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Jurasova V, Andel R, Katonova A, Veverova K, Zuntychova T, Horakova H, Vyhnalek M, Kolarova T, Matoska V, Blennow K, Hort J. CSF neurogranin levels as a biomarker in Alzheimer's disease and frontotemporal lobar degeneration: a cross-sectional analysis. Alzheimers Res Ther 2024; 16:199. [PMID: 39242539 PMCID: PMC11378641 DOI: 10.1186/s13195-024-01566-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 08/24/2024] [Indexed: 09/09/2024]
Abstract
BACKGROUND There is initial evidence suggesting that biomarker neurogranin (Ng) may distinguish Alzheimer's disease (AD) from other neurodegenerative diseases. Therefore, we assessed (a) the discriminant ability of cerebrospinal fluid (CSF) Ng levels to distinguish between AD and frontotemporal lobar degeneration (FTLD) pathology and between different stages within the same disease, (b) the relationship between Ng levels and cognitive performance in both AD and FTLD pathology, and (c) whether CSF Ng levels vary by apolipoprotein E (APOE) polymorphism in the AD continuum. METHODS Participants with subjective cognitive decline (SCD) (n = 33), amnestic mild cognitive impairment (aMCI) due to AD (n = 109), AD dementia (n = 67), MCI due to FTLD (n = 25), and FTLD dementia (n = 29) were recruited from the Czech Brain Aging Study. One-way analysis of covariance (ANCOVA) assessed Ng levels in diagnostic subgroups. Linear regressions evaluated the relationship between CSF Ng levels, memory scores, and APOE polymorphism. RESULTS Ng levels were higher in aMCI-AD patients compared to MCI-FTLD (F[1, 134] = 15.16, p < .001), and in AD-dementia compared to FTLD-dementia (F[1, 96] = 4.60, p = .029). Additionally, Ng levels were higher in FTLD-dementia patients compared to MCI-FTLD (F[1, 54]= 4.35, p = .034), lower in SCD participants compared to aMCI-AD (F[1, 142] = 10.72, p = .001) and AD-dementia (F[1, 100] = 20.90, p < .001), and did not differ between SCD participants and MCI-FTLD (F[1, 58]= 1.02, p = .491) or FTLD-dementia (F[1, 62]= 2.27, p = .051). The main effect of diagnosis across the diagnostic subgroups on Aβ1-42/Ng ratio was significant too (F[4, 263]=, p < .001). We found a non-significant association between Ng levels and memory scores overall (β=-0.25, p = .154) or in AD diagnostic subgroups, and non-significant differences in this association between overall AD APOE ε4 carriers and non-carriers (β=-0.32, p = .358). CONCLUSIONS In this first study to-date to assess MCI and dementia due to AD or FTLD within one study, elevated CSF Ng appears to be an early biomarker of AD-related impairment, but its role as a biomarker appears to diminish after dementia diagnosis, whereby dementia-related underlying processes in AD and FTLD may begin to merge. The Aβ1-42/Ng ratio discriminated AD from FTLD patients better than Ng alone. CSF Ng levels were not related to memory in AD or FTLD, suggesting that Ng may be a marker of the biological signs of disease state rather than cognitive deficits.
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Affiliation(s)
- Vanesa Jurasova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic.
| | - Ross Andel
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, USA
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - Alzbeta Katonova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
| | - Katerina Veverova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
| | - Terezie Zuntychova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
| | - Hana Horakova
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - Martin Vyhnalek
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - Tereza Kolarova
- Department of Clinical Biochemistry, Hematology and Immunology, Homolka Hospital, Prague, Czech Republic
| | - Vaclav Matoska
- Department of Clinical Biochemistry, Hematology and Immunology, Homolka Hospital, Prague, Czech Republic
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jakub Hort
- Memory Clinic, Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
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Jackson RJ, Hyman BT, Serrano-Pozo A. Multifaceted roles of APOE in Alzheimer disease. Nat Rev Neurol 2024; 20:457-474. [PMID: 38906999 DOI: 10.1038/s41582-024-00988-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2024] [Indexed: 06/23/2024]
Abstract
For the past three decades, apolipoprotein E (APOE) has been known as the single greatest genetic modulator of sporadic Alzheimer disease (AD) risk, influencing both the average age of onset and the lifetime risk of developing AD. The APOEε4 allele significantly increases AD risk, whereas the ε2 allele is protective relative to the most common ε3 allele. However, large differences in effect size exist across ethnoracial groups that are likely to depend on both global genetic ancestry and local genetic ancestry, as well as gene-environment interactions. Although early studies linked APOE to amyloid-β - one of the two culprit aggregation-prone proteins that define AD - in the past decade, mounting work has associated APOE with other neurodegenerative proteinopathies and broader ageing-related brain changes, such as neuroinflammation, energy metabolism failure, loss of myelin integrity and increased blood-brain barrier permeability, with potential implications for longevity and resilience to pathological protein aggregates. Novel mouse models and other technological advances have also enabled a number of therapeutic approaches aimed at either attenuating the APOEε4-linked increased AD risk or enhancing the APOEε2-linked AD protection. This Review summarizes this progress and highlights areas for future research towards the development of APOE-directed therapeutics.
