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Apolipoprotein E ɛ4-related effects on cognition are limited to the Alzheimer's disease spectrum. GeroScience 2021; 44:195-209. [PMID: 34591236 PMCID: PMC8811053 DOI: 10.1007/s11357-021-00450-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 08/23/2021] [Indexed: 11/29/2022] Open
Abstract
Whether the deleterious effects of APOE4 are restricted to the Alzheimer’s disease (AD) spectrum or cause cognitive impairment irrespectively of the development of AD is still a matter of debate, and the focus of this study. Our analyses included APOE4 genotype, neuropsychological variables, amyloid-βeta (Aβ) and Tau markers, FDG-PET values, and hippocampal volumetry data derived from the healthy controls sample of the ADNI database. We formed 4 groups of equal size (n = 30) based on APOE4 carriage and amyloid-PET status. Baseline and follow-up (i.e., 48 months post-baseline) results indicated that Aβ-positivity was the most important factor to explain poorer cognitive performance, while APOE4 only exerted a significant effect in Aβ-positive subjects. Additionally, multiple regression analyses evidenced that, within the Aβ-positive sample, hippocampal volumetry explained most of the variability in cognitive performance for APOE4 carriers. These findings represent a strong support for the so-called preclinical/prodromal hypothesis, which states that the reported differences in cognitive performance between healthy carriers and non-carriers are mainly due to the APOE4’s capability to increase the risk of AD. Moreover, our results reinforce the notion that a synergistic interaction of Aβ and APOE4 elicits a neurodegenerative process in the hippocampus that might be the main cause of impaired cognitive performance.
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Ma YH, Wu JH, Xu W, Shen XN, Wang HF, Hou XH, Cao XP, Bi YL, Dong Q, Feng L, Tan L, Yu JT. Associations of Green Tea Consumption and Cerebrospinal Fluid Biomarkers of Alzheimer's Disease Pathology in Cognitively Intact Older Adults: The CABLE Study. J Alzheimers Dis 2021; 77:411-421. [PMID: 32804140 DOI: 10.3233/jad-200410] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND Green tea has been widely recognized in ameliorating cognitive impairment and Alzheimer's disease (AD), especially the progression of cognitive dysfunction. But the underlying mechanism is still unclear. OBJECTIVE This study was designed to determine the role of green tea consumption in the association with cerebrospinal fluid (CSF) biomarkers of AD pathology and to ascertain whether specific population backgrounds showed the differences toward these relationships. METHODS Multivariate linear models analyzed the available data on CSF biomarkers and frequency of green tea consumption of 722 cognitively intact participants from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) database, and we additionally detected the interaction effects of tea consumption with APOEɛ4 status and gender using a two-way analysis of covariance. RESULTS Frequent green tea consumption was associated with a decreased level of CSF total-tau protein (t-tau) (p = 0.041) but not with the levels of CSF amyloid-β 42 (Aβ42) and CSF phosphorylated tau. The more pronounced associations of green tea consumption with CSF t-tau (p = 0.007) and CSF t-tau/Aβ42 (p = 0.039) were observed in individuals aged 65 years or younger. Additionally, males with frequent green tea consumption had a significantly low level of CSF t-tau/Aβ42 and a modest trend toward decreased CSF t-tau. There were no interaction effects of green tea consumption with APOEɛ4 and gender. CONCLUSION Collectively, our findings consolidated the favorable effects of green tea on the mitigation of AD risk. The constituents of green tea may improve abnormal tau metabolism and are promising targets in interventions and drug therapies.
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Affiliation(s)
- Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jia-Huan Wu
- Department of Neurology, Dalian Medical University, Dalian, China
| | - Wei Xu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xue-Ning Shen
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Hui-Fu Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xiao-He Hou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xi-Peng Cao
- Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan-Lin Bi
- Department of Anesthesiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lei Feng
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
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Properzi MJ, Buckley RF, Chhatwal JP, Donohue MC, Lois C, Mormino EC, Johnson KA, Sperling RA, Schultz AP. Nonlinear Distributional Mapping (NoDiM) for harmonization across amyloid-PET radiotracers. Neuroimage 2019; 186:446-454. [PMID: 30458305 PMCID: PMC6338495 DOI: 10.1016/j.neuroimage.2018.11.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Revised: 10/24/2018] [Accepted: 11/15/2018] [Indexed: 01/12/2023] Open
Abstract
INTRODUCTION There is a growing need in clinical research domains for direct comparability between amyloid-beta (Aβ) Positron Emission Tomography (PET) measures obtained via different radiotracers and processing methodologies. Previous efforts to provide a common measurement scale fail to account for non-linearities between measurement scales that can arise from these differences. We introduce a new application of distribution mapping, based on well established statistical orthodoxy, that we call Nonlinear Distribution Mapping (NoDiM). NoDiM uses cumulative distribution functions to derive mappings between Aβ-PET measurements from different tracers and processing streams that align data based on their location in their respective distributions. METHODS Utilizing large datasets of Florbetapir (FBP) from the Alzheimer's Disease Neuroimaging Initiative (n = 349 female (%) = 53) and Pittsburgh Compound B (PiB) from the Harvard Aging Brain Study (n = 305 female (%) = 59.3) and the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (n = 184 female (%) = 53.3), we fit explicit mathematical models of a mixture of two normal distributions, with parameter estimates from Gaussian Mixture Models, to each tracer's empirical data. We demonstrate the accuracy of these fits, and then show the ability of NoDiM to transform FBP measurements into PiB-like units. RESULTS A mixture of two normal distributions fit both the FBP and PiB empirical data and provides a strong basis for derivation of a transfer function. Transforming Aβ-PET data with NoDiM results in FBP and PiB distributions that are closely aligned throughout their entire range, while a linear transformation does not. Additionally the NoDiM transform better matches true positive and false positive profiles across tracers. DISCUSSION The NoDiM transformation provides a useful alternative to the linear mapping advocated in the Centiloid project, and provides improved correspondence between measurements from different tracers across the range of observed values. This improved alignment enables disparate measures to be merged on to continuous scale, and better enables the use of uniform thresholds across tracers.
