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Gurdon B, Yates SC, Csucs G, Groeneboom NE, Hadad N, Telpoukhovskaia M, Ouellette A, Ouellette T, O'Connell KMS, Singh S, Murdy TJ, Merchant E, Bjerke I, Kleven H, Schlegel U, Leergaard TB, Puchades MA, Bjaalie JG, Kaczorowski CC. Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model. Commun Biol 2024; 7:605. [PMID: 38769398 PMCID: PMC11106287 DOI: 10.1038/s42003-024-06242-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 04/24/2024] [Indexed: 05/22/2024] Open
Abstract
Alzheimer's disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.
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Affiliation(s)
- Brianna Gurdon
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
| | - Sharon C Yates
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Gergely Csucs
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Nicolaas E Groeneboom
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Niran Hadad
- The Jackson Laboratory, Bar Harbor, ME, USA
- Translational Genomics Research Institute, Phoenix, AZ, USA
| | | | - Andrew Ouellette
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
| | - Tionna Ouellette
- The Jackson Laboratory, Bar Harbor, ME, USA
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA
| | - Kristen M S O'Connell
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA
| | - Surjeet Singh
- The Jackson Laboratory, Bar Harbor, ME, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Ingvild Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Heidi Kleven
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ulrike Schlegel
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
| | - Catherine C Kaczorowski
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA.
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA.
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA.
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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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Lopez E, Etxebarria-Elezgarai J, García-Sebastián M, Altuna M, Ecay-Torres M, Estanga A, Tainta M, López C, Martínez-Lage P, Amigo JM, Seifert A. Unlocking Preclinical Alzheimer's: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics. Int J Mol Sci 2024; 25:4737. [PMID: 38731955 PMCID: PMC11084676 DOI: 10.3390/ijms25094737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 04/23/2024] [Accepted: 04/24/2024] [Indexed: 05/13/2024] Open
Abstract
Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods.
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Affiliation(s)
- Eneko Lopez
- CIC nanoGUNE BRTA, 20018 San Sebasián, Spain; (E.L.); (J.E.-E.)
- Department of Physics, University of the Basque Country (UPV/EHU), 20018 San Sebastián, Spain
| | | | - Maite García-Sebastián
- Center for Research and Advanced Therapies, CITA-Alzhéimer Foundation, 20009 San Sebastián, Spain; (M.G.-S.); (M.A.); (M.E.-T.); (A.E.); (M.T.); (C.L.); (P.M.-L.)
| | - Miren Altuna
- Center for Research and Advanced Therapies, CITA-Alzhéimer Foundation, 20009 San Sebastián, Spain; (M.G.-S.); (M.A.); (M.E.-T.); (A.E.); (M.T.); (C.L.); (P.M.-L.)
| | - Mirian Ecay-Torres
- Center for Research and Advanced Therapies, CITA-Alzhéimer Foundation, 20009 San Sebastián, Spain; (M.G.-S.); (M.A.); (M.E.-T.); (A.E.); (M.T.); (C.L.); (P.M.-L.)
| | - Ainara Estanga
- Center for Research and Advanced Therapies, CITA-Alzhéimer Foundation, 20009 San Sebastián, Spain; (M.G.-S.); (M.A.); (M.E.-T.); (A.E.); (M.T.); (C.L.); (P.M.-L.)
| | - Mikel Tainta
- Center for Research and Advanced Therapies, CITA-Alzhéimer Foundation, 20009 San Sebastián, Spain; (M.G.-S.); (M.A.); (M.E.-T.); (A.E.); (M.T.); (C.L.); (P.M.-L.)
| | - Carolina López
- Center for Research and Advanced Therapies, CITA-Alzhéimer Foundation, 20009 San Sebastián, Spain; (M.G.-S.); (M.A.); (M.E.-T.); (A.E.); (M.T.); (C.L.); (P.M.-L.)
| | - Pablo Martínez-Lage
- Center for Research and Advanced Therapies, CITA-Alzhéimer Foundation, 20009 San Sebastián, Spain; (M.G.-S.); (M.A.); (M.E.-T.); (A.E.); (M.T.); (C.L.); (P.M.-L.)
| | - Jose Manuel Amigo
- IKERBASQUE, Basque Foundation for Science, 48009 Bilbao, Spain
- Department of Analytical Chemistry, University of the Basque Country, 48940 Leioa, Spain
| | - Andreas Seifert
- CIC nanoGUNE BRTA, 20018 San Sebasián, Spain; (E.L.); (J.E.-E.)