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Affiliation(s)
- Rosemary J Jackson
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.
| | - Alberto Serrano-Pozo
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA.
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Delvenne A, Gobom J, Schindler SE, Kate MT, Reus LM, Dobricic V, Tijms BM, Benzinger TLS, Cruchaga C, Teunissen CE, Ramakers I, Martinez-Lage P, Tainta M, Vandenberghe R, Schaeverbeke J, Engelborghs S, Roeck ED, Popp J, Peyratout G, Tsolaki M, Freund-Levi Y, Lovestone S, Streffer J, Barkhof F, Bertram L, Blennow K, Zetterberg H, Visser PJ, Vos SJB. CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease. Alzheimers Dement 2024. [PMID: 38970402 DOI: 10.1002/alz.14103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 06/05/2024] [Accepted: 06/06/2024] [Indexed: 07/08/2024]
Abstract
INTRODUCTION We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. METHODS Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. RESULTS Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. DISCUSSION Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. HIGHLIGHTS In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.
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Affiliation(s)
- Aurore Delvenne
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Johan Gobom
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Mara Ten Kate
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Lianne M Reus
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam University Medical Centers (AUMC), Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Inez Ramakers
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | - Mikel Tainta
- Fundación CITA-Alzhéimer Fundazioa, Donostia, Spain
| | - Rik Vandenberghe
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Jolien Schaeverbeke
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Bru-BRAIN, Universitair Ziekenhuis Brussel and NEUR Research Group, Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Julius Popp
- Old Age Psychiatry, University Hospital Lausanne, Lausanne, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatry University Hospital Zürich, Zürich, Switzerland
| | | | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Medical School, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Thessaloniki, Greece
| | - Yvonne Freund-Levi
- Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, Huddinge, Stockholm, Sweden
- Department of Psychiatry in Region Örebro County and School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Old Age Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Simon Lovestone
- University of Oxford, United Kingdom (currently at Johnson and Johnson Medical Ltd., Oxford, UK
| | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- H. Lundbeck A/S, Valby, Denmark
| | - Frederik Barkhof
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Bonanni R, Cariati I, Cifelli P, Frank C, Annino G, Tancredi V, D'Arcangelo G. Exercise to Counteract Alzheimer's Disease: What Do Fluid Biomarkers Say? Int J Mol Sci 2024; 25:6951. [PMID: 39000060 PMCID: PMC11241657 DOI: 10.3390/ijms25136951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 06/14/2024] [Accepted: 06/22/2024] [Indexed: 07/16/2024] Open
Abstract
Neurodegenerative diseases (NDs) represent an unsolved problem to date with an ever-increasing population incidence. Particularly, Alzheimer's disease (AD) is the most widespread ND characterized by an accumulation of amyloid aggregates of beta-amyloid (Aβ) and Tau proteins that lead to neuronal death and subsequent cognitive decline. Although neuroimaging techniques are needed to diagnose AD, the investigation of biomarkers within body fluids could provide important information on neurodegeneration. Indeed, as there is no definitive solution for AD, the monitoring of these biomarkers is of strategic importance as they are useful for both diagnosing AD and assessing the progression of the neurodegenerative state. In this context, exercise is known to be an effective non-pharmacological management strategy for AD that can counteract cognitive decline and neurodegeneration. However, investigation of the concentration of fluid biomarkers in AD patients undergoing exercise protocols has led to unclear and often conflicting results, suggesting the need to clarify the role of exercise in modulating fluid biomarkers in AD. Therefore, this critical literature review aims to gather evidence on the main fluid biomarkers of AD and the modulatory effects of exercise to clarify the efficacy and usefulness of this non-pharmacological strategy in counteracting neurodegeneration in AD.
