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Xu L, Ren C, Jing C, Wang G, Wei H, Kong M, Ba M. Predicting amyloid-PET and clinical conversion in apolipoprotein E ε3/ε3 non-demented individuals with multidimensional factors. Eur J Neurosci 2024; 60:3742-3758. [PMID: 38698692 DOI: 10.1111/ejn.16376] [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: 01/08/2024] [Revised: 04/14/2024] [Accepted: 04/16/2024] [Indexed: 05/05/2024]
Abstract
The apolipoprotein E (APOE) ε4 is a well-established risk factor of amyloid-β (Aβ) in Alzheimer's disease (AD). However, because of the high prevalence of APOE ε3, there may be a large number of people with APOE ε3/ε3 who are non-demented and have Aβ pathology. There are limited studies on assessing Aβ status and clinical conversion in the APOE ε3/ε3 non-demented population. Two hundred and ninety-three non-demented individuals with APOE ε3/ε3 from ADNI database were divided into Aβ-positron emission tomography (Aβ-PET) positivity (+) and Aβ-PET negativity (-) groups using cut-off value of >1.11. Stepwise regression searched for a single or multidimensional clinical variables for predicting Aβ-PET (+), and the receiver operating characteristic curve (ROC) assessed the accuracy of the predictive models. The Cox regression model explored the risk factors associated with clinical conversion to mild cognitive impairment (MCI) or AD. The results showed that the combination of sex, education, ventricle and white matter hyperintensity (WMH) volume can accurately predict Aβ-PET status in cognitively normal (CN), and the combination of everyday cognition study partner total (EcogSPTotal) score, age, plasma p-tau 181 and WMH can accurately predict Aβ-PET status in MCI individuals. EcogSPTotal score were independent predictors of clinical conversion to MCI or AD. The findings may provide a non-invasive and effective tool to improve the efficiency of screening Aβ-PET (+), accelerate and reduce costs of AD trial recruitment in future secondary prevention trials or help to select patients at high risk of disease progression in clinical trials.
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Affiliation(s)
- Lijuan Xu
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Chao Ren
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Chenxi Jing
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Gang Wang
- School of Ulsan Ship and Ocean College, Ludong University, Yantai, China
| | - Hongchun Wei
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Min Kong
- Department of Neurology, Yantaishan Hospital, Yantai City, Shandong, China
| | - Maowen Ba
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
- Yantai Regional Sub Center of National Center for Clinical Medical Research of Neurological Diseases, Shandong, China
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Yan D, Xiong C, Zhong Q, Yao Y, Chen S, Mei X, Zhu S. Identification of late-life depression and mild cognitive impairment via serum surface-enhanced Raman spectroscopy and multivariate statistical analysis. BIOMEDICAL OPTICS EXPRESS 2023; 14:2920-2933. [PMID: 37342695 PMCID: PMC10278622 DOI: 10.1364/boe.487939] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 04/16/2023] [Accepted: 05/09/2023] [Indexed: 06/23/2023]
Abstract
Identification of age-related neuropsychiatric disorders, i.e., late-life depression (LDD) and mild cognitive impairment (MCI) is of imperative clinical value considering the large probability of misdiagnosis and current lack of sensitive, non-invasive and low-cost diagnostic approaches. Here, the serum surface-enhanced Raman spectroscopy (SERS) technique is proposed to identify healthy controls, LDD and MCI patients. Based on SERS peaks analysis, abnormal levels of ascorbic acid, saccharide, cell-free DNA and amino acids in serum are found to be potential biomarkers for identifying LDD and MCI. These biomarkers might be related to oxidative stress, nutritional status, lipid peroxidation and metabolic abnormalities. Moreover, partial least square analysis-linear discriminant analysis (PLS-LDA) is applied to those collected SERS spectra. Finally, the overall identification accuracy is 83.2%, and accuracies are 91.6% and 85.7% for differentiating healthy versus neuropsychiatric disorders and LDD versus MCI, respectively. Thus, the serum SERS combined with multivariate statistical analysis has proved its successful potential for rapid, sensitive and non-invasive identification of healthy, LDD and MCI, which may open new avenues for early diagnosis and timely intervention for age-related neuropsychiatric disorders.
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Affiliation(s)
- Denghui Yan
- Research Institute of Medical and Biological Engineering, Ningbo University, Ningbo 315211, China
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
| | - Changchun Xiong
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China
| | - Qingshan Zhong
- School of Materials Science and Chemical Engineering, Ningbo University, Ningbo 315211, China
| | - Yudong Yao
- Research Institute of Medical and Biological Engineering, Ningbo University, Ningbo 315211, China
| | - Shuo Chen
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110167, China
| | - Xi Mei
- Ningbo Kangning Hospital, Ningbo Key Laboratory of Sleep Medicine, Affiliated Tongyi Hospital of Medical College of Ningbo University, Ningbo 315211, China
| | - Shanshan Zhu
- Research Institute of Medical and Biological Engineering, Ningbo University, Ningbo 315211, China
- Health Science Center, Ningbo University, Ningbo 315211, China
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou 350117, China
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Liu KY, Thambisetty M, Howard R. How can secondary dementia prevention trials of Alzheimer's disease be clinically meaningful? Alzheimers Dement 2022; 19:10.1002/alz.12788. [PMID: 36161763 PMCID: PMC10039957 DOI: 10.1002/alz.12788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 07/06/2022] [Accepted: 08/09/2022] [Indexed: 11/08/2022]
Abstract
After clinical trial failures in symptomatic Alzheimer's disease (AD), our field has moved to earlier intervention in cognitively normal individuals with biomarker evidence of AD. This offers potential for dementia prevention, but mainly low and variable rates of progression to AD dementia reduce the usefulness of trials' data in decision making by potential prescribers. With results from several Phase 3 secondary prevention studies anticipated within the next few years and the Food and Drug Administration's recent endorsement of amyloid beta as a surrogate outcome biomarker for AD clinical trials, it is time to question the clinical significance of changes in biomarkers, adequacy of current trial durations, and criteria for treatment success if cognitively unimpaired patients and their doctors are to meaningfully evaluate the potential value of new agents. We argue for a change of direction toward trial designs that can unambiguously inform clinical decision making about dementia risk and progression.
