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Ferreira PCL, Therriault J, Tissot C, Ferrari-Souza JP, Benedet AL, Povala G, Bellaver B, Leffa DT, Brum WS, Lussier FZ, Bezgin G, Servaes S, Vermeiren M, Macedo AC, Cabrera A, Stevenson J, Triana-Baltzer G, Kolb H, Rahmouni N, Klunk WE, Lopez O, Villemagne VL, Cohen A, Tudorascu DL, Zimmer ER, Karikari TK, Ashton NJ, Zetterberg H, Blennow K, Gauthier S, Rosa-Neto P, Pascoal TA. Plasma p-tau231 and p-tau217 inform on tau tangles aggregation in cognitively impaired individuals. Alzheimers Dement 2023; 19:4463-4474. [PMID: 37534889 PMCID: PMC10592380 DOI: 10.1002/alz.13393] [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: 02/24/2023] [Revised: 06/15/2023] [Accepted: 06/19/2023] [Indexed: 08/04/2023]
Abstract
INTRODUCTION Phosphorylated tau (p-tau) biomarkers have been recently proposed to represent brain amyloid-β (Aβ) pathology. Here, we evaluated the plasma biomarkers' contribution beyond the information provided by demographics (age and sex) to identify Aβ and tau pathologies in individuals segregated as cognitively unimpaired (CU) and impaired (CI). METHODS We assessed 138 CU and 87 CI with available plasma p-tau231, 217+ , and 181, Aβ42/40, GFAP and Aβ- and tau-PET. RESULTS In CU, only plasma p-tau231 and p-tau217+ significantly improved the performance of the demographics in detecting Aβ-PET positivity, while no plasma biomarker provided additional information to identify tau-PET positivity. In CI, p-tau217+ and GFAP significantly contributed to demographics to identify both Aβ-PET and tau-PET positivity, while p-tau231 only provided additional information to identify tau-PET positivity. DISCUSSION Our results support plasma p-tau231 and p-tau217+ as state markers of early Aβ deposition, but in later disease stages they inform on tau tangle accumulation. HIGHLIGHTS It is still unclear how much plasma biomarkers contribute to identification of AD pathology across the AD spectrum beyond the information already provided by demographics (age + sex). Plasma p-tau231 and p-tau217+ contribute to demographic information to identify brain Aβ pathology in preclinical AD. In CI individuals, plasma p-tau231 contributes to age and sex to inform on the accumulation of tau tangles, while p-tau217+ and GFAP inform on both Aβ deposition and tau pathology.
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Affiliation(s)
- Pamela C. L Ferreira
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Cécile Tissot
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - João Pedro Ferrari-Souza
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Andréa L. Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Guilherme Povala
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Bruna Bellaver
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Douglas T. Leffa
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Wagner S. Brum
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Firoza Z. Lussier
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Marie Vermeiren
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Arthur C. Macedo
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Arlec Cabrera
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, 92121-1126, USA
| | - Hartmuth Kolb
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, 92121-1126, USA
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - William E. Klunk
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Oscar Lopez
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Victor L. Villemagne
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Ann Cohen
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Dana L. Tudorascu
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Eduardo R. Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Graduate Program in Biological Sciences: Pharmacology and Therapeuctis, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Brain Insitute of Rio Grande do Sul, PUCRS, Porto Alegre, 90619-900, Brazil
| | - Thomas K. Karikari
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, 431 41, Sweden
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, HKG, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Serge Gauthier
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Tharick A. Pascoal
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
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Burns RB, Barry MJ, Blacker D, Kanjee Z. Would You Screen This Patient for Cognitive Impairment? : Grand Rounds Discussion From Beth Israel Deaconess Medical Center. Ann Intern Med 2023; 176:1405-1412. [PMID: 37812780 DOI: 10.7326/m23-1808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/11/2023] Open
Abstract
Dementia, according to the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, is defined by a significant decline in 1 or more cognitive domains that interferes with a person's independence in daily activities. Mild cognitive impairment (MCI) differs from dementia in that the impairment is not sufficient to interfere with independence. For the purposes of this discussion, cognitive impairment (CI) includes both dementia and MCI. Various screening tests are available for CI. These tests ask patients to perform a series of tasks that assess 1 or more domains of cognitive function or ask a caregiver to report on the patient's abilities. A positive result on a screening test does not equate to a diagnosis of CI; rather, it should lead to additional testing to confirm the diagnosis. On review of the evidence, the U.S. Preventive Services Task Force (USPSTF) concluded in 2020 that the evidence was insufficient to assess the balance of benefits and harms of screening for CI in older adults ("I statement"). The USPSTF did clarify that although there is insufficient evidence, there may be important reasons to identify CI. In this article, 2 experts review the available evidence to answer the following questions: What screening tools are available, and how effective are they in identifying patients with CI? What interventions are available for patients found to have CI, to what extent do they improve patient outcomes, and what, if any, negative effects occur? And, would they recommend screening for CI, and why or why not?
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Affiliation(s)
- Risa B Burns
- Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts (R.B.B., Z.K.)
| | - Michael J Barry
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, Massachusetts (M.J.B.)
| | - Deborah Blacker
- Harvard T.H. Chan School of Public Health, Massachusetts General Hospital, Boston, Massachusetts (D.B.)
| | - Zahir Kanjee
- Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts (R.B.B., Z.K.)
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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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Theron D, Hopkins LN, Sutherland HG, Griffiths LR, Fernandez F. Can Genetic Markers Predict the Sporadic Form of Alzheimer's Disease? An Updated Review on Genetic Peripheral Markers. Int J Mol Sci 2023; 24:13480. [PMID: 37686283 PMCID: PMC10488021 DOI: 10.3390/ijms241713480] [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: 08/04/2023] [Revised: 08/22/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia that affects millions of individuals worldwide. Although the research over the last decades has provided new insight into AD pathophysiology, there is currently no cure for the disease. AD is often only diagnosed once the symptoms have become prominent, particularly in the late-onset (sporadic) form of AD. Consequently, it is essential to further new avenues for early diagnosis. With recent advances in genomic analysis and a lower cost of use, the exploration of genetic markers alongside RNA molecules can offer a key avenue for early diagnosis. We have here provided a brief overview of potential genetic markers differentially expressed in peripheral tissues in AD cases compared to controls, as well as considering the changes to the dynamics of RNA molecules. By integrating both genotype and RNA changes reported in AD, biomarker profiling can be key for developing reliable AD diagnostic tools.
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Affiliation(s)
- Danelda Theron
- School of Behavioural and Health Sciences, Faculty of Heath Sciences, Australian Catholic University, Banyo, QLD 4014, Australia;
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Lloyd N. Hopkins
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Heidi G. Sutherland
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Lyn R. Griffiths
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
| | - Francesca Fernandez
- School of Behavioural and Health Sciences, Faculty of Heath Sciences, Australian Catholic University, Banyo, QLD 4014, Australia;
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059, Australia; (L.N.H.); (H.G.S.); (L.R.G.)
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Li X, Wu Q, Kong Y, Lu C. Mild cognitive impairment in type 2 diabetes is associated with fibrinogen-to-albumin ratios. PeerJ 2023; 11:e15826. [PMID: 37576498 PMCID: PMC10414025 DOI: 10.7717/peerj.15826] [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: 05/16/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023] Open
Abstract
Background Cognitive impairment is the main manifestation of diabetes central neuropathy. Currently, there is no effective dementia treatment; early diagnosis and treatment are particularly crucial. Inflammation index fibrinogen-to-albumin ratio (FAR) has been shown to predict complications of type 2 diabetes (diabetic kidney disease and diabetes-related arteriosclerosis), but its relationship with mild cognitive impairment (MCI) in type 2 diabetes (T2D) is undetermined. In this study, we examined the association between the FAR and mild cognitive impairment in type 2 diabetes. Methods This is a retrospective and cross-sectional study. From January 2022 to December 2022, we have retrieved 328 inpatient medical records for T2D patients hospitalized at the First Hospital of Harbin Medical University from the hospital's electronic system. Subjects' cognitive function was assessed and grouped by the MoCA scales. Subjects' demographic and various laboratory indicators were collected. Using Spearman's bivariate correlation analysis, the FAR and other clinical variables were analyzed for association strength. A multiple linear regression analysis was conducted to determine the independent relationship between FAR and MoCA scores. Multivariate logistic regression was used to analyze the independent relationship between FAR and MCI. The capacity of the FAR to detect MCI was carried using receiver operating characteristic (ROC) analysis. Results The included participants' (n = 328; 61.9% male) mean age was 52.62 ± 10.92 years. MoCA scores and MCI prevalence significantly differed (p < 0.05) between the four subgroups of FAR quartiles. The FAR and the MoCA score were significantly negatively correlated in the entire population (p < 0.05). Based on the multiple linear regression analysis, lnFAR and lnMoCA are significantly correlated (β = -0.449, t = -8.21, p < 0.05, R2 = 0.469). In multivariate logistic regression analysis, FAR and MCI were independently correlated after adjusting for covariates (OR 95% CI 34.70 [13.90-86.66]). Finally, the analysis of receptor working characteristics shows that the optimal FAR cut-off value was 0.08 (sensitivity: 95.81%, specificity: 84.47%) for detecting MCI in type 2 diabetes. Conclusion In type 2 diabetes, the FAR was positive associations with MCI and negative associations with MoCA score. The high FAR was associated with an increased risk of MCI. FAR maybe a appropriate indicator of MCI risk for type 2 diabetes.
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Affiliation(s)
- Xinyu Li
- Department of Endocrinology, First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Qian Wu
- Department of Endocrinology, First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Yanqi Kong
- Department of Endocrinology, First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Chong Lu
- Department of Neurology, Heilongjiang Provincial Hospital, Harbin, Heilongjiang, China
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Wharton SB, Simpson JE, Ince PG, Richardson CD, Merrick R, Matthews FE, Brayne C. Insights into the pathological basis of dementia from population-based neuropathology studies. Neuropathol Appl Neurobiol 2023; 49:e12923. [PMID: 37462105 PMCID: PMC10946587 DOI: 10.1111/nan.12923] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/13/2023] [Accepted: 06/29/2023] [Indexed: 08/17/2023]
Abstract
The epidemiological neuropathology perspective of population and community-based studies allows unbiased assessment of the prevalence of various pathologies and their relationships to late-life dementia. In addition, this approach provides complementary insights to conventional case-control studies, which tend to be more representative of a younger clinical cohort. The Cognitive Function and Ageing Study (CFAS) is a longitudinal study of cognitive impairment and frailty in the general United Kingdom population. In this review, we provide an overview of the major findings from CFAS, alongside other studies, which have demonstrated a high prevalence of pathology in the ageing brain, particularly Alzheimer's disease neuropathological change and vascular pathology. Increasing burdens of these pathologies are the major correlates of dementia, especially neurofibrillary tangles, but there is substantial overlap in pathology between those with and without dementia, particularly at intermediate burdens of pathology and also at the oldest ages. Furthermore, additional pathologies such as limbic-predominant age-related TDP-43 encephalopathy, ageing-related tau astrogliopathy and primary age-related tauopathies contribute to late-life dementia. Findings from ageing population-representative studies have implications for the understanding of dementia pathology in the community. The high prevalence of pathology and variable relationship to dementia status has implications for disease definition and indicate a role for modulating factors on cognitive outcome. The complexity of late-life dementia, with mixed pathologies, indicates a need for a better understanding of these processes across the life-course to direct the best research for reducing risk in later life of avoidable clinical dementia syndromes.
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Affiliation(s)
- Stephen B. Wharton
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
| | - Julie E. Simpson
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
| | - Paul G. Ince
- Sheffield Institute for Translational NeuroscienceUniversity of SheffieldSheffieldUK
| | | | - Richard Merrick
- Cambridge Public Health, School of Clinical MedicineUniversity of CambridgeSheffieldUK
| | | | - Carol Brayne
- Cambridge Public Health, School of Clinical MedicineUniversity of CambridgeSheffieldUK
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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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58
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Xu C, Zhao L, Dong C. The performance of plasma phosphorylated tau231 in detecting Alzheimer's disease: A systematic review with meta-analysis. Eur J Neurosci 2023; 58:3132-3149. [PMID: 37501373 DOI: 10.1111/ejn.16085] [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: 04/29/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/29/2023]
Abstract
Cerebrospinal fluid (CSF) phosphorylated tau231 (P-tau231) is associated with neuropathological outcomes of Alzheimer's disease (AD). The invasive access of cerebrospinal fluid has greatly stimulated interest in the identification of blood-based P-tau231, and the recent advent of single-molecule array assay for the quantification of plasma P-tau231 may provide a turning point to evaluate the usefulness of P-tau231 as an AD-related biomarker. Yet, in the plasma P-tau231 literature, findings with regard to its diagnostic utility have been inconsistent, and thus, we aimed to statistically investigate the potential of plasma P-tau231 in the context of AD via meta-analysis. Publications on plasma P-tau231 were systematically retrieved from PubMed, EMBASE, the Cochrane library and Web of Science databases. A total of 10 studies covering 2007 participants were included, and we conducted random-effect or fixed-effect meta-analysis, sensitivity analysis and publication bias analysis using the STATA SE 14.0 software. According to our quantitative integration, plasma P-tau231 increased from cognitively unimpaired (CU) populations to mild cognitive impairment to AD and showed significant changes in pairwise comparisons of AD, mild cognitive impairment and CU. Plasma P-tau231 level was significantly higher in CU controls with positive amyloid-β (Aβ) status compared with Aβ-negative CU group. Additionally, the excellent diagnostic accuracy of plasma P-tau231 for asymptomatic Aβ pathology was verified by the pooled value of area under the receiver operating characteristic curves (standard mean difference [95% confidence interval]: .75 [.69, .81], P < 0.00001). Overall, the increased plasma P-tau231 concentrations were found in relation to the early development and progression of AD.
