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Shen H, Liu K, Kong F, Ren M, Wang X, Wang S. Strategies for measuring concentrations and forms of amyloid-β peptides. Biosens Bioelectron 2024; 259:116405. [PMID: 38776801 DOI: 10.1016/j.bios.2024.116405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 05/01/2024] [Accepted: 05/17/2024] [Indexed: 05/25/2024]
Abstract
Alzheimer's disease (AD) is affecting more and more people worldwide without the effective treatment, while the existed pathological mechanism has been confirmed barely useful in the treatment. Amyloid-β peptide (Aβ), a main component of senile plaque, is regarded as the most promising target in AD treatment. Aβ clearance from AD brain seems to be a reliably therapeutic strategy, as the two exited drugs, GV-971 and aducanumab, are both developed based on it. However, doubt still exists. To exhaustive expound on the pathological mechanism of Aβ, rigorous analyses on the concentrations and aggregation forms are essential. Thus, it is attracting broad attention these years. However, most of the sensors have not been used in pathological studies, as the lack of the bridge between analytical chemist and pathologists. In this review, we made a brief introduce on Aβ-related pathological mechanism included in β-amyloid hypothesis to elucidate the detection conditions of sensor methods. Furthermore, a summary of the sensor methods was made, which were based on Aβ concentrations and form detections that have been developed in the past 10 years. As the greatest number of the sensors were built on fluorescent spectroscopy, electrochemistry, and Roman spectroscopy, detailed elucidation on them was made. Notably, the aggregation process is another important factor in revealing the progress of AD and developing the treatment methods, so the sensors on monitoring Aβ aggregation processes were also summarized.
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Affiliation(s)
- Hangyu Shen
- State Key Laboratory of Biobased Materials and Green Papermaking, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, 250353, PR China
| | - Keyin Liu
- State Key Laboratory of Biobased Materials and Green Papermaking, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, 250353, PR China
| | - Fangong Kong
- State Key Laboratory of Biobased Materials and Green Papermaking, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, 250353, PR China
| | - Mingguang Ren
- State Key Laboratory of Biobased Materials and Green Papermaking, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, 250353, PR China
| | - Xiaoying Wang
- State Key Laboratory of Biobased Materials and Green Papermaking, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, 250353, PR China; Shandong Haizhibao Ocean Technology Co., Ltd, Weihai, Shandong, 264333, PR China.
| | - Shoujuan Wang
- State Key Laboratory of Biobased Materials and Green Papermaking, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, 250353, PR China.
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Ioannou K, Bucci M, Tzortzakakis A, Savitcheva I, Nordberg A, Chiotis K. Tau PET positivity predicts clinically relevant cognitive decline driven by Alzheimer's disease compared to comorbid cases; proof of concept in the ADNI study. Mol Psychiatry 2024:10.1038/s41380-024-02672-9. [PMID: 39179903 DOI: 10.1038/s41380-024-02672-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/26/2024] [Accepted: 07/09/2024] [Indexed: 08/26/2024]
Abstract
β-amyloid (Aβ) pathology is not always coupled with Alzheimer's disease (AD) relevant cognitive decline. We assessed the accuracy of tau PET to identify Aβ(+) individuals who show prospective disease progression. 396 cognitively unimpaired and impaired individuals with baseline Aβ and tau PET and a follow-up of ≥ 2 years were selected from the Alzheimer's Disease Neuroimaging Initiative dataset. The participants were dichotomously grouped based on either clinical conversion (i.e., change of diagnosis) or cognitive deterioration (fast (FDs) vs. slow decliners (SDs)) using data-driven clustering of the individual annual rates of cognitive decline. To assess cognitive decline in individuals with isolated Aβ(+) or absence of both Aβ and tau (T) pathologies, we investigated the prevalence of non-AD comorbidities and FDG PET hypometabolism patterns suggestive of AD. Baseline tau PET uptake was higher in Aβ(+)FDs than in Aβ(-)FD/SDs and Aβ(+)SDs, independently of baseline cognitive status. Baseline tau PET uptake identified MCI Aβ(+) Converters and Aβ(+)FDs with an area under the curve of 0.85 and 0.87 (composite temporal region of interest) respectively, and was linearly related to the annual rate of cognitive decline in Aβ(+) individuals. The T(+) individuals constituted largely a subgroup of those being Aβ(+) and those clustered as FDs. The most common biomarker profiles in FDs (n = 70) were Aβ(+)T(+) (n = 34, 49%) and Aβ(+)T(-) (n = 19, 27%). Baseline Aβ load was higher in Aβ(+)T(+)FDs (M = 83.03 ± 31.42CL) than in Aβ(+)T(-)FDs (M = 63.67 ± 26.75CL) (p-value = 0.038). Depression diagnosis was more prevalent in Aβ(+)T(-)FDs compared to Aβ(+)T(+)FDs (47% vs. 15%, p-value = 0.021), as were FDG PET hypometabolism pattern not suggestive of AD (86% vs. 50%, p-value = 0.039). Our findings suggest that high tau PET uptake is coupled with both Aβ pathology and accelerated cognitive decline. In cases of isolated Aβ(+), cognitive decline may be associated with changes within the AD spectrum in a multi-morbidity context, i.e., mixed AD.
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Affiliation(s)
- Konstantinos Ioannou
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Marco Bucci
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Antonios Tzortzakakis
- Division of Radiology, Department for Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden
- Medical Radiation Physics and Nuclear Medicine, Section for Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Section for Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden.
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van der Veere PJ, Hoogland J, Visser LNC, Van Harten AC, Rhodius-Meester HF, Sikkes SAM, Venkatraghavan V, Barkhof F, Teunissen CE, van de Giessen E, Berkhof J, Van Der Flier WM. Predicting Cognitive Decline in Amyloid-Positive Patients With Mild Cognitive Impairment or Mild Dementia. Neurology 2024; 103:e209605. [PMID: 38986053 PMCID: PMC11238942 DOI: 10.1212/wnl.0000000000209605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Cognitive decline rates in Alzheimer disease (AD) vary greatly. Disease-modifying treatments may alter cognitive decline trajectories, rendering their prediction increasingly relevant. We aimed to construct clinically applicable prediction models of cognitive decline in amyloid-positive patients with mild cognitive impairment (MCI) or mild dementia. METHODS From the Amsterdam Dementia Cohort, we selected amyloid-positive participants with MCI or mild dementia and at least 2 longitudinal Mini-Mental State Examination (MMSE) measurements. Amyloid positivity was based on CSF AD biomarker concentrations or amyloid PET. We used linear mixed modeling to predict MMSE over time, describing trajectories using a cubic time curve and interactions between linear time and the baseline predictors age, sex, baseline MMSE, APOE ε4 dose, CSF β-amyloid (Aβ) 1-42 and pTau, and MRI total brain and hippocampal volume. Backward selection was used to reduce model complexity. These models can predict MMSE over follow-up or the time to an MMSE value. MCI and mild dementia were modeled separately. Internal 5-fold cross-validation was performed to calculate the explained variance (R2). RESULTS In total, 961 participants were included (age 65 ± 7 years, 49% female), 310 had MCI (MMSE 26 ± 2) and 651 had mild dementia (MMSE 22 ± 4), with 4 ± 2 measurements over 2 (interquartile range 1-4) years. Cognitive decline rates increased over time for both MCI and mild dementia (model comparisons linear vs squared vs cubic time fit; p < 0.05 favoring a cubic fit). For MCI, backward selection retained age, sex, and CSF Aβ1-42 and pTau concentrations as time-varying effects altering the MMSE trajectory. For mild dementia, retained time-varying effects were Aβ1-42, age, APOE ε4, and baseline MMSE. R2 was 0.15 for the MCI model and 0.26 for mild dementia in internal cross-validation. A hypothetical patient with MCI, baseline MMSE 28, and CSF Aβ1-42 of 925 pg/mL was predicted to reach an MMSE of 20 after 6.0 years (95% CI 5.4-6.7) and after 8.6 years with a hypothetical treatment reducing decline by 30%. DISCUSSION We constructed models for MCI and mild dementia that predict MMSE over time. These models could inform patients about their potential cognitive trajectory and the remaining uncertainty and aid in conversations about individualized potential treatment effects.
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Affiliation(s)
- Pieter J van der Veere
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Jeroen Hoogland
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Leonie N C Visser
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Argonde C Van Harten
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Hanneke F Rhodius-Meester
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Sietske A M Sikkes
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Vikram Venkatraghavan
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Frederik Barkhof
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Charlotte E Teunissen
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Elsmarieke van de Giessen
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Johannes Berkhof
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Wiesje M Van Der Flier
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
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4
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Verberk IMW, Jutte J, Kingma MY, Vigneswaran S, Gouda MMTEE, van Engelen MP, Alcolea D, Arranz J, Fortea J, Lleó A, Chevalier C, Marizzoni M, van de Giessen EM, Lemstra AW, Pijnenburg YAL, van der Flier WM, den Braber A, Wilson D, Schut MC, van Harten AC, Teunissen CE. Development of thresholds and a visualization tool for use of a blood test in routine clinical dementia practice. Alzheimers Dement 2024. [PMID: 39096164 DOI: 10.1002/alz.14088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 05/28/2024] [Accepted: 05/31/2024] [Indexed: 08/05/2024]
Abstract
INTRODUCTION We developed a multimarker blood test result interpretation tool for the clinical dementia practice, including phosphorylated (P-)tau181, amyloid-beta (Abeta)42/40, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). METHODS We measured the plasma biomarkers with Simoa (n = 1199), applied LASSO regression for biomarker selection and receiver operating characteristics (ROC) analyses to determine diagnostic accuracy. We validated our findings in two independent cohorts and constructed a visualization approach. RESULTS P-tau181, GFAP, and NfL were selected. This combination had area under the curve (AUC) = 83% to identify amyloid positivity in pre-dementia stages, AUC = 87%-89% to differentiate Alzheimer's or controls from frontotemporal dementia, AUC = 74%-76% to differentiate Alzheimer's or controls from dementia with Lewy bodies. Highly reproducible AUCs were obtained in independent cohorts. The resulting visualization tool includes UpSet plots to visualize the stand-alone biomarker results and density plots to visualize the biomarker results combined. DISCUSSION Our multimarker blood test interpretation tool is ready for testing in real-world clinical dementia settings. HIGHLIGHTS We developed a multimarker blood test interpretation tool for clinical dementia practice. Our interpretation tool includes plasma biomarkers P-tau, GFAP, and NfL. Our tool is particularly useful for Alzheimer's and frontotemporal dementia diagnosis.
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Affiliation(s)
- Inge M W Verberk
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jolien Jutte
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Translational Artificial Intelligence Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health, Amsterdam, The Netherlands
| | - Maurice Y Kingma
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Translational Artificial Intelligence Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health, Amsterdam, The Netherlands
| | - Sinthujah Vigneswaran
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Alzheimer Center, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Mariam M T E E Gouda
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Marie-Paule van Engelen
- Alzheimer Center, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Javier Arranz
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Claire Chevalier
- Memory Centre, Division of Geriatrics and Rehabilitation, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland
| | - Moira Marizzoni
- Laboratory of Biological Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Elsmarieke M van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Afina W Lemstra
- Alzheimer Center, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Alzheimer Center, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam Public Health, Methodology & Digital Health, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anouk den Braber
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Alzheimer Center, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - David Wilson
- Quanterix corporation, Billerica, Massachusetts, USA
| | - Martijn C Schut
- Translational Artificial Intelligence Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health, Amsterdam, The Netherlands
| | - Argonde C van Harten
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Alzheimer Center, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
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Mackay GA, Gall C, Jampana R, Sleith C, Lip GYH. Scottish Intercollegiate Guidelines Network Guidance on Dementia: The Investigation of Suspected Dementia (SIGN 168) with Focus on Biomarkers-Executive Summary. Thromb Haemost 2024. [PMID: 38788775 DOI: 10.1055/a-2332-6426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
This is an executive summary of the recent guidance produced by the Scottish Intercollegiate Guidelines Network (SIGN) dementia guideline group with regards to the investigation of suspected dementia. This is a sub-section of the broader SIGN 168 guideline released in November 2023. The guideline group included clinicians with expertise in Old Age Psychiatry, Neurology, Radiology, and Nuclear Medicine supported by colleagues from the SIGN and Healthcare Improvement Scotland teams. There was representation from carers and support organizations with experience of dementia, to ensure the recommendations were appropriate from the perspective of the people being assessed for possible dementia and their carers. As the 2018 National Institute for Health and Clinical Excellence (NICE) dementia review included a review of the evidenced investigation of dementia, the SIGN guideline development group decided to focus on a review on the up-to-date evidence regarding the role of imaging and fluid biomarkers in the diagnosis of dementia. To give context to the consideration of more advanced diagnostic biomarker investigations, the guideline and this summary include the NICE guidance on the use of standard investigations as well as more specialist investigations. The evidence review supports consideration of the use of structural imaging, nuclear medicine imaging, and established Alzheimer's cerebrospinal fluid biomarkers (amyloid and tau) in the diagnosis of dementia. Although routine use of amyloid positron emission tomography imaging was not recommended, its potential use, under specialist direction, in patients with atypical or young-onset presentations of suspected Alzheimer's dementia was included as a clinical good practice point.
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Affiliation(s)
- Graham Andrew Mackay
- Department of Neurology, Aberdeen Royal Infirmary, Foresterhill, Aberdeen, United Kingdom
| | - Claire Gall
- Department of Neurology, Queen Elizabeth University Hospital, Glasgow, United Kingdom
| | - Ravi Jampana
- Department of Neuroradiology, Queen Elizabeth University Hospital, Glasgow, United Kingdom
| | - Carolyn Sleith
- Healthcare Improvement Scotland, Edinburgh, United Kingdom
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom
- Department of Clinical Medicine, Danish Center for Health Services Research, Aalborg University, Aalborg, Denmark
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6
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Rhodius-Meester HFM, van Maurik IS, Collij LE, van Gils AM, Koikkalainen J, Tolonen A, Pijnenburg YAL, Berkhof J, Barkhof F, van de Giessen E, Lötjönen J, van der Flier WM. Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET. PLoS One 2024; 19:e0303111. [PMID: 38768188 PMCID: PMC11104589 DOI: 10.1371/journal.pone.0303111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 04/18/2024] [Indexed: 05/22/2024] Open
Abstract
BACKGROUND The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. METHODS We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. RESULTS The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). CONCLUSION Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.
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Affiliation(s)
- Hanneke F. M. Rhodius-Meester
- Alzheimer Center Amsterdam, Neurology, Amsterdam UMC Location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Internal Medicine, Geriatric Medicine Section, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Ingrid S. van Maurik
- Alzheimer Center Amsterdam, Neurology, Amsterdam UMC Location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Epidemiology and Data Science, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
| | - Lyduine E. Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Aniek M. van Gils
- Alzheimer Center Amsterdam, Neurology, Amsterdam UMC Location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | | | | | - Yolande A. L. Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Amsterdam UMC Location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Johannes Berkhof
- Epidemiology and Data Science, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Elsmarieke van de Giessen
- Alzheimer Center Amsterdam, Neurology, Amsterdam UMC Location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Neurology, Amsterdam UMC Location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Epidemiology and Data Science, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
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Altomare D, Libri I, Alberici A, Rivolta J, Padovani A, Ashton NJ, Zetterberg H, Blennow K, Borroni B. Plasma biomarkers increase diagnostic confidence in patients with Alzheimer's disease or frontotemporal lobar degeneration. Alzheimers Res Ther 2024; 16:107. [PMID: 38734612 PMCID: PMC11088144 DOI: 10.1186/s13195-024-01474-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 05/01/2024] [Indexed: 05/13/2024]
Abstract
BACKGROUND The recent development of techniques to assess plasma biomarkers has changed the way the research community envisions the future of diagnosis and management of Alzheimer's disease (AD) and other neurodegenerative disorders. This work aims to provide real world evidence on the clinical impact of plasma biomarkers in an academic tertiary care center. METHODS Anonymized clinical reports of patients diagnosed with AD or Frontotemporal Lobar Degeneration with available plasma biomarkers (Aβ42, Aβ42/Aβ40, p-tau181, p-tau231, NfL, GFAP) were independently assessed by two neurologists who expressed diagnosis and diagnostic confidence three times: (T0) at baseline based on the information collected during the first visit, (T1) after plasma biomarkers, and (T2) after traditional biomarkers (when available). Finally, we assessed whether clinicians' interpretation of plasma biomarkers and the consequent clinical impact are consistent with the final diagnosis, determined after the conclusion of the diagnostic clinical and instrumental work-up by the actual managing physicians who had complete access to all available information. RESULTS Clinicians assessed 122 reports, and their concordance ranged from 81 to 91% at the three time points. At T1, the presentation of plasma biomarkers resulted in a change of diagnosis in 2% (2/122, p = 1.00) of cases, and in increased diagnostic confidence in 76% (91/120, p < 0.001) of cases with confirmed diagnosis. The change in diagnosis and the increase in diagnostic confidence after plasma biomarkers were consistent with the final diagnosis in 100% (2/2) and 81% (74/91) of cases, respectively. At T2, the presentation of traditional biomarkers resulted in a further change of diagnosis in 13% (12/94, p = 0.149) of cases, and in increased diagnostic confidence in 88% (72/82, p < 0.001) of cases with confirmed diagnosis. CONCLUSIONS In an academic tertiary care center, plasma biomarkers supported clinicians by increasing their diagnostic confidence in most cases, despite a negligible impact on diagnosis. Future prospective studies are needed to assess the full potential of plasma biomarkers on clinical grounds.
