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Vassilaki M, Pittock RR, Aakre JA, Castillo AM, Ramanan VK, Kremers WK, Jack CR, Vemuri P, Lowe VJ, Knopman DS, Petersen RC, Graff-Radford J. Author Response: Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging. Neurology 2024; 102:e209377. [PMID: 38648608 DOI: 10.1212/wnl.0000000000209377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024] Open
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Karstens AJ, Christianson TJ, Lundt ES, Machulda MM, Mielke MM, Fields JA, Kremers WK, Graff-Radford J, Vemuri P, Jack CR, Knopman DS, Petersen RC, Stricker NH. Mayo normative studies: regression-based normative data for ages 30-91 years with a focus on the Boston Naming Test, Trail Making Test and Category Fluency. J Int Neuropsychol Soc 2024; 30:389-401. [PMID: 38014536 PMCID: PMC11014770 DOI: 10.1017/s1355617723000760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
OBJECTIVE Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample. METHOD The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo's Older Americans Normative Studies (MOANS) norms. RESULTS Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6-27% variance explained), sex (0-13%), and education (2-10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS. CONCLUSIONS Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.
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Affiliation(s)
- Aimee J. Karstens
- Division of Neurocognitive Disorders, Department of
Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Teresa J. Christianson
- Division of Biomedical Statistics and Informatics,
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Emily S. Lundt
- Division of Biomedical Statistics and Informatics,
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Mary M. Machulda
- Division of Neurocognitive Disorders, Department of
Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Michelle M. Mielke
- Department of Epidemiology and Prevention, Wake Forest
University School of Medicine, Winston-Salem, NC, USA
- Department of Gerontology and Geriatric Medicine, Wake
Forest University School of Medicine, Winston-Salem, NC, USA
| | - Julie A. Fields
- Division of Neurocognitive Disorders, Department of
Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Walter K. Kremers
- Division of Biomedical Statistics and Informatics,
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | | | | | | | - Nikki H. Stricker
- Division of Neurocognitive Disorders, Department of
Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
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Singh NA, Goodrich AW, Graff-Radford J, Machulda MM, Sintini I, Carlos AF, Robinson CG, Reid RI, Lowe VJ, Jack CR, Petersen RC, Boeve BF, Josephs KA, Kantarci K, Whitwell JL. Altered structural and functional connectivity in Posterior Cortical Atrophy and Dementia with Lewy bodies. Neuroimage 2024; 290:120564. [PMID: 38442778 PMCID: PMC11019668 DOI: 10.1016/j.neuroimage.2024.120564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 03/03/2024] [Indexed: 03/07/2024] Open
Abstract
Posterior cortical atrophy (PCA) and dementia with Lewy bodies (DLB) show distinct atrophy and overlapping hypometabolism profiles, but it is unknown how disruptions in structural and functional connectivity compare between these disorders and whether breakdowns in connectivity relate to either atrophy or hypometabolism. Thirty amyloid-positive PCA patients, 24 amyloid-negative DLB patients and 30 amyloid-negative cognitively unimpaired (CU) healthy individuals were recruited at Mayo Clinic, Rochester, MN, and underwent a 3T head MRI, including structural MRI, resting state functional MRI (rsfMRI) and diffusion tensor imaging (DTI) sequences, as well as [18F] fluorodeoxyglucose (FDG) PET. We assessed functional connectivity within and between 12 brain networks using rsfMRI and the CONN functional connectivity toolbox and calculated regional DTI metrics using the Johns Hopkins atlas. Multivariate linear-regression models corrected for multiple comparisons and adjusted for age and sex compared DTI metrics and within-network and between-network functional connectivity across groups. Regional gray-matter volumes and FDG-PET standard uptake value ratios (SUVRs) were calculated and analyzed at the voxel-level using SPM12. We used univariate linear-regression models to investigate the relationship between connectivity measures, gray-matter volume, and FDG-PET SUVR. On DTI, PCA showed degeneration in occipito-parietal white matter, posterior thalamic radiations, splenium of the corpus collosum and sagittal stratum compared to DLB and CU, with greater degeneration in the temporal white matter and the fornix compared to CU. We observed no white-matter degeneration in DLB compared to CU. On rsfMRI, reduced within-network connectivity was present in dorsal and ventral default mode networks (DMN) and the dorsal-attention network in PCA compared to DLB and CU, with reduced within-network connectivity in the visual and sensorimotor networks compared to CU. DLB showed reduced connectivity in the cerebellar network compared to CU. Between-network analysis showed increased connectivity in both cerebellar-to-sensorimotor and cerebellar-to-dorsal attention network connectivity in PCA and DLB. PCA showed reduced anterior DMN-to-cerebellar and dorsal attention-to-sensorimotor connectivity, while DLB showed reduced posterior DMN-to-sensorimotor connectivity compared to CU. PCA showed reduced dorsal DMN-to-visual connectivity compared to DLB. The multimodal analysis revealed weak associations between functional connectivity and volume in PCA, and between functional connectivity and metabolism in DLB. These findings suggest that PCA and DLB have unique connectivity alterations, with PCA showing more widespread disruptions in both structural and functional connectivity; yet some overlap was observed with both disorders showing increased connectivity from the cerebellum.
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Affiliation(s)
| | - Austin W Goodrich
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | | | - Mary M Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, United States
| | - Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Arenn F Carlos
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | | | - Robert I Reid
- Department of Radiology, Mayo Clinic, Rochester, MN, United States; Department of Information Technology, Mayo Clinic, Rochester, MN, United States
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
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Kouri N, Frankenhauser I, Peng Z, Labuzan SA, Boon BDC, Moloney CM, Pottier C, Wickland DP, Caetano-Anolles K, Corriveau-Lecavalier N, Tranovich JF, Wood AC, Hinkle KM, Lincoln SJ, Spychalla AJ, Senjem ML, Przybelski SA, Engelberg-Cook E, Schwarz CG, Kwan RS, Lesser ER, Crook JE, Carter RE, Ross OA, Lachner C, Ertekin-Taner N, Ferman TJ, Fields JA, Machulda MM, Ramanan VK, Nguyen AT, Reichard RR, Jones DT, Graff-Radford J, Boeve BF, Knopman DS, Petersen RC, Jack CR, Kantarci K, Day GS, Duara R, Graff-Radford NR, Dickson DW, Lowe VJ, Vemuri P, Murray ME. Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease. JAMA Neurol 2024:2817289. [PMID: 38619853 PMCID: PMC11019448 DOI: 10.1001/jamaneurol.2024.0784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/05/2024] [Indexed: 04/16/2024]
Abstract
Importance Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = -0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = -0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.
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Affiliation(s)
- Naomi Kouri
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
| | - Isabelle Frankenhauser
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
- Paracelsus Medical Private University, Salzburg, Austria
| | - Zhongwei Peng
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
| | | | | | | | - Cyril Pottier
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
| | - Daniel P. Wickland
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
| | | | - Nick Corriveau-Lecavalier
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | | | - Ashley C. Wood
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
| | - Kelly M. Hinkle
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
| | | | | | | | - Scott A. Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | | | | | - Rain S. Kwan
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
| | - Elizabeth R. Lesser
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
| | - Julia E. Crook
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
| | - Rickey E. Carter
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida
| | - Owen A. Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
| | - Christian Lachner
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, Florida
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
| | - Tanis J. Ferman
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, Florida
| | - Julie A. Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
| | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota
| | | | - Aivi T. Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - R. Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - David T. Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | | | | | | | | | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, Florida
| | | | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
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Hamouda AM, Pennington Z, Shafi M, Astudillo Potis MD, Hallak H, Graff-Radford J, Jones DT, Botha H, Cutsforth-Gregory JK, Cogswell PM, Elder BD. Ventriculoperitoneal shunt placement safety in idiopathic Normal Pressure Hydrocephalus: Anticoagulated versus non-anticoagulated patients. World Neurosurg 2024:S1878-8750(24)00581-3. [PMID: 38604534 DOI: 10.1016/j.wneu.2024.04.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 04/02/2024] [Accepted: 04/03/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Many patients with idiopathic normal pressure hydrocephalus (iNPH) have medical comorbidities requiring anticoagulation that could negatively impact outcomes. This study evaluated the safety of ventriculoperitoneal shunt (VPS) placement in iNPH patients on systemic anticoagulation versus those not on anticoagulation. METHODS Patients > 60 years of age with iNPH who underwent shunting between 2018 and 2022 were retrospectively reviewed. Baseline demographics, comorbidities (quantified by modified Frailty Index (mFI) and Charlson Comorbidity Index (CCI)), anticoagulant/antiplatelet agent use (other than aspirin), operative details, and complications were collected. Outcomes of interest were the occurrence of postoperative hemorrhage and overdrainage. RESULTS A total of 234 patients were included in the study (mean age 75.22 ± 6.04 years; 66.7% male); 36 were on anticoagulation/antiplatelet therapy (excluding aspirin). This included 6 on Warfarin, 19 on direct Xa inhibitors, 10 on Clopidogrel, and one on both Clopidogrel and Warfarin. Notably, 70% of patients (164/234) used aspirin alone or combined with anticoagulation or clopidogrel. Baseline mFI was similar between groups, but those on anticoagulant/antiplatelet therapy had a higher mean CCI (2.67±1.87 vs. 1.75±1.84; p=0.001). Patients on anticoagulants were more likely to experience tract hemorrhage (11.1 vs. 2.5%; p=0.03), with no significant difference in the rates of intraventricular hemorrhage or overdrainage related subdural fluid collection. CONCLUSIONS Anticoagulant and antiplatelet agents are common in the iNPH population, and patients on these agents experienced higher rates of tract hemorrhage following VPS placement; however, overall hemorrhagic complication rates were similar.
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Affiliation(s)
| | - Zach Pennington
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, 55905, USA
| | - Mahnoor Shafi
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - Hannah Hallak
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | | | - Benjamin D Elder
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, 55905, USA.
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6
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Corriveau-Lecavalier N, Barnard LR, Botha H, Graff-Radford J, Ramanan VK, Lee J, Dicks E, Rademakers R, Boeve BF, Machulda MM, Fields JA, Dickson DW, Graff-Radford N, Knopman DS, Lowe VJ, Petersen RC, Jack CR, Jones DT. Uncovering the distinct macro-scale anatomy of dysexecutive and behavioural degenerative diseases. Brain 2024; 147:1483-1496. [PMID: 37831661 PMCID: PMC10994526 DOI: 10.1093/brain/awad356] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 08/28/2023] [Accepted: 10/03/2023] [Indexed: 10/15/2023] Open
Abstract
There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behaviour and personality. This is due to an incomplete understanding of the macro-scale anatomy underlying these symptomatologies, a partial overlap in clinical features and the fact that both phenotypes can emerge from the same pathology and vice versa. We collected data from a patient cohort of which 52 had dysexecutive Alzheimer's disease, 30 had behavioural variant frontotemporal dementia (bvFTD), seven met clinical criteria for bvFTD but had Alzheimer's disease pathology (behavioural Alzheimer's disease) and 28 had amnestic Alzheimer's disease. We first assessed group-wise differences in clinical and cognitive features and patterns of fluorodeoxyglucose (FDG) PET hypometabolism. We then performed a spectral decomposition of covariance between FDG-PET images to yield latent patterns of relative hypometabolism unbiased by diagnostic classification, which are referred to as 'eigenbrains'. These eigenbrains were subsequently linked to clinical and cognitive data and meta-analytic topics from a large external database of neuroimaging studies reflecting a wide range of mental functions. Finally, we performed a data-driven exploratory linear discriminant analysis to perform eigenbrain-based multiclass diagnostic predictions. Dysexecutive Alzheimer's disease and bvFTD patients were the youngest at symptom onset, followed by behavioural Alzheimer's disease, then amnestic Alzheimer's disease. Dysexecutive Alzheimer's disease patients had worse cognitive performance on nearly all cognitive domains compared with other groups, except verbal fluency which was equally impaired in dysexecutive Alzheimer's disease and bvFTD. Hypometabolism was observed in heteromodal cortices in dysexecutive Alzheimer's disease, temporo-parietal areas in amnestic Alzheimer's disease and frontotemporal areas in bvFTD and behavioural Alzheimer's disease. The unbiased spectral decomposition analysis revealed that relative hypometabolism in heteromodal cortices was associated with worse dysexecutive symptomatology and a lower likelihood of presenting with behaviour/personality problems, whereas relative hypometabolism in frontotemporal areas was associated with a higher likelihood of presenting with behaviour/personality problems but did not correlate with most cognitive measures. The linear discriminant analysis yielded an accuracy of 82.1% in predicting diagnostic category and did not misclassify any dysexecutive Alzheimer's disease patient for behavioural Alzheimer's disease and vice versa. Our results strongly suggest a double dissociation in that distinct macro-scale underpinnings underlie predominant dysexecutive versus personality/behavioural symptomatology in dementia syndromes. This has important implications for the implementation of criteria to diagnose and distinguish these diseases and supports the use of data-driven techniques to inform the classification of neurodegenerative diseases.
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Affiliation(s)
| | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Jeyeon Lee
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ellen Dicks
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
- Center for Molecular Neurology, Antwerp University, Antwerp, Belgium
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
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7
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Mak E, Reid RI, Przybelski SA, Lesnick TG, Schwarz CG, Senjem ML, Raghavan S, Vemuri P, Jack CR, Min HK, Jain MK, Miyagawa T, Forsberg LK, Fields JA, Savica R, Graff-Radford J, Jones DT, Botha H, St Louis EK, Knopman DS, Ramanan VK, Dickson DW, Graff-Radford NR, Ferman TJ, Petersen RC, Lowe VJ, Boeve BF, O'Brien JT, Kantarci K. Influences of amyloid-β and tau on white matter neurite alterations in dementia with Lewy bodies. NPJ Parkinsons Dis 2024; 10:76. [PMID: 38570511 PMCID: PMC10991290 DOI: 10.1038/s41531-024-00684-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer's disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models. We evaluated the associations of tau and amyloid-β with DTI and NODDI parameters and examined the correlations of AD-related white matter injury with Clinical Dementia Rating (CDR). Structural equation models (SEM) explored relationships among age, APOE ε4, amyloid-β, tau, and white matter injury. The DLB spectrum group exhibited widespread white matter abnormalities, including reduced fractional anisotropy, increased mean diffusivity, and decreased neurite density index. Tau was significantly associated with limbic and temporal white matter injury, which was, in turn, associated with worse CDR. SEM revealed that amyloid-β exerted indirect effects on white matter injury through tau. We observed widespread disruptions in white matter tracts in DLB that were not attributed to AD pathologies, likely due to α-synuclein-related injury. However, a fraction of the white matter injury could be attributed to AD pathology. Our findings underscore the impact of AD pathology on white matter integrity in DLB and highlight the utility of NODDI in elucidating the biological basis of white matter injury in DLB.