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Affiliation(s)
- Chang Xu
- Department of Neurology, the First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Li Zhao
- Department of Neurology, the First Affiliated Hospital, Dalian Medical University, Dalian, China
| | - Chunbo Dong
- Department of Neurology, the First Affiliated Hospital, Dalian Medical University, Dalian, China
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59
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Bucci M, Bluma M, Savitcheva I, Ashton NJ, Chiotis K, Matton A, Kivipelto M, Di Molfetta G, Blennow K, Zetterberg H, Nordberg A. Profiling of plasma biomarkers in the context of memory assessment in a tertiary memory clinic. Transl Psychiatry 2023; 13:268. [PMID: 37491358 PMCID: PMC10368630 DOI: 10.1038/s41398-023-02558-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 06/24/2023] [Accepted: 07/03/2023] [Indexed: 07/27/2023] Open
Abstract
Plasma biomarkers have shown promising performance in research cohorts in discriminating between different stages of Alzheimer's disease (AD). Studies in clinical populations are necessary to provide insights on the clinical utility of plasma biomarkers before their implementation in real-world settings. Here we investigated plasma biomarkers (glial fibrillary acidic protein (GFAP), tau phosphorylated at 181 and 231 (pTau181, pTau231), amyloid β (Aβ) 42/40 ratio, neurofilament light) in 126 patients (age = 65 ± 8) who were admitted to the Clinic for Cognitive Disorders, at Karolinska University Hospital. After extensive clinical assessment (including CSF analysis), patients were classified as: mild cognitive impairment (MCI) (n = 75), AD (n = 25), non-AD dementia (n = 16), no dementia (n = 9). To refine the diagnosis, patients were examined with [18F]flutemetamol PET (Aβ-PET). Aβ-PET images were visually rated for positivity/negativity and quantified in Centiloid. Accordingly, 68 Aβ+ and 54 Aβ- patients were identified. Plasma biomarkers were measured using single molecule arrays (SIMOA). Receiver-operated curve (ROC) analyses were performed to detect Aβ-PET+ using the different biomarkers. In the whole cohort, the Aβ-PET centiloid values correlated positively with plasma GFAP, pTau231, pTau181, and negatively with Aβ42/40 ratio. While in the whole MCI group, only GFAP was associated with Aβ PET centiloid. In ROC analyses, among the standalone biomarkers, GFAP showed the highest area under the curve discriminating Aβ+ and Aβ- compared to other plasma biomarkers. The combination of plasma biomarkers via regression was the most predictive of Aβ-PET, especially in the MCI group (prior to PET, n = 75) (sensitivity = 100%, specificity = 82%, negative predictive value = 100%). In our cohort of memory clinic patients (mainly MCI), the combination of plasma biomarkers was sensitive in ruling out Aβ-PET negative individuals, thus suggesting a potential role as rule-out tool in clinical practice.
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Affiliation(s)
- Marco Bucci
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Marina Bluma
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University, SE-14186, Stockholm, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Anna Matton
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
| | - Miia Kivipelto
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, SE-43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, SE-43180, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, 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, WI, 53792, USA
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, SE-14183, Stockholm, Sweden.
- Theme Inflammation and Aging, Karolinska University Hospital, SE-14186, Stockholm, Sweden.
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60
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Bermudez C, Graff-Radford J, Syrjanen JA, Stricker NH, Algeciras-Schimnich A, Kouri N, Kremers WK, Petersen RC, Jack CR, Knopman DS, Dickson DW, Nguyen AT, Reichard RR, Murray ME, Mielke MM, Vemuri P. Plasma biomarkers for prediction of Alzheimer's disease neuropathologic change. Acta Neuropathol 2023; 146:13-29. [PMID: 37269398 PMCID: PMC10478071 DOI: 10.1007/s00401-023-02594-w] [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: 02/12/2023] [Revised: 05/14/2023] [Accepted: 05/24/2023] [Indexed: 06/05/2023]
Abstract
While plasma biomarkers for Alzheimer's disease (AD) are increasingly being evaluated for clinical diagnosis and prognosis, few population-based autopsy studies have evaluated their utility in the context of predicting neuropathological changes. Our goal was to investigate the utility of clinically available plasma markers in predicting Braak staging, neuritic plaque score, Thal phase, and overall AD neuropathological change (ADNC).We utilized a population-based prospective study of 350 participants with autopsy and antemortem plasma biomarker testing using clinically available antibody assay (Quanterix) consisting of Aβ42/40 ratio, p-tau181, GFAP, and NfL. We utilized a variable selection procedure in cross-validated (CV) logistic regression models to identify the best set of plasma predictors along with demographic variables, and a subset of neuropsychological tests comprising the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo-PACC). ADNC was best predicted with plasma GFAP, NfL, p-tau181 biomarkers along with APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.798). Braak staging was best predicted using plasma GFAP, p-tau181, and cognitive scores (CV AUC = 0.774). Neuritic plaque score was best predicted using plasma Aβ42/40 ratio, p-tau181, GFAP, and NfL biomarkers (CV AUC = 0.770). Thal phase was best predicted using GFAP, NfL, p-tau181, APOE ε4 carrier status and Mayo-PACC cognitive score (CV AUC = 0.754). We found that GFAP and p-tau provided non-overlapping information on both neuritic plaque and Braak stage scores whereas Aβ42/40 and NfL were mainly useful for prediction of neuritic plaque scores. Separating participants by cognitive status improved predictive performance, particularly when plasma biomarkers were included. Plasma biomarkers can differentially inform about overall ADNC pathology, Braak staging, and neuritic plaque score when combined with demographics and cognitive variables and have significant utility for earlier detection of AD.
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Affiliation(s)
- Camilo Bermudez
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55902, USA.
| | | | - Jeremy A Syrjanen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Nikki H Stricker
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Naomi Kouri
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55902, USA
| | | | - David S Knopman
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55902, USA
| | | | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - R Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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61
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Yu L, Boyle PA, Janelidze S, Petyuk VA, Wang T, Bennett DA, Hansson O, Schneider JA. Plasma p-tau181 and p-tau217 in discriminating PART, AD and other key neuropathologies in older adults. Acta Neuropathol 2023; 146:1-11. [PMID: 37031430 PMCID: PMC10261204 DOI: 10.1007/s00401-023-02570-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 04/10/2023]
Abstract
We examined whether plasma p-tau181 and p-tau217 are specific biomarkers of pathologically confirmed Alzheimer's disease (AD). In particular, we investigated the utility of plasma p-tau for differentiating AD from primary age-related tauopathy (PART), as well as AD with mixed pathologies. Data came from 269 older adults who participated in the Religious Orders Study or the Rush Memory and Aging Project. Blood samples were collected during annual clinical evaluations. Participants died and underwent brain autopsy. P-tau181 and p-tau217 were quantified in the plasma samples proximate to death (average interval before death: 1.4 years) using Lilly-developed MSD immunoassays. Uniform neuropathologic evaluations assessed AD, PART, and other common degenerative and cerebrovascular conditions. Plasma p-tau217 was more strongly correlated with brain β-amyloid and paired helical filament tau (PHFtau) tangles than p-tau181. Both p-tau markers were associated with greater odds of AD, but p-tau217 had higher accuracy (area under the ROC curve (AUC): 0.83) than p-tau181 (AUC: 0.76). Plasma p-tau markers were almost exclusively associated with AD pathologic indices with the exception of cerebral amyloid angiopathy. Compared to p-tau181, p-tau217 showed a higher AUC (0.82 versus 0.74) in differentiating AD from PART. For either p-tau, we did not observe a level difference between individuals with AD alone and those with mixed AD pathologies. In summary, plasma p-tau181and p-tau217 were specifically associated with AD pathological changes. Further, our data provide initial evidence that p-tau217 may be able to differentiate between AD and PART in individuals with comparable burdens of tau tangle pathology. These results demonstrate the specificity of p-tau217 for AD, supporting its use to identify patients suitable for anti-AD therapies including β-amyloid immunotherapies.
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Affiliation(s)
- Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Patricia A Boyle
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Tianhao Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.
- Memory Clinic, Skåne University Hospital, SE-205 02, Malmö, Sweden.
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA.
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA.
- Department of Pathology, Rush University Medical Center, Chicago, IL, USA.
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62
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Kunwar A, Ablordeppey KK, Mireskandari A, Sheinerman K, Kiefer M, Umansky S, Kumar G. Analytical Validation of a Novel MicroRNA Panel for Risk Stratification of Cognitive Impairment. Diagnostics (Basel) 2023; 13:2170. [PMID: 37443567 DOI: 10.3390/diagnostics13132170] [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: 05/03/2023] [Revised: 06/15/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023] Open
Abstract
We have been developing a novel approach to identify cognitive impairment-related biomarkers by profiling brain-enriched and inflammation-associated microRNA (miRNA) in plasma specimens of cognitively unimpaired and cognitively impaired patients. Here, we present an analytical validation of the novel miRNA panel, CogniMIR®, using two competing quantitative PCR technologies for the expression analysis of 24 target miRNAs. Total RNA from the plasma specimens was isolated using the MagMAX mirVana Kit, and RT-qPCR was performed using stem-loop-based TaqMan and LNA-based qPCR assays. Evaluation of RNA dilution series for our target 24 miRNAs, performed by two operators on two different days, demonstrated that all CogniMIR® panel miRNAs can be reliably and consistently detected by both qPCR technologies, with sample input as low as 20 copies in a qPCR reaction. Intra-run and inter-run repeatability and reproducibility analyses using RNA specimens demonstrated that both operators generated repeatable and consistent Cts, with R2 values of 0.94 to 0.99 and 0.96 to 0.97, respectively. The study results clearly indicate the suitability of miRNA profiling of plasma specimens using either of the qPCR technologies. However, the LNA-based qPCR technology appears to be more operationally friendly and better suited for a CAP/CLIA-certified clinical laboratory.
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Affiliation(s)
- Arzu Kunwar
- DiamiR Biosciences Laboratory, 2 Church Street South, Suite B05, New Haven, CT 06519, USA
| | | | - Alidad Mireskandari
- DiamiR Biosciences Laboratory, 2 Church Street South, Suite B05, New Haven, CT 06519, USA
| | - Kira Sheinerman
- DiamiR Biosciences Laboratory, 2 Church Street South, Suite B05, New Haven, CT 06519, USA
| | - Michael Kiefer
- DiamiR Biosciences Laboratory, 2 Church Street South, Suite B05, New Haven, CT 06519, USA
| | - Samuil Umansky
- DiamiR Biosciences Laboratory, 2 Church Street South, Suite B05, New Haven, CT 06519, USA
| | - Gyanendra Kumar
- DiamiR Biosciences Laboratory, 2 Church Street South, Suite B05, New Haven, CT 06519, USA
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63
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Telser J, Grossmann K, Wohlwend N, Risch L, Saely CH, Werner P. Phosphorylated tau in Alzheimer's disease. Adv Clin Chem 2023; 116:31-111. [PMID: 37852722 DOI: 10.1016/bs.acc.2023.05.001] [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] [Indexed: 10/20/2023]
Abstract
There is a need for blood biomarkers to detect individuals at different Alzheimer's disease (AD) stages because obtaining cerebrospinal fluid-based biomarkers is invasive and costly. Plasma phosphorylated tau proteins (p-tau) have shown potential as such biomarkers. This systematic review was conducted according to the PRISMA guidelines and aimed to determine whether quantification of plasma tau phosphorylated at threonine 181 (p-tau181), threonine 217 (p-tau217) and threonine 231 (p-tau231) is informative in the diagnosis of AD. All p-tau isoforms increase as a function of Aβ-accumulation and discriminate healthy individuals from those at preclinical AD stages with high accuracy. P-tau231 increases earliest, followed by p-tau181 and p-tau217. In advanced stages, all p-tau isoforms are associated with the clinical classification of AD and increase with disease severity, with the greatest increase seen for p-tau217. This is also reflected by a better correlation of p-tau217 with Aβ scans, whereas both, p-tau217 and p-tau181 correlated equally with tau scans. However, at the very advanced stages, p-tau181 begins to plateau, which may mirror the trajectory of the Aβ pathology and indicate an association with a more intermediate risk of AD. Across the AD continuum, the incremental increase in all biomarkers is associated with structural changes in widespread brain regions and underlying cognitive decline. Furthermore, all isoforms differentiate AD from non-AD neurodegenerative disorders, making them specific for AD. Incorporating p-tau181, p-tau217 and p-tau231 in clinical use requires further studies to examine ideal cut-points and harmonize assays.
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Affiliation(s)
- Julia Telser
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Kirsten Grossmann
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Niklas Wohlwend
- Laboratory Dr. Risch, Vaduz, Liechtenstein; Department of Internal Medicine Spital Grabs, Spitalregion Rheintal Werdenberg Sarganserland, Grabs, Switzerland
| | - Lorenz Risch
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein; University Institute of Clinical Chemistry, University Hospital and University of Bern, Inselspital, Bern, Switzerland
| | - Christoph H Saely
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT), Feldkirch, Austria
| | - Philipp Werner
- Department of Neurology, State Hospital of Rankweil, Academic Teaching Hospital, Rankweil, Austria.
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64
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Van Egroo M, Riphagen JM, Ashton NJ, Janelidze S, Sperling RA, Johnson KA, Yang HS, Bennett DA, Blennow K, Hansson O, Zetterberg H, Jacobs HIL. Ultra-high field imaging, plasma markers and autopsy data uncover a specific rostral locus coeruleus vulnerability to hyperphosphorylated tau. Mol Psychiatry 2023; 28:2412-2422. [PMID: 37020050 PMCID: PMC10073793 DOI: 10.1038/s41380-023-02041-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 04/07/2023]
Abstract
Autopsy data indicate that the locus coeruleus (LC) is one of the first sites in the brain to accumulate hyperphosphorylated tau pathology, with the rostral part possibly being more vulnerable in the earlier stages of the disease. Taking advantage of recent developments in ultra-high field (7 T) imaging, we investigated whether imaging measures of the LC also reveal a specific anatomic correlation with tau using novel plasma biomarkers of different species of hyperphosphorylated tau, how early in adulthood these associations can be detected and if are associated with worse cognitive performance. To validate the anatomic correlations, we tested if a rostro-caudal gradient in tau pathology is also detected at autopsy in data from the Rush Memory and Aging Project (MAP). We found that higher plasma measures of phosphorylated tau, in particular ptau231, correlated negatively with dorso-rostral LC integrity, whereas correlations for neurodegenerative plasma markers (neurofilament light, total tau) were scattered throughout the LC including middle to caudal sections. In contrast, the plasma Aβ42/40 ratio, associated with brain amyloidosis, did not correlate with LC integrity. These findings were specific to the rostral LC and not observed when using the entire LC or the hippocampus. Furthermore, in the MAP data, we observed higher rostral than caudal tangle density in the LC, independent of the disease stage. The in vivo LC-phosphorylated tau correlations became significant from midlife, with the earliest effect for ptau231, starting at about age 55. Finally, interactions between lower rostral LC integrity and higher ptau231 concentrations predicted lower cognitive performance. Together, these findings demonstrate a specific rostral vulnerability to early phosphorylated tau species that can be detected with dedicated magnetic resonance imaging measures, highlighting the promise of LC imaging as an early marker of AD-related processes.