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Affiliation(s)
- Daniele Altomare
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| | - Ilenia Libri
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| | - Antonella Alberici
- Department of Continuity of Care and Frailty, Azienda Socio Sanitaria Territoriale (ASST) Spedali Civili, Brescia, Italy
| | - Jasmine Rivolta
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
| | - Alessandro Padovani
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy
- Department of Continuity of Care and Frailty, Azienda Socio Sanitaria Territoriale (ASST) Spedali Civili, Brescia, Italy
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, Maurice Wohl Clinical Neuroscience Institute, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute, UCL, London, W1T 7NF, UK
- Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Barbara Borroni
- Department of Clinical and Experimental Sciences, Neurology Unit, University of Brescia, Brescia, Italy.
- Department of Continuity of Care and Frailty, Azienda Socio Sanitaria Territoriale (ASST) Spedali Civili, Brescia, Italy.
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Chen K, Wang M, Wu J, Zuo C, Huang Y, Wang W, Zhao M, Zhang Y, Zhang X, Chen S, Liu W, Li M, Ge J, Ma X, Wang J, Zheng L, Guan Y, Dong Q, Cui M, Xie F, Zhao Q, Yu J. Incremental value of amyloid PET in a tertiary memory clinic setting in China. Alzheimers Dement 2024; 20:2516-2525. [PMID: 38329281 PMCID: PMC11032579 DOI: 10.1002/alz.13728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 02/09/2024]
Abstract
INTRODUCTION The objective of this study is to investigate the incremental value of amyloid positron emission tomography (Aβ-PET) in a tertiary memory clinic setting in China. METHODS A total of 1073 patients were offered Aβ-PET using 18F-florbetapir. The neurologists determined a suspected etiology (Alzheimer's disease [AD] or non-AD) with a percentage estimate of their confidence and medication prescription both before and after receiving the Aβ-PET results. RESULTS After disclosure of the Aβ-PET results, etiological diagnoses changed in 19.3% of patients, and diagnostic confidence increased from 69.3% to 85.6%. Amyloid PET results led to a change of treatment plan in 36.5% of patients. Compared to the late-onset group, the early-onset group had a more frequent change in diagnoses and a higher increase in diagnostic confidence. DISCUSSION Aβ-PET has significant impacts on the changes of diagnoses and management in Chinese population. Early-onset cases are more likely to benefit from Aβ-PET than late-onset cases. HIGHLIGHTS Amyloid PET contributes to diagnostic changes and its confidence in Chinese patients. Amyloid PET leads to a change of treatment plans in Chinese patients. Early-onset cases are more likely to benefit from amyloid PET than late-onset cases.
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Affiliation(s)
- Ke‐Liang Chen
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Ming‐Yu Wang
- School of MedicineQingdao UniversityQingdaoShandongChina
- Departments of NeurologyWeifang People's HospitalWeifangShandongChina
| | - Jie Wu
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Chuan‐Tao Zuo
- Department of Nuclear Medicine & PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Yu‐Yuan Huang
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Wei‐Yi Wang
- Department of Nuclear Medicine & PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Meng Zhao
- Department of Neurologythe First Hospital of Jilin UniversityChangchunJilinChina
| | - Ya‐Ru Zhang
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Xue Zhang
- Department of NeurologyQingdao shi zhongxin yiyuanQingdaoShandongChina
| | - Shu‐Fen Chen
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Wei‐Shi Liu
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Meng‐Meng Li
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Jing‐Jie Ge
- Department of Nuclear Medicine & PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Xiao‐Xi Ma
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Jie Wang
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Li Zheng
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Yi‐Hui Guan
- Department of Nuclear Medicine & PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Qiang Dong
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Mei Cui
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Fang Xie
- Department of Nuclear Medicine & PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Qian‐Hua Zhao
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
| | - Jin‐Tai Yu
- Department of Neurology and National Center for Neurological DiseasesHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan UniversityShanghaiChina
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Dyer AH, Dolphin H, O'Connor A, Morrison L, Sedgwick G, McFeely A, Killeen E, Gallagher C, Davey N, Connolly E, Lyons S, Young C, Gaffney C, Ennis R, McHale C, Joseph J, Knight G, Kelly E, O'Farrelly C, Bourke NM, Fallon A, O'Dowd S, Kennelly SP. Protocol for the Tallaght University Hospital Institute for Memory and Cognition-Biobank for Research in Ageing and Neurodegeneration. BMJ Open 2023; 13:e077772. [PMID: 38070888 PMCID: PMC10729202 DOI: 10.1136/bmjopen-2023-077772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/13/2023] [Indexed: 12/18/2023] Open
Abstract
INTRODUCTION Alzheimer's disease and other dementias affect >50 million individuals globally and are characterised by broad clinical and biological heterogeneity. Cohort and biobank studies have played a critical role in advancing the understanding of disease pathophysiology and in identifying novel diagnostic and treatment approaches. However, further discovery and validation cohorts are required to clarify the real-world utility of new biomarkers, facilitate research into the development of novel therapies and advance our understanding of the clinical heterogeneity and pathobiology of neurodegenerative diseases. METHODS AND ANALYSIS The Tallaght University Hospital Institute for Memory and Cognition Biobank for Research in Ageing and Neurodegeneration (TIMC-BRAiN) will recruit 1000 individuals over 5 years. Participants, who are undergoing diagnostic workup in the TIMC Memory Assessment and Support Service (TIMC-MASS), will opt to donate clinical data and biological samples to a biobank. All participants will complete a detailed clinical, neuropsychological and dementia severity assessment (including Addenbrooke's Cognitive Assessment, Repeatable Battery for Assessment of Neuropsychological Status, Clinical Dementia Rating Scale). Participants undergoing venepuncture/lumbar puncture as part of the clinical workup will be offered the opportunity to donate additional blood (serum/plasma/whole blood) and cerebrospinal fluid samples for longitudinal storage in the TIMC-BRAiN biobank. Participants are followed at 18-month intervals for repeat clinical and cognitive assessments. Anonymised clinical data and biological samples will be stored securely in a central repository and used to facilitate future studies concerned with advancing the diagnosis and treatment of neurodegenerative diseases. ETHICS AND DISSEMINATION Ethical approval has been granted by the St. James's Hospital/Tallaght University Hospital Joint Research Ethics Committee (Project ID: 2159), which operates in compliance with the European Communities (Clinical Trials on Medicinal Products for Human Use) Regulations 2004 and ICH Good Clinical Practice Guidelines. Findings using TIMC-BRAiN will be published in a timely and open-access fashion.
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Affiliation(s)
- Adam H Dyer
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Helena Dolphin
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | | | - Laura Morrison
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Gavin Sedgwick
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Aoife McFeely
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Emily Killeen
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Conal Gallagher
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Naomi Davey
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Eimear Connolly
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Shane Lyons
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Conor Young
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Christine Gaffney
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Ruth Ennis
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Cathy McHale
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Jasmine Joseph
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Graham Knight
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | - Emmet Kelly
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
| | | | - Nollaig M Bourke
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Aoife Fallon
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Sean O'Dowd
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
- Academic Unit of Neurology, Trinity College Dublin, Dublin, Ireland
| | - Sean P Kennelly
- Institute of Memory and Cognition, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity College Dublin, Dublin, Ireland
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10
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van Maurik IS, Bakker ED, van Unnik AAJM, Broulikova HM, Zwan MD, van de Giessen E, Berkhof J, Bouwman FH, Bosmans JE, van der Flier WM. How healthy participants value additional diagnostic testing with amyloid-PET in patients diagnosed with mild cognitive impairment - a bidding game experiment. Alzheimers Res Ther 2023; 15:208. [PMID: 38017549 PMCID: PMC10683285 DOI: 10.1186/s13195-023-01346-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 10/25/2023] [Indexed: 11/30/2023]
Abstract
BACKGROUND To estimate the perceived value of additional testing with amyloid-PET in Euros in healthy participants acting as analogue patients with mild cognitive impairment (MCI). METHODS One thousand four hundred thirty-one healthy participants acting as analogue MCI patients (mean age 65 ± 8, 929 (75%) female) were recruited via the Dutch Brain Research Registry. Participants were asked to identify with a presented case (video vignette) of an MCI patient and asked whether they would prefer additional diagnostic testing with amyloid PET in this situation. If yes, respondents were asked how much they would be willing to pay for additional diagnostic testing. Monetary value was elicited via a bidding game in which participants were randomized over three conditions: (A) additional testing results in better patient management, (B) Same as condition A and a delay in institutionalization of 3 months, and (C) same as A and a delay in institutionalization of 6 months. Participants who were not willing to take a test were compared with participants who were willing to take a test using logit models. The highest monetary value per condition was analyzed using random-parameter mixed models. RESULTS The vast majority of participants acting as analogue MCI patients (87% (n = 1238)) preferred additional testing with amyloid PET. Participants who were not interested were more often female (OR = 1.61 95% CI [1.09-2.40]) and expressed fewer worries to get AD (OR = 0.64 [0.47-0.87]). The median "a priori" (i.e., before randomization) monetary value of additional diagnostic testing was €1500 (IQR 500-1500). If an additional amyloid PET resulted in better patient management (not further specified; condition A), participants were willing to pay a median price of €2000 (IQR = 1000-3500). Participants were willing to pay significantly more than condition A (better patient management) if amyloid-PET testing additionally resulted in a delay in institutionalization of 3 months (€530 [255-805] on top of €2000, condition B) or 6 months (€596 [187-1005] on top of €2000, condition C). CONCLUSIONS Members of the general population acting as MCI patients are willing to pay a substantial amount of money for amyloid-PET and this increases when diagnostic testing leads to better patient management and the prospect to live longer at home.
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Affiliation(s)
- I S van Maurik
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, De Boelelaan 1118, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Epidemiology and Data Science, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands.
| | - E D Bakker
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, De Boelelaan 1118, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - A A J M van Unnik
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, De Boelelaan 1118, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - H M Broulikova
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - M D Zwan
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, De Boelelaan 1118, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - E van de Giessen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, De Boelelaan 1118, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands
| | - J Berkhof
- Epidemiology and Data Science, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
| | - F H Bouwman
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, De Boelelaan 1118, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - J E Bosmans
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - W M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, De Boelelaan 1118, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Epidemiology and Data Science, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
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11
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Collij LE, Farrar G, Zwan M, van de Giessen E, Ossenkoppele R, Barkhof F, Rozemuller AJM, Pijnenburg YAL, van der Flier WM, Bouwman F. Clinical outcomes up to 9 years after [ 18F]flutemetamol amyloid-PET in a symptomatic memory clinic population. Alzheimers Res Ther 2023; 15:207. [PMID: 38012799 PMCID: PMC10680192 DOI: 10.1186/s13195-023-01351-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023]
Abstract
BACKGROUND Previous studies demonstrated increases in diagnostic confidence and change in patient management after amyloid-PET. However, studies investigating longitudinal outcomes over an extended period of time are limited. Therefore, we aimed to investigate clinical outcomes up to 9 years after amyloid-PET to support the clinical validity of the imaging technique. METHODS We analyzed longitudinal data from 200 patients (Mage = 61.8, 45.5% female, MMMSE = 23.3) suspected of early-onset dementia that underwent [18F]flutemetamol-PET. Baseline amyloid status was determined through visual read (VR). Information on mortality was available with a mean follow-up of 6.7 years (range = 1.1-9.3). In a subset of 108 patients, longitudinal cognitive scores and clinical etiological diagnosis (eDx) at least 1 year after amyloid-PET acquisition were available (M = 3.06 years, range = 1.00-7.02). VR - and VR + patients were compared on mortality rates with Cox Hazard's model, prevalence of stable eDx using chi-square test, and longitudinal cognition with linear mixed models. Neuropathological data was available for 4 patients (mean delay = 3.59 ± 1.82 years, range = 1.2-6.3). RESULTS At baseline, 184 (92.0%) patients were considered to have dementia. The majority of VR + patients had a primary etiological diagnosis of AD (122/128, 95.3%), while the VR - group consisted mostly of non-AD etiologies, most commonly frontotemporal lobar degeneration (30/72, 40.2%). Overall mortality rate was 48.5% and did not differ between VR - and VR + patients. eDx at follow-up was consistent with baseline diagnosis for 92/108 (85.2%) patients, with most changes observed in VR - cases (VR - = 14/35, 40% vs VR + = 2/73, 2.7%, χ2 = 26.03, p < 0.001), who at no time received an AD diagnosis. VR + patients declined faster than VR - patients based on MMSE (β = - 1.17, p = 0.004), episodic memory (β = - 0.78, p = 0.003), fluency (β = - 1.44, p < 0.001), and attention scores (β = 16.76, p = 0.03). Amyloid-PET assessment was in line with post-mortem confirmation in all cases; two cases were VR + and showed widespread AD pathology, while the other two cases were VR - and showed limited amyloid pathology. CONCLUSION In a symptomatic population, we observed that amyloid-status did not impact mortality rates, but is predictive of cognitive functioning over time across several domains. Also, we show particular validity for a negative amyloid-PET assessment, as these patients did not receive an AD diagnosis at follow-up.
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Affiliation(s)
- Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands.
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
| | | | - Marissa Zwan
- Alzheimer Center and Department of Neurology, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center and Department of Neurology, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, London, UK
| | | | - Yolande A L Pijnenburg
- Alzheimer Center and Department of Neurology, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center and Department of Neurology, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
| | - Femke Bouwman
- Alzheimer Center and Department of Neurology, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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12
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Coomans EM, de Koning LA, Rikken RM, Verfaillie SCJ, Visser D, den Braber A, Tomassen J, van de Beek M, Collij LE, Lemstra AW, Windhorst AD, Barkhof F, Golla SSV, Visser PJ, Scheltens P, van der Flier WM, Ossenkoppele R, van Berckel BNM, van de Giessen E. Performance of a [ 18F]Flortaucipir PET Visual Read Method Across the Alzheimer Disease Continuum and in Dementia With Lewy Bodies. Neurology 2023; 101:e1850-e1862. [PMID: 37748892 PMCID: PMC10663007 DOI: 10.1212/wnl.0000000000207794] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/24/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Recently, the US Food and Drug Administration approved the tau-binding radiotracer [18F]flortaucipir and an accompanying visual read method to support the diagnostic process in cognitively impaired patients assessed for Alzheimer disease (AD). Studies evaluating this visual read method are limited. In this study, we evaluated the performance of the visual read method in participants along the AD continuum and dementia with Lewy bodies (DLB) by determining its reliability, accordance with semiquantitative analyses, and associations with clinically relevant variables. METHODS We included participants who underwent tau-PET at Amsterdam University Medical Center. A subset underwent follow-up tau-PET. Two trained nuclear medicine physicians visually assessed all scans. Inter-reader agreement was calculated using Cohen κ. To examine the concordance of visual read tau positivity with semiquantification, we defined standardized uptake value ratio (SUVr) positivity using different threshold approaches. To evaluate the prognostic value of tau-PET visual read, we performed linear mixed models with longitudinal Mini-Mental State Examination (MMSE). RESULTS We included 263 participants (mean age 68.5 years, 45.6% female), including 147 cognitively unimpaired (CU) participants, 97 amyloid-positive participants with mild cognitive impairment or AD dementia (AD), and 19 participants with DLB. The visual read inter-reader agreement was excellent (κ = 0.95, CI 0.91-0.99). None of the amyloid-negative CU participants (0/92 [0%]) and 1 amyloid-negative participant with DLB (1/12 [8.3%]) were tau-positive. Among amyloid-positive participants, 13 CU participants (13/52 [25.0%]), 85 with AD (85/97 [87.6%]), and 3 with DLB (3/7 [42.9%]) were tau-positive. Two-year follow-up visual read status was identical to baseline. Tau-PET visual read corresponded strongly to SUVr status, with up to 90.4% concordance. Visual read tau positivity was associated with a decline on the MMSE in CU participants (β = -0.52, CI -0.74 to -0.30, p < 0.001) and participants with AD (β = -0.30, CI -0.58 to -0.02, p = 0.04). DISCUSSION The excellent inter-reader agreement, strong correspondence with SUVr, and longitudinal stability indicate that the visual read method is reliable and robust, supporting clinical application. Furthermore, visual read tau positivity was associated with prospective cognitive decline, highlighting its additional prognostic potential. Future studies in unselected cohorts are needed for a better generalizability to the clinical population. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that [18F]flortaucipir visual read accurately distinguishes patients with low tau-tracer binding from those with high tau-tracer binding and is associated with amyloid positivity and cognitive decline.
