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Lopez OL, Villemagne VL, Chang YF, Cohen AD, Klunk WE, Mathis CA, Pascoal T, Ikonomovic MD, Rowe C, Dore V, Snitz BE, Lopresti BJ, Kamboh MI, Aizenstein HJ, Kuller LH. Association Between β-Amyloid Accumulation and Incident Dementia in Individuals 80 Years or Older Without Dementia. Neurology 2024; 102:e207920. [PMID: 38165336 PMCID: PMC10870745 DOI: 10.1212/wnl.0000000000207920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 10/03/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES While the highest prevalence of dementia occurs in individuals older than 80 years, most imaging studies focused on younger populations. The rates of β-amyloid (Aβ) accumulation and the effect of Alzheimer disease (AD) pathology on progression to dementia in this age group remain unexplored. In this study, we examined the relationship between changes in Aβ deposition over time and incident dementia in nondemented individuals followed during a period of 11 years. METHODS We examined 94 participants (age 85.9 + 2.8 years) who had up to 5 measurements of Pittsburgh compound-B (PiB)-PET and clinical evaluations from 2009 to 2020. All 94 participants had 2 PiB-PET scans, 76 participants had 3 PiB-PET scans, 18 participants had 4 PiB-PET scans, and 10 participants had 5 PiB-PET scans. The rates of Aβ deposition were compared with 120 nondemented individuals younger than 80 years (69.3 ± 5.4 years) from the Australian Imaging, Biomarker, and Lifestyle (AIBL) study who had 3 or more annual PiB-PET assessments. RESULTS By 2020, 49% of the participants developed dementia and 63% were deceased. There was a gradual increase in Aβ deposition in all participants whether they were considered Aβ positive or negative at baseline. In a Cox model controlled for age, sex, education level, APOE-4 allele, baseline Mini-Mental State Examination, and mortality, short-term change in Aβ deposition was not significantly associated with incident dementia (HR 2.19 (0.41-11.73). However, baseline Aβ burden, cortical thickness, and white matter lesions volume were the predictors of incident dementia. Aβ accumulation was faster (p = 0.01) in the older cohort (5.6%/year) when compared with AIBL (4.1%/year). In addition, baseline Aβ deposition was a predictor of short-term change (mean time 1.88 years). DISCUSSION There was an accelerated Aβ accumulation in cognitively normal individuals older than 80 years. Baseline Aβ deposition was a determinant of incident dementia and short-term change in Aβ deposition suggesting that an active Aβ pathologic process was present when these participants were cognitively normal. Consequently, age may not be a limiting factor for the use of the emergent anti-Aβ therapies.
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Affiliation(s)
- Oscar L Lopez
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Victor L Villemagne
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Yue-Fang Chang
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Ann D Cohen
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - William E Klunk
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Chester A Mathis
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Tharick Pascoal
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Milos D Ikonomovic
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Christopher Rowe
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Vincent Dore
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Beth E Snitz
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Brian J Lopresti
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - M Ilyas Kamboh
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Howard J Aizenstein
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
| | - Lewis H Kuller
- From the Departments of Neurology (O.L.L., W.E.K., M.D.I., B.E.S.), Psychiatry (O.L.L., V.L.V., A.D.C., W.E.K., T.P., H.J.A.), Neurosurgery (Y.-F.C.), Radiology (A.D.C., C.A.M., B.J.L.), Epidemiology (L.H.K.), and Human Genetics, Graduate School of Public Health (M.I.K.), University of Pittsburgh, PA; Department of Molecular Imaging and Therapy (C.R.), Austin Health, Melbourne; The Florey Institute of Neuroscience and Mental Health (C.R., V.D.), University of Melbourne; and CSIRO Health and Biosecurity (V.D.), Melbourne, Australia
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Hajat A, Park C, Adam C, Fitzpatrick AL, Ilango SD, Leary C, Libby T, Lopez O, Semmens EO, Kaufman JD. Air pollution and plasma amyloid beta in a cohort of older adults: Evidence from the Ginkgo Evaluation of Memory study. ENVIRONMENT INTERNATIONAL 2023; 172:107800. [PMID: 36773564 PMCID: PMC9974914 DOI: 10.1016/j.envint.2023.107800] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 01/20/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
Air pollution has been linked to Alzheimer's disease and related dementias (ADRD), but the mechanisms connecting air pollution to ADRD have not been firmly established. Air pollution may cause oxidative stress and neuroinflammation and contribute to the deposition of amyloid beta (Aβ) in the brain. We examined the association between fine particulate matter<2.5 μm in diameter (PM2.5), particulate matter<10 μm in diameter (PM10), nitrogen dioxide (NO2), and plasma based measures of Aβ1-40, Aβ1-42 and Aβ1-42/Aβ1-40 using data from 3044 dementia-free participants of the Ginkgo Evaluation of Memory Study (GEMS). Air pollution exposures were estimated at residential addresses that incorporated address histories dating back to 1980, resulting in one-, five-, 10- and 20- year exposure averages. Aβ was measured at baseline (2000-2002) and then again at the end of the study (2007-2008) allowing for linear regression models to assess cross-sectional associations and linear random effects models to evaluate repeated measures. After adjustment for socio-demographic and behavioral covariates, we found small positive associations between each air pollutant and Aβ1-40 but no association with Aβ1-42 or the ratio measures in cross sectional analysis. In repeat measures analysis, we found larger positive associations between each air pollutant and all three outcomes. We observed a 4.43% (95% CI 3.26%, 5.60%) higher Aβ1-40 level, 9.73% (6.20%, 13.38%) higher Aβ1-42 and 1.57% (95% CI: 0.94%, 2.20%) higher Aβ1-42/Aβ1-40 ratio associated with a 2 µg/m3 higher 20-year average PM2.5. Associations with other air pollutants were similar. Our study contributes to the broader evidence base on air pollution and ADRD biomarkers by evaluating longer air pollution exposure averaging periods to better mimic disease progression and provides a modifiable target for ADRD prevention.