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Grants
- R01 AG017917 NIA NIH HHS
- R01 AG068398 NIA NIH HHS
- R21 AG074220 NIA NIH HHS
- K23 AG062750 NIA NIH HHS
- R01 AG068062 NIA NIH HHS
- K01 AG001016 NIA NIH HHS
- ZEN-21-848495 Alzheimer's Association
- P01 AG036694 NIA NIH HHS
- R01 AG062559 NIA NIH HHS
- R01 AG015819 NIA NIH HHS
- U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
- Alzheimer Nederland WE.03-2019-02
- BrightFocus Foundation (BrightFocus)
- Alzheimer’s Association
- Alzheimer’s Drug Discovery Foundation (ADDF)
- Swedish Research Council (#2017-00915), the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615), the Swedish Alzheimer Foundation (#AF-930351, #AF-939721 and #AF-968270), Hjärnfonden, Sweden (#FO2017-0243 and #ALZ2022-0006), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986 and #ALFGBG-965240), the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236)
- Cure Alzheimer’s Fund (Alzheimer’s Disease Research Foundation)
- Swedish Research Council (2016-00906), the Knut and Alice Wallenberg foundation (2017-0383), the Marianne and Marcus Wallenberg foundation (2015.0125), the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson’s disease) at Lund University, the Swedish Alzheimer Foundation (AF-939932), the Swedish Brain Foundation (FO2021-0293), The Parkinson foundation of Sweden (1280/20), the Cure Alzheimer’s fund, the Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse, the Skåne University Hospital Foundation (2020-O000028), Regionalt Forskningsstöd (2020-0314) and the Swedish federal government under the ALF agreement (2018-Projekt0279)
- HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018-02532), the European Research Council (#681712 and #101053962), Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, and #ADSF-21-831377-C), the Bluefield Project, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), the European Union Joint Programme – Neurodegenerative Disease Research (JPND2021-00694), and the UK Dementia Research Institute at UCL (UKDRI-1003).
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Affiliation(s)
- Maxime Van Egroo
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Joost M Riphagen
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Reisa A Sperling
- Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Keith A Johnson
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Hyun-Sik Yang
- Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - David A Bennett
- Department of Neurological Sciences, Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 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, Clear Water Bay, Hong Kong, China
| | - Heidi I L Jacobs
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands.
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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65
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Jack CR, Wiste HJ, Algeciras-Schimnich A, Figdore DJ, Schwarz CG, Lowe VJ, Ramanan VK, Vemuri P, Mielke MM, Knopman DS, Graff-Radford J, Boeve BF, Kantarci K, Cogswell PM, Senjem ML, Gunter JL, Therneau TM, Petersen RC. Predicting amyloid PET and tau PET stages with plasma biomarkers. Brain 2023; 146:2029-2044. [PMID: 36789483 PMCID: PMC10151195 DOI: 10.1093/brain/awad042] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 01/21/2023] [Indexed: 02/16/2023] Open
Abstract
Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
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Affiliation(s)
- Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Dan J Figdore
- Department of Laboratory Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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66
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Lu J, Zhang Z, Wu P, Liang X, Zhang H, Hong J, Clement C, Yen TC, Ding S, Wang M, Xiao Z, Rominger A, Shi K, Guan Y, Zuo C, Zhao Q. The heterogeneity of asymmetric tau distribution is associated with an early age at onset and poor prognosis in Alzheimer's disease. Neuroimage Clin 2023; 38:103416. [PMID: 37137254 PMCID: PMC10176076 DOI: 10.1016/j.nicl.2023.103416] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/13/2023] [Accepted: 04/22/2023] [Indexed: 05/05/2023]
Abstract
PURPOSE Left-right asymmetry, an important feature of brain development, has been implicated in neurodegenerative diseases, although it's less discussed in typical Alzheimer's disease (AD). We sought to investigate whether asymmetric tau deposition plays a potential role in AD heterogeneity. METHODS Two independent cohorts consisting of patients with mild cognitive impairment due to AD and AD dementia with tau PET imaging were enrolled [the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort with 18F-Flortaucipir, the Shanghai Memory Study (SMS) cohort with 18F-Florzolotau]. Based on the absolute global tau interhemispheric differences, each cohort was divided into two groups (asymmetric versus symmetric tau distribution). The two groups were cross-sectionally compared in terms of demographic, cognitive characteristics, and pathological burden. The cognitive decline trajectories were analyzed longitudinally. RESULTS Fourteen (23.3%) and 42 (48.3%) patients in the ADNI and SMS cohorts showed an asymmetric tau distribution, respectively. An asymmetric tau distribution was associated with an earlier age at disease onset (proportion of early-onset AD: ADNI/SMS/combined cohorts, p = 0.093/0.026/0.001) and more severe pathological burden (i.e., global tau burden: ADNI/SMS cohorts, p < 0.001/= 0.007). And patients with an asymmetric tau distribution were characterized by a steeper cognitive decline longitudinally (i.e., the annual decline of Mini-Mental Status Examination score: ADNI/SMS/combined cohorts, p = 0.053 / 0.035 / < 0.001). CONCLUSIONS Asymmetry in tau deposition, which may be associated with an earlier age at onset, more severe pathological burden, and a steeper cognitive decline, is potentially an important characteristic of AD heterogeneity.
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Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Zhengwei Zhang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoniu Liang
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jimin Hong
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Christoph Clement
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | | | - Saineng Ding
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Min Wang
- Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China; Department of Informatics, Technische Universität München, Munich, Germany
| | - Zhenxu Xiao
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland; Department of Informatics, Technische Universität München, Munich, Germany
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Chuantao Zuo
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Qianhua Zhao
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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67
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Cousins KAQ, Irwin DJ, Chen-Plotkin A, Shaw LM, Arezoumandan S, Lee EB, Wolk DA, Weintraub D, Spindler M, Deik A, Grossman M, Tropea TF. Plasma GFAP associates with secondary Alzheimer's pathology in Lewy body disease. Ann Clin Transl Neurol 2023; 10:802-813. [PMID: 37000892 DOI: 10.1002/acn3.51768] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/13/2023] [Accepted: 03/14/2023] [Indexed: 04/03/2023] Open
Abstract
OBJECTIVE Within Lewy body spectrum disorders (LBSD) with α-synuclein pathology (αSyn), concomitant Alzheimer's disease (AD) pathology is common and is predictive of clinical outcomes, including cognitive impairment and decline. Plasma phosphorylated tau 181 (p-tau181 ) is sensitive to AD neuropathologic change (ADNC) in clinical AD, and plasma glial fibrillary acidic protein (GFAP) is associated with the presence of β-amyloid plaques. While these plasma biomarkers are well tested in clinical and pathological AD, their diagnostic and prognostic performance for concomitant AD in LBSD is unknown. METHODS In autopsy-confirmed αSyn-positive LBSD, we tested how plasma p-tau181 and GFAP differed across αSyn with concomitant ADNC (αSyn+AD; n = 19) and αSyn without AD (αSyn; n = 30). Severity of burden was scored on a semiquantitative scale for several pathologies (e.g., β-amyloid and tau), and scores were averaged across sampled brainstem, limbic, and neocortical regions. RESULTS Linear models showed that plasma GFAP was significantly higher in αSyn+AD compared to αSyn (β = 0.31, 95% CI = 0.065-0.56, and P = 0.015), after covarying for age at plasma, plasma-to-death interval, and sex; plasma p-tau181 was not (P = 0.37). Next, linear models tested associations of AD pathological features with both plasma analytes, covarying for plasma-to-death, age at plasma, and sex. GFAP was significantly associated with brain β-amyloid (β = 15, 95% CI = 6.1-25, and P = 0.0018) and tau burden (β = 12, 95% CI = 2.5-22, and P = 0.015); plasma p-tau181 was not associated with either (both P > 0.34). INTERPRETATION Findings indicate that plasma GFAP may be sensitive to concomitant AD pathology in LBSD, especially accumulation of β-amyloid plaques.
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Affiliation(s)
- Katheryn A Q Cousins
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sanaz Arezoumandan
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Daniel Weintraub
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Meredith Spindler
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Andres Deik
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Murray Grossman
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Thomas F Tropea
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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68
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Andersson E, Schultz N, Saito T, Saido TC, Blennow K, Gouras GK, Zetterberg H, Hansson O. Cerebral Aβ deposition precedes reduced cerebrospinal fluid and serum Aβ42/Aβ40 ratios in the App NL-F/NL-F knock-in mouse model of Alzheimer's disease. Alzheimers Res Ther 2023; 15:64. [PMID: 36964585 PMCID: PMC10039589 DOI: 10.1186/s13195-023-01196-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 02/22/2023] [Indexed: 03/26/2023]
Abstract
BACKGROUND Aβ42/Aβ40 ratios in cerebrospinal fluid (CSF) and blood are reduced in preclinical Alzheimer's disease (AD), but their temporal and correlative relationship with cerebral Aβ pathology at this early disease stage is not well understood. In the present study, we aim to investigate such relationships using App knock-in mouse models of preclinical AD. METHODS CSF, serum, and brain tissue were collected from 3- to 18-month-old AppNL-F/NL-F knock-in mice (n = 48) and 2-18-month-old AppNL/NL knock-in mice (n = 35). The concentrations of Aβ42 and Aβ40 in CSF and serum were measured using Single molecule array (Simoa) immunoassays. Cerebral Aβ plaque burden was assessed in brain tissue sections by immunohistochemistry and thioflavin S staining. Furthermore, the concentrations of Aβ42 in soluble and insoluble fractions prepared from cortical tissue homogenates were measured using an electrochemiluminescence immunoassay. RESULTS In AppNL-F/NL-F knock-in mice, Aβ42/Aβ40 ratios in CSF and serum were significantly reduced from 12 and 16 months of age, respectively. The initial reduction of these biomarkers coincided with cerebral Aβ pathology, in which a more widespread Aβ plaque burden and increased levels of Aβ42 in the brain were observed from approximately 12 months of age. Accordingly, in the whole study population, Aβ42/Aβ40 ratios in CSF and serum showed a negative hyperbolic association with cerebral Aβ plaque burden as well as the levels of both soluble and insoluble Aβ42 in the brain. These associations tended to be stronger for the measures in CSF compared with serum. In contrast, no alterations in the investigated fluid biomarkers or apparent cerebral Aβ plaque pathology were found in AppNL/NL knock-in mice during the observation time. CONCLUSIONS Our findings suggest a temporal sequence of events in AppNL-F/NL-F knock-in mice, in which initial deposition of Aβ aggregates in the brain is followed by a decline of the Aβ42/Aβ40 ratio in CSF and serum once the cerebral Aβ pathology becomes significant. Our results also indicate that the investigated biomarkers were somewhat more strongly associated with measures of cerebral Aβ pathology when assessed in CSF compared with serum.
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Affiliation(s)
- Emelie Andersson
- Clinical Memory Research Unit, Lund University, 22184, Lund, Sweden.
| | - Nina Schultz
- Clinical Memory Research Unit, Lund University, 22184, Lund, Sweden
| | - Takashi Saito
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Takaomi C Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Brain Science Institute, Wako-Shi, Saitama, Japan
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Gunnar K Gouras
- Department of Experimental Medical Science, Experimental Dementia Research Unit, Lund University, Lund, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, 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, WI, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, 22184, Lund, Sweden.
- Memory Clinic, SkåneUniversity Hospital, 20502, Malmö, Sweden.
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69
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Gonzalez-Ortiz F, Kac PR, Brum WS, Zetterberg H, Blennow K, Karikari TK. Plasma phospho-tau in Alzheimer's disease: towards diagnostic and therapeutic trial applications. Mol Neurodegener 2023; 18:18. [PMID: 36927491 PMCID: PMC10022272 DOI: 10.1186/s13024-023-00605-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 02/15/2023] [Indexed: 03/18/2023] Open
Abstract
As the leading cause of dementia, Alzheimer's disease (AD) is a major burden on affected individuals, their families and caregivers, and healthcare systems. Although AD can be identified and diagnosed by cerebrospinal fluid or neuroimaging biomarkers that concord with neuropathological evidence and clinical symptoms, challenges regarding practicality and accessibility hinder their widespread availability and implementation. Consequently, many people with suspected cognitive impairment due to AD do not receive a biomarker-supported diagnosis. Blood biomarkers have the capacity to help expand access to AD diagnostics worldwide. One such promising biomarker is plasma phosphorylated tau (p-tau), which has demonstrated specificity to AD versus non-AD neurodegenerative diseases, and will be extremely important to inform on clinical diagnosis and eligibility for therapies that have recently been approved. This review provides an update on the diagnostic and prognostic performances of plasma p-tau181, p-tau217 and p-tau231, and their associations with in vivo and autopsy-verified diagnosis and pathological hallmarks. Additionally, we discuss potential applications and unanswered questions of plasma p-tau for therapeutic trials, given their recent addition to the biomarker toolbox for participant screening, recruitment and during-trial monitoring. Outstanding questions include assay standardization, threshold generation and biomarker verification in diverse cohorts reflective of the wider community attending memory clinics and included in clinical trials.