- IKERBASQUE, Basque Foundation for Science, 48009 Bilbao, Spain
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Xiong C, Schindler SE, Henson RL, Wolk D, Shaw LM, Agboola F, Morris JC, Lu R, Luo J. Correlational analyses of biomarkers that are harmonized through a bridging study due to measurement errors. Stat Methods Med Res 2024; 33:185-202. [PMID: 37994004 PMCID: PMC10939855 DOI: 10.1177/09622802231215810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Evaluating correlations between disease biomarkers and clinical outcomes is crucial in biomedical research. During the early stages of many chronic diseases, changes in biomarkers and clinical outcomes are often subtle. A major challenge to detecting subtle correlations is that studies with large sample sizes are usually needed to achieve sufficient statistical power. This challenge is even greater when biofluid and imaging biomarker data are used because the required procedures are burdensome, perceived as invasive, and/or expensive, limiting sample sizes in individual studies. Combining data across multiple studies may increase statistical power, but biomarker data may be generated using different assay platforms, scanner types, or processing protocols, which may affect measured biomarker values. Therefore, harmonizing biomarker data is essential to combining data across studies. Bridging studies involve re-processing of a subset of samples or imaging scans to evaluate how biomarker values vary by studies. This presents an analytic challenge on how to best harmonize biomarker data across studies to allow unbiased and optimal estimates of their correlations with standardized clinical outcomes. We conceptualize that a latent biomarker underlies the observed biomarkers across studies, and propose a novel approach that integrates the data in the bridging study with the study-specific biomarker data for estimating the biological correlations between biomarkers and clinical outcomes. Through extensive simulations, we compare our method to several alternative methods/algorithms often used to estimate the correlations. Finally, we demonstrate the application of this methodology to a real-world multi-center Alzheimer's disease biomarker study to correlate cerebrospinal fluid biomarker concentrations with cognitive outcomes.
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Affiliation(s)
- Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E. Schindler
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Rachel L. Henson
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David Wolk
- Perelman School of Medicine, University of Pennsylvania
| | - Leslie M. Shaw
- Perelman School of Medicine, University of Pennsylvania
- Department of Pathology and Laboratory Medicine, University of Pennsylvania
| | - Folasade Agboola
- Division of Biostatistics, 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
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Departments of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Ruijin Lu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Jingqin Luo
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA
- Siteman Cancer Center Biostatistics Core, Washington University School of Medicine, St. Louis, MO, USA
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Angelopoulou E, Bougea A, Hatzimanolis A, Stefanis L, Scarmeas N, Papageorgiou S. Mild Behavioral Impairment in Parkinson's Disease: An Updated Review on the Clinical, Genetic, Neuroanatomical, and Pathophysiological Aspects. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:115. [PMID: 38256375 PMCID: PMC10820007 DOI: 10.3390/medicina60010115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 12/30/2023] [Accepted: 01/05/2024] [Indexed: 01/24/2024]
Abstract
Neuropsychiatric symptoms (NPS), including depression, anxiety, apathy, visual hallucinations, and impulse control disorders, are very common during the course of Parkinson's disease (PD), occurring even at the prodromal and premotor stages. Mild behavioral impairment (MBI) represents a recently described neurobehavioral syndrome, characterized by the emergence of persistent and impactful NPS in later life, reflecting arisk of dementia. Accumulating evidence suggests that MBI is highly prevalent in non-demented patients with PD, also being associated with an advanced disease stage, more severe motor deficits, as well as global and multiple-domain cognitive impairment. Neuroimaging studies have revealed that MBI in patients with PD may be related todistinct patterns of brain atrophy, altered neuronal connectivity, and distribution of dopamine transporter (DAT) depletion, shedding more light on its pathophysiological background. Genetic studies in PD patients have also shown that specific single-nucleotide polymorphisms (SNPs) may be associated with MBI, paving the way for future research in this field. In this review, we summarize and critically discuss the emerging evidence on the frequency, associated clinical and genetic factors, as well as neuroanatomical and neurophysiological correlates of MBI in PD, aiming to elucidate the underlying pathophysiology and its potential role as an early "marker" of cognitive decline, particularly in this population. In addition, we aim to identify research gaps, and propose novel relative areas of interest that could aid in our better understanding of the relationship of this newly defined diagnostic entity with PD.
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Affiliation(s)
- Efthalia Angelopoulou
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
| | - Anastasia Bougea
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
| | - Alexandros Hatzimanolis
- Department of Psychiatry, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece;
| | - Leonidas Stefanis
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
| | - Nikolaos Scarmeas
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
- Department of Neurology, Columbia University, New York, NY 10032, USA
| | - Sokratis Papageorgiou
- Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece; (E.A.); (L.S.); (N.S.); (S.P.)