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Affiliation(s)
- Roberto Bonanni
- Department of Biomedicine and Prevention, "Tor Vergata" University of Rome, 00133 Rome, Italy
| | - Ida Cariati
- Department of Systems Medicine, "Tor Vergata" University of Rome, 00133 Rome, Italy
| | - Pierangelo Cifelli
- Department of Applied Clinical and Biotechnological Sciences, University of L'Aquila, 67100 L'Aquila, Italy
| | - Claudio Frank
- UniCamillus-Saint Camillus International University of Health Sciences, 00131 Rome, Italy
| | - Giuseppe Annino
- Department of Systems Medicine, "Tor Vergata" University of Rome, 00133 Rome, Italy
- Centre of Space Bio-Medicine, "Tor Vergata" University of Rome, 00133 Rome, Italy
- Sports Engineering Laboratory, Department of Industrial Engineering, "Tor Vergata" University of Rome, 00133 Rome, Italy
| | - Virginia Tancredi
- Department of Systems Medicine, "Tor Vergata" University of Rome, 00133 Rome, Italy
- Centre of Space Bio-Medicine, "Tor Vergata" University of Rome, 00133 Rome, Italy
| | - Giovanna D'Arcangelo
- Department of Systems Medicine, "Tor Vergata" University of Rome, 00133 Rome, Italy
- Centre of Space Bio-Medicine, "Tor Vergata" University of Rome, 00133 Rome, Italy
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Li Y, Yen D, Hendrix RD, Gordon BA, Dlamini S, Barthélemy NR, Aschenbrenner AJ, Henson RL, Herries EM, Volluz K, Kirmess K, Eastwood S, Meyer M, Heller M, Jarrett L, McDade E, Holtzman DM, Benzinger TL, Morris JC, Bateman RJ, Xiong C, Schindler SE. Timing of Biomarker Changes in Sporadic Alzheimer's Disease in Estimated Years from Symptom Onset. Ann Neurol 2024; 95:951-965. [PMID: 38400792 PMCID: PMC11060905 DOI: 10.1002/ana.26891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/26/2023] [Accepted: 01/30/2024] [Indexed: 02/26/2024]
Abstract
OBJECTIVE A clock relating amyloid positron emission tomography (PET) to time was used to estimate the timing of biomarker changes in sporadic Alzheimer disease (AD). METHODS Research participants were included who underwent cerebrospinal fluid (CSF) collection within 2 years of amyloid PET. The ages at amyloid onset and AD symptom onset were estimated for each individual. The timing of change for plasma, CSF, imaging, and cognitive measures was calculated by comparing restricted cubic splines of cross-sectional data from the amyloid PET positive and negative groups. RESULTS The amyloid PET positive sub-cohort (n = 118) had an average age of 70.4 ± 7.4 years (mean ± standard deviation) and 16% were cognitively impaired. The amyloid PET negative sub-cohort (n = 277) included individuals with low levels of amyloid plaque burden at all scans who were cognitively unimpaired at the time of the scans. Biomarker changes were detected 15-19 years before estimated symptom onset for CSF Aβ42/Aβ40, plasma Aβ42/Aβ40, CSF pT217/T217, and amyloid PET; 12-14 years before estimated symptom onset for plasma pT217/T217, CSF neurogranin, CSF SNAP-25, CSF sTREM2, plasma GFAP, and plasma NfL; and 7-9 years before estimated symptom onset for CSF pT205/T205, CSF YKL-40, hippocampal volumes, and cognitive measures. INTERPRETATION The use of an amyloid clock enabled visualization and analysis of biomarker changes as a function of estimated years from symptom onset in sporadic AD. This study demonstrates that estimated years from symptom onset based on an amyloid clock can be used as a continuous staging measure for sporadic AD and aligns with findings in autosomal dominant AD. ANN NEUROL 2024;95:951-965.
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Affiliation(s)
- Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel Yen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Rachel D. Hendrix
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian A. Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sibonginkhosi Dlamini
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicolas R. Barthélemy
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Rachel L. Henson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Elizabeth M. Herries
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Katherine Volluz
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | | | | | | | - Maren Heller
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Lea Jarrett
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric McDade
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer 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 Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, 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 Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
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Shue F, White LJ, Hendrix R, Ulrich J, Henson RL, Knight W, Martens YA, Wang N, Roy B, Starling SC, Ren Y, Xiong C, Asmann YW, Syrjanen JA, Vassilaki M, Mielke MM, Timsina J, Sung YJ, Cruchaga C, Holtzman DM, Bu G, Petersen RC, Heckman MG, Kanekiyo T. CSF biomarkers of immune activation and Alzheimer's disease for predicting cognitive impairment risk in the elderly. SCIENCE ADVANCES 2024; 10:eadk3674. [PMID: 38569027 PMCID: PMC10990276 DOI: 10.1126/sciadv.adk3674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 02/23/2024] [Indexed: 04/05/2024]
Abstract
The immune system substantially influences age-related cognitive decline and Alzheimer's disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 (N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aβ42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aβ42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aβ42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.