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Affiliation(s)
- Fernando Gonzalez-Ortiz
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Przemysław R. Kac
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Wagner S. Brum
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.8532.c0000 0001 2200 7498Graduate Program in Biological Sciences: Biochemistry, Universidade Federal Do Rio Grande Do Sul (UFRGS), Porto Alegre, Brazil
| | - Henrik Zetterberg
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- grid.83440.3b0000000121901201Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- grid.83440.3b0000000121901201UK Dementia Research Institute at UCL, London, UK
- grid.24515.370000 0004 1937 1450Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Thomas K. Karikari
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- grid.21925.3d0000 0004 1936 9000Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
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70
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Salvadó G, Ossenkoppele R, Ashton NJ, Beach TG, Serrano GE, Reiman EM, Zetterberg H, Mattsson-Carlgren N, Janelidze S, Blennow K, Hansson O. Specific associations between plasma biomarkers and postmortem amyloid plaque and tau tangle loads. EMBO Mol Med 2023; 15:e17123. [PMID: 36912178 PMCID: PMC10165361 DOI: 10.15252/emmm.202217123] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/14/2023] Open
Abstract
Several promising plasma biomarkers for Alzheimer's disease have been recently developed, but their neuropathological correlates have not yet been fully determined. To investigate and compare independent associations between multiple plasma biomarkers (p-tau181, p-tau217, p-tau231, Aβ42/40, GFAP, and NfL) and neuropathologic measures of amyloid and tau, we included 105 participants from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with antemortem plasma samples and a postmortem neuropathological exam, 48 of whom had longitudinal p-tau217 and p-tau181. When simultaneously including plaque and tangle loads, the Aβ42/40 ratio and p-tau231 were only associated with plaques (ρAβ42/40 [95%CI] = -0.53[-0.65, -0.35], ρp-tau231 [95%CI] = 0.28[0.10, 0.43]), GFAP was only associated with tangles (ρGFAP [95%CI] = 0.39[0.17, 0.57]), and p-tau217 and p-tau181 were associated with both plaques (ρp-tau217 [95%CI] = 0.40[0.21, 0.56], ρp-tau181 [95%CI] = 0.36[0.15, 0.50]) and tangles (ρp-tau217 [95%CI] = 0.52[0.34, 0.66]; ρp-tau181 [95%CI] = 0.36[0.17, 0.52]). A model combining p-tau217 and the Aβ42/40 ratio showed the highest accuracy for predicting the presence of Alzheimer's disease neuropathological change (ADNC, AUC[95%CI] = 0.89[0.82, 0.96]) and plaque load (R2 = 0.55), while p-tau217 alone was optimal for predicting tangle load (R2 = 0.45). Our results suggest that high-performing assays of plasma p-tau217 and Aβ42/40 might be an optimal combination to assess Alzheimer's-related pathology in vivo.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley, NHS Foundation, London, UK
| | | | | | - Eric M Reiman
- Banner Alzheimer's Institute, Arizona State University and University of Arizona, Phoenix, AZ, 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
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - 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
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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71
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Silva-Spínola A, Lima M, Leitão MJ, Bernardes C, Durães J, Duro D, Tábuas-Pereira M, Santana I, Baldeiras I. Blood biomarkers in mild cognitive impairment patients: Relationship between analytes and progression to Alzheimer disease dementia. Eur J Neurol 2023; 30:1565-1573. [PMID: 36880887 DOI: 10.1111/ene.15762] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 02/23/2023] [Accepted: 02/24/2023] [Indexed: 03/08/2023]
Abstract
BACKGROUND AND PURPOSE Blood-based biomarkers are promising tools for the diagnosis of Alzheimer disease (AD) at prodromal stages (mild cognitive impairment [MCI]) and are hoped to be implemented as screening tools for patients with cognitive complaints. In this work, we evaluated the potential of peripheral neurological biomarkers to predict progression to AD dementia and the relation between blood and cerebrospinal fluid (CSF) AD markers in MCI patients referred from a general neurological department. METHODS A group of 106 MCI patients followed at the Neurology Department of Coimbra University Hospital was included. Data regarding baseline neuropsychological evaluation, CSF levels of amyloid β 42 (Aβ42), Aβ40, total tau (t-Tau), and phosphorylated tau 181 (p-Tau181) were available for all the patients. Aβ42, Aβ40, t-Tau, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) levels were determined in baseline stored serum and plasma samples by commercial SiMoA (Single Molecule Array) assays. Progression from MCI to AD dementia was assessed at follow-up (mean = 5.8 ± 3.4 years). RESULTS At baseline, blood markers NfL, GFAP, and p-Tau181 were significantly increased in patients who progressed to AD at follow-up (p < 0.001). In contrast, plasma Aβ42/40 ratio and t-Tau showed no significant differences between groups. NfL, GFAP, and p-Tau181 demonstrated good diagnostic accuracy to identify progression to AD dementia (area under the curve [AUC] = 0.81, 0.80, and 0.76, respectively), which improved when combined (AUC = 0.89). GFAP and p-Tau181 were correlated with CSF Aβ42. Association of p-Tau181 with NfL was mediated by GFAP, with a significant indirect association of 88% of the total effect. CONCLUSIONS Our findings highlight the potential of combining blood-based GFAP, NfL, and p-Tau181 to be applied as a prognostic tool in MCI.
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Affiliation(s)
- Anuschka Silva-Spínola
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Center for Informatics and Systems, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Marisa Lima
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Center for Research in Neuropsychology and Cognitive Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Maria João Leitão
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Catarina Bernardes
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - João Durães
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Diana Duro
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Miguel Tábuas-Pereira
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Isabel Santana
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Inês Baldeiras
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
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Abstract
PURPOSE OF REVIEW Several plasma biomarkers for Alzheimer's disease and related disorders (ADRD) have demonstrated clinical and technical robustness. However, are they ready for clinical implementation? This review critically appraises current evidence for and against the immediate use of plasma biomarkers in clinical care. RECENT FINDINGS Plasma biomarkers have significantly improved our understanding of ADRD time-course, risk factors, diagnosis and prognosis. These advances are accelerating the development and in-human testing of therapeutic candidates, and the selection of individuals with subtle biological evidence of disease who fit the criteria for early therapeutic targeting. However, standardized tests and well validated cut-off values are lacking. Moreover, some assays (e.g., plasma Aβ methods) have poor robustness to withstand inevitable day-to-day technical variations. Additionally, recent reports suggest that common comorbidities of aging (e.g., kidney disease, diabetes, hypertension) can erroneously affect plasma biomarker levels, clinical utility and generalizability. Furthermore, it is unclear if health disparities can explain reported racial/ethnic differences in biomarker levels and functions. Finally, current clinically approved plasma methods are more expensive than CSF assays, questioning their cost effectiveness. SUMMARY Plasma biomarkers have biological and clinical capacity to detect ADRD. However, their widespread use requires issues around thresholds, comorbidities and diverse populations to be addressed.
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Affiliation(s)
- Wasiu G. Balogun
- Department of Neurosciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Thomas K. Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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73
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Gonzalez-Ortiz F, Turton M, Kac PR, Smirnov D, Premi E, Ghidoni R, Benussi L, Cantoni V, Saraceno C, Rivolta J, Ashton NJ, Borroni B, Galasko D, Harrison P, Zetterberg H, Blennow K, Karikari TK. Brain-derived tau: a novel blood-based biomarker for Alzheimer's disease-type neurodegeneration. Brain 2023; 146:1152-1165. [PMID: 36572122 PMCID: PMC9976981 DOI: 10.1093/brain/awac407] [Citation(s) in RCA: 62] [Impact Index Per Article: 62.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 09/23/2022] [Accepted: 09/25/2022] [Indexed: 12/28/2022] Open
Abstract
Blood-based biomarkers for amyloid beta and phosphorylated tau show good diagnostic accuracies and agreements with their corresponding CSF and neuroimaging biomarkers in the amyloid/tau/neurodegeneration [A/T/(N)] framework for Alzheimer's disease. However, the blood-based neurodegeneration marker neurofilament light is not specific to Alzheimer's disease while total-tau shows lack of correlation with CSF total-tau. Recent studies suggest that blood total-tau originates principally from peripheral, non-brain sources. We sought to address this challenge by generating an anti-tau antibody that selectively binds brain-derived tau and avoids the peripherally expressed 'big tau' isoform. We applied this antibody to develop an ultrasensitive blood-based assay for brain-derived tau, and validated it in five independent cohorts (n = 609) including a blood-to-autopsy cohort, CSF biomarker-classified cohorts and memory clinic cohorts. In paired samples, serum and CSF brain-derived tau were significantly correlated (rho = 0.85, P < 0.0001), while serum and CSF total-tau were not (rho = 0.23, P = 0.3364). Blood-based brain-derived tau showed equivalent diagnostic performance as CSF total-tau and CSF brain-derived tau to separate biomarker-positive Alzheimer's disease participants from biomarker-negative controls. Furthermore, plasma brain-derived tau accurately distinguished autopsy-confirmed Alzheimer's disease from other neurodegenerative diseases (area under the curve = 86.4%) while neurofilament light did not (area under the curve = 54.3%). These performances were independent of the presence of concomitant pathologies. Plasma brain-derived tau (rho = 0.52-0.67, P = 0.003), but not neurofilament light (rho = -0.14-0.17, P = 0.501), was associated with global and regional amyloid plaque and neurofibrillary tangle counts. These results were further verified in two memory clinic cohorts where serum brain-derived tau differentiated Alzheimer's disease from a range of other neurodegenerative disorders, including frontotemporal lobar degeneration and atypical parkinsonian disorders (area under the curve up to 99.6%). Notably, plasma/serum brain-derived tau correlated with neurofilament light only in Alzheimer's disease but not in the other neurodegenerative diseases. Across cohorts, plasma/serum brain-derived tau was associated with CSF and plasma AT(N) biomarkers and cognitive function. Brain-derived tau is a new blood-based biomarker that outperforms plasma total-tau and, unlike neurofilament light, shows specificity to Alzheimer's disease-type neurodegeneration. Thus, brain-derived tau demonstrates potential to complete the AT(N) scheme in blood, and will be useful to evaluate Alzheimer's disease-dependent neurodegenerative processes for clinical and research purposes.
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Affiliation(s)
- Fernando Gonzalez-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
| | - Michael Turton
- Bioventix Plc, Romans Business Park, Farnham, Surrey GU9 7SX, UK
| | - Przemysław R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
| | - Denis Smirnov
- University of California, San Diego and Shiely-Marcos Alzheimer’s Disease Research Center, La Jolla, CA 92037, USA
| | - Enrico Premi
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25121, Italy
| | - Luisa Benussi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25121, Italy
| | - Valentina Cantoni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Claudia Saraceno
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25121, Italy
| | - Jasmine Rivolta
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg 405 30, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, SE5 8AF, UK
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Douglas Galasko
- University of California, San Diego and Shiely-Marcos Alzheimer’s Disease Research Center, La Jolla, CA 92037, USA
| | - Peter Harrison
- Bioventix Plc, Romans Business Park, Farnham, Surrey GU9 7SX, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 431 80, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
- Hong Kong Center for Neurodegenerative Diseases, Shatin, N.T., Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 431 80, Sweden
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
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74
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Husain M. Screening for Alzheimer's disease: plasma biomarkers and what else? Brain 2023; 146:407-408. [PMID: 36780495 DOI: 10.1093/brain/awac490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023] Open
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75
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Pan D, Zeng A, Yang B, Lai G, Hu B, Song X, Jiang T. Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2204717. [PMID: 36575159 PMCID: PMC9951348 DOI: 10.1002/advs.202204717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/29/2022] [Indexed: 06/17/2023]
Abstract
Deep learning (DL) on brain magnetic resonance imaging (MRI) data has shown excellent performance in differentiating individuals with Alzheimer's disease (AD). However, the value of DL in detecting progressive structural MRI (sMRI) abnormalities linked to AD pathology has yet to be established. In this study, an interpretable DL algorithm named the Ensemble of 3-dimensional convolutional neural network (Ensemble 3DCNN) with enhanced parsing techniques is proposed to investigate the longitudinal trajectories of whole-brain sMRI changes denoting AD onset and progression. A set of 2369 T1-weighted images from the multi-centre Alzheimer's Disease Neuroimaging Initiative and Open Access Series of Imaging Studies cohorts are applied to model derivation, validation, testing, and pattern analysis. An Ensemble-3DCNN-based P-score is generated, based on which multiple brain regions, including amygdala, insular, parahippocampal, and temporal gyrus, exhibit early and connected progressive neurodegeneration. Complex individual variability in the sMRI is also observed. This study combining non-invasive sMRI and interpretable DL in detecting patterned sMRI changes confirmed AD pathological progression, shedding new light on predicting AD progression using whole-brain sMRI.
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Affiliation(s)
- Dan Pan
- School of Electronics and InformationGuangdong Polytechnic Normal UniversityGuangzhou510665China
| | - An Zeng
- Faculty of Computers, Guangdong University of TechnologyGuangzhou510006China
| | - Baoyao Yang
- Faculty of Computers, Guangdong University of TechnologyGuangzhou510006China
| | - Gangyong Lai
- Faculty of Computers, Guangdong University of TechnologyGuangzhou510006China
| | - Bing Hu
- Department of RadiologyThe Third Affiliated Hospital of SUN Yat‐sen UniversityGuangzhou510630China
| | - Xiaowei Song
- Clinical Research CentreSurrey Memorial HospitalFraser HealthSurreyBritish ColumbiaV3V 1Z2Canada
| | - Tianzi Jiang
- Brainnetome Center & National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing100190China
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76
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Planche V, Bouteloup V, Pellegrin I, Mangin JF, Dubois B, Ousset PJ, Pasquier F, Blanc F, Paquet C, Hanon O, Bennys K, Ceccaldi M, Annweiler C, Krolak-Salmon P, Godefroy O, Wallon D, Sauvee M, Boutoleau-Bretonnière C, Bourdel-Marchasson I, Jalenques I, Chene G, Dufouil C. Validity and Performance of Blood Biomarkers for Alzheimer Disease to Predict Dementia Risk in a Large Clinic-Based Cohort. Neurology 2023; 100:e473-e484. [PMID: 36261295 PMCID: PMC9931079 DOI: 10.1212/wnl.0000000000201479] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 09/13/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVE Blood biomarkers for Alzheimer disease (AD) have consistently proven to be associated with CSF or PET biomarkers and effectively discriminate AD from other neurodegenerative diseases. Our aim was to test their utility in clinical practice, from a multicentric unselected prospective cohort where patients presented with a large spectrum of cognitive deficits or complaints. METHODS The MEMENTO cohort enrolled 2,323 outpatients with subjective cognitive complaint (SCC) or mild cognitive impairment (MCI) consulting in 26 French memory clinics. Participants had neuropsychological assessments, MRI, and blood sampling at baseline. CSF sampling and amyloid PET were optional. Baseline blood Aβ42/40 ratio, total tau, p181-tau, and neurofilament light chain (NfL) were measured using a Simoa HD-X analyzer. An expert committee validated incident dementia cases during a 5-year follow-up period. RESULTS Overall, 2,277 individuals had at least 1 baseline blood biomarker available (n = 357 for CSF subsample, n = 649 for PET subsample), among whom 257 were diagnosed with clinical AD/mixed dementia during follow-up. All blood biomarkers but total tau were mildly correlated with their equivalence in the CSF (r = 0.33 to 0.46, p < 0.0001) and were associated with amyloid-PET status (p < 0.0001). Blood p181-tau was the best blood biomarker to identify amyloid-PET positivity (area under the curve = 0.74 [95% CI = 0.69; 0.79]). Higher blood and CSF p181-tau and NfL concentrations were associated with accelerated time to AD dementia onset with similar incidence rates, whereas blood Aβ42/40 was less efficient than CSF Aβ42/40. Blood p181-tau alone was the best blood predictor of 5-year AD/mixed dementia risk (c-index = 0.73 [95% CI = 0.69; 0.77]); its accuracy was higher in patients with clinical dementia rating (CDR) = 0 (c-index = 0.83 [95% CI = 0.69; 0.97]) than in patients with CDR = 0.5 (c-index = 0.70 [95% CI = 0.66; 0.74]). A "clinical" reference model (combining demographics and neuropsychological assessment) predicted AD/mixed dementia risk with a c-index = 0.88 [95% CI = 0.86-0.91] and performance increased to 0.90 [95% CI = 0.88; 0.92] when adding blood p181-tau + Aβ42/40. A "research" reference model (clinical model + apolipoprotein E genotype and AD signature on MRI) had a c-index = 0.91 [95% CI = 0.89-0.93] increasing to 0.92 [95% CI = 0.90; 0.93] when adding blood p181-tau + Aβ42/40. Chronic kidney disease and vascular comorbidities did not affect predictive performances. DISCUSSION In a clinic-based cohort of patients with SCC or MCI, blood biomarkers may be good hallmarks of underlying pathology but add little to 5-year dementia risk prediction models including traditional predictors.