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Affiliation(s)
- Michael J Properzi
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Rachel F Buckley
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA; The Florey Institute, The University of Melbourne, Victoria, Australia; Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia
| | - Jasmeer P Chhatwal
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael C Donohue
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA
| | - Cristina Lois
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | | | - Keith A Johnson
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA; Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Aaron P Schultz
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA.
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Macêdo PT, Aquino ACQ, Meurer YSR, Brandão LEM, Campêlo CLC, Lima RH, Costa MR, Ribeiro AM, Silva RH. Subtle Alterations in Spatial Memory Induced by Amyloid Peptides Infusion in Rats. Front Aging Neurosci 2018; 10:18. [PMID: 29441014 PMCID: PMC5797637 DOI: 10.3389/fnagi.2018.00018] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 01/15/2018] [Indexed: 12/20/2022] Open
Abstract
The cause of Alzheimer's disease (AD) remains uncertain. The accumulation of amyloid peptides (Aβ) is the main pathophysiological hallmark of the disease. Spatial deficit is an important initial sign of AD, while other types of memory impairments that appear in later stages. The Barnes maze allows the detection of subtle alterations in spatial search by the analysis of use of different strategies. Previous findings showed a general performance deficit in this task following long-term (35 days) infusion of Aβ, which corresponds to the moderate or severe impairments of the disease. In the present study, we evaluated the effects of a low-dose 15-day long treatment with Aβ peptides on spatial and non-spatial strategies of rats tested in the Barnes maze. Aβ peptides (0.5 μL/site/day; 30 pmoL solution of Aβ1-40:Aβ1-42 10:1) or saline were bilaterally infused into the CA1 (on the first treatment day) and intraventricularly (on the following 15 days) in 6-month-old Wistar male rats. Aβ infusion induced a deficit in the performance (increased latency and distance traveled to reach the target compared to saline group). In addition, a significant association between treatment and search strategy in the retrieval trial was found: Aβ group preferred the non-spatial search strategy, while saline group preferred the spatial search. In conclusion, the protocol of Aβ infusion used here induced a subtle cognitive deficit that was specific to spatial aspects. Indeed, animals under Aβ treatment still showed retrieval, but using non-spatial strategies. We suggest that this approach is potentially useful to the study of the initial memory deficits in early AD.
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Affiliation(s)
- Priscila Tavares Macêdo
- Memory Studies Laboratory, Physiology Department, Universidade Federal do Rio Grande do Norte, Natal, Brazil.,Brain Institute, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Antônio C Q Aquino
- Memory Studies Laboratory, Physiology Department, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Ywlliane S R Meurer
- Memory Studies Laboratory, Physiology Department, Universidade Federal do Rio Grande do Norte, Natal, Brazil.,Behavioral Neuroscience Laboratory, Pharmacology Department, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Luiz E M Brandão
- Memory Studies Laboratory, Physiology Department, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Clarissa L C Campêlo
- Memory Studies Laboratory, Physiology Department, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Ramon H Lima
- Memory Studies Laboratory, Physiology Department, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Marcos R Costa
- Brain Institute, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Alessandra M Ribeiro
- Laboratory of Neuroscience and Bioprospecting of Natural Products, Department of Biosciences, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Regina H Silva
- Behavioral Neuroscience Laboratory, Pharmacology Department, Universidade Federal de São Paulo, São Paulo, Brazil
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Mak E, Gabel S, Mirette H, Su L, Williams GB, Waldman A, Wells K, Ritchie K, Ritchie C, O’Brien J. Structural neuroimaging in preclinical dementia: From microstructural deficits and grey matter atrophy to macroscale connectomic changes. Ageing Res Rev 2017; 35:250-264. [PMID: 27777039 DOI: 10.1016/j.arr.2016.10.001] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Revised: 08/26/2016] [Accepted: 10/19/2016] [Indexed: 12/18/2022]
Abstract
The last decade has witnessed a proliferation of neuroimaging studies characterising brain changes associated with Alzheimer's disease (AD), where both widespread atrophy and 'signature' brain regions have been implicated. In parallel, a prolonged latency period has been established in AD, with abnormal cerebral changes beginning many years before symptom onset. This raises the possibility of early therapeutic intervention, even before symptoms, when treatments could have the greatest effect on disease-course modification. Two important prerequisites of this endeavour are (1) accurate characterisation or risk stratification and (2) monitoring of progression using neuroimaging outcomes as a surrogate biomarker in those without symptoms but who will develop AD, here referred to as preclinical AD. Structural neuroimaging modalities have been used to identify brain changes related to risk factors for AD, such as familial genetic mutations, risk genes (for example apolipoprotein epsilon-4 allele), and/or family history. In this review, we summarise structural imaging findings in preclinical AD. Overall, the literature suggests early vulnerability in characteristic regions, such as the medial temporal lobe structures and the precuneus, as well as white matter tracts in the fornix, cingulum and corpus callosum. We conclude that while structural markers are promising, more research and validation studies are needed before future secondary prevention trials can adopt structural imaging biomarkers as either stratification or surrogate biomarkers.