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Affiliation(s)
- Elijah Mak
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Robert I Reid
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Hoon Ki Min
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Manoj K Jain
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
| | - Toji Miyagawa
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Rodolfo Savica
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Erik K St Louis
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
- Center for Sleep Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | - Dennis W Dickson
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, USA
| | | | - Tanis J Ferman
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Ronald C Petersen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
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8
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Sintini I, Singh NA, Li D, Mielke MM, Machulda MM, Schwarz CG, Senjem ML, Jack CR, Lowe VJ, Graff-Radford J, Josephs KA, Whitwell JL. Plasma glial fibrillary acidic protein in the visual and language variants of Alzheimer's disease. Alzheimers Dement 2024. [PMID: 38528318 DOI: 10.1002/alz.13713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 03/27/2024]
Abstract
INTRODUCTION Glial fibrillary acidic protein (GFAP) in plasma is a proxy for astrocytic activity and is elevated in amyloid-β (Aβ)-positive individuals, making GFAP a potential blood-based biomarker for Alzheimer's disease (AD). METHODS We assessed plasma GFAP in 72 Aβ-positive participants diagnosed with the visual or language variant of AD who underwent Aβ- and tau-PET. Fifty-nine participants had follow-up imaging. Linear regression was applied on GFAP and imaging quantities. RESULTS GFAP did not correlate with Aβ- or tau-PET cross-sectionally. There was a limited positive correlation between GFAP and rates of tau accumulation, particularly in the language variant of AD, although associations were weaker after removing one outlier patient with the highest GFAP level. DISCUSSION Among Aβ-positive AD participants with atypical presentations, plasma GFAP did not correlate with levels of AD pathology on PET, suggesting that the associations between GFAP and AD pathology might plateau during the advanced phase of the disease.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Danni Li
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
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9
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Shir D, Corriveau-Lecavalier N, Bermudez Noguera C, Barnard L, Pham NTT, Botha H, Duffy JR, Clark HM, Utianski RL, Knopman DS, Petersen RC, Boeve BF, Murray ME, Nguyen AT, Reichard RR, Dickson DW, Day GS, Kremers WK, Graff-Radford NR, Jones DT, Machulda MM, Fields JA, Whitwell JL, Josephs KA, Graff-Radford J. Clinicoradiological and neuropathological evaluation of primary progressive aphasia. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-332862. [PMID: 38514176 DOI: 10.1136/jnnp-2023-332862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/28/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Primary progressive aphasia (PPA) defines a group of neurodegenerative disorders characterised by language decline. Three PPA variants correlate with distinct underlying pathologies: semantic variant PPA (svPPA) with transactive response DNA-binding protein of 43 kD (TDP-43) proteinopathy, agrammatic variant PPA (agPPA) with tau deposition and logopenic variant PPA (lvPPA) with Alzheimer's disease (AD). Our objectives were to differentiate PPA variants using clinical and neuroimaging features, assess progression and evaluate structural MRI and a novel 18-F fluorodeoxyglucose positron emission tomography (FDG-PET) image decomposition machine learning algorithm for neuropathology prediction. METHODS We analysed 82 autopsied patients diagnosed with PPA from 1998 to 2022. Clinical histories, language characteristics, neuropsychological results and brain imaging were reviewed. A machine learning framework using a k-nearest neighbours classifier assessed FDG-PET scans from 45 patients compared with a large reference database. RESULTS PPA variant distribution: 35 lvPPA (80% AD), 28 agPPA (89% tauopathy) and 18 svPPA (72% frontotemporal lobar degeneration-TAR DNA-binding protein (FTLD-TDP)). Apraxia of speech was associated with 4R-tauopathy in agPPA, while pure agrammatic PPA without apraxia was linked to 3R-tauopathy. Longitudinal data revealed language dysfunction remained the predominant deficit for patients with lvPPA, agPPA evolved to corticobasal or progressive supranuclear palsy syndrome (64%) and svPPA progressed to behavioural variant frontotemporal dementia (44%). agPPA-4R-tauopathy exhibited limited pre-supplementary motor area atrophy, lvPPA-AD displayed temporal atrophy extending to the superior temporal sulcus and svPPA-FTLD-TDP had severe temporal pole atrophy. The FDG-PET-based machine learning algorithm accurately predicted clinical diagnoses and underlying pathologies. CONCLUSIONS Distinguishing 3R-taupathy and 4R-tauopathy in agPPA may rely on apraxia of speech presence. Additional linguistic and clinical features can aid neuropathology prediction. Our data-driven brain metabolism decomposition approach effectively predicts underlying neuropathology.
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Affiliation(s)
- Dror Shir
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Leland Barnard
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph R Duffy
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Heather M Clark
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Rene L Utianski
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Quantitative Health Sciences, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - R Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Mary M Machulda
- Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Julie A Fields
- Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
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10
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Walton RL, Koga S, Beasley AI, White LJ, Griesacker T, Murray ME, Kasanuki K, Hou X, Fiesel FC, Springer W, Uitti RJ, Fields JA, Botha H, Ramanan VK, Kantarci K, Lowe VJ, Jack CR, Ertekin-Taner N, Savica R, Graff-Radford J, Petersen RC, Parisi JE, Reichard RR, Graff-Radford NR, Ferman TJ, Boeve BF, Wszolek ZK, Dickson DW, Ross OA, Heckman MG. Role of GBA variants in Lewy body disease neuropathology. Acta Neuropathol 2024; 147:54. [PMID: 38472443 PMCID: PMC11049671 DOI: 10.1007/s00401-024-02699-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 01/26/2024] [Accepted: 01/27/2024] [Indexed: 03/14/2024]
Abstract
Rare and common GBA variants are risk factors for both Parkinson's disease (PD) and dementia with Lewy bodies (DLB). However, the degree to which GBA variants are associated with neuropathological features in Lewy body disease (LBD) is unknown. Herein, we assessed 943 LBD cases and examined associations of 15 different neuropathological outcomes with common and rare GBA variants. Neuropathological outcomes included LBD subtype, presence of a high likelihood of clinical DLB (per consensus guidelines), LB counts in five cortical regions, tyrosine hydroxylase immunoreactivity in the dorsolateral and ventromedial putamen, ventrolateral substantia nigra neuronal loss, Braak neurofibrillary tangle (NFT) stage, Thal amyloid phase, phospho-ubiquitin (pS65-Ub) level, TDP-43 pathology, and vascular disease. Sequencing of GBA exons revealed a total of 42 different variants (4 common [MAF > 0.5%], 38 rare [MAF < 0.5%]) in our series, and 165 cases (17.5%) had a copy of the minor allele for ≥ 1 variant. In analysis of common variants, p.L483P was associated with a lower Braak NFT stage (OR = 0.10, P < 0.001). In gene-burden analysis, presence of the minor allele for any GBA variant was associated with increased odds of a high likelihood of DLB (OR = 2.00, P < 0.001), a lower Braak NFT stage (OR = 0.48, P < 0.001), a lower Thal amyloid phase (OR = 0.55, P < 0.001), and a lower pS65-Ub level (β: -0.37, P < 0.001). Subgroup analysis revealed that GBA variants were most common in LBD cases with a combination of transitional/diffuse LBD and Braak NFT stage 0-II or Thal amyloid phase 0-1, and correspondingly that the aforementioned associations of GBA gene-burden with a decreased Braak NFT stage and Thal amyloid phase were observed only in transitional or diffuse LBD cases. Our results indicate that in LBD, GBA variants occur most frequently in cases with greater LB pathology and low AD pathology, further informing disease-risk associations of GBA in PD, PD dementia, and DLB.
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Affiliation(s)
- Ronald L Walton
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Shunsuke Koga
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Launia J White
- Division of Clinical Trials and Biostatistics, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, USA
| | | | | | - Koji Kasanuki
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Xu Hou
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | | | - Ryan J Uitti
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Julie A Fields
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Kejal Kantarci
- Department of Neuroradiology, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | - Clifford R Jack
- Department of Neuroradiology, Mayo Clinic, Rochester, MN, USA
| | - Nilufer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Rodolfo Savica
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Joseph E Parisi
- Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - R Ross Reichard
- Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Tanis J Ferman
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, USA
| | | | | | | | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL, USA
| | - Michael G Heckman
- Division of Clinical Trials and Biostatistics, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, USA.
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11
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Pradeep A, Raghavan S, Przybelski SA, Preboske G, Schwarz CG, Lowe VJ, Knopman DS, Petersen RC, Jack CR, Graff-Radford J, Cogswell PM, Vemuri P. Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population? Res Sq 2024:rs.3.rs-4017874. [PMID: 38558965 PMCID: PMC10980106 DOI: 10.21203/rs.3.rs-4017874/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Background White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer's imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods We identified 1144 participants from the Mayo Clinic Study of Aging consisting of older adults from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET and tau-PET standardized uptake value ratio, WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.78). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97). Conclusion Our study investigates risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.
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12
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Karki P, Murphy MC, Cogswell PM, Senjem ML, Graff-Radford J, Elder BD, Perry A, Graffeo CS, Meyer FB, Jack CR, Ehman RL, Huston J. Prediction of Surgical Outcomes in Normal Pressure Hydrocephalus by MR Elastography. AJNR Am J Neuroradiol 2024; 45:328-334. [PMID: 38272572 DOI: 10.3174/ajnr.a8108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 11/21/2023] [Indexed: 01/27/2024]
Abstract
BACKGROUND AND PURPOSE Normal pressure hydrocephalus is a treatable cause of dementia associated with distinct mechanical property signatures in the brain as measured by MR elastography. In this study, we tested the hypothesis that specific anatomic features of normal pressure hydrocephalus are associated with unique mechanical property alterations. Then, we tested the hypothesis that summary measures of these mechanical signatures can be used to predict clinical outcomes. MATERIALS AND METHODS MR elastography and structural imaging were performed in 128 patients with suspected normal pressure hydrocephalus and 44 control participants. Patients were categorized into 4 subgroups based on their anatomic features. Surgery outcome was acquired for 68 patients. Voxelwise modeling was performed to detect regions with significantly different mechanical properties between each group. Mechanical signatures were summarized using pattern analysis and were used as features to train classification models and predict shunt outcomes for 2 sets of feature spaces: a limited 2D feature space that included the most common features found in normal pressure hydrocephalus and an expanded 20-dimensional (20D) feature space that included features from all 4 morphologic subgroups. RESULTS Both the 2D and 20D classifiers performed significantly better than chance for predicting clinical outcomes with estimated areas under the receiver operating characteristic curve of 0.66 and 0.77, respectively (P < .05, permutation test). The 20D classifier significantly improved the diagnostic OR and positive predictive value compared with the 2D classifier (P < .05, permutation test). CONCLUSIONS MR elastography provides further insight into mechanical alterations in the normal pressure hydrocephalus brain and is a promising, noninvasive method for predicting surgical outcomes in patients with normal pressure hydrocephalus.
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Affiliation(s)
- Pragalv Karki
- From the Department of Radiology (P.K., M.C.M., P.M.C., M.L.S., J.G.-R., C.R.J., R.L.E., J.H.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Matthew C Murphy
- From the Department of Radiology (P.K., M.C.M., P.M.C., M.L.S., J.G.-R., C.R.J., R.L.E., J.H.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Petrice M Cogswell
- From the Department of Radiology (P.K., M.C.M., P.M.C., M.L.S., J.G.-R., C.R.J., R.L.E., J.H.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Matthew L Senjem
- From the Department of Radiology (P.K., M.C.M., P.M.C., M.L.S., J.G.-R., C.R.J., R.L.E., J.H.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Jonathan Graff-Radford
- Department of Neurology (J.G.-R.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Benjamin D Elder
- Department of Neurologic Surgery (B.D.E., C.S.G., F.B.M.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Avital Perry
- Department of Neurosurgery (A.P.), Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Christopher S Graffeo
- Department of Neurologic Surgery (B.D.E., C.S.G., F.B.M.), Mayo Clinic College of Medicine, Rochester, Minnesota
- Department of Neurosurgery (C.S.G.), University of Oklahoma, Oklahoma City, Oklahoma
| | - Fredric B Meyer
- Department of Neurologic Surgery (B.D.E., C.S.G., F.B.M.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Clifford R Jack
- From the Department of Radiology (P.K., M.C.M., P.M.C., M.L.S., J.G.-R., C.R.J., R.L.E., J.H.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Richard L Ehman
- From the Department of Radiology (P.K., M.C.M., P.M.C., M.L.S., J.G.-R., C.R.J., R.L.E., J.H.), Mayo Clinic College of Medicine, Rochester, Minnesota
| | - John Huston
- From the Department of Radiology (P.K., M.C.M., P.M.C., M.L.S., J.G.-R., C.R.J., R.L.E., J.H.), Mayo Clinic College of Medicine, Rochester, Minnesota
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13
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Lee J, Burkett BJ, Min HK, Senjem ML, Dicks E, Corriveau-Lecavalier N, Mester CT, Wiste HJ, Lundt ES, Murray ME, Nguyen AT, Reichard RR, Botha H, Graff-Radford J, Barnard LR, Gunter JL, Schwarz CG, Kantarci K, Knopman DS, Boeve BF, Lowe VJ, Petersen RC, Jack CR, Jones DT. Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning. Brain 2024; 147:980-995. [PMID: 37804318 PMCID: PMC10907092 DOI: 10.1093/brain/awad346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 08/30/2023] [Accepted: 09/24/2023] [Indexed: 10/09/2023] Open
Abstract
Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.
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Affiliation(s)
- Jeyeon Lee
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea
| | - Brian J Burkett
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hoon-Ki Min
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Matthew L Senjem
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ellen Dicks
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Carly T Mester
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Emily S Lundt
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ross R Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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14
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Corriveau-Lecavalier N, Tosakulwong N, Lesnick TG, Fought AJ, Reid RI, Schwarz CG, Senjem ML, Jack CR, Jones DT, Vemuri P, Rademakers R, Ramos EM, Geschwind DH, Knopman DS, Botha H, Savica R, Graff-Radford J, Ramanan VK, Fields JA, Graff-Radford N, Wszolek Z, Forsberg LK, Petersen RC, Heuer HW, Boxer AL, Rosen HJ, Boeve BF, Kantarci K. Neurite-based white matter alterations in MAPT mutation carriers: A multi-shell diffusion MRI study in the ALLFTD consortium. Neurobiol Aging 2024; 134:135-145. [PMID: 38091751 PMCID: PMC10872472 DOI: 10.1016/j.neurobiolaging.2023.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 11/28/2023] [Accepted: 12/01/2023] [Indexed: 12/23/2023]
Abstract
We assessed white matter (WM) integrity in MAPT mutation carriers (16 asymptomatic, 5 symptomatic) compared to 31 non-carrier family controls using diffusion tensor imaging (DTI) (fractional anisotropy; FA, mean diffusivity; MD) and neurite orientation dispersion and density imaging (NODDI) (neurite density index; NDI, orientation and dispersion index; ODI). Linear mixed-effects models accounting for age and family relatedness revealed alterations across DTI and NODDI metrics in all mutation carriers and in symptomatic carriers, with the most significant differences involving fronto-temporal WM tracts. Asymptomatic carriers showed higher entorhinal MD and lower cingulum FA and patterns of higher ODI mostly involving temporal areas and long association and projections fibers. Regression models between estimated time to or time from disease and DTI and NODDI metrics in key regions (amygdala, cingulum, entorhinal, inferior temporal, uncinate fasciculus) in all carriers showed increasing abnormalities with estimated time to or time from disease onset, with FA and NDI showing the strongest relationships. Neurite-based metrics, particularly ODI, appear to be particularly sensitive to early WM involvement in asymptomatic carriers.