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Alshaheri Durazo A, Weigand AJ, Bangen KJ, Membreno R, Mudaliar S, Thomas KR. Type 2 Diabetes Moderates the Association Between Amyloid and 1-Year Change in Everyday Functioning in Older Veterans. J Alzheimers Dis 2024; 97:219-228. [PMID: 38160359 DOI: 10.3233/jad-230917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) affects ∼25% of Veterans, a prevalence rate double that of the general population. T2DM is associated with greater dementia risk and has been shown to exacerbate the impact of Alzheimer's disease (AD) risk factors on declines in daily functioning; however, there are few studies that investigate these patterns in older Veterans. OBJECTIVE This study sought to determine whether T2DM moderates the association between amyloid-β (Aβ) positron emission tomography (PET) and 1-year change in everyday functioning in older Veterans. METHODS One-hundred-ninety-eight predominately male Vietnam-Era Veterans without dementia from the Department of Defense-Alzheimer's Disease Neuroimaging Initiative (DoD-ADNI) with (n = 74) and without (n = 124) T2DM completed Aβ PET imaging and everyday functioning measures, including the Clinical Dementia Rating-Sum of Boxes (CDR-SB) and Everyday Cognition (ECog). Linear mixed effects models tested the moderating role of T2DM on the association between Aβ PET and 1-year change in everyday functioning. RESULTS The 3-way T2DM×Aβ PET×time interaction was significant for CDR-SB (p < 0.001) as well as the Memory (p = 0.007) and Language (p = 0.011) subscales from the ECog. Greater amyloid burden was associated with greater increases in functional difficulties, but only in Veterans with T2DM. CONCLUSIONS Higher Aβ was only associated with declines in everyday functioning over 1 year in Veterans with T2DM. Given that people with T2DM are more likely to have co-occurring cerebrovascular disease, the combination of multiple neuropathologies may result in faster declines. Future studies should examine how diabetes duration, severity, and medications impact these associations.
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Affiliation(s)
- Alin Alshaheri Durazo
- San Diego State University, San Diego, CA, USA
- VA San Diego Healthcare System, San Diego, CA, USA
| | - Alexandra J Weigand
- San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Katherine J Bangen
- VA San Diego Healthcare System, San Diego, CA, USA
- University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Rachel Membreno
- San Diego State University, San Diego, CA, USA
- VA San Diego Healthcare System, San Diego, CA, USA
| | - Sunder Mudaliar
- VA San Diego Healthcare System, San Diego, CA, USA
- University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Kelsey R Thomas
- VA San Diego Healthcare System, San Diego, CA, USA
- University of California, San Diego School of Medicine, La Jolla, CA, USA
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Babulal GM, Chen L, Murphy SA, Doherty JM, Johnson AM, Morris JC. Neuropsychiatric Symptoms and Alzheimer Disease Biomarkers Independently Predict Progression to Incident Cognitive Impairment. Am J Geriatr Psychiatry 2023; 31:1190-1199. [PMID: 37544835 PMCID: PMC10861300 DOI: 10.1016/j.jagp.2023.07.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/21/2023] [Accepted: 07/21/2023] [Indexed: 08/08/2023]
Abstract
OBJECTIVES To investigate the effect of neuropsychiatric symptoms and depression symptoms, respectively, and Alzheimer disease (AD) biomarkers (cerebrospinal fluid [CSF] or Positron Emission Tomography [PET] imaging) on the progression to incident cognitive impairment among cognitively normal older adults. DESIGN Prospective, observation, longitudinal study. SETTING Knight Alzheimer Disease Research Center (ADRC) at Washington University School of Medicine. PARTICIPANTS Older adults aged 65 and above who participated in AD longitudinal studies (n = 286). MEASUREMENTS CSF and PET biomarkers, Clinical Dementia Rating (CDR), Geriatric Depression Scale (GDS), and Neuropsychiatric Inventory Questionnaire (NPI-Q). RESULTS Participants had an average follow-up of eight years, and 31 progressed from CDR 0 to CDR >0. After adjusting for sex, age, and education in the Cox proportional hazards survival models, neuropsychiatric symptoms as a time-dependent covariate was statistically significant in the three CSF (Aβ42/Aβ40, t-Tau/Aβ42, p-Tau/Aβ42) PET imaging models (HR = 1.33-1.50). The biomarkers were also significant as main effects (HR = 2.00-4.04). Change in depression symptoms was not significant in any models. The interactions between biomarkers and neuropsychiatric symptoms and depression were not statistically significant. CONCLUSIONS Changes in neuropsychiatric symptoms increase the risk of progression to cognitive impairment among healthy, cognitively normal adults, independent of AD biomarkers. Routine assessment of neuropsychiatric symptoms could provide valuable clinical information about cognitive functioning and preclinical disease state.