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Affiliation(s)
- Vincent Planche
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand.
| | - Vincent Bouteloup
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Isabelle Pellegrin
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Jean-Francois Mangin
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Bruno Dubois
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Pierre-Jean Ousset
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Florence Pasquier
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Frederic Blanc
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Claire Paquet
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Olivier Hanon
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Karim Bennys
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Mathieu Ceccaldi
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Cédric Annweiler
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Pierre Krolak-Salmon
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Olivier Godefroy
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - David Wallon
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Mathilde Sauvee
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Claire Boutoleau-Bretonnière
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Isabelle Bourdel-Marchasson
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Isabelle Jalenques
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Genevieve Chene
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
| | - Carole Dufouil
- From the Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives; CHU de Bordeaux (V.P.), Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche; Univ. Bordeaux (V.B., G.C., C.D.), Inserm U1219, PHARes Team, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED); CHU Bordeaux (V.B., G.C., C.D.), CIC 1401 EC, Pôle Santé Publique; CHU de Bordeaux (I.P.), Département d'Immunologie et d'Immunogénétique; Univ. Paris-Saclay (J.-F.M.), CEA, CNRS, Baobab UMR9027, Neurospin, CATI Multicenter Neuroimaging Platform, US52, UAR 9031, Gif-sur-Yvette; Sorbonne-Université (B.D.), Service des Maladies Cognitives et Comportementales et Institut de La Mémoire et de La Maladie d'Alzheimer (IM2A), Hôpital de La Salpêtrière, AP-PH, Paris; Univ. Toulouse (P.-J.O.), Inserm U1027, Gérontopôle, Departement de Gériatrie, CHU Purpan, Toulouse; Univ. Lille (F.P.), Inserm U1171, Centre Mémoire de Ressources et de Recherche, CHU Lille, DISTAlz, Lille; Univ. Strasbourg (F.B.), CNRS, ICube Laboratory, UMR 7357, Fédération de Médecine Translationnelle de Strasbourg, Centre Mémoire de Ressources et de Recherche, Pôle de Gériatrie, Strasbourg; Univ. Paris (C.P.), Inserm U1144, Groupe Hospitalier Lariboisière Fernand-Widal, AP-HP; Univ. Paris Cité (O.H.), EA 4468, AP-HP, Hôpitaux Universitaires Paris Centre, Service de Gériatrie, Hôpital Broca; CHU de Montpellier (K.B.), Pôle de Neurosciences, Département de Neurologie, Centre Mémoire de Ressources et de Recherche, Montpellier; Univ. Aix Marseille (M.C.), Inserm UMR 1106, Institut de Neurosciences des Systèmes, Centre Mémoire de Ressources et de Recherche, Département de Neurologie et de Neuropsychologie, AP-HM, Marseille; Univ. Angers (C.A.), UPRES EA 4638, Centre Mémoire de Ressources et de Recherche, Département de Gériatrie, CHU d'Angers, Angers; Univ. Lyon (P.K.-S.), Inserm U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Centre Mémoire Ressource et Recherche de Lyon (CMRR), Hôpital des Charpennes, Hospices Civils de Lyon; Univ. Picardie (O.G.), UR UPJV4559, Laboratoire de Neurosciences Fonctionnelles et Pathologies, Service de Neurologie, CHU Amiens; Univ. Normandie (D.W.), UNIROUEN, Inserm U1245, Departement de Neurologie, CNR-MAJ, CHU de Rouen; Centre Mémoire de Ressources et de Recherche Grenoble Arc Alpin (M.S.), Pôle de Psychiatrie et Neurologie, CHU Grenoble Alpes; CHU de Nantes (C.B.-B.), Département de Neurologie, Centre Mémoire de Ressources et Recherche, Nantes; Univ. Bordeaux (I.B.-M.), CNRS UMR 5536, Centre de Résonance Magnétique des Systèmes Biologiques, Pôle de Gérontologie Clinique, CHU de Bordeaux; and Univ. Clermont Auvergne (I.J.), CNRS, CHU Clermont-Ferrand, Centre Mémoire de Ressources et de Recherche, Service de Psychiatrie de L'Adulte A et Psychologie Médicale, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand
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Beversdorf DQ, Scharre DW. The Dilemma of the Clinical Utility of Alzheimer Biomarker Evaluation in Everyday Clinical Practice: My Favorite PETs. Neurology 2023; 100:109-110. [PMID: 36175147 DOI: 10.1212/wnl.0000000000201478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 09/13/2022] [Indexed: 02/05/2023] Open
Affiliation(s)
- David Q Beversdorf
- From the Departments of Radiology (D.Q.B.), Neurology, and Psychological Sciences, Columbia, MO; and Department of Neurology (D.W.S.), Ohio State University, Columbus.
| | - Douglas W Scharre
- From the Departments of Radiology (D.Q.B.), Neurology, and Psychological Sciences, Columbia, MO; and Department of Neurology (D.W.S.), Ohio State University, Columbus
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Assessment of Plasma and Cerebrospinal Fluid Biomarkers in Different Stages of Alzheimer's Disease and Frontotemporal Dementia. Int J Mol Sci 2023; 24:ijms24021226. [PMID: 36674742 PMCID: PMC9864037 DOI: 10.3390/ijms24021226] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/23/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023] Open
Abstract
Alzheimer's disease (AD) is the primary type of dementia, followed by frontotemporal lobar degeneration (FTLD). They share some clinical characteristics, mainly at the early stages. So, the identification of early, specific, and minimally invasive biomarkers is required. In this study, some plasma biomarkers (Amyloid β42, p-Tau181, t-Tau, neurofilament light (NfL), TAR DNA-binding protein 43 (TDP-43)) were determined by single molecule array technology (SIMOA®) in control subjects (n = 22), mild cognitive impairment due to AD (MCI-AD, n = 33), mild dementia due to AD (n = 12), and FTLD (n = 11) patients. The correlations between plasma and cerebrospinal fluid (CSF) levels and the accuracy of plasma biomarkers for AD early diagnosis and discriminating from FTLD were analyzed. As result, plasma p-Tau181 and NfL levels correlated with the corresponding CSF levels. Additionally, plasma p-Tau181 showed good accuracy for distinguishing between the controls and AD, as well as discriminating between AD and FTLD. Moreover, plasma NfL could discriminate dementia-AD vs. controls, FTLD vs. controls, and MCI-AD vs. dementia-AD. Therefore, the determination of these biomarkers in plasma is potentially helpful in AD spectrum diagnosis, but also discriminating from FTLD. In addition, the accessibility of these potential early and specific biomarkers may be useful for AD screening protocols in the future.
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Wan K, Yin W, Tang Y, Zhu W, Wang Z, Zhou X, Zhang W, Zhang C, Yu X, Zhao W, Li C, Zhu X, Sun Z. Brain Gray Matter Volume Mediated the Correlation Between Plasma P-Tau and Cognitive Function of Early Alzheimer's Disease in China: A Cross-Sectional Observational Study. J Alzheimers Dis 2023; 92:81-93. [PMID: 36710682 DOI: 10.3233/jad-221100] [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] [Indexed: 01/28/2023]
Abstract
BACKGROUND The primary manifestations of Alzheimer's disease (AD) include cognitive decline and brain gray matter volume (GMV) atrophy. Recent studies have found that plasma phosphorylated-tau (p-tau) concentrations perform better in diagnosing, differentiating, and monitoring the progression of AD. However, the correlation between plasma p-tau, GMV, and cognition remains unclear. OBJECTIVE To investigate whether GMV plays a mediating role in the association between plasma p-tau concentrations and cognition. METHODS In total, 99 participants (47 patients with AD and 52 cognitively unimpaired [CU] individuals) were included. All participants underwent neuropsychological assessments, laboratory examinations, and magnetic resonance imaging scans. Plasma p-tau217 and p-tau181 concentrations were measured using an enzyme-linked immunosorbent assay kit. Voxel-based morphometry was performed to assess participants' brain GMV. Partial correlation and mediation analyses were conducted in AD group. RESULTS Plasma p-tau concentrations were significantly higher in the AD group than in the CU group. Patients with AD had significant brain GMV atrophy in the right hippocampus, bilateral middle temporal gyrus, and right inferior temporal gyrus. In the AD group, there were significant correlations between plasma p-tau217 concentrations, GMV, and Mini-Mental State Examination (MMSE) scores. Brain GMV of the right hippocampus mediated the association between plasma p-tau217 concentrations and MMSE scores. A significant correlation between plasma p-tau181 and MMSE scores was not identified. CONCLUSION The findings indicate that p-tau217 is a promising biomarker for central processes affecting brain GMV and cognitive function. This may provide potential targets for future intervention and treatment of tau-targeting therapies in the early stages of AD.
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Affiliation(s)
- Ke Wan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Wenwen Yin
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Yating Tang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Wenhao Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Zhiqiang Wang
- Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania, Australia
| | - Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Wei Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Cun Zhang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xianfeng Yu
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Wenming Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chenchen Li
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Xiaoqun Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
| | - Zhongwu Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, China
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80
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Brook ES, D'Alonzo ZJ, Lam V, Chan DC, Dhaliwal SS, Watts GF, Mamo JCL, Takechi R. Plasma Amyloid-β Homeostasis Is Associated with Body Mass Index and Weight Loss in People with Overweight and Obesity. J Alzheimers Dis 2023; 93:653-664. [PMID: 37066906 DOI: 10.3233/jad-220529] [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] [Indexed: 04/18/2023]
Abstract
BACKGROUND Obesity is linked to a higher incidence of Alzheimer's disease (AD). Studies show that plasma amyloid-β (Aβ) dyshomeostasis, particularly low 42/40 ratio indicates a heightened risk for developing AD. However, the relationship between body mass index (BMI) and circulating plasma Aβ has not been extensively studied. OBJECTIVE We hypothesized that people with a high BMI have altered plasma Aβ homeostasis compared with people with a lower BMI. We also tested whether reducing BMI by calorie-restriction could normalize plasma concentrations of Aβ. METHODS Plasma concentrations of Aβ40, Aβ42, and Aβ42/40 ratio were measured in 106 participants with BMIs classified as lean, overweight, or obese. From this cohort, twelve participants with overweight or obese BMIs entered a 12-week calorie-restriction weight loss program. We then tested whether decreasing BMI affected plasma Aβ concentrations. RESULTS Plasma Aβ42/40 ratio was 17.54% lower in participants with an obese BMI compared to lean participants (p < 0.0001), and 11.76% lower compared to participants with an overweight BMI (p < 0.0001). The weight loss regimen decreased BMI by an average of 4.02% (p = 0.0005) and was associated with a 6.5% decrease in plasma Aβ40 (p = 0.0425). However, weight loss showed negligible correlations with plasma Aβ40, Aβ42, and Aβ42/40 ratio. CONCLUSION Obesity is associated with aberrant plasma Aβ homeostasis which may be associated with an increased risk for AD. Weight loss appears to lower Aβ40, but large-scale longitudinal studies in addition to molecular studies are required to elucidate the underlying mechanisms of how obesity and weight loss influence plasma Aβ homeostasis.
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Affiliation(s)
- Emily S Brook
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Australia
- Curtin Medical School, Faculty of Health Sciences, Curtin University, Bentley, Australia
| | - Zachary J D'Alonzo
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Australia
- Curtin Medical School, Faculty of Health Sciences, Curtin University, Bentley, Australia
| | - Virginie Lam
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Australia
- School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, Australia
| | - Dick C Chan
- Medical School, University of Western Australia, Perth, Australia
| | - Satvinder S Dhaliwal
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Australia
- Duke-NUS Medical School, National University of Singapore, Singapore
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Minden, Pulau Pinang, Malaysia
- Singapore University of Social Sciences, Singapore
| | - Geraldb F Watts
- Medical School, University of Western Australia, Perth, Australia
- Cardiometabolic Service, Department of Cardiology and Internal Medicine, Royal Perth Hospital, Perth, Australia
| | - John C L Mamo
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Australia
- School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, Australia
- Perron Institute of Neurological and Translational Sciences, Nedlands, Australia
| | - Ryusuke Takechi
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Australia
- School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, Australia
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81
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Ashton NJ, Janelidze S, Mattsson-Carlgren N, Binette AP, Strandberg O, Brum WS, Karikari TK, González-Ortiz F, Di Molfetta G, Meda FJ, Jonaitis EM, Koscik RL, Cody K, Betthauser TJ, Li Y, Vanmechelen E, Palmqvist S, Stomrud E, Bateman RJ, Zetterberg H, Johnson SC, Blennow K, Hansson O. Differential roles of Aβ42/40, p-tau231 and p-tau217 for Alzheimer's trial selection and disease monitoring. Nat Med 2022; 28:2555-2562. [PMID: 36456833 PMCID: PMC9800279 DOI: 10.1038/s41591-022-02074-w] [Citation(s) in RCA: 122] [Impact Index Per Article: 61.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 10/03/2022] [Indexed: 12/03/2022]
Abstract
Blood biomarkers indicative of Alzheimer's disease (AD) pathology are altered in both preclinical and symptomatic stages of the disease. Distinctive biomarkers may be optimal for the identification of AD pathology or monitoring of disease progression. Blood biomarkers that correlate with changes in cognition and atrophy during the course of the disease could be used in clinical trials to identify successful interventions and thereby accelerate the development of efficient therapies. When disease-modifying treatments become approved for use, efficient blood-based biomarkers might also inform on treatment implementation and management in clinical practice. In the BioFINDER-1 cohort, plasma phosphorylated (p)-tau231 and amyloid-β42/40 ratio were more changed at lower thresholds of amyloid pathology. Longitudinally, however, only p-tau217 demonstrated marked amyloid-dependent changes over 4-6 years in both preclinical and symptomatic stages of the disease, with no such changes observed in p-tau231, p-tau181, amyloid-β42/40, glial acidic fibrillary protein or neurofilament light. Only longitudinal increases of p-tau217 were also associated with clinical deterioration and brain atrophy in preclinical AD. The selective longitudinal increase of p-tau217 and its associations with cognitive decline and atrophy was confirmed in an independent cohort (Wisconsin Registry for Alzheimer's Prevention). These findings support the differential association of plasma biomarkers with disease development and strongly highlight p-tau217 as a surrogate marker of disease progression in preclinical and prodromal AD, with impact for the development of new disease-modifying treatments.
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Affiliation(s)
- Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fernándo González-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Francisco J Meda
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Karly Cody
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Sebastian Palmqvist
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of Medicine, 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
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, 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
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- ADx NeuroSciences, Technologiepark 94, Ghent, Belgium.