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Affiliation(s)
- Emma M Coomans
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden.
| | - Lotte A de Koning
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Roos M Rikken
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Sander C J Verfaillie
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Denise Visser
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Anouk den Braber
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Jori Tomassen
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Marleen van de Beek
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Lyduine E Collij
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Afina W Lemstra
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Albert D Windhorst
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Frederik Barkhof
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Sandeep S V Golla
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Pieter Jelle Visser
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Philip Scheltens
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Wiesje M van der Flier
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Rik Ossenkoppele
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Bart N M van Berckel
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
| | - Elsmarieke van de Giessen
- From the Radiology & Nuclear Medicine (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Brain Imaging (E.M.C., L.A.d.K., R.M.R., S.C.J.V., D.V., L.E.C., A.D.W., F.B., S.S.V.G., B.N.M.v.B., E.v.d.G.), Amsterdam Neuroscience; Medical Psychology (S.C.J.V.), Amsterdam UMC location University of Amsterdam; Alzheimer Center Amsterdam (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc; Neurodegeneration (A.d.B., J.T., M.v.d.B., A.W.L., P.J.V., P.S., W.M.v.d.F., R.O.), Amsterdam Neuroscience; Department of Biological Psychology (A.d.B.), Vrije Universiteit Amsterdam, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; Alzheimer Center Limburg (P.J.V.), School for Mental Health and Neuroscience, Maastricht University, the Netherlands; Division of Neurogeriatrics (P.J.V.), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology & Data Science (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and Clinical Memory Research Unit (R.O.), Lund University, Sweden
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13
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Rabinovici GD, Carrillo MC, Apgar C, Gareen IF, Gutman R, Hanna L, Hillner BE, March A, Romanoff J, Siegel BA, Smith K, Song Y, Weber C, Whitmer RA, Gatsonis C. Amyloid Positron Emission Tomography and Subsequent Health Care Use Among Medicare Beneficiaries With Mild Cognitive Impairment or Dementia. JAMA Neurol 2023; 80:1166-1173. [PMID: 37812437 PMCID: PMC10562987 DOI: 10.1001/jamaneurol.2023.3490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 08/11/2023] [Indexed: 10/10/2023]
Abstract
Importance Results of amyloid positron emission tomography (PET) have been shown to change the management of patients with mild cognitive impairment (MCI) or dementia who meet Appropriate Use Criteria (AUC). Objective To determine if amyloid PET is associated with reduced hospitalizations and emergency department (ED) visits over 12 months in patients with MCI or dementia. Design, Setting, and Participants This nonrandomized controlled trial analyzed participants in the Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) study, an open-label, multisite, longitudinal study that enrolled participants between February 2016 and December 2017 and followed up through December 2018. These participants were recruited at 595 clinical sites that provide specialty memory care across the US. Eligible participants were Medicare beneficiaries 65 years or older with a diagnosis of MCI or dementia within the past 24 months who met published AUC for amyloid PET. Each IDEAS study participant was matched to a control Medicare beneficiary who had not undergone amyloid PET. Data analysis was conducted on December 13, 2022. Exposure Participants underwent amyloid PET at imaging centers. Main Outcomes and Measures The primary end points were the proportions of patients with 12-month inpatient hospital admissions and ED visits. One of 4 secondary end points was the rate of hospitalizations and rate of ED visits in participants with positive vs negative amyloid PET results. Health care use was ascertained from Medicare claims data. Results The 2 cohorts (IDEAS study participants and controls) each comprised 12 684 adults, including 6467 females (51.0%) with a median (IQR) age of 77 (73-81) years. Over 12 months, 24.0% of the IDEAS study participants were hospitalized, compared with 25.1% of the matched control cohort, for a relative reduction of -4.49% (97.5% CI, -9.09% to 0.34%). The 12-month ED visit rates were nearly identical between the 2 cohorts (44.8% in both IDEAS study and control cohorts) for a relative reduction of -0.12% (97.5% CI, -3.19% to 3.05%). Both outcomes fell short of the prespecified effect size of 10% or greater relative reduction. Overall, 1467 of 6848 participants (21.4%) with positive amyloid PET scans were hospitalized within 12 months compared with 1081 of 4209 participants (25.7%) with negative amyloid PET scans (adjusted odds ratio, 0.83; 95% CI, 0.78-0.89). Conclusions and Relevance Results of this nonrandomized controlled trial showed that use of amyloid PET was not associated with a significant reduction in 12-month hospitalizations or ED visits. Rates of hospitalization were lower in patients with positive vs negative amyloid PET results.
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Affiliation(s)
- Gil D. Rabinovici
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
- Associate Editor, JAMA Neurology
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco
| | | | - Charles Apgar
- Center for Research and Innovation, American College of Radiology, Reston, Virginia
| | - Ilana F. Gareen
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
| | - Roee Gutman
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
- Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island
| | - Lucy Hanna
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Bruce E. Hillner
- Department of Medicine, Virginia Commonwealth University, Richmond
| | - Andrew March
- Center for Research and Innovation, American College of Radiology, Reston, Virginia
| | - Justin Romanoff
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Barry A. Siegel
- Edward Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri
| | - Karen Smith
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco
| | - Yunjie Song
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
- Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island
| | | | - Rachel A. Whitmer
- Department of Public Health Sciences and Neurology, University of California, Davis, Davis
| | - Constantine Gatsonis
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
- Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island
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14
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Monane M, Johnson KG, Snider BJ, Turner RS, Drake JD, Maraganore DM, Bicksel JL, Jacobs DH, Ortega JL, Henderson J, Jiang Y, Huang S, Coppinger J, Fogelman I, West T, Braunstein JB. A blood biomarker test for brain amyloid impacts the clinical evaluation of cognitive impairment. Ann Clin Transl Neurol 2023; 10:1738-1748. [PMID: 37550958 PMCID: PMC10578891 DOI: 10.1002/acn3.51863] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/06/2023] [Accepted: 07/09/2023] [Indexed: 08/09/2023] Open
Abstract
OBJECTIVE The objective of this study was to examine clinicians' patient selection and result interpretation of a clinically validated mass spectrometry test measuring amyloid beta and ApoE blood biomarkers combined with patient age (PrecivityAD® blood test) in symptomatic patients evaluated for Alzheimer's disease (AD) or other causes of cognitive decline. METHODS The Quality Improvement and Clinical Utility PrecivityAD Clinician Survey (QUIP I, ClinicalTrials.gov Identifier: NCT05477056) was a prospective, single-arm cohort study among 366 patients evaluated by neurologists and other cognitive specialists. Participants underwent blood biomarker testing and received an amyloid probability score (APS), indicating the likelihood of a positive result on an amyloid positron emission tomography (PET) scan. The primary study outcomes were appropriateness of patient selection as well as result interpretation associated with PrecivityAD blood testing. RESULTS A 95% (347/366) concordance rate was noted between clinicians' patient selection and the test's intended use criteria. In the final analysis including these 347 patients (median age 75 years, 56% women), prespecified test result categories incorporated 133 (38%) low APS, 162 (47%) high APS, and 52 (15%) intermediate APS patients. Clinicians' pretest and posttest AD diagnosis probability changed from 58% to 23% in low APS patients and 71% to 89% in high APS patients (p < 0.0001). Anti-AD drug therapy decreased by 46% in low APS patients (p < 0.0001) and increased by 57% in high APS patients (p < 0.0001). INTERPRETATION These findings demonstrate the clinical utility of the PrecivityAD blood test in clinical care and may have added relevance as new AD therapies are introduced.
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Affiliation(s)
| | - Kim G. Johnson
- Department of Psychiatry & Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
| | - B. Joy Snider
- Washington University School of MedicineSt. LouisMissouriUSA
| | | | - Jonathan D. Drake
- Warren Alpert Medical School at Brown UniversityProvidenceRhode IslandUSA
| | | | | | | | | | | | | | | | | | | | - Tim West
- C2N Diagnostics, LLCSt. LouisMissouriUSA
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15
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Zhang S, Dong H, Bian J, Li D, Liu C. Targeting amyloid proteins for clinical diagnosis of neurodegenerative diseases. FUNDAMENTAL RESEARCH 2023; 3:505-519. [PMID: 38933553 PMCID: PMC11197785 DOI: 10.1016/j.fmre.2022.10.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/16/2022] [Accepted: 10/19/2022] [Indexed: 11/05/2022] Open
Abstract
Abnormal aggregation and accumulation of pathological amyloid proteins such as amyloid-β, Tau, and α-synuclein play key pathological roles and serve as histological hallmarks in different neurodegenerative diseases (NDs) such as Alzheimer's disease (AD) and Parkinson's disease (PD). In addition, various post-translational modifications (PTMs) have been identified on pathological amyloid proteins and are subjected to change during disease progression. Given the central role of amyloid proteins in NDs, tremendous efforts have been made to develop amyloid-targeting strategies for clinical diagnosis and molecular classification of NDs. In this review, we summarize two major strategies for targeting amyloid aggregates, with a focus on the trials in AD diagnosis. The first strategy is a positron emission tomography (PET) scan of protein aggregation in the brain. We mainly focus on introducing the development of small-molecule PET tracers for specifically recognizing pathological amyloid fibrils. The second strategy is the detection of PTM biomarkers on amyloid proteins in cerebrospinal fluid and plasma. We discuss the pathological roles of different PTMs in diseases and how we can use the PTM profile of amyloid proteins for clinical diagnosis. Finally, we point out the potential technical challenges of these two strategies, and outline other potential strategies, as well as a combination of multiple strategies, for molecular diagnosis of NDs.
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Affiliation(s)
- Shenqing Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Hui Dong
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Jiang Bian
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Dan Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, China
- Bio-X-Renji Hospital Research Center, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Cong Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
- State Key Laboratory of Bio-Organic and Natural Products Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China
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Pemberton HG, Buckley C, Battle M, Bollack A, Patel V, Tomova P, Cooke D, Balhorn W, Hegedorn K, Lilja J, Brand C, Farrar G. Software compatibility analysis for quantitative measures of [ 18F]flutemetamol amyloid PET burden in mild cognitive impairment. EJNMMI Res 2023; 13:48. [PMID: 37225974 DOI: 10.1186/s13550-023-00994-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
RATIONALE Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. METHODS Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software's MIMneuro, Syntermed's NeuroQ, Hermes Medical Solutions' BRASS and GE Healthcare's CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. RESULTS Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss') and individual software pairings (Cohen's), were ≥ 0.9 signifying "almost perfect" inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957-0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r2 = 0.98). CONCLUSION Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | | | - Mark Battle
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Vrajesh Patel
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Petya Tomova
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | | | | | | | | | - Christine Brand
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Gill Farrar
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
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17
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Altomare D, Barkhof F, Caprioglio C, Collij LE, Scheltens P, Lopes Alves I, Bouwman F, Berkhof J, van Maurik IS, Garibotto V, Moro C, Delrieu J, Payoux P, Saint-Aubert L, Hitzel A, Molinuevo JL, Grau-Rivera O, Gispert JD, Drzezga A, Jessen F, Zeyen P, Nordberg A, Savitcheva I, Jelic V, Walker Z, Edison P, Demonet JF, Gismondi R, Farrar G, Stephens AW, Frisoni GB. Clinical Effect of Early vs Late Amyloid Positron Emission Tomography in Memory Clinic Patients: The AMYPAD-DPMS Randomized Clinical Trial. JAMA Neurol 2023:2804755. [PMID: 37155177 PMCID: PMC10167601 DOI: 10.1001/jamaneurol.2023.0997] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Importance Amyloid positron emission tomography (PET) allows the direct assessment of amyloid deposition, one of the main hallmarks of Alzheimer disease. However, this technique is currently not widely reimbursed because of the lack of appropriately designed studies demonstrating its clinical effect. Objective To assess the clinical effect of amyloid PET in memory clinic patients. Design, Setting, and Participants The AMYPAD-DPMS is a prospective randomized clinical trial in 8 European memory clinics. Participants were allocated (using a minimization method) to 3 study groups based on the performance of amyloid PET: arm 1, early in the diagnostic workup (within 1 month); arm 2, late in the diagnostic workup (after a mean [SD] 8 [2] months); or arm 3, if and when the managing physician chose. Participants were patients with subjective cognitive decline plus (SCD+; SCD plus clinical features increasing the likelihood of preclinical Alzheimer disease), mild cognitive impairment (MCI), or dementia; they were assessed at baseline and after 3 months. Recruitment took place between April 16, 2018, and October 30, 2020. Data analysis was performed from July 2022 to January 2023. Intervention Amyloid PET. Main Outcome and Measure The main outcome was the difference between arm 1 and arm 2 in the proportion of participants receiving an etiological diagnosis with a very high confidence (ie, ≥90% on a 50%-100% visual numeric scale) after 3 months. Results A total of 844 participants were screened, and 840 were enrolled (291 in arm 1, 271 in arm 2, 278 in arm 3). Baseline and 3-month visit data were available for 272 participants in arm 1 and 260 in arm 2 (median [IQR] age: 71 [65-77] and 71 [65-77] years; 150/272 male [55%] and 135/260 male [52%]; 122/272 female [45%] and 125/260 female [48%]; median [IQR] education: 12 [10-15] and 13 [10-16] years, respectively). After 3 months, 109 of 272 participants (40%) in arm 1 had a diagnosis with very high confidence vs 30 of 260 (11%) in arm 2 (P < .001). This was consistent across cognitive stages (SCD+: 25/84 [30%] vs 5/78 [6%]; P < .001; MCI: 45/108 [42%] vs 9/102 [9%]; P < .001; dementia: 39/80 [49%] vs 16/80 [20%]; P < .001). Conclusion and Relevance In this study, early amyloid PET allowed memory clinic patients to receive an etiological diagnosis with very high confidence after only 3 months compared with patients who had not undergone amyloid PET. These findings support the implementation of amyloid PET early in the diagnostic workup of memory clinic patients. Trial Registration EudraCT Number: 2017-002527-21.