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Affiliation(s)
- Kathy Y. Liu
- Division of Psychiatry, University College London, London, UK
| | - Madhav Thambisetty
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, USA
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
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Zhu Z, Yang L, Li Z, Liu Q. Cyanidin-3-O-glucoside, cyanidin, and oxidation products of cyanidin protect neuronal function through alleviating inflammation and oxidative damage. J Food Sci 2022; 87:2159-2172. [PMID: 35340035 DOI: 10.1111/1750-3841.16125] [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: 08/12/2021] [Revised: 02/24/2022] [Accepted: 02/27/2022] [Indexed: 11/28/2022]
Abstract
Neurotoxicity seriously affects the normal function of the nervous system. Cyanidin-3-O-glucoside (C3G) is the most abundant anthocyanin widely distributed in plants. Using β-amyloid (Aβ) transgenic Caenorhabditis elegans and cell models, the neuroprotective effect of C3G was examined. The results showed that C3G remarkably suppressed Aβ aggregation, enhanced antioxidant capacity, improved the sensitive capacity towards chemical compounds, and boosted the memory ability of C. elegans. There was no significant difference between preventive and long-term treatment groups at the same dosage of C3G. Given the rapid metabolism and oxidation of C3G in vivo, the antioxidative and anti-inflammatory activities of C3G, the metabolite cyanidin (Cy), oxidation products of Cy (OP), as well as protocatechuic acid (PCA) at the corresponding level in OP were compared by using lipopolysaccharide (LPS)-stimulated BV2 microglia cell model. The results indicated that C3G, Cy, and OP could prevent BV2 cells against LPS-induced inflammation and oxidative damage. There was no significant difference on antioxidative and anti-inflammatory activities among C3G, Cy, and OP at the same level. Notably, PCA at the corresponding concentration in OP exhibited limited antioxidative and anti-inflammatory activities. The results suggested that C3G could exert neuroprotective function through the metabolite Cy and its oxidation products by inhibiting inflammation and oxidative damage, and PCA was not the primary bioactive species in OP. PRACTICAL APPLICATION: This study confirmed the neuroprotection of cyanidin-3-O-glucoside (C3G) in transgenic Caenorhabditis elegans. C3G, its metabolite cyanidin (Cy), and oxidation products of Cy (OP) alleviated both neuroinflammation and oxidative damage. It highlighted that C3G-rich foods could exert neuroprotective potential through their oxidation products, the constitution, and existence of OP in vivo need further study.
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Affiliation(s)
- Zhenzhu Zhu
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing of Jiangsu Province, Nanjing University of Finance and Economics, Nanjing, China
| | - Lipin Yang
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing of Jiangsu Province, Nanjing University of Finance and Economics, Nanjing, China
| | - Zhong Li
- Agricultural and Forestry Products Deep Processing Technology and Equipment Engineering Center of Jiangsu Province, College of Forestry, Nanjing Forestry University, Nanjing, China
| | - Qin Liu
- College of Food Science and Engineering, Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing of Jiangsu Province, Nanjing University of Finance and Economics, Nanjing, China
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Kagerer SM, Schroeder C, van Bergen JMG, Schreiner SJ, Meyer R, Steininger SC, Vionnet L, Gietl AF, Treyer V, Buck A, Pruessmann KP, Hock C, Unschuld PG. Low Subicular Volume as an Indicator of Dementia-Risk Susceptibility in Old Age. Front Aging Neurosci 2022; 14:811146. [PMID: 35309894 PMCID: PMC8926841 DOI: 10.3389/fnagi.2022.811146] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction Hippocampal atrophy is an established Alzheimer’s Disease (AD) biomarker. Volume loss in specific subregions as measurable with ultra-high field magnetic resonance imaging (MRI) may reflect earliest pathological alterations. Methods Data from positron emission tomography (PET) for estimation of cortical amyloid β (Aβ) and high-resolution 7 Tesla T1 MRI for assessment of hippocampal subfield volumes were analyzed in 61 non-demented elderly individuals who were divided into risk-categories as defined by high levels of cortical Aβ and low performance in standardized episodic memory tasks. Results High cortical Aβ and low episodic memory interactively predicted subicular volume [F(3,57) = 5.90, p = 0.018]. The combination of high cortical Aβ and low episodic memory was associated with significantly lower subicular volumes, when compared to participants with high episodic memory (p = 0.004). Discussion Our results suggest that low subicular volume is linked to established indicators of AD risk, such as increased cortical Aβ and low episodic memory. Our data support subicular volume as a marker of dementia-risk susceptibility in old-aged non-demented persons.
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Affiliation(s)
- Sonja M. Kagerer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Clemens Schroeder
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | | | - Simon J. Schreiner
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Rafael Meyer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| | - Stefanie C. Steininger
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Laetitia Vionnet
- Institute for Biomedical Engineering, University of Zurich and ETH Zürich, Zurich, Switzerland
| | - Anton F. Gietl
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Alfred Buck
- Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zürich, Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Neurimmune, Schlieren, Switzerland
| | - Paul G. Unschuld
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Psychogeriatric Medicine, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, University of Zurich and ETH Zürich, Zurich, Switzerland
- Geriatric Psychiatry, Department of Psychiatry, University Hospitals of Geneva, University of Geneva, Geneva, Switzerland
- *Correspondence: Paul G. Unschuld,
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Yu JC, Hlávka JP, Joe E, Richmond FJ, Lakdawalla DN. Impact of non‐binding FDA guidances on primary endpoint selection in Alzheimer's disease trials. ALZHEIMER'S & DEMENTIA: TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2022; 8:e12280. [PMID: 35356740 PMCID: PMC8943597 DOI: 10.1002/trc2.12280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 02/10/2022] [Accepted: 02/11/2022] [Indexed: 11/08/2022]
Abstract
Introduction The U.S. Food and Drug Administration (FDA)'s guidances help describe the agency's current thinking on regulatory issues and serve as a means of informal policymaking that is non‐binding. This study examines the impact of two guidance documents for Alzheimer's disease (AD) trials. The first guidance in 2013 encouraged the use of cognitive/functional endpoints, while the second in 2018 modified such recommendation. Methods Using pivotal trial data, we applied a regression discontinuity in time (RDiT) framework to examine trialist response to these guidance documents. Results were stratified by disease‐modifying therapy (DMT) status, and controlled for disease staging, FDA registration status, and trial phase. Results Among AD DMT trials, annual use of cognitive/functional composite endpoints significantly increased after the 2013 guidance (+12.9%, P < .001), and significantly decreased after the 2018 guidance (–19.9%, P = .022). Discussion Although guidance documents do not set new legal standards or impose binding requirements, our findings indicate they are broadly followed by AD trialists.