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Affiliation(s)
- Ganesh M Babulal
- Department of Neurology (GMB, SAM, JCM), Washington University in St. Louis, St. Louis, MO; Institute of Public Health (GMB), Washington University in St. Louis, St. Louis, MO; Department of Psychology, Faculty of Humanities (GMB), University of Johannesburg, Johannesburg, South Africa; Department of Clinical Research and Leadership (GMB), The George Washington University School of Medicine and Health Sciences, Washington, DC.
| | - Ling Chen
- Division of Biostatistics (LC), Washington University in St. Louis, St. Louis, MO
| | - Samantha A Murphy
- Department of Neurology (GMB, SAM, JCM), Washington University in St. Louis, St. Louis, MO
| | - Jason M Doherty
- Department of Neurology (GMB, SAM, JCM), Washington University in St. Louis, St. Louis, MO
| | - Ann M Johnson
- Center for Clinical Studies (AMJ), Washington University in St. Louis, St. Louis, MO
| | - John C Morris
- Department of Neurology (GMB, SAM, JCM), Washington University in St. Louis, St. Louis, MO; Hope Center for Neurological Disorders (JCM), Washington University in St. Louis, St. Louis, MO
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Wang ZB, Tan L, Gao PY, Ma YH, Fu Y, Sun Y, Yu JT. Associations of the A/T/N profiles in PET, CSF, and plasma biomarkers with Alzheimer's disease neuropathology at autopsy. Alzheimers Dement 2023; 19:4421-4435. [PMID: 37506291 DOI: 10.1002/alz.13413] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/03/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023]
Abstract
INTRODUCTION To examine the extent to which positron emission tomography (PET)-, cerebrospinal fluid (CSF)-, and plasma-related amyloid-β/tau/neurodegeneration (A/T/N) biomarkers are associated with Alzheimer's disease (AD) neuropathology at autopsy. METHODS A total of 100 participants who respectively underwent antemortem biomarker measurements and postmortem neuropathology were included in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We examined the associations of PET-, CSF-, and plasma-related A/T/N biomarkers in combinations or alone with AD neuropathological changes (ADNC). RESULTS PET- and CSF-related A/T/N biomarkers in combination showed high concordance with the ADNC stage and alone showed high accuracy in discriminating autopsy-confirmed AD. However, the plasma-related A/T/N biomarkers alone showed better discriminative performance only when combined with apolipoprotein E (APO)E ε4 genotype. DISCUSSION This study supports that PET- and CSF-related A/T/N profiles can be used to predict accurately the stages of AD neuropathology. For diagnostic settings, PET-, CSF-, and plasma-related A/T/N biomarkers are all useful diagnostic tools to detect the presence of AD neuropathology. HIGHLIGHTS PET- and CSF-related A/T/N biomarkers in combination can accurately predict the specific stages of AD neuropathology. PET- and CSF-related A/T/N biomarkers alone may serve as a precise diagnostic tool for detecting AD neuropathology at autopsy. Plasma-related A/T/N biomarkers may need combined risk factors when used as a diagnostic tool. Aβ PET and CSF p-tau181/Aβ42 were most consistent with Aβ pathology, while tau PET and CSF p-tau181/Aβ42 were most consistent with tau pathology.