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Affiliation(s)
- Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)-Location VUmc, Amsterdam, the Netherlands
- Institute of Neurology, Institute of Healthcare Engineering, University College London, London, United Kingdom
| | - Camilla Caprioglio
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)-Location VUmc, Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)-Location VUmc, Amsterdam, the Netherlands
| | - Femke Bouwman
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Johannes Berkhof
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Ingrid S van Maurik
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers-Location VUmc, Amsterdam, the Netherlands
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
| | - Christian Moro
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Julien Delrieu
- Gérontopôle, Department of Geriatrics, Toulouse University Hospital, Toulouse, France
- Maintain Aging Research Team, CERPOP, Inserm, Université Paul Sabatier, Toulouse, France
| | - Pierre Payoux
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
- Toulouse NeuroImaging Center (ToNIC), UMR1214 Inserm, Université de Toulouse III, Toulouse, France
| | - Laure Saint-Aubert
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
- Toulouse NeuroImaging Center (ToNIC), UMR1214 Inserm, Université de Toulouse III, Toulouse, France
| | - Anne Hitzel
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- H. Lundbeck, Copenhagen, Denmark
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Forschungszentrum Jülich, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Excellence Cluster Cellular Stress Responses in Aging-Related Diseases (CECAD), Medical Faculty, University of Cologne, Cologne, Germany
| | - Philip Zeyen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center of Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Section for Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Vesna Jelic
- Cognitive Disorders Clinic, Theme Inflammation and Aging, Karolinska University Hospital-Huddinge, Stockholm, Sweden
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, United Kingdom
- St Margaret's Hospital, Essex Partnership University NHS Foundation Trust, Essex, United Kingdom
| | - Paul Edison
- Division of Neurology, Department of Brain Sciences, Imperial College London, London, United Kingdom
| | | | | | | | | | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
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18
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Mank A, van Maurik IS, Rijnhart JJM, Rhodius‐Meester HFM, Visser LNC, Lemstra AW, Sikkes SAM, Teunissen CE, van Giessen EM, Berkhof J, van der Flier WM. Determinants of informal care time, distress, depression, and quality of life in care partners along the trajectory of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12418. [PMID: 37114014 PMCID: PMC10126754 DOI: 10.1002/dad2.12418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/19/2023] [Accepted: 03/01/2023] [Indexed: 04/29/2023]
Abstract
Introduction We evaluated determinants associated with care partner outcomes along the Alzheimer's disease (AD) stages. Methods We included n = 270 care partners of amyloid-positive patients in the pre-dementia and dementia stages of AD. Using linear regression analysis, we examined determinants of four care partner outcomes: informal care time, caregiver distress, depression, and quality of life (QoL). Results More behavioral symptoms and functional impairment in patients were associated with more informal care time and depressive symptoms in care partners. More behavioral symptoms were related with more caregiver distress. Spouse care partners spent more time on informal care and QoL was lower in female care partners. Behavioral problems and subtle functional impairment of the patient predisposed for worse care partner outcomes already in the pre-dementia stages. Discussion Both patient and care partner determinants contribute to the care partner outcomes, already in early disease stages. This study provides red flags for high care partner burden.
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Affiliation(s)
- Arenda Mank
- Alzheimer Center Amsterdam, Department of NeurologyVrije Universiteit AmsterdamAmsterdam UMC VUmcAmsterdamthe Netherlands
- Amsterdam NeuroscienceNeurodegenerationAmsterdamthe Netherlands
- Amsterdam UMCVrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamthe Netherlands
| | - Ingrid S. van Maurik
- Alzheimer Center Amsterdam, Department of NeurologyVrije Universiteit AmsterdamAmsterdam UMC VUmcAmsterdamthe Netherlands
- Amsterdam NeuroscienceNeurodegenerationAmsterdamthe Netherlands
- Amsterdam UMCVrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamthe Netherlands
| | | | - Hanneke F. M. Rhodius‐Meester
- Alzheimer Center Amsterdam, Department of NeurologyVrije Universiteit AmsterdamAmsterdam UMC VUmcAmsterdamthe Netherlands
- Department of Internal MedicineGeriatric Medicine SectionVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Geriatric MedicineThe Memory ClinicOslo University HospitalOsloNorway
| | - Leonie N. C. Visser
- Department of Medical PsychologyAmsterdam UMC, AMCUniversity of AmsterdamAmsterdamthe Netherlands
- Amsterdam Public Health Research InstituteQuality of CareAmsterdamthe Netherlands
| | - Afina W. Lemstra
- Alzheimer Center Amsterdam, Department of NeurologyVrije Universiteit AmsterdamAmsterdam UMC VUmcAmsterdamthe Netherlands
- Amsterdam NeuroscienceNeurodegenerationAmsterdamthe Netherlands
| | - Sietske A. M. Sikkes
- Alzheimer Center Amsterdam, Department of NeurologyVrije Universiteit AmsterdamAmsterdam UMC VUmcAmsterdamthe Netherlands
- Amsterdam NeuroscienceNeurodegenerationAmsterdamthe Netherlands
| | - Charlotte E. Teunissen
- Amsterdam NeuroscienceNeurodegenerationAmsterdamthe Netherlands
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije UniversiteitAmsterdam UMC, VUmcAmsterdamthe Netherlands
| | - Elsmarieke M. van Giessen
- Department of Radiology & Nuclear Medicine Vrije Universiteit AmsterdamAmsterdam UMC, VUmcAmsterdamthe Netherlands
| | - Johannes Berkhof
- Amsterdam UMCVrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamthe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Department of NeurologyVrije Universiteit AmsterdamAmsterdam UMC VUmcAmsterdamthe Netherlands
- Amsterdam NeuroscienceNeurodegenerationAmsterdamthe Netherlands
- Amsterdam UMCVrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamthe Netherlands
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19
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Panegyres PK, Robins P. Brain Amyloid in Sporadic Young Onset Alzheimer’s Disease. J Alzheimers Dis Rep 2023; 7:263-270. [PMID: 37090959 PMCID: PMC10116166 DOI: 10.3233/adr-220110] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 03/13/2023] [Indexed: 04/03/2023] Open
Abstract
Background: Controversy exists as to the role of the amyloid-β (Aβ) peptide in the pathophysiology of Alzheimer’s disease (AD). Objective: To clarify the effect of age on Aβ deposition in sporadic AD by exploring the degree of amyloid burden in patients with sporadic young onset AD (YOAD). Methods: Patients were diagnosed with YOAD with dementia starting before the age of 65 years (N = 42; males = 20, females = 22). A cross-sectional analysis of amyloid binding using positron emission tomography (PET) imaging was performed using the C-Pittsburgh Compound B (PiB). The global standardized uptake value ratios (gSUVR) were examined using the Wilcoxon two-sample test, as were the cognitive scores between disease and healthy control populations. Differences in PiB retention in different anatomical areas were compared using the Kruskal-Wallis test. The contrast in APOE genotyping between groups was calculated with Fisher’s Exact Test. Results: Women had a median gSUVR = 2.68±0.73 and 73% had at least one APOE ɛ4 allele. Men had gSUVR = 2.37±0.54, with 80% having at least one APOE ɛ4 allele. The gSUVRs were significantly higher than the control populations for men and women and had significantly greater frequency of APOE ɛ4. Men and women analyzed together had significantly greater amyloid burden and APOE ɛ4 allele frequencies than controls, but no differences existed between them in gSUVR nor in the anatomical distribution of amyloid uptake. Conclusion: Men and women with YOAD have greater amyloid uptake than controls and have more APOE ɛ4 alleles. Our findings suggest that the Aβ peptide is operational in young onset dementia and driven by the APOE ɛ4 allele.
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Affiliation(s)
- Peter K. Panegyres
- Neurodegenerative Disorders Research Pty Ltd, West Perth, WA, Australia
- School of Medicine, The University of Western Australia, Nedlands, WA, Australia
- Correspondence to: Professor P.K. Panegyres, Neurodegenerative Disorders Research Pty Ltd, 4 Lawrence Avenue, West Perth, 6005 Western Australia, Australia. Tel.: +61 8 6317 9472; Fax: +61 8 6210 1188; E-mail:
| | - Peter Robins
- Department of Nuclear Medicine and WA PET Service, Nedlands, WA, Australia
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20
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Prajjwal P, Asharaf S, Makhanasa D, Yamparala A, Tariq H, Aleti S, Gadam S, Vora N. Association of Alzheimer's dementia with oral bacteria, vitamin B12, folate, homocysteine levels, and insulin resistance along with its pathophysiology, genetics, imaging, and biomarkers. Dis Mon 2023; 69:101546. [PMID: 36931946 DOI: 10.1016/j.disamonth.2023.101546] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Alzheimer's disease is a prevalent form of dementia, particularly among the elderly population. It is characterized by progressive cognitive decline and neurodegeneration. Despite numerous studies, the exact cause of Alzheimer's disease remains uncertain, and various theories have been proposed, including Aβ amyloid deposition in the brain and tau protein hyper-phosphorylation. This review article explores the potential pathogenesis of Alzheimer's disease, focusing on the effects of derangements in the levels of vitamin B12, folate, and homocysteine, as well as the impact of oral bacteria causing periodontitis and insulin resistance, and their relationship to Alzheimer's. Studies have shown that high levels of homocysteine and low levels of vitamin B12 and folate, are associated with an increased risk of developing Alzheimer's disease. The article also explores the link between Alzheimer's disease and oral bacteria, specifically dental infections and periodontitis, which contribute to the inflammatory processes in the nervous system of Alzheimer's patients. There could be derangement in the insulin signaling further causing disruption in glucose metabolism within the brain, suggesting that Alzheimer's disease may represent a form of type 2 diabetes mellitus associated with the brain, commonly known as type 3 diabetes. Neuroimaging techniques, including MRI, PET, and tau PET, can identify the predictive characteristics of Alzheimer's disease, with amyloid PET being the most useful in ruling out the disease. The article concludes by stressing the importance of understanding genetic and neuroimaging factors in the diagnosing and treating Alzheimer's disease.
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Affiliation(s)
| | - Shahnaz Asharaf
- Internal Medicine, Travancore Medical College, Kollam, Kerala, India
| | | | | | - Halla Tariq
- Internal Medicine, Multan Medical and Dental College, Multan, Pakistan
| | - Soumya Aleti
- Internal Medicine, Berkshire Medical Center, Pittsfield, MA, USA
| | - Srikanth Gadam
- Internal Medicine, Postdoctoral Research Fellow, Mayo Clinic, USA
| | - Neel Vora
- Internal Medicine, B. J. Medical College, Ahmedabad, India
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21
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Altomare D, Collij L, Caprioglio C, Scheltens P, van Berckel BNM, Alves IL, Berkhof J, de Gier Y, Garibotto V, Moro C, Poitrine L, Delrieu J, Payoux P, Saint-Aubert L, Molinuevo JL, Grau-Rivera O, Gispert JD, Minguillón C, Fauria K, Sanchez MF, Rădoi A, Drzezga A, Jessen F, Escher C, Zeyen P, Nordberg A, Savitcheva I, Jelic V, Walker Z, Lee HY, Lee L, Demonet JF, Plaza Wuthrich S, Gismondi R, Farrar G, Barkhof F, Stephens AW, Frisoni GB. Description of a European memory clinic cohort undergoing amyloid-PET: The AMYPAD Diagnostic and Patient Management Study. Alzheimers Dement 2023; 19:844-856. [PMID: 35715930 DOI: 10.1002/alz.12696] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 03/11/2022] [Accepted: 04/29/2022] [Indexed: 11/11/2022]
Abstract
INTRODUCTION AMYPAD Diagnostic and Patient Management Study (DPMS) aims to investigate the clinical utility and cost-effectiveness of amyloid-PET in Europe. Here we present participants' baseline features and discuss the representativeness of the cohort. METHODS Participants with subjective cognitive decline plus (SCD+), mild cognitive impairment (MCI), or dementia were recruited in eight European memory clinics from April 16, 2018, to October 30, 2020, and randomized into three arms: ARM1, early amyloid-PET; ARM2, late amyloid-PET; and ARM3, free-choice. RESULTS A total of 840 participants (244 SCD+, 341 MCI, and 255 dementia) were enrolled. Sociodemographic/clinical features did not differ significantly among recruiting memory clinics or with previously reported cohorts. The randomization assigned 35% of participants to ARM1, 32% to ARM2, and 33% to ARM3; cognitive stages were distributed equally across the arms. DISCUSSION The features of AMYPAD-DPMS participants are as expected for a memory clinic population. This ensures the generalizability of future study results.
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Affiliation(s)
- Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Lyduine Collij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC) - Location VUmc, Amsterdam, The Netherlands
| | - Camilla Caprioglio
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers (UMC) - Location VUmc, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC) - Location VUmc, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC) - Location VUmc, Amsterdam, The Netherlands
| | - Johannes Berkhof
- Department of Epidemiology and Data Science, Amsterdam University Medical Centers (UMC) - Location VUmc, Amsterdam, The Netherlands
| | - Yvonne de Gier
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC) - Location VUmc, Amsterdam, The Netherlands
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
| | - Christian Moro
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Léa Poitrine
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Julien Delrieu
- Gérontopôle, Department of Geriatrics, Toulouse University Hospital, Toulouse, France
- Maintain Aging Research team, CERPOP, Inserm, Université Paul Sabatier, Toulouse, France
| | - Pierre Payoux
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
- Toulouse NeuroImaging Center (ToNIC), Inserm, Université Paul Sabatier, Toulouse, France
| | - Laure Saint-Aubert
- Department of Nuclear Medicine, Toulouse University Hospital, Toulouse, France
- Toulouse NeuroImaging Center (ToNIC), Université de Toulouse, Inserm, Université Paul Sabatier, Toulouse, France
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- H. Lundbeck A/S, Copenhagen, Denmark
| | - Oriol Grau-Rivera
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Juan-Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Marta Felez Sanchez
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Andreea Rădoi
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Forschungszentrum Jülich, Germany
| | - Frank Jessen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Claus Escher
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Philip Zeyen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center of Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Section for Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Vesna Jelic
- Cognitive Disorders Clinic, Theme Inflammation and Aging, Karolinska University Hospital-Huddinge, Stockholm, Sweden
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, UK
- St. Margaret's Hospital, Essex Partnership University NHS Foundation Trust, Essex, UK
| | - Ho-Yun Lee
- St. Margaret's Hospital, Essex Partnership University NHS Foundation Trust, Essex, UK
| | - Lean Lee
- Division of Psychiatry, University College London, London, UK
| | | | - Sonia Plaza Wuthrich
- Leenaards Memory Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | | | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC) - Location VUmc, Amsterdam, The Netherlands
- Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | | | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
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22
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Andronie-Cioara FL, Ardelean AI, Nistor-Cseppento CD, Jurcau A, Jurcau MC, Pascalau N, Marcu F. Molecular Mechanisms of Neuroinflammation in Aging and Alzheimer's Disease Progression. Int J Mol Sci 2023; 24:ijms24031869. [PMID: 36768235 PMCID: PMC9915182 DOI: 10.3390/ijms24031869] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 01/01/2023] [Accepted: 01/11/2023] [Indexed: 01/20/2023] Open
Abstract
Aging is the most prominent risk factor for late-onset Alzheimer's disease. Aging associates with a chronic inflammatory state both in the periphery and in the central nervous system, the evidence thereof and the mechanisms leading to chronic neuroinflammation being discussed. Nonetheless, neuroinflammation is significantly enhanced by the accumulation of amyloid beta and accelerates the progression of Alzheimer's disease through various pathways discussed in the present review. Decades of clinical trials targeting the 2 abnormal proteins in Alzheimer's disease, amyloid beta and tau, led to many failures. As such, targeting neuroinflammation via different strategies could prove a valuable therapeutic strategy, although much research is still needed to identify the appropriate time window. Active research focusing on identifying early biomarkers could help translating these novel strategies from bench to bedside.