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Affiliation(s)
- Jeffrey C. Yu
- School of Pharmacy University of Southern California Los Angeles California USA
- Leonard D. Schaeffer Center for Health Policy & Economics Los Angeles California USA
| | - Jakub P. Hlávka
- Leonard D. Schaeffer Center for Health Policy & Economics Los Angeles California USA
- Sol Price School of Public Policy University of Southern California Los Angeles California USA
| | - Elizabeth Joe
- Keck School of Medicine University of Southern California Los Angeles California USA
| | - Frances J. Richmond
- School of Pharmacy University of Southern California Los Angeles California USA
| | - Darius N. Lakdawalla
- School of Pharmacy University of Southern California Los Angeles California USA
- Leonard D. Schaeffer Center for Health Policy & Economics Los Angeles California USA
- Sol Price School of Public Policy University of Southern California Los Angeles California USA
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Mura T, Coley N, Amieva H, Berr C, Gabelle A, Ousset PJ, Vellas B, Andrieu S. Cognitive decline as an outcome and marker of progression toward dementia, in early preventive trials. Alzheimers Dement 2021; 18:676-687. [PMID: 34482607 DOI: 10.1002/alz.12431] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 05/05/2021] [Accepted: 06/24/2021] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Recent Food and Drug Administration guidance endorses cognitive assessment as a possible primary endpoint for early trials for Alzheimer's disease but emphasizes the need for certainty regarding the relationship with progression to dementia. METHODS We compared the validity of the 2-year change (Y0-Y2) of 11 markers of neuropsychological and functional abilities for the prediction of incident dementia over the following 3 years (Y2-Y5), in 860 subjects aged 70 years or older, who consulted for memory loss and were included in the "GuidAge" prevention trial. RESULTS The Free and Cued Selective Reminding Test-Free Recall (FCSRT-FR) score showed the most predictive 2-year change (area under the curve = 0.72 95% confidence interval = 0.64;0.81). Changes in other subscores of the FCSRT, verbal fluencies tasks, and composite cognitive score were also significantly predictive. Conversely, 2-year change of Mini-Mental State Examination, Trail Making test (TMT)-A, TMT-B, Clinical Dementia Rating Sum of Boxes, and Instrumental Activities of Daily Living scores did not significantly predict occurrence of dementia. CONCLUSION The FCSRT, the Fluency Task, and the composite cognitive score appear to be good cognitive markers of progression toward dementia in early prevention trials.
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Affiliation(s)
- Thibault Mura
- INSERM-University of Toulouse, UMR1027, Toulouse, France.,Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France.,Department of Biostatistics, Clinical Epidemiology, Public Health and Innovation in Methodology (BESPIM), CHU Nîmes, University of Montpellier, Nimes, France
| | - Nicola Coley
- INSERM-University of Toulouse, UMR1027, Toulouse, France.,Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France
| | - Hélène Amieva
- Inserm U1219 Bordeaux Population Health Center, Université de Bordeaux, Bordeaux, France
| | - Claudine Berr
- INSERM-University of Montpellier, U1061, Montpellier, France.,Memory Resources and Research Center, Department of Neurology, Gui de Chauliac University Hospital, Montpellier, France
| | - Audrey Gabelle
- INSERM-University of Montpellier, U1061, Montpellier, France.,Memory Resources and Research Center, Department of Neurology, Gui de Chauliac University Hospital, Montpellier, France
| | - Pierre-Jean Ousset
- INSERM-University of Toulouse, UMR1027, Toulouse, France.,Department of Geriatric Medicine, CHU Toulouse, Gerontopole, Toulouse, France
| | - Bruno Vellas
- INSERM-University of Toulouse, UMR1027, Toulouse, France.,Department of Geriatric Medicine, CHU Toulouse, Gerontopole, Toulouse, France
| | - Sandrine Andrieu
- INSERM-University of Toulouse, UMR1027, Toulouse, France.,Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France
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Stricker NH, Lundt ES, Albertson SM, Machulda MM, Pudumjee SB, Kremers WK, Jack CR, Knopman DS, Petersen RC, Mielke MM. Diagnostic and Prognostic Accuracy of the Cogstate Brief Battery and Auditory Verbal Learning Test in Preclinical Alzheimer's Disease and Incident Mild Cognitive Impairment: Implications for Defining Subtle Objective Cognitive Impairment. J Alzheimers Dis 2021; 76:261-274. [PMID: 32538841 DOI: 10.3233/jad-200087] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND There are detectable cognitive differences in cognitively unimpaired (CU) individuals with preclinical Alzheimer's disease (AD). OBJECTIVE To determine whether cross-sectional performance on the Cogstate Brief Battery (CBB) and Auditory Verbal Learning Test (AVLT) could identify 1) CU participants with preclinical AD defined by neuroimaging biomarkers of amyloid and tau, and 2) incident mild cognitive impairment (MCI)/dementia. METHOD CU participants age 50+ were eligible if they had 1) amyloid (A) and tau (T) imaging within two years of their baseline CBB or 2) at least one follow-up visit. AUROC analyses assessed the ability of measures to differentiate groups. We explored the frequency of cross-sectional subtle objective cognitive impairment (sOBJ) defined as performance ≤-1 SD on CBB Learning/Working Memory Composite (Lrn/WM) or AVLT delayed recall using age-corrected normative data. RESULTS A+T+ (n = 33, mean age 79.5) and A+T- (n = 61, mean age 77.8) participants were older than A-T- participants (n = 146, mean age 66.3), and comparable on sex and education. Lrn/WM did not differentiate A + T+or A+T- from A-T- participants. AVLT differentiated both A+T+ and A+T- from A-T- participants; 45% of A+T+ and 25% of A+T- participants met sOBJ criteria. The follow-up cohort included 150 CU individuals who converted to MCI/dementia and 450 age, sex, and education matched controls. Lrn/WM and AVLT differentiated between stable and converter CU participants. CONCLUSION Among CU participants, AVLT helped differentiate A+T+ and A+T- from A-T- participants. The CBB did not differentiate biomarker subgroups, but showed potential for predicting incident MCI/dementia. Results inform future definitions of sOBJ.