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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82
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Wilson EN, Young CB, Ramos Benitez J, Swarovski MS, Feinstein I, Vandijck M, Le Guen Y, Kasireddy NM, Shahid M, Corso NK, Wang Q, Kennedy G, Trelle AN, Lind B, Channappa D, Belnap M, Ramirez V, Skylar-Scott I, Younes K, Yutsis MV, Le Bastard N, Quinn JF, van Dyck CH, Nairn A, Fredericks CA, Tian L, Kerchner GA, Montine TJ, Sha SJ, Davidzon G, Henderson VW, Longo FM, Greicius MD, Wagner AD, Wyss-Coray T, Poston KL, Mormino EC, Andreasson KI. Performance of a fully-automated Lumipulse plasma phospho-tau181 assay for Alzheimer's disease. Alzheimers Res Ther 2022; 14:172. [PMID: 36371232 PMCID: PMC9652927 DOI: 10.1186/s13195-022-01116-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 10/31/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND The recent promise of disease-modifying therapies for Alzheimer's disease (AD) has reinforced the need for accurate biomarkers for early disease detection, diagnosis and treatment monitoring. Advances in the development of novel blood-based biomarkers for AD have revealed that plasma levels of tau phosphorylated at various residues are specific and sensitive to AD dementia. However, the currently available tests have shortcomings in access, throughput, and scalability that limit widespread implementation. METHODS We evaluated the diagnostic and prognostic performance of a high-throughput and fully-automated Lumipulse plasma p-tau181 assay for the detection of AD. Plasma from older clinically unimpaired individuals (CU, n = 463) and patients with mild cognitive impairment (MCI, n = 107) or AD dementia (n = 78) were obtained from the longitudinal Stanford University Alzheimer's Disease Research Center (ADRC) and the Stanford Aging and Memory Study (SAMS) cohorts. We evaluated the discriminative accuracy of plasma p-tau181 for clinical AD diagnosis, association with amyloid β peptides and p-tau181 concentrations in CSF, association with amyloid positron emission tomography (PET), and ability to predict longitudinal cognitive and functional change. RESULTS The assay showed robust performance in differentiating AD from control participants (AUC 0.959, CI: 0.912 to 0.990), and was strongly associated with CSF p-tau181, CSF Aβ42/Aβ40 ratio, and amyloid-PET global SUVRs. Associations between plasma p-tau181 with CSF biomarkers were significant when examined separately in Aβ+ and Aβ- groups. Plasma p-tau181 significantly increased over time in CU and AD diagnostic groups. After controlling for clinical diagnosis, age, sex, and education, baseline plasma p-tau181 predicted change in MoCA overall and change in CDR Sum of Boxes in the AD group over follow-up of up to 5 years. CONCLUSIONS This fully-automated and available blood-based biomarker assay therefore may be useful for early detection, diagnosis, prognosis, and treatment monitoring of AD.
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Affiliation(s)
- Edward N. Wilson
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA
| | - Christina B. Young
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Javier Ramos Benitez
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Michelle S. Swarovski
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Igor Feinstein
- grid.168010.e0000000419368956Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA USA
| | | | - Yann Le Guen
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Nandita M. Kasireddy
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Marian Shahid
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Nicole K. Corso
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Qian Wang
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Gabriel Kennedy
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Alexandra N. Trelle
- grid.168010.e0000000419368956Psychology, Stanford University, Stanford, CA USA
| | - Betty Lind
- grid.410404.50000 0001 0165 2383Neurology, Portland VA Medical Center, Portland, OR USA ,grid.5288.70000 0000 9758 5690Neurology, Oregon Health & Science University, Portland, OR USA
| | - Divya Channappa
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Pathology, Stanford University, Stanford, CA USA
| | - Malia Belnap
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Veronica Ramirez
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Irina Skylar-Scott
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Kyan Younes
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Maya V. Yutsis
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | | | - Joseph F. Quinn
- grid.410404.50000 0001 0165 2383Neurology, Portland VA Medical Center, Portland, OR USA ,grid.5288.70000 0000 9758 5690Neurology, Oregon Health & Science University, Portland, OR USA
| | | | - Angus Nairn
- grid.47100.320000000419368710Psychiatry, Yale University, New Haven, CT USA
| | - Carolyn A. Fredericks
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Lu Tian
- grid.168010.e0000000419368956Biomedical Data Science, Stanford University, Stanford, CA USA
| | - Geoffrey A. Kerchner
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Thomas J. Montine
- grid.168010.e0000000419368956Pathology, Stanford University, Stanford, CA USA
| | - Sharon J. Sha
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA
| | - Guido Davidzon
- grid.168010.e0000000419368956Radiology, Stanford University, Stanford, CA USA
| | - Victor W. Henderson
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Epidemiology & Population Health, Stanford University, Stanford, CA USA
| | - Frank M. Longo
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA
| | - Michael D. Greicius
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA
| | - Anthony D. Wagner
- grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Psychology, Stanford University, Stanford, CA USA
| | - Tony Wyss-Coray
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA
| | - Kathleen L. Poston
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA
| | - Elizabeth C. Mormino
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA
| | - Katrin I. Andreasson
- grid.168010.e0000000419368956Neurology & Neurological Sciences, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA USA ,grid.499295.a0000 0004 9234 0175Chan Zuckerberg Biohub, San Francisco, CA 94158 USA
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83
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Abstract
Alzheimer's disease (AD) characterization has progressed from being indexed using clinical symptomatology followed by neuropathological examination at autopsy to in vivo signatures using cerebrospinal fluid (CSF) biomarkers and positron emission tomography. The core AD biomarkers reflect amyloid-β plaques (A), tau pathology (T) and neurodegeneration (N), following the ATN schedule, and are now being introduced into clinical routine practice. This is an important development, as disease-modifying treatments are now emerging. Further, there are now reproducible data on CSF biomarkers which reflect synaptic pathology, neuroinflammation and common co-pathologies. In addition, the development of ultrasensitive techniques has enabled the core CSF biomarkers of AD pathophysiology to be translated to blood (e.g., phosphorylated tau, amyloid-β and neurofilament light). In this chapter, we review where we stand with both core and novel CSF biomarkers, as well as the explosion of data on blood biomarkers. Also, we discuss potential applications in research aiming to better understand the disease, as well as possible use in routine clinical practice and therapeutic trials.
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Affiliation(s)
- Joel Simrén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden.
| | - Anders Elmgren
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, United Kingdom; UK Dementia Research Institute, University College London, London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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84
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Satoh-Asahara N, Yamakage H, Tanaka M, Kawasaki T, Matsuura S, Tatebe H, Akiguchi I, Tokuda T. Soluble TREM2 and Alzheimer-related biomarker trajectories in the blood of patients with diabetes based on their cognitive status. Diabetes Res Clin Pract 2022; 193:110121. [PMID: 36272585 DOI: 10.1016/j.diabres.2022.110121] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/11/2022] [Accepted: 10/13/2022] [Indexed: 12/01/2022]
Abstract
AIM We aimed to elucidate the dynamics of blood biomarkers according to the severity of cognitive impairment in patients with type 2 diabetes mellitus (DM) and to identify useful biomarkers for diabetes-related dementia. METHODS This was a cross-sectional, nested case-control study of 121 Japanese DM and non-DM patients with different levels of cognitive functioning. We evaluated participants' cognitive functions, blood biomarkers related to Alzheimer's disease, and soluble triggering receptors expressed on myeloid cells 2 (sTREM2). We then compared these biomarkers between the DM and non-DM and across the different cognitive strata. RESULTS In all cognitive strata, significantly lower levels of serum sTREM2 were observed in the DM than in the non-DM. We also found that plasma levels of phosphorylated tau (p-tau) increased with increasing levels of cognitive decline in both the DM and non-DM. However, this was accompanied by a decrease in plasma amyloid-β(Aβ42/Aβ40 ratios in non-DM only. CONCLUSION This study revealed novel characteristic trajectories of dementia-related blood biomarkers in diabetes-related dementia, suggesting the pathological involvement of molecular cascades initiated by impaired microglial activation. This results in decreased serum sTREM2, followed by tauopathy without substantial amyloid plaques, reflected by plasma p-tau elevation with no decrease in the Aβ42/Aβ40 ratio. Clinical trials (the unique trial number and the name of the registry): UMIN000048032, https://www.umin.ac.jp.
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Affiliation(s)
- Noriko Satoh-Asahara
- Clinical Research Institute for Endocrine & Metabolic Disease, National Hospital Organization, Kyoto Medical Center, 1-1 Fukakusa Mukaihata-cho, Fushimi-ku, Kyoto 612-8555, Japan; Department of Metabolic Syndrome and Nutritional Science, Research Institute of Environmental Medicine, Nagoya University, Aichi 464-8601, Japan.
| | - Hajime Yamakage
- Clinical Research Institute for Endocrine & Metabolic Disease, National Hospital Organization, Kyoto Medical Center, 1-1 Fukakusa Mukaihata-cho, Fushimi-ku, Kyoto 612-8555, Japan
| | - Masashi Tanaka
- Clinical Research Institute for Endocrine & Metabolic Disease, National Hospital Organization, Kyoto Medical Center, 1-1 Fukakusa Mukaihata-cho, Fushimi-ku, Kyoto 612-8555, Japan; Department of Physical Therapy, Health Science University, Yamanashi 401-0380, Japan
| | - Teruaki Kawasaki
- Center of Neurological and Cerebrovascular Diseases, Koseikai Takeda Hospital, Kyoto, Japan
| | - Sayo Matsuura
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), 4-9-1 Anagawa, Inage-ku, Chiba-shi, Chiba 263-0024, Japan
| | - Harutsugu Tatebe
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), 4-9-1 Anagawa, Inage-ku, Chiba-shi, Chiba 263-0024, Japan
| | - Ichiro Akiguchi
- Center of Neurological and Cerebrovascular Diseases, Koseikai Takeda Hospital, Kyoto, Japan
| | - Takahiko Tokuda
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology (QST), 4-9-1 Anagawa, Inage-ku, Chiba-shi, Chiba 263-0024, Japan
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85
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Graff-Radford J, Mielke MM, Hofrenning EI, Kouri N, Lesnick TG, Moloney CM, Rabinstein A, Cabrera-Rodriguez JN, Rothberg DM, Przybelski SA, Petersen RC, Knopman DS, Dickson DW, Jack CR, Algeciras-Schimnich A, Nguyen AT, Murray ME, Vemuri P. Association of plasma biomarkers of amyloid and neurodegeneration with cerebrovascular disease and Alzheimer's disease. Neurobiol Aging 2022; 119:1-7. [PMID: 35952440 PMCID: PMC9732897 DOI: 10.1016/j.neurobiolaging.2022.07.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/30/2022] [Accepted: 07/20/2022] [Indexed: 12/13/2022]
Abstract
The objective of this study was to determine the differential mapping of plasma biomarkers to postmortem neuropathology measures. We identified 64 participants in a population-based study with antemortem plasma markers (amyloid-β [Aβ] x-42, Aβx-40, neurofilament light [NfL], and total tau [T-tau]) who also had neuropathologic assessments of Alzheimer's and cerebrovascular pathology. We conducted weighted linear-regression models to evaluate relationships between plasma measures and neuropathology. Higher plasma NfL and Aβ42/40 ratio were associated with cerebrovascular neuropathologic scales (p < 0.05) but not with Braak stage, neuritic plaque score, or Thal phase. Plasma Aβ42/40 and NfL explained up to 18% of the variability in cerebrovascular neuropathologic scales. In participants predominantly with modest levels of Alzheimer's pathologic change, biomarkers of amyloid and neurodegeneration were associated with cerebrovascular neuropathology. NfL is a non-specific marker of brain injury, therefore its association with cerebrovascular neuropathology was expected. The association between elevated Aβ42/40 and cerebrovascular disease pathology needs further investigation but could be due to the use of less specific amyloid-β assays (x-40, x-42).
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Affiliation(s)
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic, Rochester, MN, USA; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA; Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | | | - Naomi Kouri
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | | | - Aivi T Nguyen
- Department of Pathology and Laboratory Medicine, Mayo Clinic, Rochester, MN, USA
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86
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Delaby C, Bousiges O, Bouvier D, Fillée C, Fourier A, Mondésert E, Nezry N, Omar S, Quadrio I, Rucheton B, Schraen-Maschke S, van Pesch V, Vicca S, Lehmann S, Bedel A. Neurofilaments contribution in clinic: state of the art. Front Aging Neurosci 2022; 14:1034684. [PMID: 36389064 PMCID: PMC9664201 DOI: 10.3389/fnagi.2022.1034684] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 10/10/2022] [Indexed: 07/26/2023] Open
Abstract
Neurological biomarkers are particularly valuable to clinicians as they can be used for diagnosis, prognosis, or response to treatment. This field of neurology has evolved considerably in recent years with the improvement of analytical methods, allowing the detection of biomarkers not only in cerebrospinal fluid (CSF) but also in less invasive fluids like blood. These advances greatly facilitate the repeated quantification of biomarkers, including at asymptomatic stages of the disease. Among the various informative biomarkers of neurological disorders, neurofilaments (NfL) have proven to be of particular interest in many contexts, such as neurodegenerative diseases, traumatic brain injury, multiple sclerosis, stroke, and cancer. Here we discuss these different pathologies and the potential value of NfL assay in the management of these patients, both for diagnosis and prognosis. We also describe the added value of NfL compared to other biomarkers currently used to monitor the diseases described in this review.