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Desikan RS, Schork AJ, Wang Y, Witoelar A, Sharma M, McEvoy LK, Holland D, Brewer JB, Chen CH, Thompson WK, Harold D, Williams J, Owen MJ, O’Donovan MC, Pericak-Vance MA, Mayeux R, Haines JL, Farrer LA, Schellenberg GD, Heutink P, Singleton AB, Brice A, Wood NW, Hardy J, Martinez M, Choi SH, DeStefano A, Ikram MA, Bis JC, Smith A, Fitzpatrick AL, Launer L, van Duijn C, Seshadri S, Ulstein ID, Aarsland D, Fladby T, Djurovic S, Hyman BT, Snaedal J, Stefansson H, Stefansson K, Gasser T, Andreassen OA, Dale AM. Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus. Mol Psychiatry 2015; 20:1588-95. [PMID: 25687773 PMCID: PMC4539304 DOI: 10.1038/mp.2015.6] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2014] [Revised: 11/29/2014] [Accepted: 01/08/2015] [Indexed: 12/18/2022]
Abstract
We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10(-7)). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.
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Affiliation(s)
- Rahul S. Desikan
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Correspondence should be addressed to: Drs. Rahul S. Desikan and Anders M. Dale, Department of Radiology, University of California, San Diego, 8950 Villa La Jolla Drive, Suite C101, La Jolla, CA, USA 92037-0841, , , Phone: (858)-822-6671, Fax: (858)-534-1078, Dr. Ole A. Andreassen: KG Jebsen Centre for Psychosis Research, Building 49, Oslo University Hospital, Ullevål, Kirkeveien 166, PO Box 4956 Nydalen, 0424 Oslo, Norway, , Ph: +47 23 02 73 50 (22 11 78 43 dir), Fax: +47 23 02 73 33
| | - Andrew J. Schork
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Yunpeng Wang
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA,NORMENT; Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Aree Witoelar
- NORMENT; Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Manu Sharma
- Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research University of Tubingen, Germany,Institute for Clinical Epidemiology and Applied Biometry, University of Tübingen, Germany
| | - Linda K. McEvoy
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Dominic Holland
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - James B. Brewer
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Chi-Hua Chen
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Denise Harold
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Wales
| | - Julie Williams
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Wales
| | - Michael J. Owen
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Wales
| | - Michael C. O’Donovan
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Wales
| | | | - Richard Mayeux
- Department of Neurology, Taub Institute on Alzheimer's Disease and the Aging Brain, and Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
| | - Jonathan L. Haines
- Department of Molecular Physiology and Biophysics, Vanderbilt Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, USA
| | - Lindsay A. Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Biostatistics, and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts, USA
| | - Gerard D. Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Peter Heutink
- German Center for Neurodegenerative Diseases (DZNE)-Tübingen, Paul-Ehrlich-Straße 15, 72076 Tübingen, Germany
| | | | - Alexis Brice
- Sorbonne Université, UPMC Univ Paris 06, UM 75, ICM; Inserm, U 1127, ICM; Cnrs, UMR 7225, ICM; ICM, Paris, F-75013 Paris, France
| | - Nicolas W. Wood
- UCL Genetics Institute; and Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - John Hardy
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | | | - Seung Hoi Choi
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Anita DeStefano
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA,The National Heart Lung and Blood Institute’s Framingham Heart Study, Framingham, MA
| | - M. Arfan Ikram
- Deparment of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Joshua C. Bis
- Deparment of Internal Medicine, University of Washington, Seattle, WA, USA
| | | | | | - Lenore Launer
- Laboratory of Epidemiology, Demography and Biometry, Intramural Research Program, National Institute on Aging, Washington, DC, USA
| | - Cornelia van Duijn
- Deparment of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA,The National Heart Lung and Blood Institute’s Framingham Heart Study, Framingham, MA