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Affiliation(s)
- Felicia Liana Andronie-Cioara
- Department of Psycho-Neurosciences and Rehabilitation, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
| | - Adriana Ioana Ardelean
- Department of Preclinical Sciences, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
| | - Carmen Delia Nistor-Cseppento
- Department of Psycho-Neurosciences and Rehabilitation, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
- Correspondence: (C.D.N.-C.); (N.P.)
| | - Anamaria Jurcau
- Department of Psycho-Neurosciences and Rehabilitation, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
| | | | - Nicoleta Pascalau
- Department of Psycho-Neurosciences and Rehabilitation, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
- Correspondence: (C.D.N.-C.); (N.P.)
| | - Florin Marcu
- Department of Psycho-Neurosciences and Rehabilitation, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania
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23
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Shimohama S, Tezuka T, Takahata K, Bun S, Tabuchi H, Seki M, Momota Y, Suzuki N, Morimoto A, Iwabuchi Y, Kubota M, Yamamoto Y, Sano Y, Shikimoto R, Funaki K, Mimura Y, Nishimoto Y, Ueda R, Jinzaki M, Nakahara J, Mimura M, Ito D. Impact of Amyloid and Tau PET on Changes in Diagnosis and Patient Management. Neurology 2023; 100:e264-e274. [PMID: 36175151 DOI: 10.1212/wnl.0000000000201389] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 08/26/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Previous studies have evaluated the diagnostic effect of amyloid PET in selected research cohorts. However, these studies did not assess the clinical impact of the combination of amyloid and tau PETs. Our objective was to evaluate the association of the combination of 2 PETs with changes in diagnosis, treatment, and management in a memory clinic cohort. METHODS All participants underwent amyloid [18F]florbetaben PET and tau PET using [18F]PI-2620 or [18F]Florzolotau, which are potentially useful for the diagnosis of non-Alzheimer disease (AD) tauopathies. Dementia specialists determined a pre- and post-PET diagnosis that existed in both a clinical syndrome (cognitive normal [CN], mild cognitive impairment [MCI], and dementia) and suspected etiology, with a confidence level. In addition, the dementia specialists determined patient treatment in terms of ancillary investigations and management. RESULTS Among 126 registered participants, 84.9% completed the study procedures and were included in the analysis (CN [n = 40], MCI [n = 25], AD [n = 20], and non-AD dementia [n = 22]). The etiologic diagnosis changed in 25.0% in the CN, 68.0% in the MCI, and 23.8% with dementia. Overall changes in management between pre- and post-PET occurred in 5.0% of CN, 52.0% of MCI, and 38.1% of dementia. Logistic regression analysis revealed that tau PET has stronger associations with change management than amyloid PET in all participants and dementia groups. DISCUSSION The combination of amyloid and tau PETs was associated with changes in management and diagnosis of MCI and dementia, and the second-generation tau PET has a strong impact on the changes in diagnosis and management in memory clinics. CLASSIFICATION OF EVIDENCE This study provides Class I evidence that the combination of amyloid and tau PETs was associated with changes in management and diagnosis of MCI and dementia.
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Affiliation(s)
- Sho Shimohama
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Toshiki Tezuka
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Keisuke Takahata
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Shogyoku Bun
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Hajime Tabuchi
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Morinobu Seki
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Yuki Momota
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Natsumi Suzuki
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Ayaka Morimoto
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Yu Iwabuchi
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Masahito Kubota
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Yasuharu Yamamoto
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Yasunori Sano
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Ryo Shikimoto
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Kei Funaki
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Yu Mimura
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Yoshinori Nishimoto
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Ryo Ueda
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Masahiro Jinzaki
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Jin Nakahara
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Masaru Mimura
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan
| | - Daisuke Ito
- From the Departments of Neurology (S.S., T.T., M.S., M.K., Y.N., J.N.), Neuropsychiatry (T.K., S.B., H.T., Yuki Momota, N.S., A.M., Y.Y., Y.S., R.S., K.F., Yu Mimura, M.M.), Radiology (Y.I., M.J.), Physiology (D.I.), and Memory Center (D.I.), Keio University School of Medicine, Tokyo; Department of Functional Brain Imaging (T.K.), Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), Chiba; and Office of Radiation Technology (R.U.), Keio University Hospital, Tokyo, Japan.
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24
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Caprioglio C, Ribaldi F, Visser LNC, Minguillon C, Collij LE, Grau-Rivera O, Zeyen P, Molinuevo JL, Gispert JD, Garibotto V, Moro C, Walker Z, Edison P, Demonet JF, Barkhof F, Scheltens P, Alves IL, Gismondi R, Farrar G, Stephens AW, Jessen F, Frisoni GB, Altomare D. Analysis of Psychological Symptoms Following Disclosure of Amyloid-Positron Emission Tomography Imaging Results to Adults With Subjective Cognitive Decline. JAMA Netw Open 2023; 6:e2250921. [PMID: 36637820 PMCID: PMC9857261 DOI: 10.1001/jamanetworkopen.2022.50921] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
IMPORTANCE Individuals who are amyloid-positive with subjective cognitive decline and clinical features increasing the likelihood of preclinical Alzheimer disease (SCD+) are at higher risk of developing dementia. Some individuals with SCD+ undergo amyloid-positron emission tomography (PET) as part of research studies and frequently wish to know their amyloid status; however, the disclosure of a positive amyloid-PET result might have psychological risks. OBJECTIVE To assess the psychological outcomes of the amyloid-PET result disclosure in individuals with SCD+ and explore which variables are associated with a safer disclosure in individuals who are amyloid positive. DESIGN, SETTING, AND PARTICIPANTS This prospective, multicenter study was conducted as part of The Amyloid Imaging to Prevent Alzheimer Disease Diagnostic and Patient Management Study (AMYPAD-DPMS) (recruitment period: from April 2018 to October 2020). The setting was 5 European memory clinics, and participants included patients with SCD+ who underwent amyloid-PET. Statistical analysis was performed from July to October 2022. EXPOSURES Disclosure of amyloid-PET result. MAIN OUTCOMES AND MEASURES Psychological outcomes were defined as (1) disclosure related distress, assessed using the Impact of Event Scale-Revised (IES-R; scores of at least 33 indicate probable presence of posttraumatic stress disorder [PTSD]); and (2) anxiety and depression, assessed using the Hospital Anxiety and Depression scale (HADS; scores of at least 15 indicate probable presence of severe mood disorder symptoms). RESULTS After disclosure, 27 patients with amyloid-positive SCD+ (median [IQR] age, 70 [66-74] years; gender: 14 men [52%]; median [IQR] education: 15 [13 to 17] years, median [IQR] Mini-Mental State Examination [MMSE] score, 29 [28 to 30]) had higher median (IQR) IES-R total score (10 [2 to 14] vs 0 [0 to 2]; P < .001), IES-R avoidance (0.00 [0.00 to 0.69] vs 0.00 [0.00 to 0.00]; P < .001), IES-R intrusions (0.50 [0.13 to 0.75] vs 0.00 [0.00 to 0.25]; P < .001), and IES-R hyperarousal (0.33 [0.00 to 0.67] vs 0.00 [0.00 to 0.00]; P < .001) scores than the 78 patients who were amyloid-negative (median [IQR], age, 67 [64 to 74] years, 45 men [58%], median [IQR] education: 15 [12 to 17] years, median [IQR] MMSE score: 29 [28 to 30]). There were no observed differences between amyloid-positive and amyloid-negative patients in the median (IQR) HADS Anxiety (-1.0 [-3.0 to 1.8] vs -2.0 [-4.8 to 1.0]; P = .06) and Depression (-1.0 [-2.0 to 0.0] vs -1.0 [-3.0 to 0.0]; P = .46) deltas (score after disclosure - scores at baseline). In patients with amyloid-positive SCD+, despite the small sample size, higher education was associated with lower disclosure-related distress (ρ = -0.43; P = .02) whereas the presence of study partner was associated with higher disclosure-related distress (W = 7.5; P = .03). No participants with amyloid-positive SCD+ showed probable presence of PTSD or severe anxiety or depression symptoms at follow-up. CONCLUSIONS AND RELEVANCE The disclosure of a positive amyloid-PET result to patients with SCD+ was associated with a bigger psychological change, yet such change did not reach the threshold for clinical concern.
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Affiliation(s)
- Camilla Caprioglio
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Leonie N. C. Visser
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm/Solna, Sweden
- Department of Medical Psychology, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | - Carolina Minguillon
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Lyduine E. Collij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | - Oriol Grau-Rivera
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Philip Zeyen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - José Luis Molinuevo
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- H. Lundbeck A/S, Denmark
| | - Juan Domingo Gispert
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Christian Moro
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, United Kingdom
- Margaret’s Hospital, Essex Partnership University NHS Foundation Trust, Essex, United Kingdom
| | - Paul Edison
- Division of Neurology, Department of Brain Sciences, Imperial College London, United Kingdom
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | | | | | | | - Frank Jessen
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Excellence Cluster Cellular Stress Responses in Aging-Related Diseases (CECAD), Medical Faculty, University of Cologne, Germany
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
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Wang J, Jin C, Zhou J, Zhou R, Tian M, Lee HJ, Zhang H. PET molecular imaging for pathophysiological visualization in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2023; 50:765-783. [PMID: 36372804 PMCID: PMC9852140 DOI: 10.1007/s00259-022-05999-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 10/09/2022] [Indexed: 11/15/2022]
Abstract
Alzheimer's disease (AD) is the most common dementia worldwide. The exact etiology of AD is unclear as yet, and no effective treatments are currently available, making AD a tremendous burden posed on the whole society. As AD is a multifaceted and heterogeneous disease, and most biomarkers are dynamic in the course of AD, a range of biomarkers should be established to evaluate the severity and prognosis. Positron emission tomography (PET) offers a great opportunity to visualize AD from diverse perspectives by using radiolabeled agents involved in various pathophysiological processes; PET imaging technique helps to explore the pathomechanisms of AD comprehensively and find out the most appropriate biomarker in each AD phase, leading to a better evaluation of the disease. In this review, we discuss the application of PET in the course of AD and summarized radiolabeled compounds with favorable imaging characteristics.
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Affiliation(s)
- Jing Wang
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XInstitute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009 Zhejiang China ,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 Zhejiang China
| | - Chentao Jin
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China
| | - Jinyun Zhou
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China
| | - Rui Zhou
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China
| | - Mei Tian
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XInstitute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009 Zhejiang China ,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 Zhejiang China
| | - Hyeon Jeong Lee
- grid.13402.340000 0004 1759 700XCollege of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310014 Zhejiang China
| | - Hong Zhang
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XInstitute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009 Zhejiang China ,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XCollege of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310014 Zhejiang China ,grid.13402.340000 0004 1759 700XKey Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310014 Zhejiang China
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Mank A, van Maurik IS, van Harten AC, Rhodius‐Meester HFM, Teunissen CE, van Berckel BNM, Berkhof J, van der Flier WM, Rijnhart JJM. Life satisfaction across the entire trajectory of Alzheimer's disease: A mediation analysis. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12389. [PMID: 36579132 PMCID: PMC9780509 DOI: 10.1002/dad2.12389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 11/16/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022]
Abstract
Introduction We studied life satisfaction across Alzheimer's disease (AD) stages and studied mobility and meaningful activities as mediators of the associations between these AD stages and life satisfaction. Methods In this cross-sectional study, we included n = 269 amyloid-positive patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD dementia from the Amsterdam Dementia Cohort. Life satisfaction was measured with the satisfaction with life scale. The mediating role of transportation, work, sports, and hobbies on life satisfaction was examined in single and multiple mediator models. Results Patients with dementia are less satisfied with life compared to SCD and MCI. These differences in life satisfaction are explained by reduced participation in meaningful activities, which in turn, was largely attributable to decreased transportation use. Discussion Our findings suggest that improving access to transportation, therewith allowing participation in meaningful activities help to maintain life satisfaction and may be an important target for intervention.
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Affiliation(s)
- Arenda Mank
- Alzheimer Center Amsterdam, NeurologyAmsterdam UMC location VUmcVrije Universiteit AmsterdamAmsterdamThe Netherlands,Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands,Amsterdam UMC, Vrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamThe Netherlands
| | - Ingrid S. van Maurik
- Alzheimer Center Amsterdam, NeurologyAmsterdam UMC location VUmcVrije Universiteit AmsterdamAmsterdamThe Netherlands,Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands,Amsterdam UMC, Vrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamThe Netherlands
| | - Argonde C. van Harten
- Alzheimer Center Amsterdam, NeurologyAmsterdam UMC location VUmcVrije Universiteit AmsterdamAmsterdamThe Netherlands,Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
| | - Hanneke F. M. Rhodius‐Meester
- Alzheimer Center Amsterdam, NeurologyAmsterdam UMC location VUmcVrije Universiteit AmsterdamAmsterdamThe Netherlands,Department of Internal MedicineGeriatric Medicine SectionVrije Universiteit AmsterdamAmsterdam UMCAmsterdamThe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Clinical ChemistryAmsterdam UMC location VUmcVrije UniversiteitAmsterdamThe Netherlands
| | - Bart N. M. van Berckel
- Alzheimer Center Amsterdam, NeurologyAmsterdam UMC location VUmcVrije Universiteit AmsterdamAmsterdamThe Netherlands,Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands,Department of Radiology & Nuclear Medicine Amsterdam Neuroscience Vrije Universiteit AmsterdamAmsterdam UMCAmsterdamThe Netherlands
| | - Johannes Berkhof
- Amsterdam UMC, Vrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamThe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, NeurologyAmsterdam UMC location VUmcVrije Universiteit AmsterdamAmsterdamThe Netherlands,Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands,Amsterdam UMC, Vrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamThe Netherlands
| | - Judith J. M. Rijnhart
- Amsterdam UMC, Vrije Universiteit AmsterdamDepartment of Epidemiology and Data ScienceAmsterdam Public Health InstituteAmsterdamThe Netherlands
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27
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Collij LE, Salvadó G, de Wilde A, Altomare D, Shekari M, Gispert JD, Bullich S, Stephens A, Barkhof F, Scheltens P, Bouwman F, van der Flier WM. Quantification of [
18
F]florbetaben amyloid‐PET imaging in a mixed memory clinic population: The ABIDE project. Alzheimers Dement 2022. [DOI: 10.1002/alz.12886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/25/2022] [Accepted: 10/27/2022] [Indexed: 12/12/2022]
Affiliation(s)
- Lyduine E. Collij
- Department of Radiology and Nuclear Medicine Amsterdam University Medical Center Amsterdam Neuroscience Amsterdam The Netherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain
- Clinical Memory Research Unit Department of Clinical Sciences Lund University Malmö Sweden
| | - Arno de Wilde
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE) University of Geneva Geneva Switzerland
- Memory Center Geneva University Hospitals Geneva Switzerland
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain
- IMIM (Hospital del Mar Medical Research Institute) Barcelona Spain
- Pompeu Fabra University Barcelona Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC) Pasqual Maragall Foundation Barcelona Spain
- IMIM (Hospital del Mar Medical Research Institute) Barcelona Spain
- Centro de Investigación Biomédica en Red de Bioingeniería Biomateriales y Nanomedicina (CIBER‐BBN) Madrid Spain
| | | | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine Amsterdam University Medical Center Amsterdam Neuroscience Amsterdam The Netherlands
- Centre for Medical Image Computing and Queen Square Institute of Neurology UCL London UK
| | - Philip Scheltens
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
| | - Femke Bouwman
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
| | - Wiesje M. van der Flier
- Department of Neurology Alzheimer Center Amsterdam Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
- Department of Epidemiology & Data Science Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
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28
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van Maurik IS, Broulikova HM, Mank A, Bakker ED, de Wilde A, Bouwman FH, Stephens AW, van Berckel BNM, Scheltens P, van der Flier WM. A more precise diagnosis by means of amyloid PET contributes to delayed institutionalization, lower mortality, and reduced care costs in a tertiary memory clinic setting. Alzheimers Dement 2022; 19:2006-2013. [PMID: 36419238 DOI: 10.1002/alz.12846] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 10/03/2022] [Accepted: 10/05/2022] [Indexed: 11/25/2022]
Abstract
INTRODUCTION We aim to study the effect of a more precise diagnosis, by means of amyloid positron emission tomography (PET), on institutionalization, mortality, and health-care costs. METHODS Between October 27, 2014 and December 31, 2016, we offered amyloid PET to all patients as part of their diagnostic work-up. Patients who accepted to undergo amyloid PET (n = 449) were propensity score matched with patients without amyloid PET (n = 571, i.e., no PET). Matched groups (both n = 444) were compared on rate of institutionalization, mortality, and health-care costs in the years after diagnosis. RESULTS Amyloid PET patients had a lower risk of institutionalization (10% [n = 45] vs. 21% [n = 92]; hazard ratio [HR] = 0.48 [0.33-0.70]) and mortality rate (11% [n = 49] vs. 18% [n = 81]; HR = 0.51 [0.36-0.73]) and lower health-care costs in the years after diagnosis compared to matched no-PET patients (β = -4573.49 [-6524.76 to -2523.74], P-value < 0.001). DISCUSSION A more precise diagnosis in tertiary memory clinic patients positively influenced the endpoints of institutionalization, death, and health-care costs.