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Affiliation(s)
- Constance Delaby
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
- Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau—Biomedical Research Institute Sant Pau—Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Olivier Bousiges
- Laboratoire de biochimie et biologie moléculaire (LBBM)—Pôle de biologie Hôpital de Hautepierre—CHU de Strasbourg, CNRS, laboratoire ICube UMR 7357 et FMTS (Fédération de Médecine Translationnelle de Strasbourg), équipe IMIS, Strasbourg, France
| | - Damien Bouvier
- Service de Biochimie et Génétique Moléculaire, CHU de Clermont-Ferrand, Clermont-Ferrand, France
| | - Catherine Fillée
- Cliniques universitaires Saint-Luc UCLouvain, Service de Biochimie Médicale, Brussels, Belgium
| | - Anthony Fourier
- Biochimie et Biologie Moléculaire—LBMMS, Unité de diagnostic des pathologies dégénératives, Centre de Biologie et Pathologie Est, Groupement Hospitalier Est, Lyon, France
| | - Etienne Mondésert
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
| | - Nicolas Nezry
- Univ. Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, Lille, France
| | - Souheil Omar
- Laboratoire de biologie médicale de l’Institut de Neurologie de Tunis, Tunis, Tunisia
| | - Isabelle Quadrio
- Biochimie et Biologie Moléculaire—LBMMS, Unité de diagnostic des pathologies dégénératives, Centre de Biologie et Pathologie Est, Groupement Hospitalier Est, Lyon, France
| | - Benoit Rucheton
- Laboratoire de Biologie, Institut Bergonié, Bordeaux, France
| | - Susanna Schraen-Maschke
- Univ. Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, Lille, France
| | - Vincent van Pesch
- Cliniques universitaires Saint-Luc UCLouvain, Service de Neurologie, Brussels, Belgium
| | - Stéphanie Vicca
- Hôpital Necker-Enfants malades, Paris, Laboratoire de Biochimie générale, DMU BioPhyGen, AP-HP.Centre—Université de Paris, Paris, France
| | - Sylvain Lehmann
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
| | - Aurelie Bedel
- Service de Biochimie, CHU Pellegrin, Bordeaux, France
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87
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Chiu PY, Yang FC, Chiu MJ, Lin WC, Lu CH, Yang SY. Relevance of plasma biomarkers to pathologies in Alzheimer's disease, Parkinson's disease and frontotemporal dementia. Sci Rep 2022; 12:17919. [PMID: 36289355 PMCID: PMC9605966 DOI: 10.1038/s41598-022-22647-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/18/2022] [Indexed: 01/20/2023] Open
Abstract
Amyloid plaques and tau tangles are pathological hallmarks of Alzheimer's disease (AD). Parkinson's disease (PD) results from the accumulation of α-synuclein. TAR DNA-binding protein (TDP-43) and total tau protein (T-Tau) play roles in FTD pathology. All of the pathological evidence was found in the biopsy. However, it is impossible to perform stein examinations in clinical practice. Assays of biomarkers in plasma would be convenient. It would be better to investigate the combinations of various biomarkers in AD, PD and FTD. Ninety-one subjects without neurodegenerative diseases, 76 patients with amnesic mild cognitive impairment (aMCI) or AD dementia, combined as AD family, were enrolled. One hundred and nine PD patients with normal cognition (PD-NC) or dementia (PDD), combined as PD family, were enrolled. Twenty-five FTD patients were enrolled for assays of plasma amyloid β 1-40 (Aβ1-40), Aβ1-42, T-Tau, α-synuclein and TDP-43 using immunomagnetic reduction (IMR). The results show that Aβs and T-Tau are major domains in AD family. α-synuclein is highly dominant in PD family. FTD is closely associated with TDP-43 and T-Tau. The dominant plasma biomarkers in AD family, PD family and FTD are consistent with pathology. This implies that plasma biomarkers are promising for precise and differential assessments of AD, PD and FTD in clinical practice.
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Affiliation(s)
- Pai-Yi Chiu
- grid.452796.b0000 0004 0634 3637Department of Neurology, Show Chwan Memorial Hospital, Chunghwa, 500 Taiwan ,MR-Guided Focus Ultrasound Center, Chang Bin Shaw Chwan Memorial Hospital, Changhwa, 505 Taiwan
| | - Fu-Chi Yang
- grid.278244.f0000 0004 0638 9360Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114 Taiwan
| | - Ming-Jang Chiu
- grid.19188.390000 0004 0546 0241Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, 100 Taiwan ,grid.19188.390000 0004 0546 0241Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, 100 Taiwan ,grid.19188.390000 0004 0546 0241Department of Psychology, National Taiwan University, Taipei, 106 Taiwan ,grid.19188.390000 0004 0546 0241Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, 106 Taiwan
| | - Wei-Che Lin
- grid.145695.a0000 0004 1798 0922Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung, 833 Taiwan
| | - Cheng-Hsien Lu
- grid.145695.a0000 0004 1798 0922Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung, 833 Taiwan
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88
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A Novel Automated Chemiluminescence Method for Detecting Cerebrospinal Fluid Amyloid-Beta 1-42 and 1-40, Total Tau and Phosphorylated-Tau: Implications for Improving Diagnostic Performance in Alzheimer's Disease. Biomedicines 2022; 10:biomedicines10102667. [PMID: 36289929 PMCID: PMC9599653 DOI: 10.3390/biomedicines10102667] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/07/2022] [Accepted: 10/18/2022] [Indexed: 11/16/2022] Open
Abstract
Recently, a fully automated instrument for the detection of the Cerebrospinal Fluid (CSF) biomarker for Alzheimer’s disease (AD) (low concentration of Amyloid-beta 42 (Aβ42), high concentration of total tau (T-tau) and Phosphorylated-tau (P-tau181)), has been implemented, namely CLEIA. We conducted a comparative analysis between ELISA and CLEIA methods in order to evaluate the analytical precision and the diagnostic performance of the novel CLEIA system on 111 CSF samples. Results confirmed a robust correlation between ELISA and CLEIA methods, with an improvement of the accuracy with the new CLEIA methodology in the detection of the single biomarkers and in their ratio values. For Aβ42 regression analysis with Passing−Bablok showed a Pearson correlation coefficient r = 0.867 (0.8120; 0.907% 95% CI p < 0.0001), T-tau analysis: r = 0.968 (0.954; 0.978% 95% CI p < 0.0001) and P-tau181: r = 0.946 (0.922; 0.962 5% 95% CI p < 0.0001). The overall ROC AUC comparison between ROC in ELISA and ROC in CLEIA confirmed a more accurate ROC AUC with the new automatic method: T-tau AUC ELISA = 0.94 (95% CI 0.89; 0.99 p < 0.0001) vs. AUC CLEIA = 0.95 (95% CI 0.89; 1.00 p < 0.0001), and P-tau181 AUC ELISA = 0.91 (95% CI 0.85; 0.98 p < 0.0001) vs. AUC CLEIA = 0.98 (95% CI 0.95; 1.00 p < 0.0001). The performance of the new CLEIA method in automation is comparable and, for tau and P-tau181, even better, as compared with standard ELISA. Hopefully, in the future, automation could be useful in clinical diagnosis and also in the context of clinical studies.
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89
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Morrison MS, Aparicio HJ, Blennow K, Zetterberg H, Ashton NJ, Karikari TK, Tripodis Y, Martin B, Palmisano JN, Sugarman MA, Frank B, Steinberg EG, Turk KW, Budson AE, Au R, Goldstein LE, Jun GR, Kowall NW, Killiany R, Qiu WQ, Stern RA, Mez J, McKee AC, Stein TD, Alosco ML. Ante-mortem plasma phosphorylated tau (181) predicts Alzheimer's disease neuropathology and regional tau at autopsy. Brain 2022; 145:3546-3557. [PMID: 35554506 PMCID: PMC10233293 DOI: 10.1093/brain/awac175] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 04/07/2022] [Accepted: 05/02/2022] [Indexed: 11/14/2022] Open
Abstract
Blood-based biomarkers such as tau phosphorylated at threonine 181 (phosphorylated-tau181) represent an accessible, cost-effective and scalable approach for the in vivo detection of Alzheimer's disease pathophysiology. Plasma-pathological correlation studies are needed to validate plasma phosphorylated-tau181 as an accurate and reliable biomarker of Alzheimer's disease neuropathological changes. This plasma-to-autopsy correlation study included participants from the Boston University Alzheimer's Disease Research Center who had a plasma sample analysed for phosphorylated-tau181 between 2008 and 2018 and donated their brain for neuropathological examination. Plasma phosphorelated-tau181 was measured with single molecule array technology. Of 103 participants, 62 (60.2%) had autopsy-confirmed Alzheimer's disease. Average time between blood draw and death was 5.6 years (standard deviation = 3.1 years). Multivariable analyses showed higher plasma phosphorylated-tau181 concentrations were associated with increased odds for having autopsy-confirmed Alzheimer's disease [AUC = 0.82, OR = 1.07, 95% CI = 1.03-1.11, P < 0.01; phosphorylated-tau standardized (z-transformed): OR = 2.98, 95% CI = 1.50-5.93, P < 0.01]. Higher plasma phosphorylated-tau181 levels were associated with increased odds for having a higher Braak stage (OR = 1.06, 95% CI = 1.02-1.09, P < 0.01) and more severe phosphorylated-tau across six cortical and subcortical brain regions (ORs = 1.03-1.06, P < 0.05). The association between plasma phosphorylated-tau181 and Alzheimer's disease was strongest in those who were demented at time of blood draw (OR = 1.25, 95%CI = 1.02-1.53), but an effect existed among the non-demented (OR = 1.05, 95% CI = 1.01-1.10). There was higher discrimination accuracy for Alzheimer's disease when blood draw occurred in years closer to death; however, higher plasma phosphorylated-tau181 levels were associated with Alzheimer's disease even when blood draw occurred >5 years from death. Ante-mortem plasma phosphorylated-tau181 concentrations were associated with Alzheimer's disease neuropathology and accurately differentiated brain donors with and without autopsy-confirmed Alzheimer's disease. These findings support plasma phosphorylated-tau181 as a scalable biomarker for the detection of Alzheimer's disease.
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Affiliation(s)
- Madeline S Morrison
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
| | - Hugo J Aparicio
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Boston University School of Medicine, Boston, MA 02118, USA
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, 413 90 Gothenburg, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, 413 90 Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London WC1N 3BG, UK
| | - Nicholas J Ashton
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, 413 90 Gothenburg, Sweden
| | - Thomas K Karikari
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, 413 90 Gothenburg, Sweden
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Brett Martin
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA 02118, USA
| | - Joseph N Palmisano
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA 02118, USA
| | - Michael A Sugarman
- Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Brandon Frank
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
| | - Eric G Steinberg
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
| | - Katherine W Turk
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, MA 02130, USA
| | - Andrew E Budson
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, MA 02130, USA
| | - Rhoda Au
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
| | - Lee E Goldstein
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Biomedical Engineering, Boston University College of Engineering, Boston, MA 02215, USA
- Department of Electrical and Computer Engineering, Boston University College of Engineering, Boston, MA 02215, USA
| | - Gyungah R Jun
- Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Neil W Kowall
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, MA 02130, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Ronald Killiany
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA
- Center for Biomedical Imaging, Boston University School of Medicine, Boston, MA 02118, USA
| | - Wei Qiao Qiu
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine, Boston, MA 02118, USA
| | - Robert A Stern
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA 02118, USA
| | - Jesse Mez
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Framingham Heart Study, Boston University School of Medicine, Boston, MA 02118, USA
| | - Ann C McKee
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, MA 02130, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA 02118, USA
- VA Bedford Healthcare System, U.S. Department of Veteran Affairs, Bedford, MA 01730, USA
| | - Thor D Stein
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, MA 02130, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA 02118, USA
- VA Bedford Healthcare System, U.S. Department of Veteran Affairs, Bedford, MA 01730, USA
| | - Michael L Alosco
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
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90
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Alvarez M, Trent E, Goncalves BDS, Pereira DG, Puri R, Frazier NA, Sodhi K, Pillai SS. Cognitive dysfunction associated with COVID-19: Prognostic role of circulating biomarkers and microRNAs. Front Aging Neurosci 2022; 14:1020092. [PMID: 36268187 PMCID: PMC9577202 DOI: 10.3389/fnagi.2022.1020092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/13/2022] [Indexed: 01/08/2023] Open
Abstract
COVID-19 is renowned as a multi-organ disease having subacute and long-term effects with a broad spectrum of clinical manifestations. The evolving scientific and clinical evidence demonstrates that the frequency of cognitive impairment after COVID-19 is high and it is crucial to explore more clinical research and implement proper diagnostic and treatment strategies. Several central nervous system complications have been reported as comorbidities of COVID-19. The changes in cognitive function associated with neurodegenerative diseases develop slowly over time and are only diagnosed at an already advanced stage of molecular pathology. Hence, understanding the common links between COVID-19 and neurodegenerative diseases will broaden our knowledge and help in strategizing prognostic and therapeutic approaches. The present review focuses on the diverse neurodegenerative changes associated with COVID-19 and will highlight the importance of major circulating biomarkers and microRNAs (miRNAs) associated with the disease progression and severity. The literature analysis showed that major proteins associated with central nervous system function, such as Glial fibrillary acidic protein, neurofilament light chain, p-tau 181, Ubiquitin C-terminal hydrolase L1, S100 calcium-binding protein B, Neuron-specific enolase and various inflammatory cytokines, were significantly altered in COVID-19 patients. Furthermore, among various miRNAs that are having pivotal roles in various neurodegenerative diseases, miR-146a, miR-155, Let-7b, miR-31, miR-16 and miR-21 have shown significant dysregulation in COVID-19 patients. Thus the review consolidates the important findings from the numerous studies to unravel the underlying mechanism of neurological sequelae in COVID-19 and the possible association of circulatory biomarkers, which may serve as prognostic predictors and therapeutic targets in future research.
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Affiliation(s)
| | | | | | | | | | | | | | - Sneha S. Pillai
- Department of Surgery, Biomedical Sciences and Medicine, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV, United States
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91
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Calderón-Garcidueñas L, Stommel EW, Lachmann I, Waniek K, Chao CK, González-Maciel A, García-Rojas E, Torres-Jardón R, Delgado-Chávez R, Mukherjee PS. TDP-43 CSF Concentrations Increase Exponentially with Age in Metropolitan Mexico City Young Urbanites Highly Exposed to PM 2.5 and Ultrafine Particles and Historically Showing Alzheimer and Parkinson's Hallmarks. Brain TDP-43 Pathology in MMC Residents Is Associated with High Cisternal CSF TDP-43 Concentrations. TOXICS 2022; 10:559. [PMID: 36287840 PMCID: PMC9611594 DOI: 10.3390/toxics10100559] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/07/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
Abstract
Environmental exposures to fine particulate matter (PM2.5) and ultrafine particle matter (UFPM) are associated with overlapping Alzheimer’s, Parkinson’s and TAR DNA-binding protein 43 (TDP-43) hallmark protein pathologies in young Metropolitan Mexico City (MMC) urbanites. We measured CSF concentrations of TDP-43 in 194 urban residents, including 92 MMC children aged 10.2 ± 4.7 y exposed to PM2.5 levels above the USEPA annual standard and to high UFPM and 26 low pollution controls (11.5 ± 4.4 y); 43 MMC adults (42.3 ± 15.9 y) and 14 low pollution adult controls (33.1 ± 12.0 y); and 19 amyotrophic lateral sclerosis (ALS) patients (52.4 ± 14.1 y). TDP-43 neuropathology and cisternal CSF data from 20 subjects—15 MMC (41.1 ± 18.9 y) and 5 low pollution controls (46 ± 16.01 y)—were included. CSF TDP-43 exponentially increased with age (p < 0.0001) and it was higher for MMC residents. TDP-43 cisternal CSF levels of 572 ± 208 pg/mL in 6/15 MMC autopsy cases forecasted TDP-43 in the olfactory bulb, medulla and pons, reticular formation and motor nuclei neurons. A 16 y old with TDP-43 cisternal levels of 1030 pg/mL exhibited TDP-43 pathology and all 15 MMC autopsy cases exhibited AD and PD hallmarks. Overlapping TDP-43, AD and PD pathologies start in childhood in urbanites with high exposures to PM2.5 and UFPM. Early, sustained exposures to PM air pollution represent a high risk for developing brains and MMC UFPM emissions sources ought to be clearly identified, regulated, monitored and controlled. Prevention of deadly neurologic diseases associated with air pollution ought to be a public health priority and preventive medicine is key.