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Affiliation(s)
- Francis Shue
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Launia J. White
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Rachel Hendrix
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jason Ulrich
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Rachel L. Henson
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - William Knight
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yuka A. Martens
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Ni Wang
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Bhaskar Roy
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | - Yingxue Ren
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 93110, USA
| | - Yan W. Asmann
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Jeremy A. Syrjanen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester MN 55905, USA
| | - Maria Vassilaki
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester MN 55905, USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester MN 55905, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 93110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 93110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 93110, USA
| | - David M. Holtzman
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Guojun Bu
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | - Michael G. Heckman
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Takahisa Kanekiyo
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
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Malek-Ahmadi M, Su Y, Ghisays V, Luo J, Devadas V, Chen Y, Lee W, Protas H, Chen K, Zetterberg H, Blennow K, Caselli RJ, Reiman EM. Plasma NfL is associated with the APOE ε4 allele, brain imaging measurements of neurodegeneration, and lower recall memory scores in cognitively unimpaired late-middle-aged and older adults. Alzheimers Res Ther 2023; 15:74. [PMID: 37038190 PMCID: PMC10084600 DOI: 10.1186/s13195-023-01221-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 03/28/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Plasma neurofilament light (NfL) is an indicator of neurodegeneration and/or neuroaxonal injury in persons with Alzheimer's disease (AD) and a wide range of other neurological disorders. Here, we characterized and compared plasma NfL concentrations in cognitively unimpaired (CU) late-middle-aged and older adults with two, one, or no copies of the APOE ε4 allele, the major genetic risk factor for AD. We then assessed plasma NfL associations with brain imaging measurements of AD-related neurodegeneration (hippocampal atrophy and a hypometabolic convergence index [HCI]), brain imaging measurements of amyloid-β plaque burden, tau tangle burden and white matter hyperintensity volume (WMHV), and delayed and total recall memory scores. METHODS Plasma NfL concentrations were measured in 543 CU 69 ± 9 year-old participants in the Arizona APOE Cohort Study, including 66 APOE ε4 homozygotes (HM), 165 heterozygotes (HT), and 312 non-carriers (NC). Robust regression models were used to characterize plasma NfL associations with APOE ε4 allelic dose before and after adjustment for age, sex, and education. They were also used to characterize plasma NfL associations with MRI-based hippocampal volume and WMHV measurements, an FDG PET-based HCI, mean cortical PiB PET measurements of amyloid-β plaque burden and meta-region-of-interest (meta-ROI) flortaucipir PET measurements of tau tangle burden, and Auditory Verbal Learning Test (AVLT) Delayed and Total Recall Memory scores. RESULTS After the adjustments noted above, plasma NfL levels were significantly greater in APOE ε4 homozygotes and heterozygotes than non-carriers and significantly associated with smaller hippocampal volumes (r = - 0.43), greater tangle burden in the entorhinal cortex and inferior temporal lobes (r = 0.49, r = 0.52, respectively), and lower delayed (r = - 0.27), and total (r = - 0.27) recall memory scores (p < 0.001). NfL levels were not significantly associated with PET measurements of amyloid-β plaque or total tangle burden. CONCLUSIONS Plasma NfL concentrations are associated with the APOE ε4 allele, brain imaging biomarkers of neurodegeneration, and less good recall memory in CU late-middle-aged and older adults, supporting its value as an indicator of neurodegeneration in the preclinical study of AD.