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Affiliation(s)
- Zhi-Bo Wang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Sun
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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9
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Motta C, Di Donna MG, Bonomi CG, Assogna M, Chiaravalloti A, Mercuri NB, Koch G, Martorana A. Different associations between amyloid-βeta 42, amyloid-βeta 40, and amyloid-βeta 42/40 with soluble phosphorylated-tau and disease burden in Alzheimer's disease: a cerebrospinal fluid and fluorodeoxyglucose-positron emission tomography study. Alzheimers Res Ther 2023; 15:144. [PMID: 37649105 PMCID: PMC10466826 DOI: 10.1186/s13195-023-01291-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: 05/25/2023] [Accepted: 08/18/2023] [Indexed: 09/01/2023]
Abstract
BACKGROUND Despite the high sensitivity of cerebrospinal fluid (CSF) amyloid beta (Aβ)42 to detect amyloid pathology, the Aβ42/Aβ40 ratio (amyR) better estimates amyloid load, with higher specificity for Alzheimer's disease (AD). However, whether Aβ42 and amyR have different meanings and whether Aβ40 represents more than an Aβ42-corrective factor remain to be clarified. Our study aimed to compare the ability of Aβ42 and amyR to detect AD pathology in terms of p-tau/Aβ42 ratio and brain glucose metabolic patterns using fluorodeoxyglucose-positron emission tomography (FDG-PET). METHODS CSF biomarkers were analyzed with EUROIMMUN ELISA. We included 163 patients showing pathological CSF Aβ42 and normal p-tau (A + T - = 98) or pathological p-tau levels (A + T + = 65) and 36 control subjects (A - T -). A + T - patients were further stratified into those with normal (CSFAβ42 + /amyR - = 46) and pathological amyR (CSFAβ42 + /amyR + = 52). We used two distinct cut-offs to determine pathological values of p-tau/Aβ42: (1) ≥ 0.086 and (2) ≥ 0.122. FDG-PET patterns were evaluated in a subsample of patients (n = 46) and compared to 24 controls. RESULTS CSF Aβ40 levels were the lowest in A - T - and in CSFAβ42 + /amyR - , higher in CSFAβ42 + /amyR + and highest in A + T + (F = 50.75; p < 0.001), resembling CSF levels of p-tau (F = 192; p < 0.001). We found a positive association between Aβ40 and p-tau in A - T - (β = 0.58; p < 0.001), CSFAβ42 + /amyR - (β = 0.47; p < 0.001), and CSFAβ42 + /amyR + patients (β = 0.48; p < 0.001) but not in A + T + . Investigating biomarker changes as a function of amyR, we observed a weak variation in CSF p-tau (+ 2 z-scores) and Aβ40 (+ 0.8 z-scores) in the normal amyR range, becoming steeper over the pathological threshold of amyR (p-tau: + 5 z-scores, Aβ40: + 4.5 z-score). CSFAβ42 + /amyR + patients showed a significantly higher probability of having pathological p-tau/Aβ42 than CSFAβ42 + /amyR - (cut-off ≥ 0.086: OR 23.3; cut-off ≥ 0.122: OR 8.8), which however still showed pathological values of p-tau/Aβ42 in some cases (cut-off ≥ 0.086: 35.7%; cut-off ≥ 0.122: 17.3%) unlike A - T - . Accordingly, we found reduced FDG metabolism in the temporoparietal regions of CSFAβ42 + /amyR - compared to controls, and further reduction in frontal areas in CSFAβ42 + /amyR + , like in A + T + . CONCLUSIONS Pathological p-tau/Aβ42 and FDG hypometabolism typical of AD can be found in patients with decreased CSF Aβ42 levels alone. AmyR positivity, associated with higher Aβ40 levels, is accompanied by higher CSF p-tau and widespread FDG hypometabolism.
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Affiliation(s)
- Caterina Motta
- UOSD Centro Demenze, University of Rome "Tor Vergata", Rome, Italy.
| | | | | | - Martina Assogna
- UOSD Centro Demenze, University of Rome "Tor Vergata", Rome, Italy
- Experimental Neuropsychophysiology Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Agostino Chiaravalloti
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
- Istituto Neurologico Mediterraneo, Pozzilli, Italy
| | | | - Giacomo Koch
- Experimental Neuropsychophysiology Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
- Human Physiology Unit, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
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10
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Wang ZB, Tan L, Wang HF, Chen SD, Fu Y, Gao PY, Ma YH, Guo Y, Hou JH, Zhang DD, Yu JT. Differences between ante mortem Alzheimer's disease biomarkers in predicting neuropathology at autopsy. Alzheimers Dement 2023; 19:3613-3624. [PMID: 36840620 DOI: 10.1002/alz.12997] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/18/2023] [Accepted: 01/19/2023] [Indexed: 02/26/2023]
Abstract
INTRODUCTION This study aimed to assess whether biomarkers related to amyloid, tau, and neurodegeneration can accurately predict Alzheimer's disease (AD) neuropathology at autopsy in early and late clinical stages. METHODS We included 100 participants who had ante mortem biomarker measurements and underwent post mortem neuropathological examination. Based on ante mortem clinical diagnosis, participants were divided into non-dementia and dementia, as early or late clinical stages. RESULTS Amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) amyloid beta (Aβ)42/phosphorylated tau (p-tau)181 showed excellent performance in differentiating autopsy-confirmed AD and predicting the risk of neuropathological changes in early and late clinical stages. However, CSF Aβ42 performed better in the early clinical stage, while CSF p-tau181, CSF t-tau, and plasma p-tau181 performed better in the late clinical stage. DISCUSSION Our findings provide important clinical information that, if using PET, CSF, and plasma biomarkers to detect AD pathology, researchers must consider their differential performances at different clinical stages of AD. HIGHLIGHTS Amyloid PET and CSF Aβ42/p-tau181 were the most promising candidate biomarkers for predicting AD pathology. CSF Aβ42 can serve as a candidate predictive biomarker in the early clinical stage of AD. CSF p-tau181, CSF t-tau, and plasma p-tau181 can serve as candidate predictive biomarkers in the late clinical stage of AD. Combining APOE ε4 genotypes can significantly improve the predictive accuracy of AD-related biomarkers for AD pathology.