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Affiliation(s)
- Ingrid S. van Maurik
- Alzheimer Center Amsterdam, Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam the Netherlands
- Amsterdam Neuroscience Neurodegeneration Amsterdam the Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam Epidemiology and Data Science Amsterdam the Netherlands
- Amsterdam Public Health Methodology Amsterdam the Netherlands
| | - Hana M. Broulikova
- Department of Health Sciences Faculty of Science Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute Amsterdam the Netherlands
| | - Arenda Mank
- Alzheimer Center Amsterdam, Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam the Netherlands
- Amsterdam Neuroscience Neurodegeneration Amsterdam the Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam Epidemiology and Data Science Amsterdam the Netherlands
- Amsterdam Public Health Methodology Amsterdam the Netherlands
| | - Els D. Bakker
- Alzheimer Center Amsterdam, Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam the Netherlands
- Amsterdam Neuroscience Neurodegeneration Amsterdam the Netherlands
| | - Arno de Wilde
- Alzheimer Center Amsterdam, Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam the Netherlands
- Amsterdam Neuroscience Neurodegeneration Amsterdam the Netherlands
- EQT Life Sciences Amsterdam the Netherlands
| | - Femke H. Bouwman
- Alzheimer Center Amsterdam, Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam the Netherlands
- Amsterdam Neuroscience Neurodegeneration Amsterdam the Netherlands
| | | | - Bart N. M. van Berckel
- Department of Radiology and Nuclear Medicine Vrije Universiteit Amsterdam, Amsterdam UMC Amsterdam the Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam the Netherlands
- Amsterdam Neuroscience Neurodegeneration Amsterdam the Netherlands
- EQT Life Sciences Amsterdam the Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam the Netherlands
- Amsterdam Neuroscience Neurodegeneration Amsterdam the Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam Epidemiology and Data Science Amsterdam the Netherlands
- Amsterdam Public Health Methodology Amsterdam the Netherlands
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Huseby CJ, Delvaux E, Brokaw DL, Coleman PD. Blood Transcript Biomarkers Selected by Machine Learning Algorithm Classify Neurodegenerative Diseases including Alzheimer's Disease. Biomolecules 2022; 12:1592. [PMID: 36358942 PMCID: PMC9687215 DOI: 10.3390/biom12111592] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/22/2022] [Accepted: 10/22/2022] [Indexed: 10/15/2023] Open
Abstract
The clinical diagnosis of neurodegenerative diseases is notoriously inaccurate and current methods are often expensive, time-consuming, or invasive. Simple inexpensive and noninvasive methods of diagnosis could provide valuable support for clinicians when combined with cognitive assessment scores. Biological processes leading to neuropathology progress silently for years and are reflected in both the central nervous system and vascular peripheral system. A blood-based screen to distinguish and classify neurodegenerative diseases is especially interesting having low cost, minimal invasiveness, and accessibility to almost any world clinic. In this study, we set out to discover a small set of blood transcripts that can be used to distinguish healthy individuals from those with Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, Friedreich's ataxia, or frontotemporal dementia. Using existing public datasets, we developed a machine learning algorithm for application on transcripts present in blood and discovered small sets of transcripts that distinguish a number of neurodegenerative diseases with high sensitivity and specificity. We validated the usefulness of blood RNA transcriptomics for the classification of neurodegenerative diseases. Information about features selected for the classification can direct the development of possible treatment strategies.
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Affiliation(s)
- Carol J. Huseby
- ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ 85281, USA
| | - Elaine Delvaux
- ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ 85281, USA
| | - Danielle L. Brokaw
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Paul D. Coleman
- ASU-Banner Neurodegenerative Disease Research Center, Arizona State University, Tempe, AZ 85281, USA
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30
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Mank A, Rijnhart JJM, van Maurik IS, Jönsson L, Handels R, Bakker ED, Teunissen CE, van Berckel BNM, van Harten AC, Berkhof J, van der Flier WM. A longitudinal study on quality of life along the spectrum of Alzheimer's disease. Alzheimers Res Ther 2022; 14:132. [PMID: 36109800 PMCID: PMC9476356 DOI: 10.1186/s13195-022-01075-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 09/06/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND Quality of life (QoL) is an important outcome from the perspective of patients and their caregivers, in both dementia and pre-dementia stages. Yet, little is known about the long-term changes in QoL over time. We aimed to compare the trajectories of QoL between amyloid-positive and amyloid-negative SCD or MCI patients and to evaluate QoL trajectories along the Alzheimer's disease (AD) continuum of cognitively normal to dementia. METHODS We included longitudinal data of 447 subjective cognitive decline (SCD), 276 mild cognitive impairment (MCI), and 417 AD dementia patients from the Amsterdam Dementia Cohort. We compared QoL trajectories (EQ-5D and visual analog scale (VAS)) between (1) amyloid-positive and amyloid-negative SCD or MCI patients and (2) amyloid-positive SCD, MCI, and dementia patients with linear mixed-effect models. The models were adjusted for age, sex, Charlson Comorbidity Index (CCI), education, and EQ-5D scale (3 or 5 level). RESULTS In SCD, amyloid-positive participants had a higher VAS at baseline but showed a steeper decline over time in EQ-5D and VAS than amyloid-negative participants. Also, in MCI, amyloid-positive patients had higher QoL at baseline but subsequently showed a steeper decline in QoL over time compared to amyloid-negative patients. When we compared amyloid-positive patients along the Alzheimer continuum, we found no difference between SCD, MCI, or dementia in baseline QoL, but QoL decreased at a faster rate in the dementia stage compared with the of SCD and MCI stages. CONCLUSIONS QoL decreased at a faster rate over time in amyloid-positive SCD or MCI patients than amyloid-negative patients. QoL decreases over time along the entire AD continuum of SCD, MCI and dementia, with the strongest decrease in dementia patients. Knowledge of QoL trajectories is essential for the future evaluation of treatments in AD.
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Affiliation(s)
- Arenda Mank
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands. .,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands. .,Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam, The Netherlands.
| | - Judith J M Rijnhart
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam, The Netherlands
| | - Ingrid S van Maurik
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.,Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam, The Netherlands
| | - Linus Jönsson
- Department for Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Solna, Sweden
| | - Ron Handels
- Department for Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Solna, Sweden.,Department of Psychiatry and Neuropsychology, Alzheimer Centre Limburg, School for Mental Health and Neurosciences, Maastricht University, Maastricht, The Netherlands
| | - Els D Bakker
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.,Department of Radiology & Nuclear Medicine Amsterdam Neuroscience Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Johannes Berkhof
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.,Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam, The Netherlands
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31
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Mank A, van Maurik IS, Rijnhart JJM, bakker ED, Bouteloup V, Le Scouarnec L, Teunissen CE, Barkhof F, Scheltens P, Berkhof J, van der Flier WM. Development of multivariable prediction models for institutionalization and mortality in the full spectrum of Alzheimer’s disease. Alzheimers Res Ther 2022; 14:110. [PMID: 35932034 PMCID: PMC9354423 DOI: 10.1186/s13195-022-01053-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 07/27/2022] [Indexed: 11/15/2022]
Abstract
Background Patients and caregivers express a desire for accurate prognostic information about time to institutionalization and mortality. Previous studies predicting institutionalization and mortality focused on the dementia stage. However, Alzheimer’s disease (AD) is characterized by a long pre-dementia stage. Therefore, we developed prediction models to predict institutionalization and mortality along the AD continuum of cognitively normal to dementia. Methods This study included SCD/MCI patients (subjective cognitive decline (SCD) or mild cognitive impairment (MCI)) and patients with AD dementia from the Amsterdam Dementia Cohort. We developed internally and externally validated prediction models with biomarkers and without biomarkers, stratified by dementia status. Determinants were selected using backward selection (p<0.10). All models included age and sex. Discriminative performance of the models was assessed with Harrell’s C statistics. Results We included n=1418 SCD/MCI patients (n=123 died, n=74 were institutionalized) and n=1179 patients with AD dementia (n=413 died, n=453 were institutionalized). For both SCD/MCI and dementia stages, the models for institutionalization and mortality included after backward selection clinical characteristics, imaging, and cerebrospinal fluid (CSF) biomarkers. In SCD/MCI, the Harrell’s C-statistics of the models were 0.81 (model without biomarkers: 0.76) for institutionalization and 0.79 (model without biomarker: 0.76) for mortality. In AD-dementia, the Harrell’s C-statistics of the models were 0.68 (model without biomarkers: 0.67) for institutionalization and 0.65 (model without biomarker: 0.65) for mortality. Models based on data from amyloid-positive patients only had similar discrimination. Conclusions We constructed prediction models to predict institutionalization and mortality with good accuracy for SCD/MCI patients and moderate accuracy for patients with AD dementia. The developed prediction models can be used to provide patients and their caregivers with prognostic information on time to institutionalization and mortality along the cognitive continuum of AD. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-01053-0.
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Pemberton HG, Collij LE, Heeman F, Bollack A, Shekari M, Salvadó G, Alves IL, Garcia DV, Battle M, Buckley C, Stephens AW, Bullich S, Garibotto V, Barkhof F, Gispert JD, Farrar G. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging 2022; 49:3508-3528. [PMID: 35389071 PMCID: PMC9308604 DOI: 10.1007/s00259-022-05784-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/25/2022] [Indexed: 12/15/2022]
Abstract
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Amersham, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Brain Research Center, Amsterdam, The Netherlands
| | - David Vallez Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark Battle
- GE Healthcare, Amersham, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | | | | | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, Geneva, Switzerland
- NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
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Newberg AB, Coble R, Khosravi M, Alavi A. Positron Emission Tomography-Based Assessment of Cognitive Impairment and Dementias, Critical Role of Fluorodeoxyglucose in such Settings. PET Clin 2022; 17:479-494. [PMID: 35717103 DOI: 10.1016/j.cpet.2022.03.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Positron emission tomography (PET) has been a key component in the diagnostic armamentarium for assessing neurodegenerative diseases such as Alzheimer or Parkinson disease. PET imaging has been useful for diagnosing these disorders, identifying their pathophysiology, and following their treatment. Further, PET imaging has been extensively used for both clinical and research purposes, particularly for helping with potential therapeutic approaches for managing neurodegenerative diseases. This article will review the current literature regarding PET imaging in patients with neurodegenerative disorders. This includes an evaluation of the most commonly used tracer fluorodeoxyglucose that measures cerebral glucose metabolism, tracers that assess neurotransmitter systems, and tracers designed to reveal disease-specific pathophysiological processes. With the continuing development of an expanding variety of radiopharmaceuticals, PET imaging will likely play a prominent role in future research and clinical applications for neurodegenerative diseases.
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Affiliation(s)
- Andrew B Newberg
- Marcus Institute of Integrative Health, Thomas Jefferson University, 789 East Lancaster Avenue, Suite 110, Villanova, PA 19085, USA; Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA.
| | - Roger Coble
- Marcus Institute of Integrative Health, Thomas Jefferson University, 789 East Lancaster Avenue, Suite 110, Villanova, PA 19085, USA; University of California Berkeley, Berkeley, CA, USA
| | - Mohsen Khosravi
- Marcus Institute of Integrative Health, Thomas Jefferson University, 789 East Lancaster Avenue, Suite 110, Villanova, PA 19085, USA
| | - Abass Alavi
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
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34
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Incremental diagnostic value of 18F-Fluetemetamol PET in differential diagnoses of Alzheimer's Disease-related neurodegenerative diseases from an unselected memory clinic cohort. Sci Rep 2022; 12:10385. [PMID: 35725910 PMCID: PMC9209498 DOI: 10.1038/s41598-022-14532-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 06/08/2022] [Indexed: 11/08/2022] Open
Abstract
To evaluate the incremental diagnostic value of 18F-Flutemetamol PET following MRI measurements on an unselected prospective cohort collected from a memory clinic. A total of 84 participants was included in this study. A stepwise study design was performed including initial analysis (based on clinical assessments), interim analysis (revision of initial analysis post-MRI) and final analysis (revision of interim analysis post-18F-Flutemetamol PET). At each time of evaluation, every participant was categorized into SCD, MCI or dementia syndromal group and further into AD-related, non-AD related or non-specific type etiological subgroup. Post 18F-Flutemetamol PET, the significant changes were seen in the syndromal MCI group (57%, p < 0.001) involving the following etiological subgroups: AD-related MCI (57%, p < 0.01) and non-specific MCI (100%, p < 0.0001); and syndromal dementia group (61%, p < 0.0001) consisting of non-specific dementia subgroup (100%, p < 0.0001). In the binary regression model, amyloid status significantly influenced the diagnostic results of interim analysis (p < 0.01). 18F-Flutemetamol PET can have incremental value following MRI measurements, particularly reflected in the change of diagnosis of individuals with unclear etiology and AD-related-suspected patients due to the role in complementing AD-related pathological information.
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35
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Fan DY, Jian JM, Huang S, Li WW, Shen YY, Wang Z, Zeng GH, Yi X, Jin WS, Liu YH, Zeng F, Bu XL, Chen LY, Mao QX, Xu ZQ, Yu JT, Wang J, Wang YJ. Establishment of combined diagnostic models of Alzheimer's disease in a Chinese cohort: the Chongqing Ageing & Dementia Study (CADS). Transl Psychiatry 2022; 12:252. [PMID: 35710549 PMCID: PMC9203516 DOI: 10.1038/s41398-022-02016-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 05/18/2022] [Accepted: 05/31/2022] [Indexed: 11/09/2022] Open
Abstract
Cerebrospinal fluid (CSF) biomarkers are essential for the accurate diagnosis of Alzheimer's disease (AD), yet their measurement levels vary widely across centers and regions, leaving no uniform cutoff values to date. Diagnostic cutoff values of CSF biomarkers for AD are lacking for the Chinese population. As a member of the Alzheimer's Association Quality Control program for CSF biomarkers, we aimed to establish diagnostic models based on CSF biomarkers and risk factors for AD in a Chinese cohort. A total of 64 AD dementia patients and 105 age- and sex-matched cognitively normal (CN) controls from the Chongqing Ageing & Dementia Study cohort were included. CSF Aβ42, P-tau181, and T-tau levels were measured by ELISA. Combined biomarker models and integrative models with demographic characteristics were established by logistic regression. The cutoff values to distinguish AD from CN were 933 pg/mL for Aβ42, 48.7 pg/mL for P-tau181 and 313 pg/mL for T-tau. The AN model, including Aβ42 and T-tau, had a higher diagnostic accuracy of 89.9%. Integrating age and APOE ε4 status to AN model (the ANA'E model) increased the diagnostic accuracy to 90.5% and improved the model performance. This study established cutoff values of CSF biomarkers and optimal combined models for AD diagnosis in a Chinese cohort.
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Affiliation(s)
- Dong-Yu Fan
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China ,grid.410570.70000 0004 1760 6682Shigatse Branch, Xinqiao Hospital, Third Military Medical University, Shigatse, China
| | - Jie-Ming Jian
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Shan Huang
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China ,grid.263452.40000 0004 1798 4018First Clinical Medical College, Shanxi Medical University, Taiyuan, China ,grid.263452.40000 0004 1798 4018Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, China
| | - Wei-Wei Li
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China ,Department of Neurology, Western Theater General Hospital, Chengdu, China
| | - Ying-Ying Shen
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Zhen Wang
- grid.410570.70000 0004 1760 6682Department of Critical Care Medicine, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Gui-Hua Zeng
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Xu Yi
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Wang-Sheng Jin
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Yu-Hui Liu
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Fan Zeng
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Xian-Le Bu
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Li-Yong Chen
- grid.410570.70000 0004 1760 6682Department of Anaesthesiology, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Qing-Xiang Mao
- grid.410570.70000 0004 1760 6682Department of Anaesthesiology, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Zhi-Qiang Xu
- grid.410570.70000 0004 1760 6682Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China ,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Jin-Tai Yu
- grid.8547.e0000 0001 0125 2443Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jun Wang
- Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China. .,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China.
| | - Yan-Jiang Wang
- Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, China. .,Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China. .,State Key Laboratory of Trauma, Burn and Combined Injury, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, China. .,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
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Chapleau M, Iaccarino L, Soleimani-Meigooni D, Rabinovici GD. The Role of Amyloid PET in Imaging Neurodegenerative Disorders: A Review. J Nucl Med 2022; 63:13S-19S. [PMID: 35649652 DOI: 10.2967/jnumed.121.263195] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/22/2022] [Indexed: 12/17/2022] Open
Abstract
Imaging of amyloid deposition using PET has been available in research studies for 2 decades and has been approved for clinical use by the U.S. Food and Drug Administration, the European Medicines Agency, and other regulatory agencies around the world. Amyloid PET is a crucial tool for the diagnosis of Alzheimer disease, as it allows the noninvasive detection of amyloid plaques, a core neuropathologic feature that defines the disease. The clinical use of amyloid PET is expected to increase with recent accelerated approval in the United States of aducanumab, an antiamyloid monoclonal antibody, for the treatment of mild cognitive impairment and mild dementia due to Alzheimer disease. However, amyloid pathology can also be found in cognitively unimpaired older adults and in patients with other neurodegenerative disorders. The aim of this review is to provide an up-to-date overview of the application of amyloid PET in neurodegenerative diseases. We provide an in-depth analysis of the clinical, pathologic, and imaging correlates; a comparison with other available biomarkers; and a review of the application of amyloid PET in clinical trials and clinical utility studies.