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Affiliation(s)
- Lilian Calderón-Garcidueñas
- College of Health, The University of Montana, Missoula, MT 59812, USA
- Universidad del Valle de México, Mexico City 14370, Mexico
| | - Elijah W. Stommel
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
| | | | | | - Chih-Kai Chao
- College of Health, The University of Montana, Missoula, MT 59812, USA
| | | | | | - Ricardo Torres-Jardón
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico
| | | | - Partha S. Mukherjee
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata 700108, India
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92
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Huang Y, Li Y, Xie F, Guo Q. Associations of plasma phosphorylated tau181 and neurofilament light chain with brain amyloid burden and cognition in objectively defined subtle cognitive decline patients. CNS Neurosci Ther 2022; 28:2195-2205. [PMID: 36074638 PMCID: PMC9627371 DOI: 10.1111/cns.13962] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 08/05/2022] [Accepted: 08/15/2022] [Indexed: 02/06/2023] Open
Abstract
AIMS There is increasing evidence that plasma biomarkers are specific biomarkers for Alzheimer's disease (AD) pathology, but their potential utility in Obj-SCD (objectively defined subtle cognitive decline) remains unclear. METHODS A total of 234 subjects, including 65 with brain amyloid beta (Aβ) negative normal cognition (Aβ- NC), 58 with Aβ-positive NC (Aβ+ NC), 63 with Aβ- Obj-SCD, and 48 with Aβ+ Obj-SCD were enrolled. Plasma Aβ42, Aβ40, Aβ42/Aβ40 ratio, phosphorylated tau181 (p-tau181), neurofilament light chain (NfL), and total tau (T-tau) were measured using Simoa assays. Logistic and linear regression analyses were used to examine the relationship between plasma biomarkers and brain amyloid, cognition, and imaging measures adjusting for age, sex, education, APOE ε4 status, and vascular risk scores. Receiver operating characteristics were used to evaluate the discriminative validity of biomarkers. RESULTS After adjustment, only plasma p-tau181 and NfL were significantly elevated in Aβ+ Obj-SCD participants compared to Aβ- NC group. Elevated p-tau181 was associated with brain amyloid accumulation, worse cognitive performance (visual episodic memory, executive function, and visuospatial function), and hippocampal atrophy. These associations mainly occurred in Aβ+ individuals. In contrast, higher NfL was correlated with brain amyloid burden and verbal memory decline. These associations predominantly occurred in Aβ- individuals. The adjusted diagnostic model combining p-tau181 and NfL levels showed the best performance in identifying Aβ+ Obj-SCD from Aβ- NC [area under the curve (AUC) = 0.814], which did not differ from the adjusted p-tau181 model (AUC = 0.763). CONCLUSIONS Our findings highlight that plasma p-tau181, alone or combined with NfL, contributes to identifying high-risk AD populations.
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Affiliation(s)
- Yanlu Huang
- Department of GerontologyShanghai Jiao Tong University Affiliated Sixth People's HospitalShanghaiChina
| | - Yuehua Li
- Department of RadiologyShanghai Jiao Tong University Affiliated Sixth People's HospitalShanghaiChina
| | - Fang Xie
- PET Center, Huashan HospitalFudan UniversityShanghaiChina
| | - Qihao Guo
- Department of GerontologyShanghai Jiao Tong University Affiliated Sixth People's HospitalShanghaiChina
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93
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Cummings J, Kinney J. Biomarkers for Alzheimer's Disease: Context of Use, Qualification, and Roadmap for Clinical Implementation. MEDICINA (KAUNAS, LITHUANIA) 2022; 58:952. [PMID: 35888671 PMCID: PMC9318582 DOI: 10.3390/medicina58070952] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/13/2022] [Accepted: 07/15/2022] [Indexed: 12/30/2022]
Abstract
Background and Objectives: The US Food and Drug Administration (FDA) defines a biomarker as a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention. Biomarkers may be used in clinical care or as drug development tools (DDTs) in clinical trials. The goal of this review and perspective is to provide insight into the regulatory guidance for the use of biomarkers in clinical trials and clinical care. Materials and Methods: We reviewed FDA guidances relevant to biomarker use in clinical trials and their transition to use in clinical care. We identified instructive examples of these biomarkers in Alzheimer's disease (AD) drug development and their application in clinical practice. Results: For use in clinical trials, biomarkers must have a defined context of use (COU) as a risk/susceptibility, diagnostic, monitoring, predictive, prognostic, pharmacodynamic, or safety biomarker. A four-stage process defines the pathway to establish the regulatory acceptance of the COU for a biomarker including submission of a letter of intent, description of the qualification plan, submission of a full qualification package, and acceptance through a qualification recommendation. Biomarkers used in clinical care may be companion biomarkers, in vitro diagnostic devices (IVDs), or laboratory developed tests (LDTs). A five-phase biomarker development process has been proposed to structure the biomarker development process. Conclusions: Biomarkers are increasingly important in drug development and clinical care. Adherence to regulatory guidance for biomarkers used in clinical trials and patient care is required to advance these important drug development and clinical tools.
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Affiliation(s)
- Jeffrey Cummings
- Pam Quirk Brain Health and Biomarker Laboratory, Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA;
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94
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Alty J, Bai Q, Li R, Lawler K, St George RJ, Hill E, Bindoff A, Garg S, Wang X, Huang G, Zhang K, Rudd KD, Bartlett L, Goldberg LR, Collins JM, Hinder MR, Naismith SL, Hogg DC, King AE, Vickers JC. The TAS Test project: a prospective longitudinal validation of new online motor-cognitive tests to detect preclinical Alzheimer's disease and estimate 5-year risks of cognitive decline and dementia. BMC Neurol 2022; 22:266. [PMID: 35850660 PMCID: PMC9289357 DOI: 10.1186/s12883-022-02772-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 06/27/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The worldwide prevalence of dementia is rapidly rising. Alzheimer's disease (AD), accounts for 70% of cases and has a 10-20-year preclinical period, when brain pathology covertly progresses before cognitive symptoms appear. The 2020 Lancet Commission estimates that 40% of dementia cases could be prevented by modifying lifestyle/medical risk factors. To optimise dementia prevention effectiveness, there is urgent need to identify individuals with preclinical AD for targeted risk reduction. Current preclinical AD tests are too invasive, specialist or costly for population-level assessments. We have developed a new online test, TAS Test, that assesses a range of motor-cognitive functions and has capacity to be delivered at significant scale. TAS Test combines two innovations: using hand movement analysis to detect preclinical AD, and computer-human interface technologies to enable robust 'self-testing' data collection. The aims are to validate TAS Test to [1] identify preclinical AD, and [2] predict risk of cognitive decline and AD dementia. METHODS Aim 1 will be addressed through a cross-sectional study of 500 cognitively healthy older adults, who will complete TAS Test items comprising measures of motor control, processing speed, attention, visuospatial ability, memory and language. TAS Test measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 (p-tau181). Aim 2 will be addressed through a 5-year prospective cohort study of 10,000 older adults. Participants will complete TAS Test annually and subtests of the Cambridge Neuropsychological Test Battery (CANTAB) biennially. 300 participants will undergo in-person clinical assessments. We will use machine learning of motor-cognitive performance on TAS Test to develop an algorithm that classifies preclinical AD risk (p-tau181-defined) and determine the precision to prospectively estimate 5-year risks of cognitive decline and AD. DISCUSSION This study will establish the precision of TAS Test to identify preclinical AD and estimate risk of cognitive decline and AD. If accurate, TAS Test will provide a low-cost, accessible enrichment strategy to pre-screen individuals for their likelihood of AD pathology prior to more expensive tests such as blood or imaging biomarkers. This would have wide applications in public health initiatives and clinical trials. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT05194787 , 18 January 2022. Retrospectively registered.
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Affiliation(s)
- Jane Alty
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia. .,School of Medicine, University of Tasmania, Hobart, Australia. .,Royal Hobart Hospital, Hobart, Tasmania, Australia.
| | - Quan Bai
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Renjie Li
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Katherine Lawler
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.,Royal Hobart Hospital, Hobart, Tasmania, Australia
| | - Rebecca J St George
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia.,School of Psychological Sciences, University of Tasmania, Hobart, Australia
| | - Edward Hill
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Aidan Bindoff
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Saurabh Garg
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Xinyi Wang
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Guan Huang
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Kaining Zhang
- School of Information and Communication Technologies, University of Tasmania, Hobart, Australia
| | - Kaylee D Rudd
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Larissa Bartlett
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Lynette R Goldberg
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Jessica M Collins
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - Mark R Hinder
- School of Psychological Sciences, University of Tasmania, Hobart, Australia
| | - Sharon L Naismith
- Healthy Brain Ageing Program, University of Sydney, Sydney, Australia
| | - David C Hogg
- School of Computing, University of Leeds, Leeds, UK
| | - Anna E King
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
| | - James C Vickers
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, Australia
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95
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Botella Lucena P, Vanherle S, Lodder C, Gutiérrez de Ravé M, Stancu IC, Lambrichts I, Vangheluwe R, Bruffaerts R, Dewachter I. Blood-based Aβ42 increases in the earliest pre-pathological stage before decreasing with progressive amyloid pathology in preclinical models and human subjects: opening new avenues for prevention. Acta Neuropathol 2022; 144:489-508. [PMID: 35796870 PMCID: PMC9381631 DOI: 10.1007/s00401-022-02458-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/21/2022] [Accepted: 06/21/2022] [Indexed: 11/27/2022]
Abstract
Blood-based (BB) biomarkers for Aβ and tau can indicate pathological processes in the brain, in the early pathological, even pre-symptomatic stages in Alzheimer’s disease. However, the relation between BB biomarkers and AD-related processes in the brain in the earliest pre-pathology stage before amyloid pathology develops, and their relation with total brain concentrations of Aβ and tau, is poorly understood. This stage presents a critical window for the earliest prevention of AD. Preclinical models with well-defined temporal progression to robust amyloid and tau pathology provide a unique opportunity to study this relation and were used here to study the link between BB biomarkers with AD-related processes in pre- and pathological stages. We performed a cross-sectional study at different ages assessing the link between BB concentrations and AD-related processes in the brain. This was complemented with a longitudinal analysis and with analysis of age-related changes in a small cohort of human subjects. We found that BB-tau concentrations increased in serum, correlating with progressive development of tau pathology and with increasing tau aggregates and p-tau concentrations in brain in TauP301S mice (PS19) developing tauopathy. BB-Aβ42 concentrations in serum decreased between 4.5 and 9 months of age, correlating with the progressive development of robust amyloid pathology in APP/PS1 (5xFAD) mice, in line with previous findings. Most importantly, BB-Aβ42 concentrations significantly increased between 1.5 and 4.5 months, i.e., in the earliest pre-pathological stage, before robust amyloid pathology develops in the brain, indicating biphasic BB-Aβ42 dynamics. Furthermore, increasing BB-Aβ42 in the pre-pathological phase, strongly correlated with increasing Aβ42 concentrations in brain. Our subsequent longitudinal analysis of BB-Aβ42 in 5xFAD mice, confirmed biphasic BB-Aβ42, with an initial increase, before decreasing with progressive robust pathology. Furthermore, in human samples, BB-Aβ42 concentrations were significantly higher in old (> 60 years) compared to young (< 50 years) subjects, as well as to age-matched AD patients, further supporting age-dependent increase of Aβ42 concentrations in the earliest pre-pathological phase, before amyloid pathology. Also BB-Aβ40 concentrations were found to increase in the earliest pre-pathological phase both in preclinical models and human subjects, while subsequent significantly decreasing concentrations in the pathological phase were characteristic for BB-Aβ42. Together our data indicate that BB biomarkers reflect pathological processes in brain of preclinical models with amyloid and tau pathology, both in the pathological and pre-pathological phase. Our data indicate a biphasic pattern of BB-Aβ42 in preclinical models and a human cohort. And most importantly, we here show that BB-Aβ increased and correlated with increasing concentrations of Aβ in the brain, in the earliest pre-pathological stage in a preclinical model. Our data thereby identify a novel critical window for prevention, using BB-Aβ as marker for accumulating Aβ in the brain, in the earliest pre-pathological stage, opening new avenues for personalized early preventive strategies against AD, even before amyloid pathology develops.
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Affiliation(s)
- Pablo Botella Lucena
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Sarah Vanherle
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Chritica Lodder
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | | | - Ilie-Cosmin Stancu
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Ivo Lambrichts
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Riet Vangheluwe
- Neurology Department, ZOL Genk General Hospital, Genk, Belgium
| | - Rose Bruffaerts
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium.,Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute (LBI), KU, 3000, Leuven, Belgium.,Department of Neurology, University Hospitals, 3000, Leuven, Belgium.,Computational Neurology, Experimental Neurobiology Unit, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ilse Dewachter
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium.
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96
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Blood phospho-tau in Alzheimer disease: analysis, interpretation, and clinical utility. Nat Rev Neurol 2022; 18:400-418. [PMID: 35585226 DOI: 10.1038/s41582-022-00665-2] [Citation(s) in RCA: 100] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2022] [Indexed: 12/11/2022]
Abstract
Well-authenticated biomarkers can provide critical insights into the biological basis of Alzheimer disease (AD) to enable timely and accurate diagnosis, estimate future burden and support therapeutic trials. Current cerebrospinal fluid and molecular neuroimaging biomarkers fulfil these criteria but lack the scalability and simplicity necessary for widespread application. Blood biomarkers of adequate effectiveness have the potential to act as first-line diagnostic and prognostic tools, and offer the possibility of extensive population screening and use that is not limited to specialized centres. Accelerated progress in our understanding of the biochemistry of brain-derived tau protein and advances in ultrasensitive technologies have enabled the development of AD-specific phosphorylated tau (p-tau) biomarkers in blood. In this Review we discuss how new information on the molecular processing of brain p-tau and secretion of specific fragments into biofluids is informing blood biomarker development, enabling the evaluation of preanalytical factors that affect quantification, and informing harmonized protocols for blood handling. We also review the performance of blood p-tau biomarkers in the context of AD and discuss their potential contexts of use for clinical and research purposes. Finally, we highlight outstanding ethical, clinical and analytical challenges, and outline the steps that need to be taken to standardize inter-laboratory and inter-assay measurements.
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97
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Ossenkoppele R, van der Kant R, Hansson O. Tau biomarkers in Alzheimer's disease: towards implementation in clinical practice and trials. Lancet Neurol 2022; 21:726-734. [DOI: 10.1016/s1474-4422(22)00168-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 03/30/2022] [Accepted: 04/04/2022] [Indexed: 10/18/2022]
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