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Affiliation(s)
- Zhi-Bo Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Hui-Fu Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yu Guo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jia-Hui Hou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Dan-Dan Zhang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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11
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Paciotti S, Wojdała AL, Bellomo G, Toja A, Chipi E, Piersma SR, Pham TV, Gaetani L, Jimenez CR, Parnetti L, Chiasserini D. Potential diagnostic value of CSF metabolism-related proteins across the Alzheimer's disease continuum. Alzheimers Res Ther 2023; 15:124. [PMID: 37454217 DOI: 10.1186/s13195-023-01269-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 07/04/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) cerebrospinal fluid (CSF) core biomarkers (Aβ42/40 ratio, p-tau, and t-tau) provide high diagnostic accuracy, even at the earliest stage of disease. However, these markers do not fully reflect the complex AD pathophysiology. Recent large scale CSF proteomic studies revealed several new AD candidate biomarkers related to metabolic pathways. In this study we measured the CSF levels of four metabolism-related proteins not directly linked to amyloid- and tau-pathways (i.e., pyruvate kinase, PKM; aldolase, ALDO; ubiquitin C-terminal hydrolase L1, UCHL1, and fatty acid-binding protein 3, FABP3) across the AD continuum. We aimed at validating the potential value of these proteins as new CSF biomarkers for AD and their possible involvement in AD pathogenesis, with specific interest on the preclinical phase of the disease. METHODS CSF PKM and ALDO activities were measured with specific enzyme assays while UCHL1 and FABP3 levels were measured with immunoassays in a cohort of patients composed as follows: preclinical AD (pre-AD, n = 19, cognitively unimpaired), mild cognitive impairment due to AD (MCI-AD, n = 50), dementia due to AD (ADdem, n = 45), and patients with frontotemporal dementia (FTD, n = 37). Individuals with MCI not due to AD (MCI, n = 30) and subjective cognitive decline (SCD, n = 52) with negative CSF AD-profile, were enrolled as control groups. RESULTS CSF UCHL1 and FABP3 levels, and PKM activity were significantly increased in AD patients, already at the pre-clinical stage. CSF PKM activity was also increased in FTD patients compared with control groups, being similar between AD and FTD patients. No difference was found in ALDO activity among the groups. UCHL1 showed good performance in discriminating early AD patients (pre-AD and MCI-AD) from controls (AUC ~ 0.83), as assessed by ROC analysis. Similar results were obtained for FABP3. Conversely, PKM provided the best performance when comparing FTD vs. MCI (AUC = 0.80). Combination of PKM, FABP3, and UCHL1 improved the diagnostic accuracy for the detection of patients within the AD continuum when compared with single biomarkers. CONCLUSIONS Our study confirmed the potential role of UCHL1 and FABP3 as neurodegenerative biomarkers for AD. Furthermore, our results validated the increase of PKM activity in CSF of AD patients, already at the preclinical phase of the disease. Increased PKM activity was observed also in FTD patients, possibly underlining similar alterations in energy metabolism in AD and FTD.
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Affiliation(s)
- Silvia Paciotti
- Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Anna Lidia Wojdała
- Laboratory of Clinical Neurochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Giovanni Bellomo
- Laboratory of Clinical Neurochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Andrea Toja
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Elena Chipi
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Sander R Piersma
- OncoProteomics Laboratory, Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Thang V Pham
- OncoProteomics Laboratory, Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Lorenzo Gaetani
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Connie R Jimenez
- OncoProteomics Laboratory, Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Lucilla Parnetti
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
| | - Davide Chiasserini
- Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy.
