory and a sequencing task.
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Abstract
Left atrial (LA) diameter is easily attainable from echocardiograph and sensitive to underlying cardiovascular disease severity, although its association with neurocognitive outcomes is not well understood. Fifty older adults (64.50 ± 9.41 years), recruited from outpatient cardiology clinics and local papers who underwent magnetic resonance imaging, were administered the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and completed psychosocial self-report measures. LA diameter was quantified using echocardiogram. Hierarchical regression analyses revealed that greater LA size was independently associated with reduced performance on the following RBANS composites: language, delayed memory, and total index (p < 0.05 for all). Hierarchical regression analysis demonstrated no significant association between LA diameter and whole brain volume (p > 0.05). The current study suggests that greater LA size is associated with cognitive dysfunction in older adults and prospective studies are needed to validate these findings and elucidate underlying mechanisms.
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Abstract
As many people struggle with maintenance of weight loss, the study of successful weight loss maintainers (SWLM) can yield important insights into factors contributing to weight loss maintenance. However, little research has examined how SWLM differ from people who are obese or normal weight (NW) in brain response to orosensory stimulation. The goal of this study was to determine if SWLM exhibit different brain responses to orosensory stimulation. Brain response to 1-min orosensory stimulation with a lemon lollipop was assessed using functional magnetic resonance imaging among 49 participants, including SWLM (n = 17), NW (n = 18), and obese (n = 14) controls. Significant brain responses were observed in nine brain regions, including the bilateral insula, left inferior frontal gyrus, left putamen, and other sensory regions. All regions also exhibited significant attenuation of this response over 1 min. The SWLM exhibited greater response compared with the other groups in all brain regions. Findings suggest that the response to orosensory stimulation peaks within 40 s and attenuates significantly between 40 and 60 s in regions associated with sensation, reward, and inhibitory control. Greater reactivity among the SWLM suggests that greater sensory reactivity to orosensory stimulation, increased anticipated reward, and subsequently greater inhibitory processing are associated with weight loss maintenance.
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Cortical thickness of the cognitive control network in obesity and successful weight loss maintenance: a preliminary MRI study. Psychiatry Res 2012; 202:77-9. [PMID: 22595506 PMCID: PMC3380138 DOI: 10.1016/j.pscychresns.2011.09.008] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2011] [Revised: 09/07/2011] [Accepted: 09/15/2011] [Indexed: 10/28/2022]
Abstract
Cortical thickness of the cognitive control network was contrasted between obese (OB), successful weight loss maintainers (SWLM), and lean individuals. OB individuals had significant thinning, most notably in the anterior cingulate and posterior parietal cortices. SWLM individuals exhibited trends towards thicker cortex than OB individuals, which may be important in future studies.
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Metabolic syndrome is associated with learning and recall impairment in middle age. Dement Geriatr Cogn Disord 2010; 29:356-62. [PMID: 20424454 PMCID: PMC2889255 DOI: 10.1159/000296071] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/03/2010] [Indexed: 01/17/2023] Open
Abstract
AIMS To determine whether middle-aged individuals with metabolic syndrome, both with and without type 2 diabetes, exhibit cognitive impairments, and to determine the role of each metabolic syndrome component in those associations. METHODS 143 participants were drawn from ongoing studies of normal aging. Metabolic syndrome was diagnosed in 73 participants (age: 60.4 +/- 8.4 years), who were contrasted with 70 age- and education-matched controls. RESULTS Metabolic syndrome was associated with reductions in recall (p = 0.006), lower overall intellectual functioning (p = 0.013), and nearly significant reductions in learning (p = 0.066) and executive functioning (p = 0.050). These effects were only marginally attenuated when controlling for type 2 diabetes diagnosis. Of the 5 components of the metabolic syndrome, insulin resistance was the only significant predictor of variance in learning and recall. In addition, the number of metabolic syndrome criteria met was inversely associated with cognitive performance. CONCLUSIONS These results indicate that impairments in cognitive functioning associated with metabolic syndrome and type 2 diabetes may begin as early as middle age and are primarily due to insulin resistance. These results demonstrate the importance of screening at-risk adults for insulin resistance in order to initiate lifestyle modifications to reverse or prevent these cognitive changes.
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