| | - Ingun Dina Ulstein
- Norwegian Centre for Dementia Research, Department of Old Age Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Dag Aarsland
- Alzheimer’s Disease Research Centre, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden; Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway; Department of Geriatric Psychiatry, Akershus University Hospital, Oslo, Norway
| | - Tormod Fladby
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Neurology, Akershus University Hospital, Norway
| | - Srdjan Djurovic
- NORMENT; Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Bradley T. Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Jon Snaedal
- Department of Geriatric Medicine, University Hospital Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE Genetics/Amgen, Reykjavik, Iceland,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Thomas Gasser
- Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research University of Tubingen, Germany
| | - Ole A. Andreassen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,NORMENT; Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Correspondence should be addressed to: Drs. Rahul S. Desikan and Anders M. Dale, Department of Radiology, University of California, San Diego, 8950 Villa La Jolla Drive, Suite C101, La Jolla, CA, USA 92037-0841, , , Phone: (858)-822-6671, Fax: (858)-534-1078, Dr. Ole A. Andreassen: KG Jebsen Centre for Psychosis Research, Building 49, Oslo University Hospital, Ullevål, Kirkeveien 166, PO Box 4956 Nydalen, 0424 Oslo, Norway, , Ph: +47 23 02 73 50 (22 11 78 43 dir), Fax: +47 23 02 73 33
| | - Anders M. Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA,Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA,Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA,Correspondence should be addressed to: Drs. Rahul S. Desikan and Anders M. Dale, Department of Radiology, University of California, San Diego, 8950 Villa La Jolla Drive, Suite C101, La Jolla, CA, USA 92037-0841, , , Phone: (858)-822-6671, Fax: (858)-534-1078, Dr. Ole A. Andreassen: KG Jebsen Centre for Psychosis Research, Building 49, Oslo University Hospital, Ullevål, Kirkeveien 166, PO Box 4956 Nydalen, 0424 Oslo, Norway, , Ph: +47 23 02 73 50 (22 11 78 43 dir), Fax: +47 23 02 73 33
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Gispert JD, Rami L, Sánchez-Benavides G, Falcon C, Tucholka A, Rojas S, Molinuevo JL. Nonlinear cerebral atrophy patterns across the Alzheimer's disease continuum: impact of APOE4 genotype. Neurobiol Aging 2015; 36:2687-701. [PMID: 26239178 DOI: 10.1016/j.neurobiolaging.2015.06.027] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2015] [Revised: 06/26/2015] [Accepted: 06/30/2015] [Indexed: 01/11/2023]
Abstract
The progression of Alzheimer's disease (AD) is characterized by complex trajectories of cerebral atrophy that are affected by interactions with age and apolipoprotein E allele ε4 (APOE4) status. In this article, we report the nonlinear volumetric changes in gray matter across the full biological spectrum of the disease, represented by the AD-cerebrospinal fluid (CSF) index. This index reflects the subject's level of pathology and position along the AD continuum. We also evaluated the associated impact of the APOE4 genotype. The atrophy pattern associated with the AD-CSF index was highly symmetrical and corresponded with the typical AD signature. Medial temporal structures showed different atrophy dynamics along the progression of the disease. The bilateral parahippocampal cortices and a parietotemporal region extending from the middle temporal to the supramarginal gyrus presented an initial increase in volume which later reverted. Similarly, a portion of the precuneus presented a rather linear inverse association with the AD-CSF index whereas some other clusters did not show significant atrophy until index values corresponded to positive CSF tau values. APOE4 carriers showed steeper hippocampal volume reductions with AD progression. Overall, the reported atrophy patterns are in close agreement with those mentioned in previous findings. However, the detected nonlinearities suggest that there may be different pathological processes taking place at specific moments during AD progression and reveal the impact of the APOE4 allele.