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Affiliation(s)
- Nick Corriveau-Lecavalier
- Department of Neurology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Timothy G Lesnick
- Departmenf of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Angela J Fought
- Departmenf of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Robert I Reid
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA; Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA; Center for Molecular Neurology, Antwerp University, Belgium
| | | | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Rodolfo Savica
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | - Hilary W Heuer
- Department of Neurology, University of California San Francisco, CA, USA
| | - Adam L Boxer
- Department of Neurology, University of California San Francisco, CA, USA
| | - Howard J Rosen
- Department of Neurology, University of California San Francisco, CA, USA
| | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
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15
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Chapleau M, La Joie R, Yong K, Agosta F, Allen IE, Apostolova L, Best J, Boon BDC, Crutch S, Filippi M, Fumagalli GG, Galimberti D, Graff-Radford J, Grinberg LT, Irwin DJ, Josephs KA, Mendez MF, Mendez PC, Migliaccio R, Miller ZA, Montembeault M, Murray ME, Nemes S, Pelak V, Perani D, Phillips J, Pijnenburg Y, Rogalski E, Schott JM, Seeley W, Sullivan AC, Spina S, Tanner J, Walker J, Whitwell JL, Wolk DA, Ossenkoppele R, Rabinovici GD. Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis. Lancet Neurol 2024; 23:168-177. [PMID: 38267189 DOI: 10.1016/s1474-4422(23)00414-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 09/22/2023] [Accepted: 10/18/2023] [Indexed: 01/26/2024]
Abstract
BACKGROUND Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. METHODS We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. FINDINGS We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid β in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). INTERPRETATION These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity. FUNDING None.
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Affiliation(s)
- Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Keir Yong
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Federica Agosta
- Vita-Salute, San Raffaele University, Milan, Italy; Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Insitute, Milan, Italy
| | - Isabel Elaine Allen
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | | | - John Best
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Baayla D C Boon
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Sebastian Crutch
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Massimo Filippi
- Vita-Salute, San Raffaele University, Milan, Italy; Neuroimaging Research Unit, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Insitute, Milan, Italy
| | | | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy; Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
| | | | - Lea T Grinberg
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Mario F Mendez
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Patricio Chrem Mendez
- Memory Center, Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia, Buenos Aires Argentina
| | - Raffaella Migliaccio
- Paris Brain Institute (ICM), FrontLab, Institut de la mémoire et de la maladie d'Alzheimer (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, Paris, France
| | - Zachary A Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Maxime Montembeault
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | | | - Sára Nemes
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Victoria Pelak
- Departments of Neurology and Ophthalmology, Divisions of Neuro-Ophthalmology and Behavioral Neurology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Daniela Perani
- Vita-Salute, San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele, San Raffaele University, Milan, Italy
| | - Jeffrey Phillips
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Yolande Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Emily Rogalski
- Mesulam Center for Cognitive Neurology & Alzheimer's Disease, Northwestern University, Evanston, IL, USA
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands
| | - William Seeley
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - A Campbell Sullivan
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Jeremy Tanner
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Jamie Walker
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | | | - David A Wolk
- Alzheimer's Disease Research Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Netherlands; Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands; Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA; Department of Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
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Stricker NH, Stricker JL, Frank RD, Fan WZ, Christianson TJ, Patel JS, Karstens AJ, Kremers WK, Machulda MM, Fields JA, Graff-Radford J, Jack CR, Knopman DS, Mielke MM, Petersen RC. Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test. J Int Neuropsychol Soc 2024; 30:138-151. [PMID: 37385974 PMCID: PMC10756923 DOI: 10.1017/s1355617723000322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
OBJECTIVE The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT). METHOD Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only. RESULTS The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups. CONCLUSIONS Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.
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Affiliation(s)
- Nikki H Stricker
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - John L Stricker
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Ryan D Frank
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Winnie Z Fan
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Jay S Patel
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Aimee J Karstens
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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Switzer AR, Graff-Radford J, Gunter JL, Elder BD, Jones DT, Huston J, Jack CR, Cogswell PM. Patients with normal pressure hydrocephalus have fewer enlarged perivascular spaces in the centrum semiovale compared to cognitively unimpaired individuals. Clin Neurol Neurosurg 2024; 237:108123. [PMID: 38262154 DOI: 10.1016/j.clineuro.2024.108123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/08/2024] [Accepted: 01/14/2024] [Indexed: 01/25/2024]
Abstract
INTRODUCTION Enlarged perivascular spaces (ePVS) may be an indicator of glymphatic dysfunction. Limited studies have evaluated the role of ePVS in idiopathic normal pressure hydrocephalus (iNPH). We aimed to characterize the distribution and number of ePVS in iNPH compared to controls. METHODS Thirty-eight patients with iNPH and a pre-shunt MRI were identified through clinical practice. Age- and sex-matched controls who had negative MRIs screening for intracranial metastases were identified through a medical record linkage system. The number of ePVS were counted in the basal nuclei (BN) and centrum semiovale (CS) using the Wardlaw method blinded to clinical diagnosis. Imaging features of disproportionately enlarged subarachnoid space hydrocephalus (DESH), callosal angle, Fazekas white matter hyperintensity (WMH) grade, and the presence of microbleeds and lacunes were also evaluated. RESULTS Both iNPH patients and controls had a mean age of 74 ± 7 years and were 34% female with equal distributions of hypertension, dyslipidemia, diabetes, stroke, and history of smoking. There were fewer ePVS in the CS of patients with iNPH compared to controls (12.66 vs. 20.39, p < 0.001) but the same in the BN (8.95 vs. 11.11, p = 0.08). This remained significant in models accounting for vascular risk factors (p = 0.002) and MRI features of DESH and WMH grade (p = 0.03). CONCLUSIONS Fewer centrum semiovale ePVS may be a biomarker for iNPH. This pattern may be caused by mechanical obstruction due to upward displacement of the brain leading to reduced glymphatic clearance.
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Affiliation(s)
- Aaron R Switzer
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | | | - Benjamin D Elder
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, 55905, USA; Department of Orthopedics, Mayo Clinic, Rochester, MN 55905, USA; Department of Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, 55905, USA
| | - John Huston
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
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18
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Gunter NB, Gebre RK, Graff-Radford J, Heckman MG, Jack CR, Lowe VJ, Knopman DS, Petersen RC, Ross OA, Vemuri P, Ramanan VK. Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes. Neurol Genet 2024; 10:e200120. [PMID: 38250184 PMCID: PMC10798228 DOI: 10.1212/nxg.0000000000200120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 11/01/2023] [Indexed: 01/23/2024]
Abstract
Background and Objectives Alzheimer disease (AD) has a polygenic architecture, for which genome-wide association studies (GWAS) have helped elucidate sequence variants (SVs) influencing susceptibility. Polygenic risk score (PRS) approaches show promise for generating summary measures of inherited risk for clinical AD based on the effects of APOE and other GWAS hits. However, existing PRS approaches, based on traditional regression models, explain only modest variation in AD dementia risk and AD-related endophenotypes. We hypothesized that machine learning (ML) models of polygenic risk (ML-PRS) could outperform standard regression-based PRS methods and therefore have the potential for greater clinical utility. Methods We analyzed combined data from the Mayo Clinic Study of Aging (n = 1,791) and the Alzheimer's Disease Neuroimaging Initiative (n = 864). An AD PRS was computed for each participant using the top common SVs obtained from a large AD dementia GWAS. In parallel, ML models were trained using those SV genotypes, with amyloid PET burden as the primary outcome. Secondary outcomes included amyloid PET positivity and clinical diagnosis (cognitively unimpaired vs impaired). We compared performance between ML-PRS and standard PRS across 100 training sessions with different data splits. In each session, data were split into 80% training and 20% testing, and then five-fold cross-validation was used within the training set to ensure the best model was produced for testing. We also applied permutation importance techniques to assess which genetic factors contributed most to outcome prediction. Results ML-PRS models outperformed the AD PRS (r2 = 0.28 vs r2 = 0.24 in test set) in explaining variation in amyloid PET burden. Among ML approaches, methods accounting for nonlinear genetic influences were superior to linear methods. ML-PRS models were also more accurate when predicting amyloid PET positivity (area under the curve [AUC] = 0.80 vs AUC = 0.63) and the presence of cognitive impairment (AUC = 0.75 vs AUC = 0.54) compared with the standard PRS. Discussion We found that ML-PRS approaches improved upon standard PRS for prediction of AD endophenotypes, partly related to improved accounting for nonlinear effects of genetic susceptibility alleles. Further adaptations of the ML-PRS framework could help to close the gap of remaining unexplained heritability for AD and therefore facilitate more accurate presymptomatic and early-stage risk stratification for clinical decision-making.
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Affiliation(s)
- Nathaniel B Gunter
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Robel K Gebre
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Jonathan Graff-Radford
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Michael G Heckman
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Clifford R Jack
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Val J Lowe
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - David S Knopman
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Ronald C Petersen
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Owen A Ross
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Prashanthi Vemuri
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
| | - Vijay K Ramanan
- From the Departments of Radiology (N.B.G., R.K.G., C.R.J., V.J.L., P.V.), Neurology (J.G.-R., D.S.K., R.C.P., V.K.R.), and Quantitative Health Sciences (R.C.P.), Mayo Clinic Rochester, MN; and Departments of Quantitative Health Sciences (M.G.H.), Neuroscience (O.A.R.), and Clinical Genomics (O.A.R.), Mayo Clinic Florida, Jacksonville
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Sintini I, Corriveau-Lecavalier N, Jones DT, Machulda MM, Gunter JL, Schwarz CG, Botha H, Carlos AF, Kamykowski MG, Singh NA, Petersen RC, Jack CR, Lowe VJ, Graff-Radford J, Josephs KA, Whitwell JL. Longitudinal default mode sub-networks in the language and visual variants of Alzheimer's disease. Brain Commun 2024; 6:fcae005. [PMID: 38444909 PMCID: PMC10914456 DOI: 10.1093/braincomms/fcae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/13/2023] [Accepted: 01/05/2024] [Indexed: 03/07/2024] Open
Abstract
Disruption of the default mode network is a hallmark of Alzheimer's disease, which has not been extensively examined in atypical phenotypes. We investigated cross-sectional and 1-year longitudinal changes in default mode network sub-systems in the visual and language variants of Alzheimer's disease, in relation to age and tau. Sixty-one amyloid-positive Alzheimer's disease participants diagnosed with posterior cortical atrophy (n = 33) or logopenic progressive aphasia (n = 28) underwent structural MRI, resting-state functional MRI and [18F]flortaucipir PET. One-hundred and twenty-two amyloid-negative cognitively unimpaired individuals and 60 amyloid-positive individuals diagnosed with amnestic Alzheimer's disease were included as controls and as a comparison group, respectively, and had structural and resting-state functional MRI. Forty-one atypical Alzheimer's disease participants, 26 amnestic Alzheimer's disease participants and 40 cognitively unimpaired individuals had one follow-up functional MRI ∼1-2 years after the baseline scan. Default mode network connectivity was calculated using the dual regression method for posterior, ventral, anterior ventral and anterior dorsal sub-systems derived from independent component analysis. A global measure of default mode network connectivity, the network failure quotient, was also calculated. Linear mixed-effects models and voxel-based analyses were computed for each connectivity measure. Both atypical and amnestic Alzheimer's disease participants had lower cross-sectional posterior and ventral and higher anterior dorsal connectivity and network failure quotient relative to cognitively unimpaired individuals. Age had opposite effects on connectivity in Alzheimer's disease participants and cognitively unimpaired individuals. While connectivity declined with age in cognitively unimpaired individuals, younger Alzheimer's disease participants had lower connectivity than the older ones, particularly in the ventral default mode network. Greater baseline tau-PET uptake was associated with lower ventral and anterior ventral default mode network connectivity in atypical Alzheimer's disease. Connectivity in the ventral default mode network declined over time in atypical Alzheimer's disease, particularly in older participants, with lower tau burden. Voxel-based analyses validated the findings of higher anterior dorsal default mode network connectivity, lower posterior and ventral default mode network connectivity and decline in ventral default mode network connectivity over time in atypical Alzheimer's disease. Visuospatial symptoms were associated with default mode network connectivity disruption. In summary, default mode connectivity disruption was similar between atypical and amnestic Alzheimer's disease variants, and discriminated Alzheimer's disease from cognitively unimpaired individuals, with decreased posterior and increased anterior connectivity and with disruption more pronounced in younger participants. The ventral default mode network declined over time in atypical Alzheimer's disease, suggesting a shift in default mode network connectivity likely related to tau pathology.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Arenn F Carlos
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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20
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Robinson CG, Coleman T, Buciuc M, Singh NA, Pham NTT, Machulda MM, Graff-Radford J, Whitwell JL, Josephs KA. Behavioral and Neuropsychiatric Differences Across Two Atypical Alzheimer's Disease Variants: Logopenic Progressive Aphasia and Posterior Cortical Atrophy. J Alzheimers Dis 2024; 97:895-908. [PMID: 38143349 PMCID: PMC10842893 DOI: 10.3233/jad-230652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2023]
Abstract
BACKGROUND Posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are two common atypical Alzheimer's disease (AD) variants. Little is known about behavioral and neuropsychiatric symptoms or activities of daily living (ADLs) in PCA and LPA, and whether they differ across syndromes. OBJECTIVE To characterize the behavioral and neuropsychiatric profiles and ADLs of PCA and LPA and compare presence/absence and severity of symptoms between syndromes. METHODS Seventy-eight atypical AD patients, 46 with PCA and 32 with LPA, completed the Neuropsychiatric Inventory Questionnaire (NPI-Q) and Cambridge Behavioral Inventory-Revised (CBI-R) at baseline and longitudinally over-time. Mann-Whitney U and Fisher's Exact Tests assessed for differences in symptoms between the two syndromes with significance set at p≤0.01. To eliminate demographic differences as confounders the groups were matched, and differences reanalyzed. RESULTS PCA were younger at onset (p = 0.006), at time of baseline assessment (p = 0.02) and had longer disease duration (p = 0.01). Neuropsychiatric symptoms were common in PCA and LPA, although more common and severe in PCA. At baseline, PCA had a higher NPI-Q total score (p = 0.01) and depression subscore (p = 0.01) than LPA. Baseline total CBI-R scores were also higher in PCA than LPA (p = 0.001) with PCA having worse scores in all 10 CBI-R categories. Longitudinally, there was no difference between groups on the NPI-Q. However, on the CBI-R, PCA had faster rates of worsening on self-grooming (p = 0.01) and self-dressing (p = 0.01) compared to LPA. CONCLUSIONS Behavioral and neuropsychiatric symptoms are common in PCA and LPA although these symptoms are more common and severe in PCA.