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Affiliation(s)
- Nikki H Stricker
- Department of Psychiatry and Psychology, Division of Neurocognitive Disorders, Mayo Clinic, Rochester, MN, USA
| | - Emily S Lundt
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Sabrina M Albertson
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Division of Neurocognitive Disorders, Mayo Clinic, Rochester, MN, USA
| | - Shehroo B Pudumjee
- Department of Psychiatry and Psychology, Division of Neurocognitive Disorders, Mayo Clinic, Rochester, MN, USA
| | - Walter K Kremers
- Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Michelle M Mielke
- Department of Neurology, Mayo Clinic, Rochester, MN, USA.,Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
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Fischer FU, Wolf D, Tüscher O, Fellgiebel A. Structural Network Efficiency Predicts Resilience to Cognitive Decline in Elderly at Risk for Alzheimer's Disease. Front Aging Neurosci 2021; 13:637002. [PMID: 33692682 PMCID: PMC7937862 DOI: 10.3389/fnagi.2021.637002] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 01/25/2021] [Indexed: 01/10/2023] Open
Abstract
Introduction: Functional imaging studies have demonstrated the recruitment of additional neural resources as a possible mechanism to compensate for age and Alzheimer's disease (AD)-related cerebral pathology, the efficacy of which is potentially modulated by underlying structural network connectivity. Additionally, structural network efficiency (SNE) is associated with intelligence across the lifespan, which is a known factor for resilience to cognitive decline. We hypothesized that SNE may be a surrogate of the physiological basis of resilience to cognitive decline in elderly persons without dementia and with age- and AD-related cerebral pathology.Methods: We included 85 cognitively normal elderly subjects or mild cognitive impairment (MCI) patients submitted to baseline diffusion imaging, liquor specimens, amyloid-PET and longitudinal cognitive assessments. SNE was calculated from baseline MRI scans using fiber tractography and graph theory. Mixed linear effects models were estimated to investigate the association of higher resilience to cognitive decline with higher SNE and the modulation of this association by increased cerebral amyloid, liquor tau or WMHV. Results: For the majority of cognitive outcome measures, higher SNE was associated with higher resilience to cognitive decline (p-values: 0.011-0.039). Additionally, subjects with higher SNE showed more resilience to cognitive decline at higher cerebral amyloid burden (p-values: <0.001-0.036) and lower tau levels (p-values: 0.002-0.015).Conclusion: These results suggest that SNE to some extent may quantify the physiological basis of resilience to cognitive decline most effective at the earliest stages of AD, namely at increased amyloid burden and before increased tauopathy.
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Affiliation(s)
- Florian U. Fischer
- Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Johannes Gutenberg University Mainz, Mainz, Germany
- Center for Mental Health in Old Age, Landeskrankenhaus (AöR), Mainz, Germany
| | - Dominik Wolf
- Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Johannes Gutenberg University Mainz, Mainz, Germany
- Center for Mental Health in Old Age, Landeskrankenhaus (AöR), Mainz, Germany
| | - Oliver Tüscher
- Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Johannes Gutenberg University Mainz, Mainz, Germany
- Leibniz Institute for Resilience Research (LIR), Mainz, Germany
| | - Andreas Fellgiebel
- Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Johannes Gutenberg University Mainz, Mainz, Germany
- Center for Mental Health in Old Age, Landeskrankenhaus (AöR), Mainz, Germany
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Gao Z, Li Z, Deng R, Liu Q, Xiao Q, Han J, Pu C, Zhang Y. Dexmedetomidine improves postoperative neurocognitive disorder after cardiopulmonary bypass in rats. Neurol Res 2021; 43:164-172. [PMID: 33076786 DOI: 10.1080/01616412.2020.1833154] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 09/30/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE To investigate whether dexmedetomidine can improve postoperative neurocognitive function after cardiopulmonary bypass in rats. METHODS A total of 45 male Sprague Dawley (SD) rats were randomly divided into sham group, control group, and dexmedetomidine (Dex) group. The rats in the sham group received skin excision and blood vessel ligation treatment, rats in the control group received cardiopulmonary bypass (CPB), and rats in the Dex group received CPB and Dex treatment. Morris water maze test and open-field tests were used to evaluate the rats' cognition. The expression of inflammatory mediators in the rats' central and peripheral regions, Aβ and Tau in the hippocampus and prefrontal cortex, and apoptosis in brain tissue were measured. RESULTS The CPB model rats were found to have significantly decreased cognitive function, increased expression of caspase-3 and Bax in the prefrontal cortex and hippocampus DG, increased apoptosis and activated microglia, and increased plasma levels of TNF-α, IL-6, and TNF-α. Dexmedetomidine reduced apoptosis in the prefrontal cortex and hippocampus DG region of rats, decreased the expression of caspase-3 and bax, inhibited microglia activation in the prefrontal cortex and hippocampus DG region of rats, and decreased the plasma levels of IL-β, IL-6, and TNF-α. CONCLUSIONS Dexmedetomidine plays a neuroprotective role by inhibiting inflammation, apoptosis, and microglia activation in the prefrontal cortex and hippocampal DG region, and attenuates the cognitive deficit identified in the control group.
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Affiliation(s)
- Zhiwei Gao
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
| | - Zhengfen Li
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
| | - Rui Deng
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
| | - Qing Liu
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
| | - Qiuxia Xiao
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
| | - Jiang Han
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
| | - Cuixia Pu
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
| | - Ying Zhang
- Department of Anesthesiology, Hospital (T.C.M)) Affiliated to Southwest Medical University, Luzhou, Sichuan, China
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11
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Insel PS, Donohue MC, Berron D, Hansson O, Mattsson-Carlgren N. Time between milestone events in the Alzheimer's disease amyloid cascade. Neuroimage 2020; 227:117676. [PMID: 33359337 DOI: 10.1016/j.neuroimage.2020.117676] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 10/29/2020] [Accepted: 12/15/2020] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVE Estimate the time-course of the spread of key pathological markers and the onset of cognitive dysfunction in Alzheimer's disease. METHODS In a cohort of 335 older adults, ranging in cognitive functioning, we estimated the time of initial changes of Aβ, tau, and decreases in cognition with respect to the time of Aβ-positivity. RESULTS Small effect sizes of change in CSF Aβ42 and regional Aβ PET were estimated to occur several decades before Aβ-positivity. Increases in CSF tau occurred 7-8 years before Aβ-positivity. Temporoparietal tau PET showed increases 4-5 years before Aβ-positivity. Subtle cognitive dysfunction was observed 4-6 years before Aβ-positivity. CONCLUSIONS Increases in tau and cognitive dysfunction occur years before commonly used thresholds for Aβ-positivity. Explicit estimates of the time for these events provide a clearer picture of the time-course of the amyloid cascade and identify potential windows for specific treatments.
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Affiliation(s)
- Philip S Insel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, United States.