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Affiliation(s)
- J D Gispert
- Clinical and Neuroimaging Departments, Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain
| | - L Rami
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - C Falcon
- Clinical and Neuroimaging Departments, Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain
| | - A Tucholka
- Clinical and Neuroimaging Departments, Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - S Rojas
- Clinical and Neuroimaging Departments, Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Department of Morphological Sciences, Anatomy and Embriology Unit, Faculty of Medicine, Autonomous University of Barcelona
| | - J L Molinuevo
- Clinical and Neuroimaging Departments, Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain; Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
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8
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Fortea J, Vilaplana E, Alcolea D, Carmona-Iragui M, Sánchez-Saudinos MB, Sala I, Antón-Aguirre S, González S, Medrano S, Pegueroles J, Morenas E, Clarimón J, Blesa R, Lleó A. Cerebrospinal fluid β-amyloid and phospho-tau biomarker interactions affecting brain structure in preclinical Alzheimer disease. Ann Neurol 2014; 76:223-30. [PMID: 24852682 DOI: 10.1002/ana.24186] [Citation(s) in RCA: 101] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Revised: 05/19/2014] [Accepted: 05/19/2014] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To assess the relationships between core cerebrospinal fluid (CSF) biomarkers and cortical thickness (CTh) in preclinical Alzheimer disease (AD). METHODS In this cross-sectional study, normal controls (n = 145) from the Alzheimer's Disease Neuroimaging Initiative underwent structural 3T magnetic resonance imaging (MRI) and lumbar puncture. CSF β-amyloid1-42 (Aβ) and phospho-tau₁₈₁p (p-tau) levels were measured by Luminex assays. Samples were dichotomized using published cutoffs (Aβ(+) /Aβ(-) and p-tau(+) /ptau(-)). CTh was measured by Freesurfer. CTh difference maps were derived from interaction and correlation analyses. Clusters from the interaction analysis were isolated to analyze the directionality of the interaction by analysis of covariance. RESULTS We found a significant biomarker interaction between CSF Aβ and CSF p-tau levels affecting brain structure. Cortical atrophy only occurs in subjects with both Aβ(+) and p-tau(+). The stratified correlation analyses showed that the relationship between p-tau and CTh is modified by Aβ status and the relationship between Aβ and CTh is modified by p-tau status. p-Tau-dependent thinning was found in different cortical regions in Aβ(+) subjects but not in Aβ(-) subjects. Cortical thickening was related to decreasing CSF Aβ values in the absence of abnormal p-tau, but no correlations were found in p-tau(+) subjects. INTERPRETATION Our data suggest that interactions between biomarkers in AD result in a 2-phase phenomenon of pathological cortical thickening associated with low CSF Aβ, followed by atrophy once CSF p-tau becomes abnormal. These interactions should be considered in clinical trials in preclinical AD, both when selecting patients and when using MRI as a surrogate marker of efficacy.
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Affiliation(s)
- Juan Fortea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau - Universitat Autònoma de Barcelona; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas - CIBERNED
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9
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Shen L, Thompson PM, Potkin SG, Bertram L, Farrer LA, Foroud TM, Green RC, Hu X, Huentelman MJ, Kim S, Kauwe JSK, Li Q, Liu E, Macciardi F, Moore JH, Munsie L, Nho K, Ramanan VK, Risacher SL, Stone DJ, Swaminathan S, Toga AW, Weiner MW, Saykin AJ. Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers. Brain Imaging Behav 2014; 8:183-207. [PMID: 24092460 PMCID: PMC3976843 DOI: 10.1007/s11682-013-9262-z] [Citation(s) in RCA: 121] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.
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Affiliation(s)
- Li Shen
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Paul M. Thompson
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617 USA
| | - Lars Bertram
- Neuropsychiatric Genetics Group, Max-Planck Institute for Molecular Genetics, Berlin, Germany
| | - Lindsay A. Farrer
- Biomedical Genetics L320, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118 USA
| | - Tatiana M. Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - Robert C. Green
- Division of Genetics and Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115 USA
| | - Xiaolan Hu
- Clinical Genetics, Exploratory Clinical & Translational Research, Bristol-Myers Squibbs, Pennington, NJ 08534 USA
| | - Matthew J. Huentelman
- Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, AZ 85004 USA
| | - Sungeun Kim
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - John S. K. Kauwe
- Departments of Biology, Neuroscience, Brigham Young University, 675 WIDB, Provo, UT 84602 USA
| | - Qingqin Li
- Department of Neuroscience Biomarkers, Janssen Research and Development, LLC, Raritan, NJ 08869 USA
| | - Enchi Liu
- Biomarker Discovery, Janssen Alzheimer Immunotherapy Research and Development, LLC, South San Francisco, CA 94080 USA
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617 USA