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Affiliation(s)
| | - Tia Coleman
- Department of Neurology, Mayo Clinic, Rochester, MN
| | - Marina Buciuc
- Department of Neurology, Medical University of South Carolina, Charleston, SC
| | | | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
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21
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Corriveau-Lecavalier N, Barnard LR, Przybelski SA, Gogineni V, Botha H, Graff-Radford J, Ramanan VK, Forsberg LK, Fields JA, Machulda MM, Rademakers R, Gavrilova RH, Lapid MI, Boeve BF, Knopman DS, Lowe VJ, Petersen RC, Jack CR, Kantarci K, Jones DT. Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET. Neuroimage Clin 2023; 41:103559. [PMID: 38147792 PMCID: PMC10944211 DOI: 10.1016/j.nicl.2023.103559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 11/21/2023] [Accepted: 12/19/2023] [Indexed: 12/28/2023]
Abstract
Genetic mutations causative of frontotemporal lobar degeneration (FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter-individual variability in their patterns of network degeneration and clinical manifestations. We collected clinical and 18Fluorodeoxyglucose-positron emission tomography (FDG-PET) data from 39 patients with genetic FTLD, including 11 carrying the C9orf72 hexanucleotide expansion, 16 carrying a MAPT mutation and 12 carrying a GRN mutation. We performed a spectral covariance decomposition analysis between FDG-PET images to yield unbiased latent patterns reflective of whole brain patterns of metabolism ("eigenbrains" or EBs). We then conducted linear discriminant analyses (LDAs) to perform EB-based predictions of genetic mutation and predominant clinical phenotype (i.e., behavior/personality, language, asymptomatic). Five EBs were significant and explained 58.52 % of the covariance between FDG-PET images. EBs indicative of hypometabolism in left frontotemporal and temporo-parietal areas distinguished GRN mutation carriers from other genetic mutations and were associated with predominant language phenotypes. EBs indicative of hypometabolism in prefrontal and temporopolar areas with a right hemispheric predominance were mostly associated with predominant behavioral phenotypes and distinguished MAPT mutation carriers from other genetic mutations. The LDAs yielded accuracies of 79.5 % and 76.9 % in predicting genetic status and predominant clinical phenotype, respectively. A small number of EBs explained a high proportion of covariance in patterns of network degeneration across FTLD-related genetic mutations. These EBs contained biological information relevant to the variability in the pathophysiological and clinical aspects of genetic FTLD, and for offering valuable guidance in complex clinical decision-making, such as decisions related to genetic testing.
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Affiliation(s)
- Nick Corriveau-Lecavalier
- Department of Neurology, Mayo Clinic Rochester, USA; Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA
| | | | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic Rochester, USA
| | | | | | | | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic Jacksonville, USA; VIB-UA Center for Molecular Neurology, VIB, University of Antwerp, Belgium
| | | | - Maria I Lapid
- Department of Psychiatry and Psychology, Mayo Clinic Rochester, USA
| | | | | | - Val J Lowe
- Department of Radiology, Mayo Clinic Rochester, USA
| | | | | | | | - David T Jones
- Department of Neurology, Mayo Clinic Rochester, USA; Department of Radiology, Mayo Clinic Rochester, USA.
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22
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Kir D, Van Houten HK, Walvatne KN, Behnken EM, Alkhouli MA, Graff-Radford J, Melduni RM, Gersh BJ, Friedman PA, Shah ND, Noseworthy PA, Yao X. Physicians' perspectives on percutaneous left atrial appendage occlusion for patients with atrial fibrillation. Am Heart J 2023; 266:14-24. [PMID: 37567353 DOI: 10.1016/j.ahj.2023.07.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 07/02/2023] [Accepted: 07/25/2023] [Indexed: 08/13/2023]
Abstract
BACKGROUND There has been an increasing uptake of transcatheter left atrial appendage occlusion (LAAO) for stroke reduction in atrial fibrillation. OBJECTIVES To investigate the perceptions and approaches among a nationally representative sample of physicians. METHODS Using the American Medical Association Physician Masterfile, we selected a random sample of 500 physicians from each of the specialties: general cardiologists, interventional cardiologists, electrophysiologists, and vascular neurologists. The participants received the survey by mail up to three times from November 9, 2021 to January 14, 2022. In addition to the questions about experiences, perceptions, and approaches, physicians were randomly assigned to 1 of the 4 versions of a patient vignette: white man, white woman, black man, and black woman, to investigate potential bias in decision-making. RESULTS The top three reasons for considering LAAO were: a history of intracranial bleeding (94.3%), a history of major extracranial bleeding (91.8%), and gastrointestinal lesions (59.0%), whereas the top three reasons for withholding LAAO were: other indications for long-term oral anticoagulation (87.7%), a low bleeding risk (77.0%), and a low stroke risk (65.6%). For the reasons limiting recommendations for LAAO, 59.8% mentioned procedural risks, 42.6% mentioned "limiting efficacy data comparing LAAO to NOAC" and 32.8% mentioned "limited safety data comparing LAAO to NOAC." There was no difference in physicians' decision-making by patients' race, gender, or the concordance between patients' and physicians' race or gender. CONCLUSIONS In the first U.S. national physician survey of LAAO, individual physicians' perspectives varied greatly, which provided information that will help customize future educational activities for different audiences. CONDENSED ABSTRACT Although diverse practice patterns of LAAO have been documented, little is known about the reasoning or perceptions that drive these variations. Unlike prior surveys that were directed to Centers that performed LAAO, the current survey obtained insights from individual physicians, not only those who perform the procedures (interventional cardiologists and electrophysiologists) but also those who are closely involved in the decision-making and referral process (general cardiologists and vascular neurologists). The findings identify key evidence gaps and help prioritize future studies to establish a consistent and evidence-based best practice for AF stroke prevention.
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Affiliation(s)
- Devika Kir
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester MN
| | - Holly K Van Houten
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Kelli N Walvatne
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Emma M Behnken
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
| | | | | | | | - Bernard J Gersh
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester MN
| | - Paul A Friedman
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester MN
| | | | - Peter A Noseworthy
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester MN; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Xiaoxi Yao
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester MN; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
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23
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Camerucci E, Elder BD, Shu Y, Messina SA, Gunter JL, Graff-Radford J, Jones DT, Botha H, Cutsforth-Gregory JK, Jack CR, Huston J, Cogswell PM. Field strength difference in extent of artifacts induced by CERTAS Plus valves in patients with idiopathic normal pressure hydrocephalus. Neuroradiol J 2023; 36:665-673. [PMID: 37118867 PMCID: PMC10649542 DOI: 10.1177/19714009231173099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND AND PURPOSE : Post-shunt MRI is usually performed at 1.5T under the general assumption that shunt-related susceptibility artifacts would be greater at higher field strengths. PURPOSE The purpose is to show that imaging post-shunt idiopathic normal pressure hydrocephalus (iNPH) patients at 3T is feasible and with reduced artifacts as compared to 1.5T. METHODS We manually measured transverse dimensions of artifact at the levels of lateral ventricles, cerebral aqueduct, and cerebellar hemisphere. Areas/volumes of artifacts were calculated assuming an elliptic/ellipsoid shape. Relative extent of shunt-related artifact between field strengths was rated by 3 readers on a 5-point Likert scale. A Wilcoxon Signed Rank Test was used to compare artifact at 1.5T vs 3T for each sequence, with a significance level set at p < 0.05. RESULTS Artifact areas were calculated in 22 iNPH patients; artifacts were on average smaller at 3T vs 1.5T on MPRAGE, DWI, and GRE sequences. On T2 FLAIR and T2 FSE, artifacts at 3T were larger than 1.5T. On the qualitative analysis, artifact effects were less at 3T vs 1.5T on DWI, greater at 3T on T2 FSE, and had mixed results on GRE. CONCLUSION Our results indicate feasibility of post-shunt imaging with the CERTAS Plus valve at 3T based on shunt-related artifact that is less than or equal in extent to that on 1.5T on most standard clinical imaging sequences. Our findings, corroborated by the qualitative image review, suggest that dedicated clinical imaging sequences for devices may allow for reduction in artifact extent at both 1.5T and 3T.
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Affiliation(s)
| | - Benjamin D Elder
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Yunhong Shu
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - John Huston
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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24
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Corriveau-Lecavalier N, Botha H, Graff-Radford J, Switzer AR, Przybelski SA, Wiste HJ, Murray ME, Reichard RR, Dickson DW, Nguyen AT, Ramanan VK, McCarter SJ, Boeve BF, Machulda MM, Fields JA, Stricker NH, Nelson PT, Grothe MJ, Knopman DS, Lowe VJ, Petersen RC, Jack CR, Jones DT. A limbic-predominant amnestic neurodegenerative syndrome associated with TDP-43 pathology. medRxiv 2023:2023.11.19.23298314. [PMID: 38045300 PMCID: PMC10690340 DOI: 10.1101/2023.11.19.23298314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a neuropathologically-defined disease that affects 40% of persons in advanced age, but its associated neurological syndrome is not defined. LATE neuropathological changes (LATE-NC) are frequently comorbid with Alzheimer's disease neuropathologic changes (ADNC). When seen in isolation, LATE-NC have been associated with a predominantly amnestic profile and slow clinical progression. We propose a set of clinical criteria for a limbic-predominant amnestic neurodegenerative syndrome (LANS) that is highly associated with LATE-NC but also other pathologic entities. The LANS criteria incorporate core, standard and advanced features that are measurable in vivo, including older age at evaluation, mild clinical syndrome, disproportionate hippocampal atrophy, impaired semantic memory, limbic hypometabolism, absence of neocortical degenerative patterns and low likelihood of neocortical tau, with degrees of certainty (highest, high, moderate, low). We operationalized this set of criteria using clinical, imaging and biomarker data to validate its associations with clinical and pathologic outcomes. We screened autopsied patients from Mayo Clinic (n = 922) and ADNI (n = 93) cohorts and applied the LANS criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; ADNI, n = 53). ADNC, ADNC/LATE-NC and LATE-NC accounted for 35%, 37% and 4% of cases in the Mayo cohort, respectively, and 30%, 22%, and 9% of cases in the ADNI cohort, respectively. The LANS criteria effectively categorized these cases, with ADNC having the lowest LANS likelihoods, LATE-NC patients having the highest likelihoods, and ADNC/LATE-NC patients having intermediate likelihoods. A logistic regression model using the LANS features as predictors of LATE-NC achieved a balanced accuracy of 74.6% in the Mayo cohort, and out-of-sample predictions in the ADNI cohort achieved a balanced accuracy of 73.3%. Patients with high LANS likelihoods had a milder and slower clinical course and more severe temporo-limbic degeneration compared to those with low likelihoods. Stratifying ADNC/LATE-NC patients from the Mayo cohort according to their LANS likelihood revealed that those with higher likelihoods had more temporo-limbic degeneration and a slower rate of cognitive decline, and those with lower likelihoods had more lateral temporo-parietal degeneration and a faster rate of cognitive decline. The implementation of LANS criteria has implications to disambiguate the different driving etiologies of progressive amnestic presentations in older age and guide prognosis, treatment, and clinical trials. The development of in vivo biomarkers specific to TDP-43 pathology are needed to refine molecular associations between LANS and LATE-NC and precise antemortem diagnoses of LATE.
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Affiliation(s)
- Nick Corriveau-Lecavalier
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Heather J. Wiste
- Department of Quantitative Health Sciences, Mayo Clinic Rochester, MN, USA
| | | | - R. Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic Rochester, MN, USA
| | | | - Aivi T. Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic Rochester, MN, USA
| | | | | | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Julie A. Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Nikki H. Stricker
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Peter T. Nelson
- Department of Pathology, University of Kentucky, Lexington, KY, USA
| | - Michel J. Grothe
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
- Wallenberg Center for Molecular and Translational Medicine and Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Clifford R. Jack
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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25
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Switzer A, Charidimou A, McCarter SJ, Vemuri P, Nguyen A, Przybelski SA, Lesnick TG, Rabinstein AA, Brown RD, Knopman DS, Petersen RC, Jack CR, Reichard RR, Graff-Radford J. Boston criteria v2.0 for cerebral amyloid angiopathy without hemorrhage: An MRI-neuropathological validation study. medRxiv 2023:2023.11.09.23298325. [PMID: 37986913 PMCID: PMC10659504 DOI: 10.1101/2023.11.09.23298325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
BACKGROUND Updated criteria for the clinical-MRI diagnosis of cerebral amyloid angiopathy (CAA) have recently been proposed. However, their performance in individuals without intracerebral hemorrhage (ICH) or transient focal neurological episodes (TFNE) is unknown. We assessed the diagnostic performance of the Boston criteria version 2.0 for CAA diagnosis in a cohort of individuals presenting without symptomatic ICH. METHODS Fifty-four participants from the Mayo Clinic Study of Aging or Alzheimer's Disease Research Center were included if they had an antemortem MRI with gradient-recall echo sequences and a brain autopsy with CAA evaluation. Performance of the Boston criteria v2.0 was compared to v1.5 using histopathologically verified CAA as the reference standard. RESULTS Median age at MRI was 75 years (IQR 65-80) with 28/54 participants having histopathologically verified CAA (i.e., moderate-to-severe CAA in at least 1 lobar region). The sensitivity and specificity of the Boston criteria v2.0 were 28.6% (95%CI: 13.2-48.7%) and 65.3% (95%CI: 44.3-82.8%) for probable CAA diagnosis (AUC 0.47) and 75.0% (55.1-89.3) and 38.5% (20.2-59.4) for any CAA diagnosis (possible + probable; AUC: 0.57), respectively. The v2.0 Boston criteria was not superior in performance compared to the prior v1.5 criteria for either CAA diagnostic category. CONCLUSIONS The Boston criteria v2.0 have low accuracy in patients who are asymptomatic or only have cognitive symptoms.. Additional biomarkers need to be explored to optimize CAA diagnosis in this population.
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26
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Pittock RR, Aakre JA, Castillo AM, Ramanan VK, Kremers WK, Jack CR, Vemuri P, Lowe VJ, Knopman DS, Petersen RC, Graff-Radford J, Vassilaki M. Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging. Neurology 2023; 101:e1837-e1849. [PMID: 37586881 PMCID: PMC10663008 DOI: 10.1212/wnl.0000000000207770] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 08/04/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Treatment options for Alzheimer disease (AD) are limited and have focused mainly on symptomatic therapy and improving quality of life. Recently, lecanemab, an anti-β-amyloid monoclonal antibody (mAb), received accelerated approval by the US Food and Drug Administration for treatment in the early stages of biomarker-confirmed symptomatic AD. An additional anti-β-amyloid mAb, aducanumab, was approved in 2021, and more will potentially become available in the near future. Research on the applicability and generalizability of the anti-β-amyloid mAb eligibility criteria on adults with biomarkers available in the general population has been lacking. The study's primary aim was to apply the clinical trial eligibility criteria for lecanemab treatment to participants with early AD of the population-based Mayo Clinic Study of Aging (MCSA) and assess the generalizability of anti-amyloid treatment. The secondary aim of this study was to apply the clinical trial eligibility criteria for aducanumab treatment in MCSA participants. METHODS This cross-sectional study aimed to apply the clinical trial eligibility criteria for lecanemab and aducanumab treatment to participants with early AD of the population-based MCSA and assess the generalizability of anti-amyloid treatment. RESULTS Two hundred thirty-seven MCSA participants (mean age [SD] 80.9 [6.3] years, 54.9% male, and 97.5% White) with mild cognitive impairment (MCI) or mild dementia and increased brain amyloid burden by PiB PET comprised the study sample. Lecanemab trial's inclusion criteria reduced the study sample to 112 (47.3% of 237) participants. The trial's exclusion criteria further narrowed the number of potentially eligible participants to 19 (overall 8% of 237). Modifying the eligibility criteria to include all participants with MCI (instead of applying additional cognitive criteria) resulted in 17.4% of participants with MCI being eligible for lecanemab treatment. One hundred four participants (43.9% of 237) fulfilled the aducanumab clinical trial's inclusion criteria. The aducanumab trial's exclusion criteria further reduced the number of available participants, narrowing those eligible to 12 (5.1% of 237). Common exclusions were related to other chronic conditions and neuroimaging findings. DISCUSSION Findings estimate the limited eligibility in typical older adults with cognitive impairment for anti-β-amyloid mAbs.