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Affiliation(s)
- Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California;
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - David Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California.,Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California; and.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California
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37
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Functional Imaging for Neurodegenerative Diseases. Presse Med 2022; 51:104121. [PMID: 35490910 DOI: 10.1016/j.lpm.2022.104121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 03/13/2022] [Accepted: 04/11/2022] [Indexed: 12/16/2022] Open
Abstract
Diagnosis and monitoring of neurodegenerative diseases has changed profoundly over the past twenty years. Biomarkers are now included in most diagnostic procedures as well as in clinical trials. Neuroimaging biomarkers provide access to brain structure and function over the course of neurodegenerative diseases. They have brought new insights into a wide range of neurodegenerative diseases and have made it possible to describe some of the imaging challenges in clinical populations. MRI mainly explores brain structure while molecular imaging, functional MRI and electro- and magnetoencephalography examine brain function. In this paper, we describe and analyse the current and potential contribution of MRI and molecular imaging in the field of neurodegenerative diseases.
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38
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Soo SA, Zailan FZ, Tan JY, Sandhu GK, Wong BYX, Wang BZ, Ng ASL, Chiew HJ, Ng KP, Kandiah N. Safety and Usefulness of Lumbar Puncture for the Diagnosis and Management of Young-Onset Cognitive Disorders. J Alzheimers Dis 2022; 87:479-488. [PMID: 35275537 DOI: 10.3233/jad-215453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Young-onset cognitive disorders (YOCD) often manifests with complex and atypical presentations due to underlying heterogenous pathologies. Therefore, a biomarker-based evaluation will allow for timely diagnosis and definitive management. OBJECTIVE Here, we evaluated the safety and usefulness of cerebrospinal fluid (CSF) sampling through lumbar puncture (LP) in YOCD patients in a tertiary clinical setting. METHODS Patients with mild cognitive impairment (MCI) and mild dementia with age of onset between 45-64 years were evaluated. Patients underwent magnetic resonance imaging and their medial temporal lobe atrophy (MTA) was rated. LP side-effects and the impact of the CSF findings on diagnosis and management were analyzed. RESULTS 142 patients (53 (37.32%) MCI, 51 (35.92%) dementia of the Alzheimer's disease [DAT] type, and 38 (26.76%) non-AD type dementia) who underwent LP between 2015 to 2021 were analyzed. Using post-LP results and MTA ratings, 74 (52.11%) patients met the AT(N) criteria for AD. 56 (39.44%) patients (28 out of 53 (50.0%) MCI, 12 out of 51 (21.43%) DAT, and 16 out of 38 (28.57%) non-AD dementia) had a change in diagnosis following LP. 13 (9.15%) patients developed side-effects post-LP (11 (84.62%) patients had headache, 1 (7.69%) patient had backache, and 1 (7.69%) patient had headache and backache). 32 (22.54%) patients had a change in management post-LP, 24 (75.0%) had medication changes, 10 (31.30%) had referrals to other specialists, and 3 (9.40%) was referred for clinical trial with disease modifying interventions. CONCLUSION LP is well-tolerated in YOCD and can bring about relevant clinical decisions with regards to the diagnosis and management of this complex clinical condition.
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Affiliation(s)
- See Ann Soo
- Department of Neurology, National Neuroscience Institute, Singapore
| | | | - Jayne Yi Tan
- Department of Neurology, National Neuroscience Institute, Singapore
| | | | | | | | | | - Hui Jin Chiew
- Department of Neurology, National Neuroscience Institute, Singapore
| | - Kok Pin Ng
- Department of Neurology, National Neuroscience Institute, Singapore.,Duke NUS Medical School, Singapore.,Lee Kong Chian School of Medicine-NTU, Singapore
| | - Nagaendran Kandiah
- Department of Neurology, National Neuroscience Institute, Singapore.,Duke NUS Medical School, Singapore.,Lee Kong Chian School of Medicine-NTU, Singapore
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39
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Smith NM, Ford JN, Haghdel A, Glodzik L, Li Y, D’Angelo D, RoyChoudhury A, Wang X, Blennow K, de Leon MJ, Ivanidze J. Statistical Parametric Mapping in Amyloid Positron Emission Tomography. Front Aging Neurosci 2022; 14:849932. [PMID: 35547630 PMCID: PMC9083453 DOI: 10.3389/fnagi.2022.849932] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/21/2022] [Indexed: 12/03/2022] Open
Abstract
Alzheimer's disease (AD), the most common cause of dementia, has limited treatment options. Emerging disease modifying therapies are targeted at clearing amyloid-β (Aβ) aggregates and slowing the rate of amyloid deposition. However, amyloid burden is not routinely evaluated quantitatively for purposes of disease progression and treatment response assessment. Statistical Parametric Mapping (SPM) is a technique comparing single-subject Positron Emission Tomography (PET) to a healthy cohort that may improve quantification of amyloid burden and diagnostic performance. While primarily used in 2-[18F]-fluoro-2-deoxy-D-glucose (FDG)-PET, SPM's utility in amyloid PET for AD diagnosis is less established and uncertainty remains regarding optimal normal database construction. Using commercially available SPM software, we created a database of 34 non-APOE ε4 carriers with normal cognitive testing (MMSE > 25) and negative cerebrospinal fluid (CSF) AD biomarkers. We compared this database to 115 cognitively normal subjects with variable AD risk factors. We hypothesized that SPM based on our database would identify more positive scans in the test cohort than the qualitatively rated [11C]-PiB PET (QR-PiB), that SPM-based interpretation would correlate better with CSF Aβ42 levels than QR-PiB, and that regional z-scores of specific brain regions known to be involved early in AD would be predictive of CSF Aβ42 levels. Fisher's exact test and the kappa coefficient assessed the agreement between SPM, QR-PiB PET, and CSF biomarkers. Logistic regression determined if the regional z-scores predicted CSF Aβ42 levels. An optimal z-score cutoff was calculated using Youden's index. We found SPM identified more positive scans than QR-PiB PET (19.1 vs. 9.6%) and that SPM correlated more closely with CSF Aβ42 levels than QR-PiB PET (kappa 0.13 vs. 0.06) indicating that SPM may have higher sensitivity than standard QR-PiB PET images. Regional analysis demonstrated the z-scores of the precuneus, anterior cingulate and posterior cingulate were predictive of CSF Aβ42 levels [OR (95% CI) 2.4 (1.1, 5.1) p = 0.024; 1.8 (1.1, 2.8) p = 0.020; 1.6 (1.1, 2.5) p = 0.026]. This study demonstrates the utility of using SPM with a "true normal" database and suggests that SPM enhances diagnostic performance in AD in the clinical setting through its quantitative approach, which will be increasingly important with future disease-modifying therapies.
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Affiliation(s)
- Natasha M. Smith
- Department of Radiology and MD Program, Weill Cornell Medicine, New York City, NY, United States
| | - Jeremy N. Ford
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
| | - Arsalan Haghdel
- Department of Radiology and MD Program, Weill Cornell Medicine, New York City, NY, United States
| | - Lidia Glodzik
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Yi Li
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Debra D’Angelo
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, NY, United States
| | - Arindam RoyChoudhury
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, NY, United States
| | - Xiuyuan Wang
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Kaj Blennow
- Department of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Mony J. de Leon
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Jana Ivanidze
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
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40
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Langheinrich T, Kobylecki C, Jones M, Thompson JC, Snowden JS, Hinz R, Pickering-Brown S, Mann D, Roncaroli F, Herholz K, Gerhard A. Amyloid-PET-Positive Patient With bvFTD: Wrong Diagnosis, False Positive Scan, or Copathology? Neurol Clin Pract 2022; 11:e952-e955. [PMID: 34992994 DOI: 10.1212/cpj.0000000000001049] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 11/30/2020] [Indexed: 11/15/2022]
Abstract
A 65-year-old man was referred to a local memory clinic with memory complaints but clinical assessment found no abnormalities. When he presented two years later to our clinic social disinhibition, reduced empathy, poor judgment and hoarding had become obvious. He showed no insight. He had ischemic heart disease and was on preventive treatment. His mother died aged 97 suffering from dementia. Neurological examination was normal. During neuropsychological examination he exhibited verbal and behavioral disinhibition, inattention, emotional blunting and unconcern. He had prominent difficulties in abstraction, set shifting and sequencing with significant impact on memory tests (table1). A clinical diagnosis of behavioral variant FTD (bvFTD) was made. MRI (figure A) showed right more than left-sided temporal atrophy, bilateral frontal and milder parietal atrophy. Fluorodeoxyglucose (FDG)-PET (figure B) demonstrated fronto-temporal hypometabolism. Metabolism in the posterior cingulate was normal. He was homozygous for the APOE ε4 allele and negative for the C9orf72 expansion and mutations in MAPT, GRN, PSEN1, and APP. [18F]-Florbetapir PET (figure C) revealed increased tracer binding in all cortical regions corresponding to a centiloid value of 74%.
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Affiliation(s)
- Tobias Langheinrich
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Christopher Kobylecki
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Matthew Jones
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Jennifer C Thompson
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Julie S Snowden
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Rainer Hinz
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Stuart Pickering-Brown
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - David Mann
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Federico Roncaroli
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Karl Herholz
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Alex Gerhard
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
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41
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Venkataraman AV, Bai W, Whittington A, Myers JF, Rabiner EA, Lingford-Hughes A, Matthews PM. Boosting the diagnostic power of amyloid-β PET using a data-driven spatially informed classifier for decision support. Alzheimers Res Ther 2021; 13:185. [PMID: 34758867 PMCID: PMC8582159 DOI: 10.1186/s13195-021-00910-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 10/02/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Amyloid-β (Aβ) PET has emerged as clinically useful for more accurate diagnosis of patients with cognitive decline. Aβ deposition is a necessary cause or response to the cellular pathology of Alzheimer's disease (AD). Usual clinical and research interpretation of amyloid PET does not fully utilise all information regarding the spatial distribution of signal. We present a data-driven, spatially informed classifier to boost the diagnostic power of amyloid PET in AD. METHODS Voxel-wise k-means clustering of amyloid-positive voxels was performed; clusters were mapped to brain anatomy and tested for their associations by diagnostic category and disease severity with 758 amyloid PET scans from volunteers in the AD continuum from the Alzheimer's Disease Neuroimaging Initiative (ADNI). A machine learning approach based on this spatially constrained model using an optimised quadratic support vector machine was developed for automatic classification of scans for AD vs non-AD pathology. RESULTS This classifier boosted the accuracy of classification of AD scans to 81% using the amyloid PET alone with an area under the curve (AUC) of 0.91 compared to other spatial methods. This increased sensitivity to detect AD by 15% and the AUC by 9% compared to the use of a composite region of interest SUVr. CONCLUSIONS The diagnostic classification accuracy of amyloid PET was improved using an automated data-driven spatial classifier. Our classifier highlights the importance of considering the spatial variation in Aβ PET signal for optimal interpretation of scans. The algorithm now is available to be evaluated prospectively as a tool for automated clinical decision support in research settings.
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Affiliation(s)
- Ashwin V Venkataraman
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK.
- UK Dementia Research Institute at Imperial College London, London, UK.
| | - Wenjia Bai
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
- Data Science Institute, Imperial College London, London, UK
| | | | - James F Myers
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
| | | | - Anne Lingford-Hughes
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, 5th Floor Burlington Danes Building, 160 Du Cane Road, London, W12 0NN, UK
- UK Dementia Research Institute at Imperial College London, London, UK
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Lee YH, Jeon S, Yoo HS, Chung SJ, Jung JH, Baik K, Sohn YH, Lee PH, Yun M, Evans AC, Ye BS. Effect of Alzheimer's Disease and Lewy Body Disease on Metabolic Changes. J Alzheimers Dis 2021; 79:1471-1487. [PMID: 33459638 DOI: 10.3233/jad-201094] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The relationship among amyloid-β (Aβ) deposition on amyloid positron emission tomography (PET), cortical metabolism on 18F-fluoro-2-deoxy-D-glucose (FDG)-PET, and clinical diagnosis has not been elucidated for both Alzheimer's disease (AD) and Lewy body disease (LBD). OBJECTIVE We investigated the patterns of cerebral metabolism according to the presence of AD and LBD. METHODS A total of 178 subjects were enrolled including 42 pure AD, 32 pure LBD, 34 Lewy body variant AD (LBVAD), 15 LBD with amyloid, 26 AD with dementia with Lewy bodies (DLB), and 29 control subjects. Pure AD, LBVAD, and AD with DLB groups had biomarker-supported diagnoses of typical AD, while pure LBD, LBD with amyloid, and AD with DLB groups had biomarker-supported diagnoses of typical LBD. Typical AD and LBD with amyloid showed amyloid-positivity on 18F-florbetaben (FBB) PET, while typical LBD and LBVAD had abnormalities on dopamine transporter PET. We measured regional patterns of glucose metabolism using FDG-PET and evaluated their relationship with AD and LBD. RESULTS Compared with control group, typical AD and typical LBD commonly exhibited hypometabolism in the bilateral temporo-parietal junction, precuneus, and posterior cingulate cortex. Typical AD showed an additional hypometabolism in the entorhinal cortex, while patients with dopamine transporter abnormality-supported diagnosis of LBD showed diffuse hypometabolism that spared the sensory-motor cortex. Although the diffuse hypometabolism in LBD also involved the occipital cortex, prominent occipital hypometabolism was only seen in LBD with amyloid group. CONCLUSION Combining clinical and metabolic evaluations may enhance the diagnostic accuracy of AD, LBD, and mixed disease cases.
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Affiliation(s)
- Yang Hyun Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Seun Jeon
- McGill Center for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Han Soo Yoo
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Jin Ho Jung
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Kyoungwon Baik
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Mijin Yun
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Alan C Evans
- McGill Center for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Byoung Seok Ye
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
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Hayashi H, Kobayashi R, Kawakatsu S, Ohba M, Morioka D, Otani K. Comparison of the decreases in regional cerebral blood flow in the posterior cingulate cortex, precuneus, and parietal lobe between suspected non-Alzheimer's disease pathophysiology and Alzheimer's disease. Psychogeriatrics 2021; 21:716-721. [PMID: 34101304 DOI: 10.1111/psyg.12729] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 05/13/2021] [Accepted: 05/18/2021] [Indexed: 01/23/2023]
Abstract
BACKGROUND Suspected non-Alzheimer's disease pathophysiology (SNAP) shows Alzheimer's disease (AD)-like neurodegeneration; however, amyloid β, which is a biological marker in AD, remains within normal levels. Since the effectiveness of anti-dementia drugs for AD on SNAP is unknown, it is important to distinguish between patients with SNAP and AD. We aimed to compare decreases in regional cerebral blood flow (rCBF) of the posterior cingulate cortex (PCC), precuneus, and parietal lobe critical to AD between SNAP and AD groups using the easy Z-score imaging system in single-photon emission computed tomography (eZIS-SPECT). METHODS We retrospectively analysed eZIS-SPECT data of 13 SNAP and 24 AD patients. The three indicators (severity, extent, and ratio) that distinguished AD patients from healthy controls in previous studies were automatically calculated and were compared between the SNAP and AD groups. Receiver operating characteristic curve analysis and the area under the curve (AUC) were used to evaluate the diagnostic performance of the three indicators of eZIS in discriminating between the two groups. RESULTS The mean values of severity, extent, and ratio were significantly lower in the SNAP group than in the AD group (P = 0.024, P = 0.044, and P = 0.045, respectively). The AUC values for severity, extent, and ratio were 0.668, 0.683, and 0.692, respectively. CONCLUSIONS The present study suggests that SNAP shows milder reduction of rCBF in the PCC, precuneus, and parietal lobe as compared to AD. However, it may be difficult to distinguish between SNAP and AD with the degrees of decrease in rCBF in these regions.