- Department of Sciences and Biomedical Technologies, University of Milan, Segrate, MI Italy
| | - Jason H. Moore
- Department of Genetics, Computational Genetics Laboratory, Dartmouth Medical School, Lebanon, NH 03756 USA
| | - Leanne Munsie
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN 46285 USA
| | - Kwangsik Nho
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Vijay K. Ramanan
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - Shannon L. Risacher
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - David J. Stone
- Merck Research Laboratories, 770 Sumneytown Pike, WP53B-120, West Point, PA 19486 USA
| | - Shanker Swaminathan
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
| | - Michael W. Weiner
- Departments of Radiology, Medicine and Psychiatry, UC San Francisco, San Francisco, CA 94143 USA
| | - Andrew J. Saykin
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - for the Alzheimer’s Disease Neuroimaging Initiative
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617 USA
- Neuropsychiatric Genetics Group, Max-Planck Institute for Molecular Genetics, Berlin, Germany
- Biomedical Genetics L320, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118 USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
- Division of Genetics and Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115 USA
- Clinical Genetics, Exploratory Clinical & Translational Research, Bristol-Myers Squibbs, Pennington, NJ 08534 USA
- Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, AZ 85004 USA
- Departments of Biology, Neuroscience, Brigham Young University, 675 WIDB, Provo, UT 84602 USA
- Department of Neuroscience Biomarkers, Janssen Research and Development, LLC, Raritan, NJ 08869 USA
- Biomarker Discovery, Janssen Alzheimer Immunotherapy Research and Development, LLC, South San Francisco, CA 94080 USA
- Department of Sciences and Biomedical Technologies, University of Milan, Segrate, MI Italy
- Department of Genetics, Computational Genetics Laboratory, Dartmouth Medical School, Lebanon, NH 03756 USA
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN 46285 USA
- Merck Research Laboratories, 770 Sumneytown Pike, WP53B-120, West Point, PA 19486 USA
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
- Departments of Radiology, Medicine and Psychiatry, UC San Francisco, San Francisco, CA 94143 USA
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Ferreira D, Perestelo-Pérez L, Westman E, Wahlund LO, Sarría A, Serrano-Aguilar P. Meta-Review of CSF Core Biomarkers in Alzheimer's Disease: The State-of-the-Art after the New Revised Diagnostic Criteria. Front Aging Neurosci 2014; 6:47. [PMID: 24715863 PMCID: PMC3970033 DOI: 10.3389/fnagi.2014.00047] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Accepted: 03/02/2014] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Current research criteria for Alzheimer's disease (AD) include cerebrospinal fluid (CSF) biomarkers into the diagnostic algorithm. However, spreading their use to the clinical routine is still questionable. OBJECTIVE To provide an updated, systematic and critical review on the diagnostic utility of the CSF core biomarkers for AD. DATA SOURCES MEDLINE, PreMedline, EMBASE, PsycInfo, CINAHL, Cochrane Library, and CRD. ELIGIBILITY CRITERIA (1a) Systematic reviews with meta-analysis; (1b) Primary studies published after the new revised diagnostic criteria; (2) Evaluation of the diagnostic performance of at least one CSF core biomarker. RESULTS The diagnostic performance of CSF biomarkers is generally satisfactory. They are optimal for discriminating AD patients from healthy controls. Their combination may also be suitable for mild cognitive impairment (MCI) prognosis. However, CSF biomarkers fail to distinguish AD from other forms of dementia. LIMITATIONS (1) Use of clinical diagnosis as standard instead of pathological postmortem confirmation; (2) variability of methodological aspects; (3) insufficiently long follow-up periods in MCI studies; and (4) lower diagnostic accuracy in primary care compared with memory clinics. CONCLUSION Additional work needs to be done to validate the application of CSF core biomarkers as they are proposed in the new revised diagnostic criteria. The use of CSF core biomarkers in clinical routine is more likely if these limitations are overcome. Early diagnosis is going to be of utmost importance when effective pharmacological treatment will be available and the CSF core biomarkers can also be implemented in clinical trials for drug development.
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Affiliation(s)
- Daniel Ferreira
- Section of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm , Sweden
| | - Lilisbeth Perestelo-Pérez
- Evaluation Unit of the Canary Islands Health Service , Santa Cruz de Tenerife , Spain ; Red de Investigación en Servicios de Salud en Enfermedades Crónicas , Santa Cruz de Tenerife , Spain
| | - Eric Westman
- Section of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm , Sweden
| | - Lars-Olof Wahlund
- Section of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet , Stockholm , Sweden
| | - Antonio Sarría
- Evaluation Unit of the Canary Islands Health Service , Santa Cruz de Tenerife , Spain ; Agency for Health Technology Assessment, Institute of Health Carlos III , Madrid , Spain
| | - Pedro Serrano-Aguilar