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12
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Vinceti M, Urbano T, Chiari A, Filippini T, Wise LA, Tondelli M, Michalke B, Shimizu M, Saito Y. Selenoprotein P concentrations and risk of progression from mild cognitive impairment to dementia. Sci Rep 2023; 13:8792. [PMID: 37258587 DOI: 10.1038/s41598-023-36084-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 05/29/2023] [Indexed: 06/02/2023] Open
Abstract
There is a growing literature investigating the effects of selenium on the central nervous system and cognitive function. However, little is known about the role of selenoprotein P, the main selenium transporter, which can also have adverse biological effects. We conducted a prospective cohort study of individuals aged 42-81 years who received a clinical diagnosis of mild cognitive impairment. Using sandwich ELISA methods, we measured full-length selenoprotein P concentrations in serum and cerebrospinal fluid to assess the relation with dementia incidence during a median follow-up of 47.3 months. We used Cox proportional hazards regression and restricted cubic splines to model such relation. Of the 54 participants, 35 developed dementia during follow-up (including 26 cases of Alzheimer's dementia). Selenoprotein P concentrations in serum and cerebrospinal fluid were highly correlated, and in spline regression analyses they each showed a positive non-linear association with dementia risk, particularly after excluding dementia cases diagnosed within 24 months of follow-up. We also observed differences in association according to the dementia subtypes considered. Risk ratios of dementia peaked at 2-6 at the highest levels of selenoprotein P, when compared to its median level, also depending on matrix, analytical methodology and dementia subtype. Findings of this study, the first to assess selenoprotein P levels in the central nervous system in vivo and the first to use a prospective study design to evaluate associations with dementia, suggest that higher circulating concentrations of selenoprotein P, both in serum and cerebrospinal fluid, predict progression of MCI to dementia. However, further confirmation of these findings is required, given the limited statistical precision of the associations and the potential for residual confounding.
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Affiliation(s)
- Marco Vinceti
- Department of Biomedical, Metabolic, and Neural Sciences, CREAGEN - Environmental, Genetic, and Nutritional Epidemiology Research Center, University of Modena and Reggio Emilia, Modena, Italy.
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neurosciences and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy.
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
| | - Teresa Urbano
- Department of Biomedical, Metabolic, and Neural Sciences, CREAGEN - Environmental, Genetic, and Nutritional Epidemiology Research Center, University of Modena and Reggio Emilia, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neurosciences and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Annalisa Chiari
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neurosciences and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, University Hospital, Modena, Italy
| | - Tommaso Filippini
- Department of Biomedical, Metabolic, and Neural Sciences, CREAGEN - Environmental, Genetic, and Nutritional Epidemiology Research Center, University of Modena and Reggio Emilia, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neurosciences and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- School of Public Health, University of California Berkeley, Berkeley, CA, USA
| | - Lauren A Wise
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Manuela Tondelli
- Neurology Unit, University Hospital, Modena, Italy
- Primary Care Department, Local Health Unit of Modena, Modena, Italy
| | - Bernhard Michalke
- Research Unit Analytical BioGeoChemistry, Helmholtz Center Munich German Research Center for Environmental Health GmbH, Neuherberg, Germany
| | - Misaki Shimizu
- Laboratory of Molecular Biology and Metabolism, Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Japan
| | - Yoshiro Saito
- Laboratory of Molecular Biology and Metabolism, Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Japan
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13
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Barthélemy NR, Saef B, Li Y, Gordon BA, He Y, Horie K, Stomrud E, Salvadó G, Janelidze S, Sato C, Ovod V, Henson RL, Fagan AM, Benzinger TLS, Xiong C, Morris JC, Hansson O, Bateman RJ, Schindler SE. CSF tau phosphorylation occupancies at T217 and T205 represent improved biomarkers of amyloid and tau pathology in Alzheimer's disease. NATURE AGING 2023; 3:391-401. [PMID: 37117788 PMCID: PMC10154225 DOI: 10.1038/s43587-023-00380-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 02/03/2023] [Indexed: 04/30/2023]
Abstract
Cerebrospinal fluid (CSF) amyloid-β peptide (Aβ)42/Aβ40 and the concentration of tau phosphorylated at site 181 (p-tau181) are well-established biomarkers of Alzheimer's disease (AD). The present study used mass spectrometry to measure concentrations of nine phosphorylated and five nonphosphorylated tau species and phosphorylation occupancies (percentage phosphorylated/nonphosphorylated) at ten sites. In the present study we show that, in 750 individuals with a median age of 71.2 years, CSF pT217/T217 predicted the presence of brain amyloid by positron emission tomography (PET) slightly better than Aβ42/Aβ40 (P = 0.02). Furthermore, for individuals with positive brain amyloid by PET (n = 263), CSF pT217/T217 was more strongly correlated with the amount of amyloid (Spearman's ρ = 0.69) than Aβ42/Aβ40 (ρ = -0.42, P < 0.0001). In two independent cohorts of participants with symptoms of AD dementia (n = 55 and n = 90), CSF pT217/T217 and pT205/T205 were better correlated with tau PET measures than CSF p-tau181 concentration. These findings suggest that CSF pT217/T217 and pT205/T205 represent improved CSF biomarkers of amyloid and tau pathology in AD.