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Affiliation(s)
- Rioghna R Pittock
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Jeremiah A Aakre
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Anna M Castillo
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Vijay K Ramanan
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Walter K Kremers
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Val J Lowe
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - David S Knopman
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Jonathan Graff-Radford
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN
| | - Maria Vassilaki
- From the Department of Neurology (R.R.P., V.K.R., D.S.K., R.C.P., J.G.-R.), Mayo Clinic, Rochester, MN; The College (R.R.P.), University of Chicago, IL; Departments of Quantitative Health Sciences (J.A.A., A.M.C., W.K.K., R.C.P., M.V.) and Radiology (C.R.J., P.V., V.J.L.), Mayo Clinic, Rochester, MN.
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Vassilaki M, Syrjanen JA, Krell-Roesch J, Graff-Radford J, Vemuri P, Scharf EL, Machulda MM, Fields JA, Kremers WK, Lowe VJ, Jack CR, Knopman DS, Petersen RC, Geda YE. Association of Cerebrovascular Imaging Biomarkers, Depression, and Anxiety, with Mild Cognitive Impairment. J Alzheimers Dis Rep 2023; 7:1237-1246. [PMID: 38025797 PMCID: PMC10657723 DOI: 10.3233/adr-230073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Accepted: 10/08/2023] [Indexed: 12/01/2023] Open
Abstract
The study included 1,738 Mayo Clinic Study of Aging participants (≥50 years old; 1,460 cognitively unimpaired and 278 with mild cognitive impairment (MCI)) and examined the cross-sectional association between cerebrovascular (CVD) imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) and Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) scores, as well as their association with MCI. High (abnormal) WMH burden was significantly associated with having BDI-II>13 and BAI > 7 scores, and both (CVD imaging biomarkers and depression/anxiety) were significantly associated with MCI when included simultaneously in the model, suggesting that both were independently associated with the odds of MCI.
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Affiliation(s)
- Maria Vassilaki
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Jeremy A. Syrjanen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Janina Krell-Roesch
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | | | | | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Julie A. Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Walter K. Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Ronald C. Petersen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Yonas E. Geda
- Department of Neurology, and the Franke Barrow Global Neuroscience Education Center, Barrow Neurological Institute, Phoenix, AZ, USA
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Ramanan VK, Gebre RK, Graff-Radford J, Hofrenning E, Algeciras-Schimnich A, Figdore DJ, Lowe VJ, Mielke MM, Knopman DS, Ross OA, Jack CR, Petersen RC, Vemuri P. Genetic risk scores enhance the diagnostic value of plasma biomarkers of brain amyloidosis. Brain 2023; 146:4508-4519. [PMID: 37279785 PMCID: PMC10629762 DOI: 10.1093/brain/awad196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 05/02/2023] [Accepted: 05/14/2023] [Indexed: 06/08/2023] Open
Abstract
Blood-based biomarkers offer strong potential to revolutionize diagnosis, trial enrolment and treatment monitoring in Alzheimer's disease (AD). However, further advances are needed before these biomarkers can achieve wider deployment beyond selective research studies and specialty memory clinics, including the development of frameworks for optimal interpretation of biomarker profiles. We hypothesized that integrating Alzheimer's disease genetic risk score (AD-GRS) data would enhance the diagnostic value of plasma AD biomarkers by better capturing extant disease heterogeneity. Analysing 962 individuals from a population-based sample, we observed that an AD-GRS was independently associated with amyloid PET levels (an early marker of AD pathophysiology) over and above APOE ε4 or plasma p-tau181, amyloid-β42/40, glial fibrillary acidic protein or neurofilament light chain. Among individuals with a high or moderately high plasma p-tau181, integrating AD-GRS data significantly improved classification accuracy of amyloid PET positivity, including the finding that the combination of a high AD-GRS and high plasma p-tau181 outperformed p-tau181 alone in classifying amyloid PET positivity (88% versus 68%; P = 0.001). A machine learning approach incorporating plasma biomarkers, demographics and the AD-GRS was highly accurate in predicting amyloid PET levels (90% training set; 89% test set) and Shapley value analyses (an explainer method based in cooperative game theory) indicated that the AD-GRS and plasma biomarkers had differential importance in explaining amyloid deposition across individuals. Polygenic risk for AD dementia appears to account for a unique portion of disease heterogeneity, which could non-invasively enhance the interpretation of blood-based AD biomarker profiles in the population.
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Affiliation(s)
- Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Robel K Gebre
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Ekaterina Hofrenning
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Daniel J Figdore
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
- Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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Mielke MM, Dage JL, Frank RD, Algeciras-Schimnich A, Knopman DS, Lowe VJ, Bu G, Vemuri P, Graff-Radford J, Jack CR, Petersen RC. Author Correction: Performance of plasma phosphorylated tau 181 and 217 in the community. Nat Med 2023; 29:2954. [PMID: 36216947 DOI: 10.1038/s41591-022-02066-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Michelle M Mielke
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
- Department of Neurology, Mayo Clinic, Rochester, MN, USA.
- Department of Epidemiology and Prevention, School of Medicine, Wake Forest University, Winston-Salem, NC, USA.
| | - Jeffrey L Dage
- Stark Neurosciences Research Institute, School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Ryan D Frank
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Guojun Bu
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | | | | | - Ronald C Petersen
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
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Gebre RK, Rial AM, Raghavan S, Wiste HJ, Johnson Sparrman KL, Heeman F, Costoya-Sánchez A, Schwarz CG, Spychalla AJ, Lowe VJ, Graff-Radford J, Knopman DS, Petersen RC, Schöll M, Jack CR, Vemuri P. Advancing Tau-PET quantification in Alzheimer's disease with machine learning: introducing THETA, a novel tau summary measure. Res Sq 2023:rs.3.rs-3290598. [PMID: 37886506 PMCID: PMC10602128 DOI: 10.21203/rs.3.rs-3290598/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Alzheimer's disease (AD) exhibits spatially heterogeneous 3R/4R tau pathology distributions across participants, making it a challenge to quantify extent of tau deposition. Utilizing Tau-PET from three independent cohorts, we trained and validated a machine learning model to identify visually positive Tau-PET scans from regional SUVR values and developed a novel summary measure, THETA, that accounts for heterogeneity in tau deposition. The model for identification of tau positivity achieved a balanced test accuracy of 95% and accuracy of ≥87% on the validation datasets. THETA captured heterogeneity of tau deposition, had better association with clinical measures, and corresponded better with visual assessments in comparison with the temporal meta-region-of-interest Tau-PET quantification methods. Our novel approach aids in identification of positive Tau-PET scans and provides a quantitative summary measure, THETA, that effectively captures the heterogeneous tau deposition seen in AD. The application of THETA for quantifying Tau-PET in AD exhibits great potential.
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Affiliation(s)
- Robel K. Gebre
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Alexis Moscoso Rial
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | | | - Heather J. Wiste
- Department of Qualitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Fiona Heeman
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Alejandro Costoya-Sánchez
- Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Travesía da Choupana s/n, Santiago de Compostela, 15706, Spain
| | | | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - Ronald C. Petersen
- Department of Qualitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Michael Schöll
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Nuclear Medicine Department and Molecular Imaging Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Travesía da Choupana s/n, Santiago de Compostela, 15706, Spain
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Ramanan VK, Graff-Radford J, Syrjanen J, Shir D, Algeciras-Schimnich A, Lucas J, Martens YA, Carrasquillo MM, Day GS, Ertekin-Taner N, Lachner C, Willis FB, Knopman DS, Jack CR, Petersen RC, Vemuri P, Graff-Radford N, Mielke MM. Association of Plasma Biomarkers of Alzheimer Disease With Cognition and Medical Comorbidities in a Biracial Cohort. Neurology 2023; 101:e1402-e1411. [PMID: 37580163 PMCID: PMC10573134 DOI: 10.1212/wnl.0000000000207675] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 06/06/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Recent advances in blood-based biomarkers offer the potential to revolutionize the diagnosis and management of Alzheimer disease (AD), but additional research in diverse populations is critical. We assessed the profiles of blood-based AD biomarkers and their relationships to cognition and common medical comorbidities in a biracial cohort. METHODS Participants were evaluated through the Mayo Clinic Jacksonville Alzheimer Disease Research Center and matched on age, sex, and cognitive status. Plasma AD biomarkers (β-amyloid peptide 1-42 [Aβ42/40], plasma tau phosphorylated at position 181 [p-tau181], glial fibrillary acidic protein [GFAP], and neurofilament light) were measured using the Quanterix SiMoA HD-X analyzer. Cognition was assessed with the Mini-Mental State Examination. Wilcoxon rank sum tests were used to assess for differences in plasma biomarker levels by sex. Linear models tested for associations of self-reported race, chronic kidney disease (CKD), and vascular risk factors with plasma AD biomarker levels. Additional models assessed for interactions between race and plasma biomarkers in predicting cognition. RESULTS The sample comprised African American (AA; N = 267) and non-Hispanic White (NHW; N = 268) participants, including 69% female participants and age range 43-100 (median 80.2) years. Education was higher in NHW participants (median 16 vs 12 years, p < 0.001) while APOE ε4 positivity was higher in AA participants (43% vs 34%; p = 0.04). We observed no differences in plasma AD biomarker levels between AA and NHW participants. These results were unchanged after stratifying by cognitive status (unimpaired vs impaired). Although the p-tau181-cognition association seemed stronger in NHW participants while the Aβ42/40-cognition association seemed stronger in AA participants, these findings did not survive after excluding individuals with CKD. Female participants displayed higher GFAP (177.5 pg/mL vs 157.73 pg/mL; p = 0.002) and lower p-tau181 (2.62 pg/mL vs 3.28 pg/mL; p = 0.001) levels than male participants. Diabetes was inversely associated with GFAP levels (β = -0.01; p < 0.001). DISCUSSION In a biracial community-based sample of adults, we observed that sex differences, CKD, and vascular risk factors, but not self-reported race, contributed to variation in plasma AD biomarkers. Although some prior studies have reported primary effects of race/ethnicity, our results reinforce the need to account for broad-based medical and social determinants of health (including sex, systemic comorbidities, and other factors) in effectively and equitably deploying plasma AD biomarkers in the general population.
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Affiliation(s)
- Vijay K Ramanan
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC.
| | - Jonathan Graff-Radford
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Jeremy Syrjanen
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Dror Shir
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Alicia Algeciras-Schimnich
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - John Lucas
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Yuka A Martens
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Minerva M Carrasquillo
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Gregory S Day
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Nilüfer Ertekin-Taner
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Christian Lachner
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Floyd B Willis
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - David S Knopman
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Clifford R Jack
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Ronald C Petersen
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Prashanthi Vemuri
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Neill Graff-Radford
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Michelle M Mielke
- From the Department of Neurology (V.K.R., J.G.-R., D.S., D.S.K., R.C.P.), Department of Quantitative Health Sciences (J.S., R.C.P.), and Department of Laboratory Medicine and Pathology (A.A.-S.), Mayo Clinic, Rochester, MN; Department of Psychiatry and Psychology (J.L., C.L.), Department of Neuroscience (Y.A.M., M.M.C., G.S.D., N.E.-T.), Department of Neurology (N.E.-T., C.L., N.G.-R.), and Department of Family Medicine (F.B.W.), Mayo Clinic, Jacksonville, FL; Department of Radiology (C.R.J., P.V.), Mayo Clinic, Rochester, MN; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
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Okine DN, Knopman DS, Mosley TH, Wong DF, Johansen MC, Walker KA, Jack CR, Kantarci K, Pike JR, Graff-Radford J, Gottesman RF. Cerebral Microbleed Patterns and Cortical Amyloid-β: The ARIC-PET Study. Stroke 2023; 54:2613-2620. [PMID: 37638398 PMCID: PMC10877560 DOI: 10.1161/strokeaha.123.042835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 08/02/2023] [Indexed: 08/29/2023]
Abstract
BACKGROUND Cerebral microbleeds (CMBs) are associated with cognitive decline, but their importance outside of cerebral amyloid angiopathy and the mechanisms of their impact on cognition are poorly understood. We evaluated the cross-sectional association between CMB patterns and cerebral Aβ (amyloid-β) deposition, by florbetapir positron emission tomography. METHODS The longitudinal ARIC study (Atherosclerosis Risk in Communities) recruited individuals from 4 US communities from 1987 to 1989. From 2012 to 2014, the ARIC-PET (Atherosclerosis Risk in Communities - Positron Emission Tomography) ancillary recruited 322 nondemented ARIC participants who completed 3T brain magnetic resonance imaging with T2*GRE as part of ARIC visit 5 to undergo florbetapir positron emission tomography imaging. Magnetic resonance imaging images were read for CMBs and superficial siderosis; on positron emission tomography, global cortical standardized uptake value ratio >1.2 was considered a positive Aβ scan. Multivariable logistic regression models evaluated CMB characteristics in association with Aβ positivity. Effect modification by sex, race, APOE status, and cognition was evaluated. RESULTS CMBs were present in 24% of ARIC-PET participants. No significant associations were found between CMBs and Aβ positivity, but a pattern of isolated lobar CMBs or superficial siderosis was associated with over 4-fold higher odds of elevated Aβ when compared with those with no CMBs (odds ratio, 4.72 [95% CI, 1.16-19.16]). A similar elevated risk was not observed in those with isolated subcortical or mixed subcortical and either lobar CMBs or superficial siderosis. Although no significant interactions were found, effect estimates for elevated Aβ were nonsignificantly lower (P>0.10, odds ratio, 0.4-0.6) for a mixed CMB pattern, and odds ratios were nonsignificantly higher for lobar-only CMBs for 4 subgroups: women (versus men); Black participants (versus White participants), APOE ε4 noncarriers (versus carriers), and cognitively normal (versus mild cognitive impairment). CONCLUSIONS In this community-based cohort of nondemented adults, lobar-only pattern of CMBs or superficial siderosis is most strongly associated with brain Aβ, with no elevated risk for a mixed CMB pattern. Further studies are needed to understand differences in CMB patterns and their meaning across subgroups.