- Evaluation Unit of the Canary Islands Health Service , Santa Cruz de Tenerife , Spain ; Red de Investigación en Servicios de Salud en Enfermedades Crónicas , Santa Cruz de Tenerife , Spain
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Desikan RS, Thompson WK, Holland D, Hess CP, Brewer JB, Zetterberg H, Blennow K, Andreassen OA, McEvoy LK, Hyman BT, Dale AM. The role of clusterin in amyloid-β-associated neurodegeneration. JAMA Neurol 2014; 71:180-7. [PMID: 24378367 PMCID: PMC4118752 DOI: 10.1001/jamaneurol.2013.4560] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
IMPORTANCE Converging evidence indicates that clusterin, a chaperone glycoprotein, influences Alzheimer disease neurodegeneration. However, the precise role of clusterin in Alzheimer disease pathogenesis is still not well understood. OBJECTIVE To elucidate the relationship between clusterin, amyloid-β (Aβ), phosphorylated tau (p-tau), and the rate of brain atrophy over time among nondemented older individuals. DESIGN, SETTING, AND PARTICIPANTS This longitudinal cohort included cognitively normal older participants and individuals with mild cognitive impairment assessed with baseline lumbar puncture and longitudinal structural magnetic resonance imaging. We examined 241 nondemented older individuals from research centers across the United States and Canada (91 participants with a Clinical Dementia Rating score of 0 and 150 individuals with a Clinical Dementia Rating score of 0.5). MAIN OUTCOMES AND MEASURES Using linear mixed-effects models, we investigated interactions between cerebrospinal fluid (CSF) clusterin, CSF Aβ1-42, and CSF p-tau at threonine 181 (p-tau181p) on the atrophy rate of the entorhinal cortex and hippocampus. RESULTS Across all participants, we found a significant interaction between CSF clusterin and CSF Aβ1-42 on the entorhinal cortex atrophy rate but not on the hippocampal atrophy rate. Cerebrospinal fluid clusterin was associated with the entorhinal cortex atrophy rate among CSF Aβ1-42-positive individuals but not among CSF Aβ1-42-negative individuals. In secondary analyses, we found significant interactions between CSF Aβ1-42 and CSF clusterin, as well as CSF Aβ1-42 and CSF p-tau181p, on the entorhinal cortex atrophy rate. We found similar results in subgroup analyses within the mild cognitive impairment and cognitively normal cohorts. CONCLUSIONS AND RELEVANCE In nondemented older individuals, Aβ-associated volume loss occurs in the presence of elevated clusterin. The effect of clusterin on Aβ-associated brain atrophy is not confounded or explained by p-tau. These findings implicate a potentially important role for clusterin in the earliest stages of the Alzheimer disease neurodegenerative process and suggest independent effects of clusterin and p-tau on Aβ-associated volume loss.
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Affiliation(s)
- Rahul S. Desikan
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Dominic Holland
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Christopher P. Hess
- Neuroradiology Section, Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - James B. Brewer
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, The Sahlgrenska Academy at Göteburg University, Mölndal, 40530, Gotheburg, Sweden
- UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, The Sahlgrenska Academy at Göteburg University, Mölndal, 40530, Gotheburg, Sweden
| | - Ole A. Andreassen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Linda K. McEvoy
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - Bradley T. Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Anders M. Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
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Desikan RS, Thompson WK, Holland D, Hess CP, Brewer JB, Zetterberg H, Blennow K, Andreassen OA, McEvoy LK, Hyman BT, Dale AM. Heart fatty acid binding protein and Aβ-associated Alzheimer's neurodegeneration. Mol Neurodegener 2013; 8:39. [PMID: 24088526 PMCID: PMC3850652 DOI: 10.1186/1750-1326-8-39] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2013] [Accepted: 09/23/2013] [Indexed: 02/04/2023] Open
Abstract
Background Epidemiological and molecular findings suggest a relationship between Alzheimer’s disease (AD) and dyslipidemia, although the nature of this association is not well understood. Results Using linear mixed effects models, we investigated the relationship between CSF levels of heart fatty acid binding protein (HFABP), a lipid binding protein involved with fatty acid metabolism and lipid transport, amyloid-β (Aβ), phospho-tau, and longitudinal MRI-based measures of brain atrophy among 295 non-demented and demented older individuals. Across all participants, we found a significant association of CSF HFABP with longitudinal atrophy of the entorhinal cortex and other AD-vulnerable neuroanatomic regions. However, we found that the relationship between CSF HABP and brain atrophy was significant only among those with low CSF Aβ1–42 and occurred irrespective of phospho-tau181p status. Conclusions Our findings indicate that Aβ-associated volume loss occurs in the presence of elevated HFABP irrespective of phospho-tau. This implicates a potentially important role for fatty acid binding proteins in Alzheimer’s disease neurodegeneration.
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Affiliation(s)
- Rahul S Desikan
- Department of Radiology, University of California, San Diego, 8950 Villa La Jolla Drive, Suite C101, La Jolla, CA 92037-0841, USA.