| | - Michael C Donohue
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, United States
| | - David Berron
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden; Department of Neurology, Skåne University Hospital, Lund, Sweden; Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
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12
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Rabin JS, Neal TE, Nierle HE, Sikkes SAM, Buckley RF, Amariglio RE, Papp KV, Rentz DM, Schultz AP, Johnson KA, Sperling RA, Hedden T. Multiple markers contribute to risk of progression from normal to mild cognitive impairment. NEUROIMAGE-CLINICAL 2020; 28:102400. [PMID: 32919366 PMCID: PMC7491146 DOI: 10.1016/j.nicl.2020.102400] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 08/17/2020] [Accepted: 08/25/2020] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To identify a parsimonious set of markers that optimally predicts subsequent clinical progression from normal to mild cognitive impairment (MCI). METHODS 250 clinically normal adults (mean age = 73.6 years, SD = 6.0) from the Harvard Aging Brain Study were assessed at baseline on a wide set of markers, including magnetic resonance imaging markers of gray matter thickness and volume, white matter lesions, fractional anisotropy, resting state functional connectivity, positron emission tomography markers of glucose metabolism and β-amyloid (Aβ) burden, and a measure of vascular risk. Participants were also tested annually on a battery of clinical and cognitive tests (median follow-up = 5.0 years, SD = 1.66). We applied least absolute shrinkage and selection operator (LASSO) Cox models to determine the minimum set of non-redundant markers that predicts subsequent clinical progression from normal to MCI, adjusting for age, sex, and education. RESULTS 23 participants (9.2%) progressed to MCI over the study period (mean years of follow-up to diagnosis = 3.96, SD = 1.89). Progression was predicted by several brain markers, including reduced entorhinal thickness (hazard ratio, HR = 1.73), greater Aβ burden (HR = 1.58), lower default network connectivity (HR = 1.42), and smaller hippocampal volume (HR = 1.30). When cognitive test scores were added to the model, the aforementioned neuroimaging markers remained significant and lower striatum volume as well as lower scores on baseline memory and processing speed tests additionally contributed to progression. CONCLUSION Among a large set of brain, vascular and cognitive markers, a subset of markers independently predicted progression from normal to MCI. These markers may enhance risk stratification by identifying clinically normal individuals who are most likely to develop clinical symptoms and would likely benefit most from therapeutic intervention.
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Affiliation(s)
- Jennifer S Rabin
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Harquail Centre for Neuromodulation and Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON M4N 3M5, Canada; Department of Medicine (Neurology), University of Toronto, Toronto, ON M5S 3H2, Canada
| | - Taylor E Neal
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hannah E Nierle
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sietske A M Sikkes
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit, The Netherlands; Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA
| | - Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Florey Institutes of Neuroscience and Mental Health, Melbourne and Melbourne School of Psychological Science, University of Melbourne, Melbourne, Australia; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Rebecca E Amariglio
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Kathryn V Papp
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Dorene M Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Keith A Johnson
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA; Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital, Boston, MA 02144, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02144, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA 02115, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA
| | - Trey Hedden
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA.
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Meng SX, Wang B, Li WT. Intermittent hypoxia improves cognition and reduces anxiety-related behavior in APP/PS1 mice. Brain Behav 2020; 10:e01513. [PMID: 31877583 PMCID: PMC7010588 DOI: 10.1002/brb3.1513] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 09/20/2019] [Accepted: 11/08/2019] [Indexed: 01/09/2023] Open
Abstract
INTRODUCTION Although hypoxia can exacerbate symptoms of various neurological disorders, accumulating evidence has indicated that intermittent hypoxia (IH) may exert protective effects against brain diseases. In the present study, we aimed to determine whether exposure to IH exerts beneficial effects in a transgenic murine model of Alzheimer's disease (AD). Because comorbid anxiety is prevalent among patients with AD, we explored the effects of IH on anxiety-like behaviors and associated factors in APP/PS1 mice. METHODS APP/PS1 mice were subjected to IH for two weeks. We assessed cognitive performance and anxiety-related behavior using standard behavioral assessments. Amyloid beta (Aβ) levels in the hippocampus were assessed using immunofluorescence and enzyme-linked immunosorbent assays (ELISA). We also assessed cell morphology and brain-derived neurotrophic factor (BDNF) expression in the hippocampus. RESULTS Exposure to IH significantly increased cognitive performance and decreased anxiety-related behaviors in APP/PS1 mice. Immunofluorescence and ELISA results revealed that IH pretreatment significantly lowered Aβ levels in the cortex and hippocampus. Morphological studies validated the neuroprotective effect of IH exposure on hippocampal neurogenesis. Molecular studies revealed IH-enhanced BDNF expression and inhibition of apoptosis-related protein expression in the hippocampus of APP/PS1 mice. CONCLUSIONS Our study demonstrates that IH improves cognition and reduces anxiety in a murine model of AD. Thus, further studies are required to determine whether IH can be used as a preventive/adjuvant therapy in patients with AD.
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Affiliation(s)
- Sheng-Xi Meng
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Bing Wang
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Wen-Tao Li
- Department of Vasculocardiology, Municipal Hospital of Traditional Chinese Medicine Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
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Svenningsson AL, Stomrud E, Insel PS, Mattsson N, Palmqvist S, Hansson O. β-amyloid pathology and hippocampal atrophy are independently associated with memory function in cognitively healthy elderly. Sci Rep 2019; 9:11180. [PMID: 31371787 PMCID: PMC6671981 DOI: 10.1038/s41598-019-47638-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 07/11/2019] [Indexed: 11/25/2022] Open
Abstract
The independent effects of different brain pathologies on age-dependent cognitive decline are unclear. We examined this in 300 cognitively unimpaired elderly individuals from the BioFINDER study. Using cognition as outcome we studied the effects of cerebrospinal fluid biomarkers for amyloid-β (Aβ42/40), neuroinflammation (YKL-40), and neurodegeneration and tau pathology (T-tau and P-tau) as well as MRI measures of white-matter lesions, hippocampal volume (HV), and regional cortical thickness. We found that Aβ positivity and HV were independently associated with memory. Results differed depending on age, with memory being associated with HV (but not Aβ) in older participants (73.3–88.4 years), and with Aβ (but not HV) in relatively younger participants (65.2–73.2 years). This indicates that Aβ and atrophy are independent contributors to memory variability in cognitively healthy elderly and that Aβ mainly affects memory in younger elderly individuals. With advancing age, the effect of brain atrophy overshadows the effect of Aβ on memory function.
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Affiliation(s)
- Anna L Svenningsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund/Malmö, Sweden. .,Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund/Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Philip S Insel
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund/Malmö, Sweden
| | - Niklas Mattsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund/Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund/Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund/Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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15
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Insel PS, Weiner M, Mackin RS, Mormino E, Lim YY, Stomrud E, Palmqvist S, Masters CL, Maruff PT, Hansson O, Mattsson N. Determining clinically meaningful decline in preclinical Alzheimer disease. Neurology 2019; 93:e322-e333. [PMID: 31289148 PMCID: PMC6669933 DOI: 10.1212/wnl.0000000000007831] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 03/17/2019] [Indexed: 11/15/2022] Open
Abstract
Objective To determine the time required for a preclinical Alzheimer disease population to decline in a meaningful way, use estimates of decline to update previous clinical trial design assumptions, and identify factors that modify β-amyloid (Aβ)–related decline. Methods In 1,120 cognitively unimpaired individuals from 3 international cohorts, we estimated the relationship between Aβ status and longitudinal changes across multiple cognitive domains and assessed interactions between Aβ and baseline factors. Power analyses were performed to explore sample size as a function of treatment effect. Results Cognitively unimpaired Aβ+ participants approach mild cognitive impairment (MCI) levels of performance 6 years after baseline, on average. Achieving 80% power in a simulated 4-year treatment trial, assuming a 25% treatment effect, required 2,000 participants/group. Multiple factors interacted with Aβ to predict cognitive decline; however, these findings were all cohort-specific. Despite design differences across the cohorts, with large sample sizes and sufficient follow-up time, the Aβ+ groups declined consistently on cognitive composite measures. Conclusions A preclinical AD population declines to the cognitive performance of an early MCI population in 6 years. Slowing this rate of decline by 40%–50% delays clinically relevant impairment by 3 years—a potentially meaningful treatment effect. However, assuming a 40%–50% drug effect highlights the difficulties in preclinical AD trial design, as a more commonly assumed treatment effect of 25% results in a required sample size of 2,000/group. Designers of preclinical AD treatment trials need to prepare for larger and longer trials than are currently being considered. Interactions with Aβ status were inconsistent and not readily generalizable.