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Affiliation(s)
| | - Yi Su
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Valentina Ghisays
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Ji Luo
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Vivek Devadas
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Yinghua Chen
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Wendy Lee
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Hillary Protas
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Kewei Chen
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Eric M Reiman
- Banner Alzheimer's Institute, 901 E. Willetta St., Phoenix, AZ, 85006, USA
- Translation Genomics Research Institute, Phoenix, AZ, USA
- University of Arizona, Phoenix, AZ, USA
- Arizona State University, Tempe, AZ, USA
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Raulin AC, Doss SV, Trottier ZA, Ikezu TC, Bu G, Liu CC. ApoE in Alzheimer’s disease: pathophysiology and therapeutic strategies. Mol Neurodegener 2022; 17:72. [PMID: 36348357 PMCID: PMC9644639 DOI: 10.1186/s13024-022-00574-4] [Citation(s) in RCA: 143] [Impact Index Per Article: 71.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 10/08/2022] [Accepted: 10/13/2022] [Indexed: 11/10/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common cause of dementia worldwide, and its prevalence is rapidly increasing due to extended lifespans. Among the increasing number of genetic risk factors identified, the apolipoprotein E (APOE) gene remains the strongest and most prevalent, impacting more than half of all AD cases. While the ε4 allele of the APOE gene significantly increases AD risk, the ε2 allele is protective relative to the common ε3 allele. These gene alleles encode three apoE protein isoforms that differ at two amino acid positions. The primary physiological function of apoE is to mediate lipid transport in the brain and periphery; however, additional functions of apoE in diverse biological functions have been recognized. Pathogenically, apoE seeds amyloid-β (Aβ) plaques in the brain with apoE4 driving earlier and more abundant amyloids. ApoE isoforms also have differential effects on multiple Aβ-related or Aβ-independent pathways. The complexity of apoE biology and pathobiology presents challenges to designing effective apoE-targeted therapeutic strategies. This review examines the key pathobiological pathways of apoE and related targeting strategies with a specific focus on the latest technological advances and tools.
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Cerebrospinal fluid growth-associated protein 43 levels in patients with progressive and stable mild cognitive impairment. Aging Clin Exp Res 2022; 34:2399-2406. [DOI: 10.1007/s40520-022-02202-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/17/2022] [Indexed: 11/25/2022]
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Liu Q, Liu H, Zhang S, Yang Q, Shen L, Jiao B. Cerebrospinal Fluid Synaptosomal-Associated Protein 25 Levels in Patients with Alzheimer’s Disease: A Meta-Analysis. J Alzheimers Dis 2022; 89:121-132. [PMID: 35848017 DOI: 10.3233/jad-215696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Several studies have shown increased levels of cerebrospinal fluid (CSF) synaptosomal-associated protein 25 (SNAP-25) in patients with Alzheimer’s disease (AD). However, results have been inconsistent thus far. Objective: We conducted meta-analyses summarizing the associations of CSF SNAP-25 levels with AD to assess the utility of SNAP-25 as a novel biomarker for AD. Methods: We conducted a meta-analysis of differences in CSF SNAP-25 levels in patients with AD or mild cognitive impairment (MCI) and in cognitively healthy controls (HC). We calculated pooled correlation coefficients comparing SNAP-25 levels and total tau (T-tau) or hyperphosphorylated tau (P-tau) in CSF. Results: Eight studies enrolling 1,162 individuals (423 AD, 275 MCI, 464 HC) were included for quantitative analysis. Patients with AD (ratio of means [RoM] = 1.50, 95% confidence interval [CI]: 1.30,1.74) and MCI (RoM = 1.45, 95% CI: 1.12,1.87) had increased levels of CSF SNAP-25 as compared to HC. The difference in CSF SNAP-25 levels when comparing AD and MCI (RoM = 1.05, 95% CI: 0.96,1.14) was not statistically significant but showed a trend toward significance. Statistically significant correlations were found when comparing CSF SNAP-25 with CSF T-tau (Spearman correlation coefficient, ρ=0.78; ρ=0.66; ρ=0.69, respectively) and P-tau (ρ=0.66; ρ=0.70; ρ=0.62, respectively) levels in patients with AD, MCI, and HC. Conclusion: Increased CSF SNAP-25 levels differentiated patients with AD or MCI from controls, suggesting the utility of this biomarker in the early diagnosis of AD.
