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      Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

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      a , 1 , 2 , 3 , 1 , 2 , 1 , 2 , b , 1 , 2 , The Alzheimer's Disease Neuroimaging Initiative
      Nature Communications
      Nature Publishing Group

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          Abstract

          Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions.

          Abstract

          Late-onset Alzheimer's disease (LOAD) is a complex multi-factorial disorder. Here, the authors perform a data-driven analysis of LOAD progression, including multimodal brain imaging, plasma and CSF biomarkers, and find vascular dysfunction is among the earliest and strongest altered events.

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          Most cited references23

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          Alzheimer's Disease is Type 3 Diabetes—Evidence Reviewed

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            The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core.

            This is a progress report of the Alzheimer's Disease Neuroimaging Initiative (ADNI) positron emission tomography (PET) Core. The Core has supervised the acquisition, quality control, and analysis of longitudinal [(18)F]fluorodeoxyglucose PET (FDG-PET) data in approximately half of the ADNI cohort. In an "add on" study, approximately 100 subjects also underwent scanning with [(11)C] Pittsburgh compound B PET for amyloid imaging. The Core developed quality control procedures and standardized image acquisition by developing an imaging protocol that has been widely adopted in academic and pharmaceutical industry studies. Data processing provides users with scans that have identical orientation and resolution characteristics despite acquisition on multiple scanner models. The Core labs have used many different approaches to characterize differences between subject groups (Alzheimer's disease, mild cognitive impairment, controls), to examine longitudinal change over time in glucose metabolism and amyloid deposition, and to assess the use of FDG-PET as a potential outcome measure in clinical trials. ADNI data indicate that FDG-PET increases statistical power over traditional cognitive measures, might aid subject selection, and could substantially reduce the sample size in a clinical trial. Pittsburgh compound B PET data showed expected group differences, and identified subjects with significant annual increases in amyloid load across the subject groups. The next activities of the PET core in ADNI will entail developing standardized protocols for amyloid imaging using the [(18)F]-labeled amyloid imaging agent AV45, which can be delivered to virtually all ADNI sites. ADNI has demonstrated the feasibility and utility of multicenter PET studies and is helping to clarify the role of biomarkers in the study of aging and dementia. Copyright 2010 The Alzheimer
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              Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models.

              Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile framework for analyzing real-life LNI data. This article presents the theory behind LME models, contrasts it with other popular approaches in the context of LNI, and is accompanied with an array of computational tools that will be made freely available through FreeSurfer - a popular Magnetic Resonance Image (MRI) analysis software package. Our core contribution is to provide a quantitative empirical evaluation of the performance of LME and competing alternatives popularly used in prior longitudinal structural MRI studies, namely repeated measures ANOVA and the analysis of annualized longitudinal change measures (e.g. atrophy rate). In our experiments, we analyzed MRI-derived longitudinal hippocampal volume and entorhinal cortex thickness measurements from a public dataset consisting of Alzheimer's patients, subjects with mild cognitive impairment and healthy controls. Our results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                21 June 2016
                2016
                : 7
                : 11934
                Affiliations
                [1 ]Department of Neurology & Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute , Montreal, Quebec, Canada H3A 2B4
                [2 ]Ludmer Centre for NeuroInformatics and Mental Health , Montreal, Quebec, Canada H3A 2B4
                [3 ]Department of Radiology and Hotchkiss Brain institute, University of Calgary , Calgary, Alberta, Canada T2N 4N1
                [4 ]UC San Francisco , California, USA
                [5 ]UC San Diego , California, USA
                [6 ]Mayo Clinic , Rochester, New York, USA
                [7 ]UC Berkeley , California, USA
                [8 ]UPenn , Philadelphia, Pennsylvania, USA
                [9 ]USC , Los Angeles, California, USA
                [10 ]UC Davis , California, USA
                [11 ]Brigham and Women's Hospital/Harvard Medical School , Boston, Massachusetts, USA
                [12 ]Indiana University , Bloomington, Indiana, USA
                [13 ]Washington University St Louis , Missouri, USA
                [14 ]Prevent Alzheimer's Disease 2020 , Rockville, Maryland, USA
                [15 ]Siemens, Munich, Germany
                [16 ]University of Pittsburg , Pennsylvania, USA
                [17 ]Cornell University , Ithaca, New York, USA
                [18 ]Albert Einstein College of Medicine of Yeshiva University , Bronx, New York, USA
                [19 ]AD Drug Discovery Foundation , New York City, New York, USA
                [20 ]Acumen Pharmaceuticals , Livermore, California, USA
                [21 ]Northwestern University , Evanston and Chicago, Illinois, USA
                [22 ]National Institute of Mental Health , Rockville, Maryland, USA
                [23 ]Brown University , Providence, Rhode Island, USA
                [24 ]Eli Lilly , Indianapolis, Indiana, USA
                [25 ]University of Washington , Seattle, Washington, USA
                [26 ]University of London , London, England
                [27 ]UCLA , Los Angeles, California, USA
                [28 ]University of Michigan , Ann Arbor, Michigan, USA
                [29 ]University of Utah , Salt Lake, Utah, USA
                [30 ]Banner Alzheimer's Institute , Phoenix, Arizona, USA
                [31 ]UC Irvine , Irvine, California, USA
                [32 ]National Institute on Aging , Bethesda, Maryland, USA
                [33 ]Johns Hopkins University , Baltimore, Maryland, USA
                [34 ]Richard Frank Consulting , Washington, DC, USA
                [35 ]Oregon Health and Science University , Portland, Oregon, USA
                [36 ]Baylor College of Medicine , Houston, Texas, USA
                [37 ]University of Alabama , Birmingham, Alabama, USA
                [38 ]Mount Sinai School of Medicine , New York City, New York, USA
                [39 ]Rush University Medical Center , Chicago, Illinois, USA
                [40 ]Wien Center , Miami, Florida, USA
                [41 ]New York University , New York City, New York, USA
                [42 ]Duke University Medical Center , Durham, North Carolina, USA
                [43 ]University of Kentucky , Lexington, Kentucky, USA
                [44 ]University of Rochester Medical Center , Rochester, New York, USA
                [45 ]University of Texas Southwestern Medical School , Dallas, Texas, USA
                [46 ]Emory University , Atlanta, Georgia, USA
                [47 ]University of Kansas, Medical Center , Kansas City, Kansas, USA
                [48 ]Mayo Clinic , Jacksonville, Florida, USA
                [49 ]Yale University School of Medicine , New Haven, Connecticut, USA
                [50 ]McGill University/Montreal-Jewish General Hospital , Montreal, Quebec, Canada
                [51 ]Sunnybrook Health Sciences , Toronto, Ontario, Canada
                [52 ]U.B.C. Clinic for AD & Related Disorders , Vancouver, British Columbia, Canada
                [53 ]Cognitive Neurology–St Joseph's , London, Ontario, Canada
                [54 ]Cleveland Clinic Lou Ruvo Center for Brain Health , Las Vegas, Nevada, USA
                [55 ]St Joseph's Health Care , London, Ontario, Canada
                [56 ]Premiere Research Institute, Palm Beach Neurology , Miami, Florida, USA
                [57 ]Georgetown University Medical Center , Washington, DC, USA
                [58 ]Banner Sun Health Research Institute , Sun City, Arizona, USA
                [59 ]Boston University , Boston, Massachusetts, USA
                [60 ]Howard University , Washington, DC, USA
                [61 ]Case Western Reserve University , Cleveland, Ohio, USA
                [62 ]Neurological Care of CNY , Liverpool, New York, USA
                [63 ]Parkwood Hospital , London, Ontario, USA
                [64 ]University of Wisconsin , Madison, Wisconsin, USA
                [65 ]Dent Neurologic Institute , Amherst, New York, USA
                [66 ]Ohio State University , Columbus, Ohio, USA
                [67 ]Albany Medical College , Albany, New York, USA
                [68 ]Hartford Hospital, Olin Neuropsychiatry Research Center , Hartford, Connecticut, USA
                [69 ]Dartmouth-Hitchcock Medical Center , Lebanon, New Hampshire, USA
                [70 ]Wake Forest University Health Sciences , Winston-Salem, North Carolina, USA
                [71 ]Rhode Island Hospital , Providence, Rhode Island, USA
                [72 ]Butler Hospital , Providence, Rhode Island, USA
                [73 ]Medical University South Carolina , Charleston, South Carolina, USA
                [74 ]Nathan Kline Institute , Orangeburg, New York, USA
                [75 ]University of Iowa College of Medicine , Iowa City, Iowa, USA
                [76 ]University of South Florida: USF Health Byrd Alzheimer's Institute , Tampa, Florida, USA
                [77 ]Department of Defense , Arlington, Virginia, USA
                [78 ]Stanford University , Stanford, California, USA
                Author notes
                [*]

                A full list of consortium members appears at the end of the paper.

                Article
                ncomms11934
                10.1038/ncomms11934
                4919512
                27327500
                c8036cdc-2a85-437f-9bc4-5ef14d891084
                Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 25 June 2015
                : 13 May 2016
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