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Affiliation(s)
- Philip S Insel
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia.
| | - Michael Weiner
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - R Scott Mackin
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Elizabeth Mormino
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Yen Ying Lim
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Erik Stomrud
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Sebastian Palmqvist
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Colin L Masters
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Paul T Maruff
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Oskar Hansson
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
| | - Niklas Mattsson
- From the Center for Imaging of Neurodegenerative Diseases (M.W., R.S.M.), Department of Veterans Affairs Medical Center; Departments of Radiology and Biomedical Imaging (P.S.I., M.W.) and Psychiatry (P.S.I., R.S.M.), University of California, San Francisco; Clinical Memory Research Unit, Faculty of Medicine (P.S.I., E.S., S.P., O.H., N.M.), Memory Clinic (E.S., S.P., O.H.) and Department of Neurology (N.M.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.), Lund University, Sweden; Department of Neurology and Neurological Sciences (E.M.), Stanford University, CA; The Florey Institute (Y.Y.L., C.L.M., P.T.M.), The University of Melbourne; and CogState (P.T.M.), Melbourne, Australia
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR, Jagust W, Morris JC, Petersen RC, Saykin AJ, Shaw LM, Toga AW, Trojanowski JQ. Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative. Alzheimers Dement 2018; 15:106-152. [PMID: 30321505 DOI: 10.1016/j.jalz.2018.08.005] [Citation(s) in RCA: 231] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Accepted: 08/21/2018] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late-onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. METHODS We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news-publications/publications/). RESULTS (1) Data-driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β-Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a "typical AD" subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. DISCUSSION ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.
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Affiliation(s)
- Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Hanseeuw BJ, Betensky RA, Mormino EC, Schultz AP, Sepulcre J, Becker JA, Jacobs HIL, Buckley RF, LaPoint MR, Vannini P, Donovan NJ, Chhatwal JP, Marshall GA, Papp KV, Amariglio RE, Rentz DM, Sperling RA, Johnson KA. PET staging of amyloidosis using striatum. Alzheimers Dement 2018; 14:1281-1292. [PMID: 29792874 PMCID: PMC6219621 DOI: 10.1016/j.jalz.2018.04.011] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Revised: 02/06/2018] [Accepted: 04/09/2018] [Indexed: 01/13/2023]
Abstract
INTRODUCTION Amyloid positron emission tomography (PET) data are commonly expressed as binary measures of cortical deposition. However, not all individuals with high cortical amyloid will experience rapid cognitive decline. Motivated by postmortem data, we evaluated a three-stage PET classification: low cortical; high cortical, low striatal; and high cortical, high striatal amyloid; hypothesizing this model could better reflect Alzheimer's dementia progression than a model based only on cortical measures. METHODS We classified PET data from 1433 participants (646 normal, 574 mild cognitive impairment, and 213 AD), explored the successive involvement of cortex and striatum using 3-year follow-up PET data, and evaluated the associations between PET stages, hippocampal volumes, and cognition. RESULTS Follow-up data indicated that PET detects amyloid first in cortex and then in striatum. Our three-category staging including striatum better predicted hippocampal volumes and subsequent cognition than a three-category staging including only cortical amyloid. DISCUSSION PET can evaluate amyloid expansion from cortex to subcortex. Using striatal signal as a marker of advanced amyloidosis may increase predictive power in Alzheimer's dementia research.
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Affiliation(s)
- Bernard J Hanseeuw
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Neurology, Cliniques Universitaires Saint-Luc, Institute of Neurosciences, Université Catholique de Louvain, Brussels, Belgium; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Rebecca A Betensky
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Elizabeth C Mormino
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jorge Sepulcre
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - John A Becker
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Heidi I L Jacobs
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands
| | - Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Molly R LaPoint
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Patrizia Vannini
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nancy J Donovan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Gad A Marshall
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kathryn V Papp
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rebecca E Amariglio
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Dorene M Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Keith A Johnson
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, Charlestown, MA, USA; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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18
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Aisen P, Touchon J, Amariglio R, Andrieu S, Bateman R, Breitner J, Donohue M, Dunn B, Doody R, Fox N, Gauthier S, Grundman M, Hendrix S, Ho C, Isaac M, Raman R, Rosenberg P, Schindler R, Schneider L, Sperling R, Tariot P, Welsh-Bohmer K, Weiner M, Vellas B. EU/US/CTAD Task Force: Lessons Learned from Recent and Current Alzheimer's Prevention Trials. JPAD-JOURNAL OF PREVENTION OF ALZHEIMERS DISEASE 2018; 4:116-124. [PMID: 29186281 DOI: 10.14283/jpad.2017.13] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
At a meeting of the EU/US/Clinical Trials in Alzheimer's Disease (CTAD) Task Force in December 2016, an international group of investigators from industry, academia, and regulatory agencies reviewed lessons learned from ongoing and planned prevention trials, which will help guide future clinical trials of AD treatments, particularly in the pre-clinical space. The Task Force discussed challenges that need to be addressed across all aspects of clinical trials, calling for innovation in recruitment and retention, infrastructure development, and the selection of outcome measures. While cognitive change provides a marker of disease progression across the disease continuum, there remains a need to identify the optimal assessment tools that provide clinically meaningful endpoints. Patient- and informant-reported assessments of cognition and function may be useful but present additional challenges. Imaging and other biomarkers are also essential to maximize the efficiency of and the information learned from clinical trials.