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Affiliation(s)
- Qianqian Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Hui Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Sizhe Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qijie Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China
- Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Bin Jiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China
- Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha, China
- Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
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Hawksworth J, Fernández E, Gevaert K. A new generation of AD biomarkers: 2019 to 2021. Ageing Res Rev 2022; 79:101654. [PMID: 35636691 DOI: 10.1016/j.arr.2022.101654] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 05/17/2022] [Accepted: 05/25/2022] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) is the most common form of dementia and cases are rising worldwide. The effort to fight this disease is hampered by a lack of disease-modifying treatments and the absence of an early, accurate diagnostic tool. Neuropathology begins years or decades before symptoms occur and, upon onset of symptoms, diagnosis can take a year or more. Such delays postpone treatment and make research into the early stages of the disease difficult. Ideally, clinicians require a minimally invasive test that can detect AD in its early stages, before cognitive symptoms occur. Advances in proteomic technologies have facilitated the study of promising biomarkers of AD. Over the last two years (2019-2021) studies have identified and validated many species which can be measured in cerebrospinal fluid (CSF), plasma, or in both fluids, and which have a high predictive value for AD. We herein discuss proteins which have been highlighted as promising biomarkers of AD in the last two years, and consider implications for future research within the research framework of the amyloid (A), tau (T), neurodegeneration (N) scoring system. We review recently identified species of amyloid and tau which may improve diagnosis when used in combination with current measures such as amyloid-beta-42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau). In addition, several proteins have been identified as likely proxies for neurodegeneration, including neurofilament light (NfL), synaptosomal-associated protein 25 (SNAP-25) and neurogranin (NRGN). Finally, proteins originating from diverse processes such as neuroinflammation, lipid transport and mitochondrial dysfunction could aid in both AD diagnosis and patient stratification.
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Timsina J, Gomez-Fonseca D, Wang L, Do A, Western D, Alvarez I, Aguilar M, Pastor P, Henson RL, Herries E, Xiong C, Schindler SE, Fagan AM, Bateman RJ, Farlow M, Morris JC, Perrin R, Moulder K, Hassenstab J, Chhatwal J, Mori H, Sung YJ, Cruchaga C. Comparative Analysis of Alzheimer's Disease Cerebrospinal Fluid Biomarkers Measurement by Multiplex SOMAscan Platform and Immunoassay-Based Approach. J Alzheimers Dis 2022; 89:193-207. [PMID: 35871346 PMCID: PMC9562128 DOI: 10.3233/jad-220399] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
BACKGROUND The SOMAscan assay has an advantage over immunoassay-based methods because it measures a large number of proteins in a cost-effective manner. However, the performance of this technology compared to the routinely used immunoassay techniques needs to be evaluated. OBJECTIVE We performed comparative analyses of SOMAscan and immunoassay-based protein measurements for five cerebrospinal fluid (CSF) proteins associated with Alzheimer's disease (AD) and neurodegeneration: NfL, Neurogranin, sTREM2, VILIP-1, and SNAP-25. METHODS We compared biomarkers measured in ADNI (N = 689), Knight-ADRC (N = 870), DIAN (N = 115), and Barcelona-1 (N = 92) cohorts. Raw protein values were transformed using z-score in order to combine measures from the different studies. sTREM2 and VILIP-1 had more than one analyte in SOMAscan; all available analytes were evaluated. Pearson's correlation coefficients between SOMAscan and immunoassays were calculated. Receiver operating characteristic curve and area under the curve were used to compare prediction accuracy of these biomarkers between the two platforms. RESULTS Neurogranin, VILIP-1, and NfL showed high correlation between SOMAscan and immunoassay measures (r > 0.9). sTREM2 had a fair correlation (r > 0.6), whereas SNAP-25 showed weak correlation (r = 0.06). Measures in both platforms provided similar predicted performance for all biomarkers except SNAP-25 and one of the sTREM2 analytes. sTREM2 showed higher AUC for SOMAscan based measures. CONCLUSION Our data indicate that SOMAscan performs as well as immunoassay approaches for NfL, Neurogranin, VILIP-1, and sTREM2. Our study shows promise for using SOMAscan as an alternative to traditional immunoassay-based measures. Follow-up investigation will be required for SNAP-25 and additional established biomarkers.
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Affiliation(s)
- Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Duber Gomez-Fonseca
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Anh Do
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Dan Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Ignacio Alvarez
- Memory Disorders Unit, Department of Neurology, University Hospital Mutua Terrassa, Terrassa, Spain
| | - Miquel Aguilar
- Memory Disorders Unit, Department of Neurology, University Hospital Mutua Terrassa, Terrassa, Spain
| | - Pau Pastor
- Memory Disorders Unit, Department of Neurology, University Hospital Mutua Terrassa, Terrassa, Spain
| | - Rachel L. Henson
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Elizabeth Herries
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E. Schindler
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M. Fagan
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J. Bateman
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Martin Farlow
- Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Health, Indianapolis, IN, USA
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Richard Perrin
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Pathology & Immunology, Washington University School of Medicine, St Louis, MO, USA
| | - Krista Moulder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Hiroshi Mori
- Dept. of Clinical Neuroscience, Osaka City University Medical School, Nagaoka Sutoku University, Japan
| | | | | | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO, USA
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