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Affiliation(s)
- Derrick N. Okine
- National Institute of Neurological Disorders and Stroke Intramural Research Program, NIH, Bethesda, MD
| | | | - Thomas H. Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Dean F. Wong
- Department of Radiology, Washington University, St. Louis, MO
| | - Michelle C. Johansen
- Department of Neurology, The John Hopkins University School of Medicine, Baltimore, MD
| | - Keenan A. Walker
- National Institute on Aging Intramural Program, NIH, Baltimore, MD
| | | | | | - James R. Pike
- Gillings School of Global Public Health, University of North Carolina
| | | | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, NIH, Bethesda, MD
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Sintini I, Graff-Radford J, Schwarz CG, Machulda MM, Singh NA, Carlos AF, Senjem ML, Jack CR, Lowe VJ, Josephs KA, Whitwell JL. Longitudinal rates of atrophy and tau accumulation differ between the visual and language variants of atypical Alzheimer's disease. Alzheimers Dement 2023; 19:4396-4406. [PMID: 37485642 PMCID: PMC10592409 DOI: 10.1002/alz.13396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 05/19/2023] [Accepted: 06/19/2023] [Indexed: 07/25/2023]
Abstract
INTRODUCTION Atypical variants of Alzheimer's disease (AD) include the visual variant, known as posterior cortical atrophy (PCA), and the language variant, known as logopenic progressive aphasia (LPA). Clinically, rates of disease progression differ between them. METHODS We evaluated 34 PCA and 29 LPA participants. Structural magnetic resonance imaging and 18 F-flortaucipir positron emission tomography were performed at baseline and at 1-year follow-up. Rates of change in tau uptake and grey matter volumes were compared between PCA and LPA with linear mixed-effects models and voxel-based analyses. RESULTS PCA had faster rates of occipital atrophy. LPA had faster rates of left temporal atrophy and faster rates of tau accumulation in the parietal, right temporal, and occipital lobes. Age was negatively associated with rates of atrophy and tau accumulation. DISCUSSION Longitudinal patterns of neuroimaging abnormalities differed between PCA and LPA, although with divergent results for tau accumulation and atrophy. HIGHLIGHTS The language variant of Alzheimer's disease accumulates tau faster than the visual variant. Each variant shows faster rates of atrophy than the other in its signature regions. Age negatively influences rates of atrophy and tau accumulation in both variants.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, USA, 55905
| | | | | | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester MN, USA, 55905
| | | | - Arenn F. Carlos
- Department of Neurology, Mayo Clinic, Rochester, MN, USA, 55905
| | - Matthew L. Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA, 55905
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA, 55905
| | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA, 55905
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Schwarz CG, Kremers WK, Weigand SD, Prakaashana CM, Senjem ML, Przybelski SA, Lowe VJ, Gunter JL, Kantarci K, Vemuri P, Graff-Radford J, Petersen RC, Knopman DS, Jack CR. Effects of de-facing software mri_reface on utility of imaging biomarkers used in Alzheimer's disease research. Neuroimage Clin 2023; 40:103507. [PMID: 37703605 PMCID: PMC10502400 DOI: 10.1016/j.nicl.2023.103507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 08/07/2023] [Accepted: 09/05/2023] [Indexed: 09/15/2023]
Abstract
Brain imaging research studies increasingly use "de-facing" software to remove or replace facial imagery before public data sharing. Several works have studied the effects of de-facing software on brain imaging biomarkers by directly comparing automated measurements from unmodified vs de-faced images, but most research brain images are used in analyses of correlations with cognitive measurements or clinical statuses, and the effects of de-facing on these types of imaging-to-cognition correlations has not been measured. In this work, we focused on brain imaging measures of amyloid (A), tau (T), neurodegeneration (N), and vascular (V) measures used in Alzheimer's Disease (AD) research. We created a retrospective sample of participants from three age- and sex-matched clinical groups (cognitively unimpaired, mild cognitive impairment, and AD dementia, and we performed region- and voxel-wise analyses of: hippocampal volume (N), white matter hyperintensity volume (V), amyloid PET (A), and tau PET (T) measures, each from multiple software pipelines, on their ability to separate cognitively defined groups and their degrees of correlation with age and Clinical Dementia Rating (CDR)-Sum of Boxes (CDR-SB). We performed each of these analyses twice: once with unmodified images and once with images de-faced with leading de-facing software mri_reface, and we directly compared the findings and their statistical strengths between the original vs. the de-faced images. Analyses with original and with de-faced images had very high agreement. There were no significant differences between any voxel-wise comparisons. Among region-wise comparisons, only three out of 55 correlations were significantly different between original and de-faced images, and these were not significant after correction for multiple comparisons. Overall, the statistical power of the imaging data for AD biomarkers was almost identical between unmodified and de-faced images, and their analyses results were extremely consistent.
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Affiliation(s)
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Division of Clinical Trials & Biostatistics, Mayo Clinic, Rochester, MN, USA
| | - Stephen D Weigand
- Department of Quantitative Health Sciences, Division of Clinical Trials & Biostatistics, Mayo Clinic, Rochester, MN, USA
| | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA; Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Division of Clinical Trials & Biostatistics, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Singh NA, Martin PR, Graff-Radford J, Machulda MM, Carrasquillo MM, Ertekin-Taner N, Josephs KA, Whitwell JL. APOE ε4 influences within and between network functional connectivity in posterior cortical atrophy and logopenic progressive aphasia. Alzheimers Dement 2023; 19:3858-3866. [PMID: 36999481 PMCID: PMC10523970 DOI: 10.1002/alz.13059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 02/07/2023] [Accepted: 03/07/2023] [Indexed: 04/01/2023]
Abstract
INTRODUCTION Presence of apolipoprotein E (APOE) ε4 has shown greater predisposition to medial temporal involvement in posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA). Little is known about its influence on memory network connectivity, a network comprised of medial temporal structures. METHODS Fifty-eight PCA and 82 LPA patients underwent structural and resting state functional magnetic resonance imaging (MRI). Bayesian hierarchical linear models assessed the influence of APOE ε4 on within and between-network connectivity for five networks. RESULTS APOE ε4 carriers showed reduced memory and language within-network connectivity in LPA and increased salience within-network connectivity in PCA compared to non-carriers. Between-network analysis showed evidence of reduced DMN connectivity in APOE ε4 carriers, with reduced DMN-to-salience and DMN-to-language network connectivity in PCA, and reduced DMN-to-visual network connectivity in LPA. DISCUSSION The APOE genotype influences brain connectivity, both within and between-networks, in atypical Alzheimer's disease. However, there was evidence that the modulatory effects of APOE differ across phenotype. HIGHLIGHTS APOE genotype is associated with reductions in within-network connectivity for the memory and language networks in LPA APOE genotype is associated with reductions in language-to-visual connectivity in LPA and PCA APOE genotype has no effect on the memory network in PCA.
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Affiliation(s)
| | - Peter R Martin
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Mary M Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
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Thotamgari SR, Babbili A, Bucchanolla P, Thakkar S, Patel HP, Spaseski MB, Graff-Radford J, Rabinstein AA, Asad ZUA, Asirvatham SJ, Holmes DR, Deshmukh A, DeSimone CV. Impact of Atrial Fibrillation on Outcomes in Patients Hospitalized With Nontraumatic Intracerebral Hemorrhage. Mayo Clin Proc Innov Qual Outcomes 2023; 7:222-230. [PMID: 37304065 PMCID: PMC10250577 DOI: 10.1016/j.mayocpiqo.2023.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023] Open
Abstract
Objective To assess the effect of atrial fibrillation (AF) on outcomes in hospitalizations for non-traumatic intracerebral hemorrhage (ICH). Patients and Methods We queried the National Inpatient Sample database between January 1, 2016, and December 31, 2019, to identify hospitalizations with an index diagnosis of non-traumatic ICH using ICD-10 code I61. The cohort was divided into patients with and without AF. Propensity score matching was used to balance the covariates between AF and non-AF groups. Logistic regression was used to analyze the association. All statistical analyses were performed using weighted values. Results Our cohort included 292,725 hospitalizations with a primary discharge diagnosis of non-traumatic ICH. From this group, 59,005 (20%) recorded a concurrent diagnosis of AF, and 46% of these patients with AF were taking anticoagulants. Patients with AF reported a higher Elixhauser comorbidity index (19.8±6.0 vs 16.6±6.4; P<.001) before propensity matching. After propensity matching, the multivariate analysis reported that AF (aOR, 2.34; 95% CI, 2.26-2.42; P<.001) and anticoagulation drug use (aOR, 1.32; 95% CI, 1.28-1.37; P<.001) were independently associated with all-cause in-hospital mortality. Moreover, AF was significantly associated with respiratory failure requiring mechanical ventilation (odds ratio, 1.57; 95% CI, 1.52-1.62; P<.001) and acute heart failure (odds ratio, 1.26; 95% CI, 1.19-1.33; P<.001) compared with the absence of AF. Conclusion These data suggest that non-traumatic ICH hospitalizations with coexistent AF are associated with worse in-hospital outcomes such as higher mortality and acute heart failure.
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Affiliation(s)
| | - Akhilesh Babbili
- Department of Internal Medicine, Louisiana State University Health, Shreveport
| | | | | | - Harsh P. Patel
- Division of Cardiology, Southern Illinois University, Springfield, IL
| | - Maja B. Spaseski
- Department of Internal Medicine, Weiss Memorial Hospital, Chicago, IL
| | | | | | - Zain Ul Abideen Asad
- Department of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City
| | | | - David R. Holmes
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
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Shir D, Pham NTT, Botha H, Koga S, Kouri N, Ali F, Knopman DS, Petersen RC, Boeve BF, Kremers WK, Nguyen AT, Murray ME, Reichard RR, Dickson DW, Graff-Radford N, Josephs KA, Whitwell J, Graff-Radford J. Clinicoradiologic and Neuropathologic Evaluation of Corticobasal Syndrome. Neurology 2023; 101:e289-e299. [PMID: 37268436 PMCID: PMC10382268 DOI: 10.1212/wnl.0000000000207397] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 03/23/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Corticobasal syndrome (CBS) is a clinical phenotype characterized by asymmetric parkinsonism, rigidity, myoclonus, and apraxia. Originally believed secondary to corticobasal degeneration (CBD), mounting clinicopathologic studies have revealed heterogenous neuropathologies. The objectives of this study were to determine the pathologic heterogeneity of CBS, the clinicoradiologic findings associated with different underlying pathologies causing CBS, and the positive predictive value (PPV) of current diagnostic criteria for CBD among patients with a CBS. METHODS Clinical data, brain MRI, and neuropathologic data of patients followed at Mayo Clinic and diagnosed with CBS antemortem were reviewed according to neuropathology category at autopsy. RESULTS The cohort consisted of 113 patients with CBS, 61 (54%) female patients. Mean ± SD disease duration was 7 ± 3.7 years; mean ± SD age at death was 70.5 ± 9.1 years. The primary neuropathologic diagnoses were 43 (38%) CBD, 27 (24%) progressive supranuclear palsy (PSP), 17 (15%) Alzheimer disease (AD), 10 (9%) frontotemporal lobar degeneration (FTLD) with TAR DNA-binding protein 43 (TDP) inclusions, 7 (6%) diffuse Lewy body disease (DLBD)/AD, and 9 (8%) with other diagnoses. Patients with CBS-AD or CBS-DLBD/AD were youngest at death (median [interquartile range]: 64 [13], 64 [11] years) while CBS-PSP were oldest (77 [12.5] years, p = 0.024). Patients with CBS-DLBD/AD had the longest disease duration (9 [6] years), while CBS-other had the shortest (3 [4.25] years, p = 0.04). Posterior cortical signs and myoclonus were more characteristic of patients with CBS-AD and patients with CBS-DLBD/AD. Patients with CBS-DLBD/AD displayed more features of Lewy body dementia. Voxel-based morphometry revealed widespread cortical gray matter loss characteristic of CBS-AD, while CBS-CBD and CBS-PSP predominantly involved premotor regions with greater amount of white matter loss. Patients with CBS-DLBD/AD showed atrophy in a focal parieto-occipital region, and patients with CBS-FTLD-TDP had predominant prefrontal cortical loss. Patients with CBS-PSP had the lowest midbrain/pons ratio (p = 0.012). Of 67 cases meeting clinical criteria for possible CBD at presentation, 27 were pathology-proven CBD, yielding a PPV of 40%. DISCUSSION A variety of neurodegenerative disorders can be identified in patients with CBS, but clinical and regional imaging differences aid in predicting underlying neuropathology. PPV analysis of the current CBD diagnostic criteria revealed suboptimal performance. Biomarkers adequately sensitive and specific for CBD are needed.
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Affiliation(s)
- Dror Shir
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Nha Trang Thu Pham
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Hugo Botha
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Shunsuke Koga
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Naomi Kouri
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Farwa Ali
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - David S Knopman
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Ronald C Petersen
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Brad F Boeve
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Walter K Kremers
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Aivi T Nguyen
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Melissa E Murray
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - R Ross Reichard
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Dennis W Dickson
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Neill Graff-Radford
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL.
| | - Keith Anthony Josephs
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Jennifer Whitwell
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL
| | - Jonathan Graff-Radford
- From the Department of Neurology (D.S., H.B., F.A., D.S.K., R.C.P., B.F.B., K.A.J., J.G.-R.), and Department of Radiology (N.T.T.P., J.W.), Mayo Clinic, Rochester, MN; Department of Neuroscience (S.K., N.K., M.E.M., D.W.D.), Mayo Clinic, Jacksonville, FL; Department of Quantitative Health Sciences (R.C.P., W.K.K.), and Department of Laboratory Medicine and Pathology (A.T.N., R.R.R.), Mayo Clinic, Rochester, MN; and Department of Neurology (N.G.-R.), Mayo Clinic, Jacksonville, FL.
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Carvalho DZ, McCarter SJ, St Louis EK, Przybelski SA, Johnson Sparrman KL, Somers VK, Boeve BF, Petersen RC, Jack CR, Graff-Radford J, Vemuri P. Association of Polysomnographic Sleep Parameters With Neuroimaging Biomarkers of Cerebrovascular Disease in Older Adults With Sleep Apnea. Neurology 2023; 101:e125-e136. [PMID: 37164654 PMCID: PMC10351545 DOI: 10.1212/wnl.0000000000207392] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 03/23/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Our objective was to determine whether polysomnographic (PSG) sleep parameters are associated with neuroimaging biomarkers of cerebrovascular disease (CVD) related to white matter (WM) integrity in older adults with obstructive sleep apnea (OSA). METHODS From the population-based Mayo Clinic Study of Aging, we identified participants without dementia who underwent at least 1 brain MRI and PSG. We quantified 2 CVD biomarkers: WM hyperintensities (WMHs) from fluid-attenuated inversion recovery (FLAIR)-MRI, and fractional anisotropy of the genu of the corpus callosum (genu FA) from diffusion MRI. For this cross-sectional analysis, we fit linear models to assess associations between PSG parameters (NREM stage 1 percentage, NREM stage 3 percentage [slow-wave sleep], mean oxyhemoglobin saturation, and log of apnea-hypopnea index [AHI]) and CVD biomarkers (log of WMH and log of genu FA), respectively, while adjusting for age (at MRI), sex, APOE ε4 status, composite cardiovascular and metabolic conditions (CMC) score, REM stage percentage, sleep duration, and interval between MRI and PSG. RESULTS We included 140 participants with FLAIR-MRI (of which 103 had additional diffusion MRI). The mean ± SD age was 72.7 ± 9.6 years at MRI with nearly 60% being men. The absolute median (interquartile range [IQR]) interval between MRI and PSG was 1.74 (0.9-3.2) years. 90.7% were cognitively unimpaired (CU) during both assessments. For every 10-point decrease in N3%, there was a 0.058 (95% CI 0.006-0.111, p = 0.030) increase in the log of WMH and 0.006 decrease (95% CI -0.012 to -0.0002, p = 0.042) in the log of genu FA. After matching for age, sex, and N3%, participants with severe OSA had higher WMH (median [IQR] 0.007 [0.005-0.015] vs 0.006 [0.003-0.009], p = 0.042) and lower genu FA (median [IQR] 0.57 [0.55-0.63] vs 0.63 [0.58-0.65], p = 0.007), when compared with those with mild/moderate OSA. DISCUSSION We found that reduced slow-wave sleep and severe OSA were associated with higher burden of WM abnormalities in predominantly CU older adults, which may contribute to greater risk of cognitive impairment, dementia, and stroke. Our study supports the association between sleep depth/fragmentation and intermittent hypoxia and CVD biomarkers. Longitudinal studies are required to assess causation.