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Affiliation(s)
- P Aisen
- PPaul Aisen, Alzheimer's Therapeutic Research Institute (ATRI), Keck School of Medicine, University of Southern California, San Diego, CA, USA,
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19
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Baker JE, Lim YY, Jaeger J, Ames D, Lautenschlager NT, Robertson J, Pietrzak RH, Snyder PJ, Villemagne VL, Rowe CC, Masters CL, Maruff P. Episodic Memory and Learning Dysfunction Over an 18-Month Period in Preclinical and Prodromal Alzheimer’s Disease. J Alzheimers Dis 2018; 65:977-988. [DOI: 10.3233/jad-180344] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Jenalle E. Baker
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- Cooperative Research Centre for Mental Health, Carlton, Victoria, Australia
| | - Yen Ying Lim
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Judith Jaeger
- CognitionMetrics, LLC., Wilmington, DE, USA
- Albert Einstein College of Medicine, Bronx, NY, USA
| | - David Ames
- National Ageing Research Institute, Parkville, VIC, Australia
- Department of Psychiatry, Academic Unit for Psychiatry of Old Age, The University of Melbourne, St. George’s Hospital, Kew, VIC, Australia
| | - Nicola T. Lautenschlager
- Department of Psychiatry, Academic Unit for Psychiatry of Old Age, The University of Melbourne, St. George’s Hospital, Kew, VIC, Australia
| | - Joanne Robertson
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Robert H. Pietrzak
- U.S. Department of Veterans Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Peter J. Snyder
- Ryan Institute for Neuroscience, University of Rhode Island, Kingston, RI, USA
| | - Victor L. Villemagne
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Christopher C. Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Paul Maruff
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
- Cogstate Ltd., Melbourne, VIC, Australia
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20
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Knopman DS, Lundt ES, Therneau TM, Vemuri P, Lowe VJ, Kantarci K, Gunter JL, Senjem ML, Mielke MM, Machulda MM, Roberts RO, Boeve BF, Jones DT, Petersen RC, Jack CR. Joint associations of β-amyloidosis and cortical thickness with cognition. Neurobiol Aging 2018; 65:121-131. [PMID: 29471214 PMCID: PMC5871603 DOI: 10.1016/j.neurobiolaging.2018.01.017] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Revised: 01/12/2018] [Accepted: 01/22/2018] [Indexed: 01/24/2023]
Abstract
In 1164 cognitively unimpaired persons, aged 50-95 years, from the population-based Mayo Clinic Study of Aging, we examined the relationships of baseline cognition and cognitive changes across the full range of cortical thickness of an Alzheimer signature region of interest and global β-amyloid levels measured by Pittsburgh compound B positron emission tomography (PIB PET) standardized uptake value ratio (SUVR). In machine-learning models accounting for both biomarkers simultaneously, worsening biomarker values were additive and associated with lower baseline global cognition and greater subsequent decline in global cognition. Associations between Alzheimer's disease signature cortical thickness or PIB PET β-amyloid SUVR and baseline cognition were mainly linear. Lower Alzheimer's disease signature cortical thickness values across the entire range of thickness predicted future decline in global cognitive scores, demonstrating its close relationship to cognitive functioning. PIB PET β-amyloid SUVR also predicted cognitive decline across its full range, even when cortical thickness was accounted for. PIB PET β-amyloid's relationship to cognitive decline was nonlinear, more prominent at lower β-amyloid levels and less prominent at higher β-amyloid levels.
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Affiliation(s)
- David S Knopman
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA.
| | - Emily S Lundt
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Terry M Therneau
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Prashanthi Vemuri
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Val J Lowe
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Kejal Kantarci
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Jeffrey L Gunter
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Mary M Machulda
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Psychology, Department of Psychiatry, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Rosebud O Roberts
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Bradley F Boeve
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA; Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic and Foundation, Rochester, MN, USA
| | - Clifford R Jack
- Mayo Clinic Alzheimer's Disease Research Center, Mayo Clinic and Foundation, Rochester, MN, USA; Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA
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21
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22
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IVKIN АА, GRIGORIEV EV, SHUKEVICH DL. DIAGNOSTICS OF COGNITIVE DYSFUNCTION IN PATIENTS IN THE INTENSIVE CARE WARDS. MESSENGER OF ANESTHESIOLOGY AND RESUSCITATION 2018. [DOI: 10.21292/2078-5658-2018-15-3-47-55] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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23
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Bertens D, Tijms BM, Vermunt L, Prins ND, Scheltens P, Visser PJ. The effect of diagnostic criteria on outcome measures in preclinical and prodromal Alzheimer's disease: Implications for trial design. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2017; 3:513-523. [PMID: 29124109 PMCID: PMC5671625 DOI: 10.1016/j.trci.2017.08.005] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Introduction We investigated the influence of different inclusion criteria for preclinical and prodromal Alzheimer's disease (AD) on changes in biomarkers and cognitive markers and on trial sample size estimates. Methods We selected 522 cognitively normal subjects and 872 subjects with mild cognitive impairment from the Alzheimer's Disease Neuroimaging Initiative study. Compared inclusion criteria were (1) preclinical or prodromal AD (amyloid marker abnormal); (2) preclinical or prodromal AD stage-1 (amyloid marker abnormal, injury marker normal); and (3) preclinical or prodromal AD stage-2 (amyloid and injury markers abnormal). Outcome measures were amyloid, neuronal injury, and cognitive markers. Results In both subjects with preclinical and prodromal AD stage-2, inclusion criteria resulted in the largest observed decline in brain volumetric measures on magnetic resonance imaging and cognitive markers. Discussion Inclusion criteria influence the observed rate of worsening in outcome measures. This has implications for trial design.