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Chételat G, Fouquet M. Neuroimaging biomarkers for Alzheimer's disease in asymptomatic APOE4 carriers. Rev Neurol (Paris) 2013; 169:729-36. [PMID: 24016463 DOI: 10.1016/j.neurol.2013.07.025] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Revised: 07/02/2013] [Accepted: 07/09/2013] [Indexed: 01/13/2023]
Abstract
INTRODUCTION The E4 allele of the apolipoprotein E (APOE4) is the major known genetic risk factor for Alzheimer's disease (AD), with a dramatic increase in the risk of developing AD as the number of APOE4 alleles increases from 0 to 2. For this reason, asymptomatic APOE4 carriers as a group offer a great opportunity to search for the presence of early biomarkers for AD. The present article reviews neuroimaging studies on APOE4 carriers, focusing on cognitively normal individuals and on the main neuroimaging biomarkers for AD, i.e. atrophy with structural MRI, hypometabolism with FDG-PET, and amyloid deposition with amyloid-PET imaging. STATE OF THE ART There are a great number of studies on the effect of APOE4 on brain structures, and they tend to show significant atrophy in APOE4 carriers compared to non-carriers especially in regions susceptible to AD pathology such as the hippocampus. However, results are rather discrepant which suggests that the effect of APOE4 on brain structure is subtle. As for FDG-PET metabolism, the few available studies show decreased metabolism, again especially in AD-sensitive regions such as posterior associative parietal areas, with a dose-dependent effect (i.e. worsening as the number of APOE4 alleles increases). Finally, there is a unanimous and major effect of APOE4 on amyloid deposition with an increase in Aβ load as the number of APOE4 alleles increases and a decrease in the age of predicted amyloid-positivity in APOE4 carriers. This graded effect of APOE4 on atrophy, hypometabolism, and amyloid deposition is consistent with multimodal neuroimaging studies suggestive of a predominant effect of APOE4 on amyloid rather than tau-related injury and on brain metabolism rather than brain structure. Neuroimaging studies also suggest that APOE4 effects may be mediated by both Aβ-dependent and Aβ-independent pathological processes. This contradicts the view that Aβ pathology is a necessary upstream event to neuronal injury in AD. PERSPECTIVES AND CONCLUSION Future studies should tell whether the mechanisms and sequences evidenced in carriers are comparable to those found in non-carriers, but it is likely that APOE4 not only influences the risk for AD, but also modulates the pathophysiological cascade. Altogether, APOE4 carriers offer a great opportunity to investigate brain changes in the asymptomatic stages of AD and to further our understanding of the pathophysiology of the disease, although precaution is needed for interpretation in AD at large.
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Affiliation(s)
- G Chételat
- Inserm, U1077, CHU de Caen, avenue de la Côte-de-Nacre, CS 30001, 14033 Caen cedex 9, France; UMR-S1077, laboratoire de neuropsychologie campus, université de Caen Basse-Normandie, 5, avenue de la Côte-de-Nacre, 14033 Caen cedex 9, France; UMR-S1077, école pratique des hautes études, avenue de la Côte-de-Nacre, CS 30001, 14033 Caen cedex 9, France.
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Abstract
BACKGROUND New research criteria for preclinical Alzheimer's disease have been proposed, which include stages for cognitively normal individuals with abnormal amyloid markers (stage 1), abnormal amyloid and neuronal injury markers (stage 2), or abnormal amyloid and neuronal injury markers and subtle cognitive changes (stage 3). We aimed to investigate the prevalence and long-term outcome of preclinical Alzheimer's disease according to these criteria. METHODS Participants were cognitively normal (clinical dementia rating [CDR]=0) community-dwelling volunteers aged at least 65 years who were enrolled between 1998 and 2011 at the Washington University School of Medicine (MO, USA). CSF amyloid-β1-42 and tau concentrations and a memory composite score were used to classify participants as normal (both markers normal), preclinical Alzheimer's disease stage 1-3, or suspected non-Alzheimer pathophysiology (SNAP, abnormal injury marker without abnormal amyloid marker). The primary outcome was the proportion of participants in each preclinical AD stage. Secondary outcomes included progression to CDR at least 0·5, symptomatic Alzheimer's disease (score of at least 0·5 for memory and at least one other domain and cognitive impairments deemed to be due to Alzheimer's disease), and mortality. We undertook survival analyses using subdistribution and standard Cox hazards models and linear mixed models. FINDINGS Of 311 participants, 129 (41%) were classed as normal, 47 (15%) as stage 1, 36 (12%) as stage 2, 13 (4%) as stage 3, 72 (23%) as SNAP, and 14 (5%) remained unclassified. The 5-year progression rate to CDR at least 0·5, symptomatic Alzheimer's disease was 2% for participants classed as normal, 11% for stage 1, 26% for stage 2, 56% for stage 3, and 5% for SNAP. Compared with individuals classed as normal, participants with preclinical Alzheimer's disease had an increased risk of death after adjusting for covariates (hazard ratio 6·2, 95% CI 1·1-35·0; p=0·040). INTERPRETATION Preclinical Alzheimer's disease is common in cognitively normal elderly people and is associated with future cognitive decline and mortality. Thus, preclinical Alzheimer's disease could be an important target for therapeutic intervention. FUNDING National Institute of Aging of the National Institutes of Health (P01-AG003991, P50-AG05681, P01-AG02676), Internationale Stichting Alzheimer Onderzoek, the Center for Translational Molecular Medicine project LeARN, the EU/EFPIA Innovative Medicines Initiative Joint Undertaking, and the Charles and Joanne Knight Alzheimer Research Initiative.
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Reinvang I, Espeseth T, Westlye LT. APOE-related biomarker profiles in non-pathological aging and early phases of Alzheimer's disease. Neurosci Biobehav Rev 2013; 37:1322-35. [DOI: 10.1016/j.neubiorev.2013.05.006] [Citation(s) in RCA: 75] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2013] [Revised: 04/10/2013] [Accepted: 05/10/2013] [Indexed: 02/01/2023]
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