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Affiliation(s)
- Diego Z Carvalho
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN.
| | - Stuart J McCarter
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Erik K St Louis
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Scott A Przybelski
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Kohl L Johnson Sparrman
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Virend K Somers
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Bradley F Boeve
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Jonathan Graff-Radford
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Department of Neurology (D.Z.C., S.J.M., E.K.S.L., B.F.B., R.C.P., J.G.-R.), Center for Sleep Medicine (D.Z.C., S.J.M., E.K.S.L., B.F.B.), Division of Pulmonary and Critical Care, Department of Internal Medicine, Department of Quantitative Health Sciences (S.A.P., R.C.P.), Department of Radiology (K.L.J.S., C.R.J., P.V.), and Department of Cardiovascular Medicine (V.K.S.), Mayo Clinic, Rochester, MN
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Diaz-Galvan P, Przybelski SA, Lesnick TG, Schwarz CG, Senjem ML, Gunter JL, Jack CR, Min HKP, Jain M, Miyagawa T, Forsberg LK, Fields JA, Savica R, Graff-Radford J, Jones DT, Botha H, St Louis EK, Knopman DS, Ramanan VK, Ross O, Graff-Radford N, Day GS, Dickson DW, Ferman TJ, Petersen RC, Lowe VJ, Boeve BF, Kantarci K. β-Amyloid Load on PET Along the Continuum of Dementia With Lewy Bodies. Neurology 2023; 101:e178-e188. [PMID: 37202168 PMCID: PMC10351554 DOI: 10.1212/wnl.0000000000207393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 03/23/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND AND OBJECTIVES β-Amyloid (Aβ) plaques can co-occur with Lewy-related pathology in patients with dementia with Lewy bodies (DLB), but Aβ load at prodromal stages of DLB still needs to be elucidated. We investigated Aβ load on PET throughout the DLB continuum, from an early prodromal stage of isolated REM sleep behavior disorder (iRBD) to a stage of mild cognitive impairment with Lewy bodies (MCI-LB), and finally DLB. METHODS We performed a cross-sectional study in patients with a diagnosis of iRBD, MCI-LB, or DLB from the Mayo Clinic Alzheimer Disease Research Center. Aβ levels were measured by Pittsburgh compound B (PiB) PET, and global cortical standardized uptake value ratio (SUVR) was calculated. Global cortical PiB SUVR values from each clinical group were compared with each other and with those of cognitively unimpaired (CU) individuals (n = 100) balanced on age and sex using analysis of covariance. We used multiple linear regression testing for interaction to study the influences of sex and APOE ε4 status on PiB SUVR along the DLB continuum. RESULTS Of the 162 patients, 16 had iRBD, 64 had MCI-LB, and 82 had DLB. Compared with CU individuals, global cortical PiB SUVR was higher in those with DLB (p < 0.001) and MCI-LB (p = 0.012). The DLB group included the highest proportion of Aβ-positive patients (60%), followed by MCI-LB (41%), iRBD (25%), and finally CU (19%). Global cortical PiB SUVR was higher in APOE ε4 carriers compared with that in APOE ε4 noncarriers in MCI-LB (p < 0.001) and DLB groups (p = 0.049). Women had higher PiB SUVR with older age compared with men across the DLB continuum (β estimate = 0.014, p = 0.02). DISCUSSION In this cross-sectional study, levels of Aβ load was higher further along the DLB continuum. Whereas Aβ levels were comparable with those in CU individuals in iRBD, a significant elevation in Aβ levels was observed in the predementia stage of MCI-LB and in DLB. Specifically, APOE ε4 carriers had higher Aβ levels than APOE ε4 noncarriers, and women tended to have higher Aβ levels than men as they got older. These findings have important implications in targeting patients within the DLB continuum for clinical trials of disease-modifying therapies.
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Affiliation(s)
- Patricia Diaz-Galvan
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Scott A Przybelski
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Timothy G Lesnick
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Christopher G Schwarz
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Matthew L Senjem
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Jeffrey L Gunter
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Clifford R Jack
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Hoon-Ki Paul Min
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Manoj Jain
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Toji Miyagawa
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Leah K Forsberg
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Julie A Fields
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Rodolfo Savica
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Jonathan Graff-Radford
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - David T Jones
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Hugo Botha
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Erik K St Louis
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - David S Knopman
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Vijay K Ramanan
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Owen Ross
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Neill Graff-Radford
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Gregory S Day
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Dennis W Dickson
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Tanis J Ferman
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Ronald C Petersen
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Val J Lowe
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Brad F Boeve
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL
| | - Kejal Kantarci
- From the Department of Radiology (P.D.-G., C.G.S., M.L.S., J.L.G., C.R.J., H.-K.P.M., V.J.L., K.K.), Department of Quantitative Health Sciences (S.A.P., T.G.L., R.C.P.), and Department of Information Technology (M.L.S.), Mayo Clinic, Rochester, MN; Department of Radiology (M.J.), Mayo Clinic, Jacksonville, FL; Department of Neurology (T.M., L.K.F., R.S., J.G.-R., D.T.J., H.B., E.K.S.L., D.S.K., V.K.R., R.C.P., B.F.B.), Department of Psychiatry and Psychology (J.A.F., E.K.S.L.), and Center for Sleep Medicine (E.K.S.L.), Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN; Mayo Clinic Health System Southwest Wisconsin (E.K.S.L.), La Crosse; Department of Neuroscience (O.R.), Department of Neurology (N.G.-R., G.S.D.), Laboratory of Medicine and Pathology (D.W.D.), and Department of Psychiatry and Psychology (T.J.F.), Mayo Clinic, Jacksonville, FL.
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Toller G, Cobigo Y, Callahan P, Appleby BS, Brushaber D, Domoto-Reilly K, Forsberg LK, Ghoshal N, Graff-Radford J, Graff-Radford NR, Grossman M, Heuer HW, Kornak J, Kremers W, Lapid MI, Leger G, Litvan I, Mackenzie IR, Pascual MB, Ramos EM, Rascovsky K, Rojas JC, Staffaroni AM, Tartaglia MC, Toga A, Weintraub S, Wszolek ZK, Boeve BF, Boxer AL, Rosen HJ, Rankin KP. Multisite ALLFTD study modeling progressive empathy loss from the earliest stages of behavioral variant frontotemporal dementia. Alzheimers Dement 2023; 19:2842-2852. [PMID: 36591730 PMCID: PMC10314956 DOI: 10.1002/alz.12898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 10/19/2022] [Accepted: 10/27/2022] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Empathy relies on fronto-cingular and temporal networks that are selectively vulnerable in behavioral variant frontotemporal dementia (bvFTD). This study modeled when in the disease process empathy changes begin, and how they progress. METHODS Four hundred thirty-one individuals with asymptomatic genetic FTD (n = 114), genetic and sporadic bvFTD (n = 317), and 163 asymptomatic non-carrier controls were enrolled. In sub-samples, we investigated empathy measured by the informant-based Interpersonal Reactivity Index (IRI) at each disease stage and over time (n = 91), and its correspondence to underlying atrophy (n = 51). RESULTS Empathic concern (estimate = 4.38, 95% confidence interval [CI] = 2.79, 5.97; p < 0.001) and perspective taking (estimate = 5.64, 95% CI = 3.81, 7.48; p < 0.001) scores declined between the asymptomatic and very mild symptomatic stages regardless of pathogenic variant status. More rapid loss of empathy corresponded with subcortical atrophy. DISCUSSION Loss of empathy is an early and progressive symptom of bvFTD that is measurable by IRI informant ratings and can be used to monitor behavior in neuropsychiatry practice and treatment trials.
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Affiliation(s)
- Gianina Toller
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Yann Cobigo
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Patrick Callahan
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | | | | | | | | | | | | | | | | | - Hilary W. Heuer
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - John Kornak
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | | | | | - Gabriel Leger
- University of California, San Diego, San Diego, CA, USA
| | - Irene Litvan
- University of California, San Diego, San Diego, CA, USA
| | - Ian R. Mackenzie
- University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | | | - Julio C. Rojas
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Adam M. Staffaroni
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | | | - Arthur Toga
- University of Southern California, Los Angeles, CA, USA
| | - Sandra Weintraub
- Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
| | | | | | - Adam L. Boxer
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Howard J. Rosen
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
| | - Katherine P. Rankin
- University of California, San Francisco, Memory and Aging Center, Department of Neurology, San Francisco, CA, USA
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Bermudez C, Graff-Radford J, Syrjanen JA, Stricker NH, Algeciras-Schimnich A, Kouri N, Kremers WK, Petersen RC, Jack CR, Knopman DS, Dickson DW, Nguyen AT, Reichard RR, Murray ME, Mielke MM, Vemuri P. Plasma biomarkers for prediction of Alzheimer's disease neuropathologic change. Acta Neuropathol 2023; 146:13-29. [PMID: 37269398 PMCID: PMC10478071 DOI: 10.1007/s00401-023-02594-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 05/14/2023] [Accepted: 05/24/2023] [Indexed: 06/05/2023]
Abstract
While plasma biomarkers for Alzheimer's disease (AD) are increasingly being evaluated for clinical diagnosis and prognosis, few population-based autopsy studies have evaluated their utility in the context of predicting neuropathological changes. Our goal was to investigate the utility of clinically available plasma markers in predicting Braak staging, neuritic plaque score, Thal phase, and overall AD neuropathological change (ADNC).We utilized a population-based prospective study of 350 participants with autopsy and antemortem plasma biomarker testing using clinically available antibody assay (Quanterix) consisting of Aβ42/40 ratio, p-tau181, GFAP, and NfL. We utilized a variable selection procedure in cross-validated (CV) logistic regression models to identify the best set of plasma predictors along with demographic variables, and a subset of neuropsychological tests comprising the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo-PACC). ADNC was best predicted with plasma GFAP, NfL, p-tau181 biomarkers along with APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.798). Braak staging was best predicted using plasma GFAP, p-tau181, and cognitive scores (CV AUC = 0.774). Neuritic plaque score was best predicted using plasma Aβ42/40 ratio, p-tau181, GFAP, and NfL biomarkers (CV AUC = 0.770). Thal phase was best predicted using GFAP, NfL, p-tau181, APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.754). We found that GFAP and p-tau provided non-overlapping information on both neuritic plaque and Braak stage scores whereas Aβ42/40 and NfL were mainly useful for prediction of neuritic plaque scores. Separating participants by cognitive status improved predictive performance, particularly when plasma biomarkers were included. Plasma biomarkers can differentially inform about overall ADNC pathology, Braak staging, and neuritic plaque score when combined with demographics and cognitive variables and have significant utility for earlier detection of AD.
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Affiliation(s)
- Camilo Bermudez
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55902, USA.
| | | | - Jeremy A Syrjanen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Nikki H Stricker
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Naomi Kouri
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55902, USA
| | | | - David S Knopman
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55902, USA
| | | | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - R Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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Singh NA, Martin PR, Graff-Radford J, Sintini I, Machulda MM, Duffy JR, Gunter JL, Botha H, Jones DT, Lowe VJ, Jack CR, Josephs KA, Whitwell JL. Altered within- and between-network functional connectivity in atypical Alzheimer's disease. Brain Commun 2023; 5:fcad184. [PMID: 37434879 PMCID: PMC10331277 DOI: 10.1093/braincomms/fcad184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 05/04/2023] [Accepted: 06/13/2023] [Indexed: 07/13/2023] Open
Abstract
Posterior cortical atrophy and logopenic progressive aphasia are atypical clinical presentations of Alzheimer's disease. Resting-state functional connectivity studies have shown functional network disruptions in both phenotypes, particularly involving the language network in logopenic progressive aphasia and the visual network in posterior cortical atrophy. However, little is known about how connectivity differs both within and between brain networks in these atypical Alzheimer's disease phenotypes. A cohort of 144 patients was recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, USA, and underwent structural and resting-state functional MRI. Spatially preprocessed data were analysed to explore the default mode network and the salience, sensorimotor, language, visual and memory networks. The data were analysed at the voxel and network levels. Bayesian hierarchical linear models adjusted for age and sex were used to analyse within- and between-network connectivity. Reduced within-network connectivity was observed in the language network in both phenotypes, with stronger evidence of reductions in logopenic progressive aphasia compared to controls. Only posterior cortical atrophy showed reduced within-network connectivity in the visual network compared to controls. Both phenotypes showed reduced within-network connectivity in the default mode and sensorimotor networks. No significant change was noted in the memory network, but a slight increase in the salience within-network connectivity was seen in both phenotypes compared to controls. Between-network analysis in posterior cortical atrophy showed evidence of reduced visual-to-language network connectivity, with reduced visual-to-salience network connectivity, compared to controls. An increase in visual-to-default mode network connectivity was noted in posterior cortical atrophy compared to controls. Between-network analysis in logopenic progressive aphasia showed evidence of reduced language-to-visual network connectivity and an increase in language-to-salience network connectivity compared to controls. Findings from the voxel-level and network-level analysis were in line with the Bayesian hierarchical linear model analysis, showing reduced connectivity in the dominant network based on diagnosis and more crosstalk between networks in general compared to controls. The atypical Alzheimer's disease phenotypes were associated with disruptions in connectivity, both within and between brain networks. Phenotype-specific differences in connectivity patterns were noted in the visual network for posterior cortical atrophy and the language network for logopenic progressive aphasia.
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Affiliation(s)
| | - Peter R Martin
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | - Joseph R Duffy
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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Sehrawat O, Kashou AH, Van Houten HK, Cohen K, Joe Henk H, Gersh BJ, Abraham NS, Graff-Radford J, Friedman PA, Siontis KC, Noseworthy PA, Yao X. Contemporary trends and barriers to oral anticoagulation therapy in Non-valvular atrial fibrillation during DOAC predominant era. Int J Cardiol Heart Vasc 2023; 46:101212. [PMID: 37168417 PMCID: PMC10164915 DOI: 10.1016/j.ijcha.2023.101212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 04/11/2023] [Accepted: 04/18/2023] [Indexed: 05/13/2023]
Abstract
There is a need to reassess contemporary oral anticoagulation (OAC) trends and barriers against guideline directed therapy in the United States. Most previous studies were performed before major guideline changes recommended direct oral anticoagulant (DOAC) use over warfarin or have otherwise lacked patient level data. Data on overuse of OAC in low-risk group is also limited. To address these knowledge gaps, we performed a nationwide analysis to analyze current trends. This is a retrospective cohort study assessing non-valvular AF identified using a large United States de-identified administrative claims database, including commercial and Medicare Advantage enrollees. Prescription fills were assessed within a 90-day follow-up from the patient's index AF encounter between January 1, 2016, and December 31, 2020. Among the 339,197 AF patients, 4.4%, 8.0%, and 87.6% were in the low-, moderate-, and high-risk groups (according to CHA2DS2-VASc score). An over (29.6%) and under (52.2%) utilization of OAC was reported in low- and high-risk AF patients. A considerably high frequency for warfarin use was also noted among high-risk group patients taking OAC (33.1%). The results suggest that anticoagulation use for stroke prevention in the United States is still comparable to the pre-DOAC era studies. About half of newly diagnosed high-risk non-valvular AF patients remain unprotected against stroke risk. Several predictors of OAC and DOAC use were also identified. Our findings may identify a population at risk of complications due to under- or over-treatment and highlight the need for future quality improvement efforts.