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Affiliation(s)
- Daniela Bertens
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Betty M Tijms
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Lisa Vermunt
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Niels D Prins
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands.,Alzheimer Research Center, Amsterdam The Netherlands
| | - Philip Scheltens
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Centre, Department of Neurology, VU University Medical Centre, Amsterdam, The Netherlands.,Alzheimer Centre, School for Mental Health and Neuroscience (MHeNS), University Medical Centre, Maastricht, The Netherlands
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24
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Donohue MC, Sperling RA, Petersen R, Sun CK, Weiner MW, Aisen PS. Association Between Elevated Brain Amyloid and Subsequent Cognitive Decline Among Cognitively Normal Persons. JAMA 2017; 317:2305-2316. [PMID: 28609533 PMCID: PMC5736301 DOI: 10.1001/jama.2017.6669] [Citation(s) in RCA: 276] [Impact Index Per Article: 39.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
IMPORTANCE Among cognitively normal individuals, elevated brain amyloid (defined by cerebrospinal fluid assays or positron emission tomography regional summaries) can be related to risk for later Alzheimer-related cognitive decline. OBJECTIVE To characterize and quantify the risk for Alzheimer-related cognitive decline among cognitively normal individuals with elevated brain amyloid. DESIGN, SETTING, AND PARTICIPANTS Exploratory analyses were conducted with longitudinal cognitive and biomarker data from 445 cognitively normal individuals in the United States and Canada. Participants were observed from August 23, 2005, to June 7, 2016, for a median of 3.1 years (interquartile range, 2.0-4.2 years; maximum follow-up, 10.3 years) as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). EXPOSURES Individuals were classified at baseline as having normal (n = 243) or elevated (n = 202) brain amyloid using positron emission tomography amyloid imaging or a cerebrospinal fluid assay of amyloid β. MAIN OUTCOMES AND MEASURES Outcomes included scores on the Preclinical Alzheimer Cognitive Composite (PACC; a sum of 4 baseline standardized z scores, which decreases with worse performance), Mini-Mental State Examination (MMSE; 0 [worst] to 30 [best] points), Clinical Dementia Rating Sum of Boxes (CDR-Sum of Boxes; 0 [best] to 18 [worst] points), and Logical Memory Delayed Recall (0 [worst] to 25 [best] story units). RESULTS Among the 445 participants (243 with normal amyloid, 202 with elevated amyloid), mean (SD) age was 74.0 (5.9) years, mean education was 16.4 (2.7) years, and 52% were women. The mean score for PACC at baseline was 0.00 (2.60); for MMSE, 29.0 (1.2); for CDR-Sum of Boxes, 0.04 (0.14); and for Logical Memory Delayed Recall, 13.1 (3.3). Compared with the group with normal amyloid, those with elevated amyloid had worse mean scores at 4 years on the PACC (mean difference, 1.51 points [95% CI, 0.94-2.10]; P < .001), MMSE (mean difference, 0.56 points [95% CI, 0.32-0.80]; P < .001), and CDR-Sum of Boxes (mean difference, 0.23 points [95% CI, 0.08-0.38]; P = .002). For Logical Memory Delayed Recall, between-group score was not statistically significant at 4 years (mean difference, 0.73 story units [95% CI, -0.02 to 1.48]; P = .056). CONCLUSIONS AND RELEVANCE Exploratory analyses of a cognitively normal cohort followed up for a median of 3.1 years suggest that elevation in baseline brain amyloid level, compared with normal brain amyloid level, was associated with higher likelihood of cognitive decline, although the findings are of uncertain clinical significance. Further research is needed to assess the clinical importance of these differences and measure longer-term associations.
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Affiliation(s)
- Michael C Donohue
- Alzheimer's Therapeutic Research Institute, Department of Neurology, University of Southern California, San Diego
| | - Reisa A Sperling
- Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts3Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts4Massachusetts General Hospital, Boston
| | | | - Chung-Kai Sun
- Alzheimer's Therapeutic Research Institute, Department of Neurology, University of Southern California, San Diego
| | - Michael W Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California-San Francisco7San Francisco VA Medical Center, San Francisco, California
| | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, Department of Neurology, University of Southern California, San Diego
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25
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Schindler SE, Jasielec MS, Weng H, Hassenstab JJ, Grober E, McCue LM, Morris JC, Holtzman DM, Xiong C, Fagan AM. Neuropsychological measures that detect early impairment and decline in preclinical Alzheimer disease. Neurobiol Aging 2017; 56:25-32. [PMID: 28482211 DOI: 10.1016/j.neurobiolaging.2017.04.004] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Revised: 04/03/2017] [Accepted: 04/07/2017] [Indexed: 10/19/2022]
Abstract
Identifying which neuropsychological measures detect early cognitive changes associated with Alzheimer disease (AD), brain pathology would be helpful clinically for the diagnosis of early AD and for the design of clinical trials. We evaluated which neuropsychological measures in our cognitive battery are most strongly associated with cerebrospinal fluid (CSF) biomarkers of AD brain pathology. We studied a large cohort (n = 233) of middle-to older-aged community-dwelling individuals (mean age 61 years) who had no clinical symptoms of dementia and underwent baseline CSF collection at baseline. Participants completed a battery of 9 neuropsychological measures at baseline and then every 1 to 3 years. CSF tau/Aβ42 was associated with baseline performance on 5/9 neuropsychological measures, especially measures of episodic memory, and longitudinal performance on 7/9 neuropsychological measures, especially measures of global cognition. The free recall portion of the Free and Cued Selective Reminding Task (FCSRT-free) detected declining cognition in the high CSF tau/Aβ42 group the earliest, followed by another measure of episodic memory and a sequencing task.
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Affiliation(s)
- Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Mateusz S Jasielec
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Hua Weng
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Jason J Hassenstab
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Ellen Grober
- Department of Neurology, Albert Einstein College of Medicine, New York, NY, USA
| | - Lena M McCue
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.
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26
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Touchon J, Rosenbaum J, Aisen P, Andrieu S, Carrillo MC, Ceccaldi M, Dartiques JF, Feldman H, Gabelle A, Isaac M, Fitten LJ, Sperling RA, Vellas B, Tariot P, Weiner M. Editorial: Collaborative Efforts to Prevent Alzheimer's Disease. J Nutr Health Aging 2017; 21:1072-1074. [PMID: 29188862 DOI: 10.1007/s12603-017-0961-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- J Touchon
- Jacques Touchon, University Hospital of Montpellier, 34025 Montpellier Cedex 5, France,
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27
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Donohue MC, Sun CK, Raman R, Insel PS, Aisen PS. Cross-validation of optimized composites for preclinical Alzheimer's disease. ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS 2016; 3:123-129. [PMID: 28758145 PMCID: PMC5527287 DOI: 10.1016/j.trci.2016.12.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Introduction We discuss optimization and validation of composite end points for presymptomatic Alzheimer's disease clinical trials. Optimized composites offer hope of substantial gains in statistical power or reduction in sample size. But there is tradeoff between optimization and face validity such that optimization should only be considered if there is a convincing rationale. As with statistically derived regions of interest in neuroimaging, validation on independent data sets is essential. Methods Using four data sets, we consider the optimized weighting of four components of a cognitive composite which includes measures of (1) global cognition, (2) semantic memory, (3) episodic memory, and (4) executive function. Weights are optimized to either discriminate amyloid positivity or maximize power to detect a treatment effect in an amyloid-positive population. We apply repeated 5 × 3-fold cross-validation to quantify the out-of-sample performance of optimized composite end points. Results We found the optimized weights varied greatly across the folds of the cross-validation with either optimization method. Both optimization methods tend to down-weight the measures of global cognition and executive function. However, when these optimized composites were applied to the validation sets, they did not provide consistent improvements in power. In fact, overall, the optimized composites performed worse than those without optimization. Discussion We find that component weight optimization does not yield valid improvements in sensitivity of this composite to detect treatment effects.
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Affiliation(s)
- Michael C Donohue
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Chung-Kai Sun
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Rema Raman
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | | | - Paul S Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
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