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Affiliation(s)
- Nicolas R Barthélemy
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
- Tracy Family SILQ Center for Neurodegenerative Biology, St. Louis, MO, USA.
| | - Benjamin Saef
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Yan Li
- 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
| | - Yingxin He
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family SILQ Center for Neurodegenerative Biology, St. Louis, MO, USA
| | - Kanta Horie
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family SILQ Center for Neurodegenerative Biology, St. Louis, MO, USA
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Chihiro Sato
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family SILQ Center for Neurodegenerative Biology, St. Louis, MO, USA
| | - Vitaliy Ovod
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family SILQ Center for Neurodegenerative Biology, St. Louis, MO, USA
| | - Rachel L Henson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer 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
| | - 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
| | - 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
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family SILQ Center for Neurodegenerative Biology, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, 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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14
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Gurdon B, Yates SC, Csucs G, Groeneboom NE, Hadad N, Telpoukhovskaia M, Ouellette A, Ouellette T, O'Connell K, Singh S, Murdy T, Merchant E, Bjerke I, Kleven H, Schlegel U, Leergaard TB, Puchades MA, Bjaalie JG, Kaczorowski CC. Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.27.530226. [PMID: 36909528 PMCID: PMC10002670 DOI: 10.1101/2023.02.27.530226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
Alzheimer's disease (AD) is characterized by neurodegeneration, pathology accumulation, and progressive cognitive decline. There is significant variation in age at onset and severity of symptoms highlighting the importance of genetic diversity in the study of AD. To address this, we analyzed cell and pathology composition of 6- and 14-month-old AD-BXD mouse brains using the semi-automated workflow (QUINT); which we expanded to allow for nonlinear refinement of brain atlas-registration, and quality control assessment of atlas-registration and brain section integrity. Near global age-related increases in microglia, astrocyte, and amyloid-beta accumulation were measured, while regional variation in neuron load existed among strains. Furthermore, hippocampal immunohistochemistry analyses were combined with bulk RNA-sequencing results to demonstrate the relationship between cell composition and gene expression. Overall, the additional functionality of the QUINT workflow delivers a highly effective method for registering and quantifying cell and pathology changes in diverse disease models.
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Affiliation(s)
- Brianna Gurdon
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
| | - Sharon C Yates
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Gergely Csucs
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Nicolaas E Groeneboom
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | | | | | - Andrew Ouellette
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
| | - Tionna Ouellette
- The Jackson Laboratory, Bar Harbor, ME
- Tufts University Graduate School of Biomedical Sciences, Medford, MA
| | - Kristen O'Connell
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
- Tufts University Graduate School of Biomedical Sciences, Medford, MA
| | | | - Tom Murdy
- The Jackson Laboratory, Bar Harbor, ME
| | | | - Ingvild Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Heidi Kleven
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ulrike Schlegel
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Catherine C Kaczorowski
- The Jackson Laboratory, Bar Harbor, ME
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME
- Tufts University Graduate School of Biomedical Sciences, Medford, MA
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15
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Wisniewski T, Masurkar AV. Gait dysfunction in Alzheimer disease. HANDBOOK OF CLINICAL NEUROLOGY 2023; 196:267-274. [PMID: 37620073 DOI: 10.1016/b978-0-323-98817-9.00013-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of age-associated dementia and will exponentially rise in prevalence in the coming decades, supporting the parallel development of the early stage detection and disease-modifying strategies. While primarily considered as a cognitive disorder, AD also features motor symptoms, primarily gait dysfunction. Such gait abnormalities can be phenotyped across classic clinical syndromes as well as by quantitative kinematic assessments to address subtle dysfunction at preclinical and prodromal stages. As such, certain measures of gait can predict the future cognitive and functional decline. Moreover, cross-sectional and longitudinal studies have associated gait abnormalities with imaging, biofluid, and genetic markers of AD across all stages. This suggests that gait assessment is an important tool in the clinical assessment of patients across the AD spectrum, especially to help identify at-risk individuals.
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Affiliation(s)
- Thomas Wisniewski
- Department of Neurology, NYU School of Medicine, New York, NY, United States; Department of Pathology, NYU School of Medicine, New York, NY, United States; Department of Psychiatry, NYU School of Medicine, New York, NY, United States; Division of Cognitive Neurology, Center for Cognitive Neurology, NYU School of Medicine, New York, NY, United States.
| | - Arjun V Masurkar
- Department of Neurology, NYU School of Medicine, New York, NY, United States; Division of Cognitive Neurology, Center for Cognitive Neurology, NYU School of Medicine, New York, NY, United States
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