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Affiliation(s)
- Ojasav Sehrawat
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
| | - Anthony H. Kashou
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
| | - Holly K. Van Houten
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States
| | - Ken Cohen
- Optum Center for Research and Innovation, Minnetonka, MN, United States
| | - Henry Joe Henk
- UnitedHealthcare, 9700 Health Care Lane, Minnetonka, MN 55343, USA
| | - Bernard J. Gersh
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
| | - Neena S. Abraham
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States
- Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Scottsdale, AZ, United States
| | | | - Paul A. Friedman
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
| | | | - Peter A. Noseworthy
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States
- Corresponding author at: Department of Cardiovascular Medicine Mayo Clinic, 200 First Street SW |, Rochester, MN 55905, United States.
| | - Xiaoxi Yao
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States
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Tian J, Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Gebre RK, Graff-Radford J, Schwarz CG, Lowe VJ, Kantarci K, Knopman DS, Petersen RC, Jack CR, Vemuri P. White Matter Degeneration Pathways Associated With Tau Deposition in Alzheimer Disease. Neurology 2023; 100:e2269-e2278. [PMID: 37068958 PMCID: PMC10259272 DOI: 10.1212/wnl.0000000000207250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 02/16/2023] [Indexed: 04/19/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The dynamics of white matter (WM) changes are understudied in Alzheimer disease (AD). Our goal was to study the association between flortaucipir PET and WM health using neurite orientation dispersion and density imaging (NODDI) and evaluate its association with cognitive performance. Specifically, we focused on NODDI's Neurite Density Index (NDI), which aids in capturing axonal degeneration in WM and has greater specificity than single-shell diffusion MRI methods. METHOD We estimated regional flortaucipir PET standard uptake value ratios (SUVRs) from 3 regions corresponding to Braak stage I, III/IV, and V/VI to capture the spatial distribution pattern of the 3R/4R tau in AD. Then, we evaluated the associations between these measurements and NDIs in 29 candidate WM tracts using Pearson correlation and multiple regression models. RESULTS Based on 223 participants who were amyloid positive (mean age of 78 years and 57.0% male, 119 cognitively unimpaired, 56 mild cognitive impairment, and 48 dementia), the results showed that WM tracts NDI decreased with increasing regional Braak tau SUVRs. Of all the significant WM tracts, the uncinate fasciculus (r = -0.274 for Braak I, -0.311 for Braak III/IV, and -0.292 for Braak V/VI, p < 0.05) and cingulum adjoining hippocampus (r = -0.274, -0.288, -0.233, p < 0.05), both tracts anatomically connected to areas of early tau deposition, were consistently found to be within the top 5 distinguishing WM tracts associated with flortaucipir SUVRs. The increase in tau deposition measurable outside the medial temporal lobes in Braak III-VI was associated with a decrease in NDI in the middle and inferior temporal WM tracts. For cognitive performance, WM NDI had similar coefficients of determination (r 2 = 31%) as regional Braak flortaucipir SUVRs (29%), and together WM NDI and regional Braak flortaucipir SUVRs explained 46% of the variance in cognitive performance. DISCUSSION We found spatially dependent WM degeneration associated with regional flortaucipir SUVRs in Braak stages, suggesting a spatial pattern in WM damage. NDI, a specific marker of axonal density, provides complementary information about disease staging and progression in addition to tau deposition. Measurements of WM changes are important for the mechanistic understanding of multifactorial pathways through which AD causes cognitive dysfunction.
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Affiliation(s)
- Jianqiao Tian
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Sheelakumari Raghavan
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Robert I Reid
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Scott A Przybelski
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Timothy G Lesnick
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Robel K Gebre
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Jonathan Graff-Radford
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Christopher G Schwarz
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Val J Lowe
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Kejal Kantarci
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - David S Knopman
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN.
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Cogswell PM, Lundt ES, Therneau TM, Mester CT, Wiste HJ, Graff-Radford J, Schwarz CG, Senjem ML, Gunter JL, Reid RI, Przybelski SA, Knopman DS, Vemuri P, Petersen RC, Jack CR. Evidence against a temporal association between cerebrovascular disease and Alzheimer's disease imaging biomarkers. Nat Commun 2023; 14:3097. [PMID: 37248223 PMCID: PMC10226977 DOI: 10.1038/s41467-023-38878-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 05/15/2023] [Indexed: 05/31/2023] Open
Abstract
Whether a relationship exists between cerebrovascular disease and Alzheimer's disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer's disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual's amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = -0.07 to 0.07); early/late amyloid or tau timing explains <1% of the variation in WMH and FA adjustment. Earlier onset of amyloid is associated with earlier onset of tau (R = 0.57, R2 = 32%). These findings support a strong mechanistic relationship between amyloid and tau aggregation, but not between WMH or FA and amyloid or tau PET.
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Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
| | - Emily S Lundt
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Carly T Mester
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | | | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Jeffrey L Gunter
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Ronald C Petersen
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
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Carlos AF, Graff-Radford J, Crum BA, Machulda MM, Pham NTT, Lowe VJ, Whitwell JL, Josephs KA. Antiphospholipid syndrome mimicking posterior cortical atrophy and the "railroad track" sign on brain fluorodeoxyglucose-positron emission tomography. J Neurol Sci 2023; 448:120615. [PMID: 36959061 PMCID: PMC10407999 DOI: 10.1016/j.jns.2023.120615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/13/2023] [Accepted: 03/14/2023] [Indexed: 03/18/2023]
Affiliation(s)
- Arenn F Carlos
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Brian A Crum
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychology and Psychiatry, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA.
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47
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Jack CR, Wiste HJ, Algeciras-Schimnich A, Figdore DJ, Schwarz CG, Lowe VJ, Ramanan VK, Vemuri P, Mielke MM, Knopman DS, Graff-Radford J, Boeve BF, Kantarci K, Cogswell PM, Senjem ML, Gunter JL, Therneau TM, Petersen RC. Predicting amyloid PET and tau PET stages with plasma biomarkers. Brain 2023; 146:2029-2044. [PMID: 36789483 PMCID: PMC10151195 DOI: 10.1093/brain/awad042] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 01/21/2023] [Indexed: 02/16/2023] Open
Abstract
Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
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Affiliation(s)
- Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Dan J Figdore
- Department of Laboratory Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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Jusue-Torres I, Brown DA, Pennington Z, Cogswell PM, Ali F, Graff-Radford N, Jones DT, Cutsforth-Gregory JK, Graff-Radford J, Kaufman KR, Elder BD. Objective assessment of patients with idiopathic normal pressure hydrocephalus following ventriculoperitoneal shunt placement using activity-monitoring data: pilot study. Neurosurg Focus 2023; 54:E6. [PMID: 37004136 DOI: 10.3171/2023.1.focus22640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 01/17/2023] [Indexed: 04/03/2023]
Abstract
OBJECTIVE Idiopathic normal pressure hydrocephalus (iNPH) results in significant morbidity in the elderly with symptoms of dementia, gait instability, and urinary incontinence. In well-selected patients, ventriculoperitoneal shunt (VPS) placement often results in clinical improvement. Most postshunt assessments of patients rely on subjective scales. The goal of this study was to assess the utility of remote activity monitoring to provide objective evidence of gait improvement following VPS placement for iNPH. METHODS Patients with iNPH were prospectively enrolled and fitted with 5 activity monitors (on the hip and bilateral thighs and ankles) that they wore for 4 days preoperatively within 30 days of surgery and for 4 days within 30 days postoperatively. Monitors collected continuous data for number of steps, cadence, body position (upright, prone, supine, and lateral decubitus), gait entropy, and the proportion of each day spent active or static. Data were retrieved from the devices and a comparison of pre- and postoperative movement assessment was performed. The gait data were also correlated with formal clinical gait assessments before and after lumbar puncture and with motion analysis laboratory testing at baseline and 1 month and 1 year after VPS placement. RESULTS Twenty patients fulfilled the inclusion and exclusion criteria (median age 76 years). The baseline median number of daily steps was 1929, the median percentage of the day spent inactive was 70%, the median percentage of the day with a static posture was 95%, the median gait velocity was 0.49 m/sec, and the median number of steps required to turn was 8. There was objective improvement in median entropy from pre- to postoperatively, increasing from 0.6 to 0.8 (p = 0.002). There were no statistically significant differences for any of the remaining variables measured by the activity monitors when comparing the preoperative to the 1-month postoperative time point. All variables from motion analysis testing showed statistically significant differences or a trend toward significance at 1 year after VPS placement. Among the significantly correlated variables at baseline, cadence was inversely correlated with percentage of gait cycle spent in the support phase (contact with ground vs swing phase). CONCLUSIONS This pilot study suggests that activity monitoring provides an early objective measure of improvement in gait entropy after VPS placement among patients with iNPH, although a more significant improvement was noted on the detailed clinical gait assessments. Further long-term studies are needed to determine the utility of remote monitoring for assessing gait improvement following VPS placement.
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Affiliation(s)
| | - Desmond A Brown
- 2National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland; and
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Gebre RK, Senjem ML, Raghavan S, Schwarz CG, Gunter JL, Hofrenning EI, Reid RI, Kantarci K, Graff-Radford J, Knopman DS, Petersen RC, Jack CR, Vemuri P. Cross-scanner harmonization methods for structural MRI may need further work: A comparison study. Neuroimage 2023; 269:119912. [PMID: 36731814 PMCID: PMC10170652 DOI: 10.1016/j.neuroimage.2023.119912] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/26/2023] [Accepted: 01/28/2023] [Indexed: 02/01/2023] Open
Abstract
The clinical usefulness MRI biomarkers for aging and dementia studies relies on precise brain morphological measurements; however, scanner and/or protocol variations may introduce noise or bias. One approach to address this is post-acquisition scan harmonization. In this work, we evaluate deep learning (neural style transfer, CycleGAN and CGAN), histogram matching, and statistical (ComBat and LongComBat) methods. Participants who had been scanned on both GE and Siemens scanners (cross-sectional participants, known as Crossover (n = 113), and longitudinally scanned participants on both scanners (n = 454)) were used. The goal was to match GE MPRAGE (T1-weighted) scans to Siemens improved resolution MPRAGE scans. Harmonization was performed on raw native and preprocessed (resampled, affine transformed to template space) scans. Cortical thicknesses were measured using FreeSurfer (v.7.1.1). Distributions were checked using Kolmogorov-Smirnov tests. Intra-class correlation (ICC) was used to assess the degree of agreement in the Crossover datasets and annualized percent change in cortical thickness was calculated to evaluate the Longitudinal datasets. Prior to harmonization, the least agreement was found at the frontal pole (ICC = 0.72) for the raw native scans, and at caudal anterior cingulate (0.76) and frontal pole (0.54) for the preprocessed scans. Harmonization with NST, CycleGAN, and HM improved the ICCs of the preprocessed scans at the caudal anterior cingulate (>0.81) and frontal poles (>0.67). In the Longitudinal raw native scans, over- and under-estimations of cortical thickness were observed due to the changing of the scanners. ComBat matched the cortical thickness distributions throughout but was not able to increase the ICCs or remove the effects of scanner changeover in the Longitudinal datasets. CycleGAN and NST performed slightly better to address the cortical thickness variations between scanner change. However, none of the methods succeeded in harmonizing the Longitudinal dataset. CGAN was the worst performer for both datasets. In conclusion, the performance of the methods was overall similar and region dependent. Future research is needed to improve the existing approaches since none of them outperformed each other in terms of harmonizing the datasets at all ROIs. The findings of this study establish framework for future research into the scan harmonization problem.
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Affiliation(s)
- Robel K Gebre
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA.
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA; Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | | | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
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50
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Corriveau-Lecavalier N, Gunter JL, Kamykowski M, Dicks E, Botha H, Kremers WK, Graff-Radford J, Wiepert DA, Schwarz CG, Yacoub E, Knopman DS, Boeve BF, Ugurbil K, Petersen RC, Jack CR, Terpstra MJ, Jones DT. Default mode network failure and neurodegeneration across aging and amnestic and dysexecutive Alzheimer's disease. Brain Commun 2023; 5:fcad058. [PMID: 37013176 PMCID: PMC10066575 DOI: 10.1093/braincomms/fcad058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 12/15/2022] [Accepted: 03/07/2023] [Indexed: 03/09/2023] Open
Abstract
From a complex systems perspective, clinical syndromes emerging from neurodegenerative diseases are thought to result from multiscale interactions between aggregates of misfolded proteins and the disequilibrium of large-scale networks coordinating functional operations underpinning cognitive phenomena. Across all syndromic presentations of Alzheimer's disease, age-related disruption of the default mode network is accelerated by amyloid deposition. Conversely, syndromic variability may reflect selective neurodegeneration of modular networks supporting specific cognitive abilities. In this study, we leveraged the breadth of the Human Connectome Project-Aging cohort of non-demented individuals (N = 724) as a normative cohort to assess the robustness of a biomarker of default mode network dysfunction in Alzheimer's disease, the network failure quotient, across the aging spectrum. We then examined the capacity of the network failure quotient and focal markers of neurodegeneration to discriminate patients with amnestic (N = 8) or dysexecutive (N = 10) Alzheimer's disease from the normative cohort at the patient level, as well as between Alzheimer's disease phenotypes. Importantly, all participants and patients were scanned using the Human Connectome Project-Aging protocol, allowing for the acquisition of high-resolution structural imaging and longer resting-state connectivity acquisition time. Using a regression framework, we found that the network failure quotient related to age, global and focal cortical thickness, hippocampal volume, and cognition in the normative Human Connectome Project-Aging cohort, replicating previous results from the Mayo Clinic Study of Aging that used a different scanning protocol. Then, we used quantile curves and group-wise comparisons to show that the network failure quotient commonly distinguished both dysexecutive and amnestic Alzheimer's disease patients from the normative cohort. In contrast, focal neurodegeneration markers were more phenotype-specific, where the neurodegeneration of parieto-frontal areas associated with dysexecutive Alzheimer's disease, while the neurodegeneration of hippocampal and temporal areas associated with amnestic Alzheimer's disease. Capitalizing on a large normative cohort and optimized imaging acquisition protocols, we highlight a biomarker of default mode network failure reflecting shared system-level pathophysiological mechanisms across aging and dysexecutive and amnestic Alzheimer's disease and biomarkers of focal neurodegeneration reflecting distinct pathognomonic processes across the amnestic and dysexecutive Alzheimer's disease phenotypes. These findings provide evidence that variability in inter-individual cognitive impairment in Alzheimer's disease may relate to both modular network degeneration and default mode network disruption. These results provide important information to advance complex systems approaches to cognitive aging and degeneration, expand the armamentarium of biomarkers available to aid diagnosis, monitor progression and inform clinical trials.
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Affiliation(s)
| | | | - Michael Kamykowski
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ellen Dicks
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Essa Yacoub
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kamil Ugurbil
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Melissa J Terpstra
- Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Radiology, University of Missouri, Columbia, MO 65211, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
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