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Affiliation(s)
- Hiroshi Hayashi
- Department of Psychiatry, Yamagata University School of Medicine, Yamagata, Japan
| | - Ryota Kobayashi
- Department of Psychiatry, Yamagata University School of Medicine, Yamagata, Japan
| | - Shinobu Kawakatsu
- Department of Neuropsychiatry, Aizu Medical Center, Fukushima Medical University, Aizuwakamatsu, Japan
| | - Makoto Ohba
- Department of Radiology, Yamagata University Hospital, Yamagata, Japan
| | - Daichi Morioka
- Department of Psychiatry, Yamagata University School of Medicine, Yamagata, Japan
| | - Koichi Otani
- Department of Psychiatry, Yamagata University School of Medicine, Yamagata, Japan
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Bischof GN, Bartenstein P, Barthel H, van Berckel B, Doré V, van Eimeren T, Foster N, Hammes J, Lammertsma AA, Minoshima S, Rowe C, Sabri O, Seibyl J, Van Laere K, Vandenberghe R, Villemagne V, Yakushev I, Drzezga A. Toward a Universal Readout for 18F-Labeled Amyloid Tracers: The CAPTAINs Study. J Nucl Med 2021; 62:999-1005. [PMID: 33712532 DOI: 10.2967/jnumed.120.250290] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 06/09/2020] [Accepted: 10/21/2020] [Indexed: 11/16/2022] Open
Abstract
To date, 3 18F-labeled PET tracers have been approved for assessing cerebral amyloid plaque pathology in the diagnostic workup of suspected Alzheimer disease (AD). Although scanning protocols are relatively similar across tracers, U.S. Food and Drug Administration- and the European Medicines Agency-approved visual rating protocols differ among the 3 tracers. This proof-of-concept study assessed the comparability of the 3 approved visual rating protocols to classify a scan as amyloid-positive or -negative, when applied by groups of experts and nonexperts to all 3 amyloid tracers. Methods: In an international multicenter approach, both expert (n = 4) and nonexpert raters (n = 3) rated scans acquired with 18F-florbetaben, 18F-florbetapir and 18F-flutemetamol. Scans obtained with each tracer were presented for reading according to all 3 approved visual rating protocols. In a randomized order, every single scan was rated by each reader according to all 3 protocols. Raters were blinded for the amyloid tracer used and asked to rate each scan as positive or negative, giving a confidence judgment after each response. Percentage of visual reader agreement, interrater reliability, and agreement of each visual read with binary quantitative measures (fixed SUV ratio threshold for positive or negative scans) were computed. These metrics were analyzed separately for expert and nonexpert groups. Results: No significant differences in using the different approved visual rating protocols were observed across the different metrics of agreement in the group of experts. Nominal differences suggested that the 18F-florbetaben visual rating protocol achieved the highest interrater reliability and accuracy especially under low confidence conditions. For the group of nonexpert raters, significant differences between the different visual rating protocols were observed with overall moderate-to-fair accuracy and with the highest reliability for the 18F-florbetapir visual rating protocol. Conclusion: We observed high interrater agreement despite applying different visual rating protocols for all 18F-labeled amyloid tracers. This implies that the results of the visual interpretation of amyloid imaging can be well standardized and do not depend on the rating protocol in experts. Consequently, the creation of a universal visual assessment protocol for all amyloid imaging tracers appears feasible, which could benefit especially the less-experienced readers.
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Affiliation(s)
- Gérard N Bischof
- University Hospital Cologne, Multimodal Neuroimaging Group, Department of Nuclear Medicine, Cologne, Germany;
| | | | - Henryk Barthel
- University Hospital of Leipzig, Department of Nuclear Medicine, Leipzig, Germany
| | - Bart van Berckel
- Amsterdam University Medical Centers, Location VUmc Radiology and Nuclear Medicine, Amsterdam, The Netherlands
| | - Vincent Doré
- CSIRO Health and Biosecurity, Parkville 3052, Victoria, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Australia
| | - Thilo van Eimeren
- University Hospital Cologne, Multimodal Neuroimaging Group, Department of Nuclear Medicine, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
- German Center of Neurodegenerative Disease (DZNE), Bonn, Germany
| | - Norman Foster
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah
| | - Jochen Hammes
- University Hospital Cologne, Multimodal Neuroimaging Group, Department of Nuclear Medicine, Cologne, Germany
| | - Adriaan A Lammertsma
- Amsterdam University Medical Centers, Location VUmc Radiology and Nuclear Medicine, Amsterdam, The Netherlands
| | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah
| | - Chris Rowe
- CSIRO Health and Biosecurity, Parkville 3052, Victoria, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Australia
| | - Osama Sabri
- University Hospital of Leipzig, Department of Nuclear Medicine, Leipzig, Germany
| | - John Seibyl
- Institute for Neurodegenerative Disorders, New Haven, Connecticut
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, University Hospital Leuven and Department of Imaging and Pathology KU Leuven, Leuven, Belgium
| | - Rik Vandenberghe
- Memory Clinic, University Hospital Leuven and Department of Neurosciences, KU Leuven, Belgium
| | - Victor Villemagne
- CSIRO Health and Biosecurity, Parkville 3052, Victoria, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, Australia
| | - Igor Yakushev
- Department of Nuclear Medicine, Technical University of Munich, Germany; and
| | - Alexander Drzezga
- University Hospital Cologne, Multimodal Neuroimaging Group, Department of Nuclear Medicine, Cologne, Germany
- German Center of Neurodegenerative Disease (DZNE), Bonn, Germany
- Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Forschungszentrum Jülich, Germany
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45
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Vera JH, Eftychiou N, Schuerer M, Rullmann M, Barthel H, Sabri O, Gisslen M, Zetterberg H, Blennow K, O'Brien C, Banerjee S, Dizdarevic S. Clinical Utility of β-Amyloid PET Imaging in People Living With HIV With Cognitive Symptoms. J Acquir Immune Defic Syndr 2021; 87:826-833. [PMID: 33587503 DOI: 10.1097/qai.0000000000002648] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 01/25/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Imaging with β-amyloid (Aβ) positron emission tomography (PET) has the potential to aid the diagnosis of the cause of cognitive impairment affecting people living with HIV (PLWH) when neurodegenerative disorders are considered. We evaluated the clinical utility of [18F]Florbetaben (FBB) in PLWH with cognitive symptoms. METHODS Imaging with FBB PET was performed in 20 patients with cognitive concerns about dementia. Neuropsychological testing, plasma neurofilament light protein, plasma Aβ40, Aβ42, and cerebrospinal fluid Aβ42, tau, and HIV RNA were obtained. FBB PET images were assessed visually by 3 readers blinded to the clinical diagnosis and quantitatively by obtaining a composite cortical to cerebellar cortex standardized uptake value ratio (SUVR). FBB SUVR from 10 age-matched healthy controls was compared with SUVR of PLWH. RESULTS Most participants were men (90%) of white ethnicity (90%) with a median age (interquartile range) of 59 (43-79) years. Median CD4 count was 682 (74-1056). All patients were on combination antiretroviral therapy with plasma and cerebrospinal fluid HIV RNA <40 copies/mL. Fourteen patients had objective cognitive impairment including 2 who met clinical criteria for a diagnosis of dementia. No significant differences in composite SUVRs between PLWH and controls [mean (SD): 1.18 (0.03) vs. 1.16 (0.09); P = 0.37] were observed. Four patients were FBB+ with the highest SUVR in the posterior cingulate, superior temporal, and frontal superior lobe. Amyloid PET results contributed to a change in diagnosis and treatment for 10 patients. CONCLUSION [18F]Florbetaben PET has potential as an adjunctive tool in the diagnosis of PLWH with cognitive impairment, increasing diagnostic certainty and optimizing management.
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Affiliation(s)
- Jaime H Vera
- Centre for Global Health Research, Brighton and Sussex Med School, United Kingdom
| | - Nicholas Eftychiou
- Department of Nuclear Medicine, Brighton and Sussex University Hospitals, United Kingdom
| | - Matti Schuerer
- Department of Nuclear Medicine, University of Leipzig, Germany
| | | | - Henryk Barthel
- Department of Nuclear Medicine, University of Leipzig, Germany
| | - Osama Sabri
- Department of Nuclear Medicine, University of Leipzig, Germany
| | - Magnus Gisslen
- Department of Infectious Diseases, University of Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Sweden
| | - Clara O'Brien
- Department of Neuropsychology, Brighton and Sussex University Hospitals, United Kingdom ; and
| | - Sube Banerjee
- Faculty of Health, University of Plymouth, United Kingdom
| | - Sabina Dizdarevic
- Department of Nuclear Medicine, Brighton and Sussex University Hospitals, United Kingdom
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Knopman DS, Amieva H, Petersen RC, Chételat G, Holtzman DM, Hyman BT, Nixon RA, Jones DT. Alzheimer disease. Nat Rev Dis Primers 2021; 7:33. [PMID: 33986301 PMCID: PMC8574196 DOI: 10.1038/s41572-021-00269-y] [Citation(s) in RCA: 811] [Impact Index Per Article: 270.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/09/2021] [Indexed: 12/21/2022]
Abstract
Alzheimer disease (AD) is biologically defined by the presence of β-amyloid-containing plaques and tau-containing neurofibrillary tangles. AD is a genetic and sporadic neurodegenerative disease that causes an amnestic cognitive impairment in its prototypical presentation and non-amnestic cognitive impairment in its less common variants. AD is a common cause of cognitive impairment acquired in midlife and late-life but its clinical impact is modified by other neurodegenerative and cerebrovascular conditions. This Primer conceives of AD biology as the brain disorder that results from a complex interplay of loss of synaptic homeostasis and dysfunction in the highly interrelated endosomal/lysosomal clearance pathways in which the precursors, aggregated species and post-translationally modified products of Aβ and tau play important roles. Therapeutic endeavours are still struggling to find targets within this framework that substantially change the clinical course in persons with AD.
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Affiliation(s)
| | - Helene Amieva
- Inserm U1219 Bordeaux Population Health Center, University of Bordeaux, Bordeaux, France
| | | | - Gäel Chételat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Ralph A Nixon
- Departments of Psychiatry and Cell Biology, New York University Langone Medical Center, New York University, New York, NY, USA
- NYU Neuroscience Institute, New York University Langone Medical Center, New York University, New York, NY, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
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47
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Ossenkoppele R, Hansson O. Towards clinical application of tau PET tracers for diagnosing dementia due to Alzheimer's disease. Alzheimers Dement 2021; 17:1998-2008. [PMID: 33984177 DOI: 10.1002/alz.12356] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/22/2021] [Accepted: 03/28/2021] [Indexed: 11/07/2022]
Abstract
The recent development of several tau positron emission tomography (PET) tracers represents a major milestone for the Alzheimer's disease (AD) field. These tau PET tracers bind tau neurofibrillary tangles, a key neuropathological characteristic of AD that is tightly linked to synaptic loss, brain atrophy, and cognitive decline. It is notable that these tau PET tracers show low uptake in most non-AD tauopathies and other neurodegenerative disorders, resulting in a diagnostic specificity that is superior to that of amyloid beta (Aβ) PET and biofluid markers, especially at an older age when incidental Aβ pathology is common. Furthermore, tau PET tracers diagnostically outperform widely used MRI markers. Given its excellent diagnostic performance due to the combination of high sensitivity and specificity for detecting tau pathology in AD dementia, we hypothesize that tau PET can become an important diagnostic tool in specialized clinics for the differential diagnosis of dementia syndromes where AD is among the major possible underlying diseases.
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Affiliation(s)
- Rik Ossenkoppele
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Oskar Hansson
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Scheltens P, De Strooper B, Kivipelto M, Holstege H, Chételat G, Teunissen CE, Cummings J, van der Flier WM. Alzheimer's disease. Lancet 2021; 397:1577-1590. [PMID: 33667416 PMCID: PMC8354300 DOI: 10.1016/s0140-6736(20)32205-4] [Citation(s) in RCA: 1620] [Impact Index Per Article: 540.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 08/21/2020] [Accepted: 10/15/2020] [Indexed: 12/16/2022]
Abstract
In this Seminar, we highlight the main developments in the field of Alzheimer's disease. The most recent data indicate that, by 2050, the prevalence of dementia will double in Europe and triple worldwide, and that estimate is 3 times higher when based on a biological (rather than clinical) definition of Alzheimer's disease. The earliest phase of Alzheimer's disease (cellular phase) happens in parallel with accumulating amyloid β, inducing the spread of tau pathology. The risk of Alzheimer's disease is 60-80% dependent on heritable factors, with more than 40 Alzheimer's disease-associated genetic risk loci already identified, of which the APOE alleles have the strongest association with the disease. Novel biomarkers include PET scans and plasma assays for amyloid β and phosphorylated tau, which show great promise for clinical and research use. Multidomain lifestyle-based prevention trials suggest cognitive benefits in participants with increased risk of dementia. Lifestyle factors do not directly affect Alzheimer's disease pathology, but can still contribute to a positive outcome in individuals with Alzheimer's disease. Promising pharmacological treatments are poised at advanced stages of clinical trials and include anti-amyloid β, anti-tau, and anti-inflammatory strategies.
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Affiliation(s)
- Philip Scheltens
- Alzheimer Centre Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands; Department of Neurology, Amsterdam University Medical Centers, Amsterdam, Netherlands; Life Science Partners, Amsterdam, Netherlands.
| | - Bart De Strooper
- VIB Center for Brain and Disease Research, Leuven, Belgium; KU Leuven Department for Neurology, Leuven, Belgium; Dementia Research Institute, University College London, London, UK
| | - Miia Kivipelto
- Division of Clinical Geriatrics and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska University Hospital, Stockholm, Sweden; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland; Ageing and Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
| | - Henne Holstege
- Alzheimer Centre Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands; Department of Clinical Genetics, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Gael Chételat
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Groupement d'Intérêt Public Cyceron, Caen, France
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, University of Nevada, Las Vegas, NV, USA; Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Wiesje M van der Flier
- Alzheimer Centre Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands; Department of Epidemiology and Datascience, Amsterdam University Medical Centers, Amsterdam, Netherlands
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Sergienko VB, Ansheles AA. Nuclear medicine and molecular imaging in clinical practice: yesterday, today and tomorrow. TERAPEVT ARKH 2021; 93:357-362. [DOI: 10.26442/00403660.2021.04.200673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 05/31/2021] [Indexed: 11/22/2022]
Abstract
Over the past 40 years, nuclear medicine has grown to be the largest non-invasive diagnostic and therapeutic industry in the world, playing a pivotal role in various fields and disciplines of clinical practice and contributing to improved quality of life and patient prognosis. Over the first 20 years of the XXI century, the number of radionuclide procedures in the world has increased significantly, primarily due to innovations in radiopharmaceuticals, continuous improvement of the technical properties of equipment and the expansion of the boundaries of multimodal imaging. The review examines the historical and current trends in the development of nuclear medicine in the world and in Russia, including those related to radionuclide diagnostics, therapy and theranostics.
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50
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Stefanovski L, Meier JM, Pai RK, Triebkorn P, Lett T, Martin L, Bülau K, Hofmann-Apitius M, Solodkin A, McIntosh AR, Ritter P. Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain. Front Neuroinform 2021; 15:630172. [PMID: 33867964 PMCID: PMC8047422 DOI: 10.3389/fninf.2021.630172] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 03/08/2021] [Indexed: 12/18/2022] Open
Abstract
Despite the acceleration of knowledge and data accumulation in neuroscience over the last years, the highly prevalent neurodegenerative disease of AD remains a growing problem. Alzheimer's Disease (AD) is the most common cause of dementia and represents the most prevalent neurodegenerative disease. For AD, disease-modifying treatments are presently lacking, and the understanding of disease mechanisms continues to be incomplete. In the present review, we discuss candidate contributing factors leading to AD, and evaluate novel computational brain simulation methods to further disentangle their potential roles. We first present an overview of existing computational models for AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (www.thevirtualbrain.org), an open-source, multiscale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics, and treatment optimization of AD.
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Affiliation(s)
- Leon Stefanovski
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Jil Mona Meier
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Roopa Kalsank Pai
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Paul Triebkorn
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Institut de Neurosciences des Systèmes, Aix Marseille Université, Marseille, France
| | - Tristram Lett
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Leon Martin
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Konstantin Bülau
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Martin Hofmann-Apitius
- Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany
| | - Ana Solodkin
- Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, United States
| | | | - Petra Ritter
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
- Einstein Center for Neuroscience Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
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