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Affiliation(s)
- Anjum Hajat
- University of Washington, Department of Epidemiology, 3980 15th Ave NE, Seattle, WA 98195, USA.
| | - Christina Park
- University of Washington, Department of Epidemiology, 3980 15th Ave NE, Seattle, WA 98195, USA
| | - Claire Adam
- University of Montana, School of Public and Community Health Sciences, Skaggs Building, 32 Campus Drive Missola, MT 59812, USA
| | - Annette L Fitzpatrick
- University of Washington, Department of Family Medicine, 4225 Roosevelt Ave NE Seattle, WA 98195, USA
| | - Sindana D Ilango
- University of Washington, Department of Epidemiology, 3980 15th Ave NE, Seattle, WA 98195, USA
| | - Cindy Leary
- University of Montana, School of Public and Community Health Sciences, Skaggs Building, 32 Campus Drive Missola, MT 59812, USA
| | - Tanya Libby
- University of Washington, Department of Epidemiology, 3980 15th Ave NE, Seattle, WA 98195, USA
| | - Oscar Lopez
- University of Pittsburgh, Department of Neurology, 811 Kaufmann Medical Building, 3471 Fifth Avenue, Pittsburgh, PA 15123, USA
| | - Erin O Semmens
- University of Montana, School of Public and Community Health Sciences, Skaggs Building, 32 Campus Drive Missola, MT 59812, USA
| | - Joel D Kaufman
- University of Washington, Department of Environmental and Occupational Health and Epidemiology, 4225 Roosevelt Ave NE, Seattle, WA 98195, USA
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3
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Winston CN, Langford O, Levin N, Raman R, Yarasheski K, West T, Abdel-Latif S, Donohue M, Nakamura A, Toba K, Masters CL, Doecke J, Sperling RA, Aisen PS, Rissman RA. Evaluation of Blood-Based Plasma Biomarkers as Potential Markers of Amyloid Burden in Preclinical Alzheimer's Disease. J Alzheimers Dis 2023; 92:95-107. [PMID: 36710683 PMCID: PMC11191492 DOI: 10.3233/jad-221118] [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] [Accepted: 12/21/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND Participant eligibility for the A4 Study was determined by amyloid PET imaging. Given the disadvantages of amyloid PET imaging in accessibility and cost, blood-based biomarkers may serve as a sufficient biomarker and more cost-effective screening tool for patient enrollment into preclinical AD trials. OBJECTIVE To determine if a blood-based screening test can adequately identify amyloid burden in participants screened into a preclinical AD trial. METHODS In this cross-sectional study, 224 participants from the A4 Study received an amyloid PET scan (18Florbetapir) within 90 days of blood sample collection. Blood samples from all study participants were processed within 2 h after phlebotomy. Plasma amyloid measures were quantified by Shimazdu and C2 N Diagnostics using mass spectrometry-based platforms. A corresponding subset of blood samples (n = 100) was processed within 24 h after phlebotomy and analyzed by C2 N. RESULTS Plasma Aβ42/Aβ40 demonstrated the highest association for Aβ accumulation in the brain with an AUC 0.76 (95%CI = 0.69, 0.82) at C2 N and 0.80 (95%CI = 0.75, 0.86) at Shimadzu. Blood samples processed to plasma within 2 h after phlebotomy provided a better prediction of amyloid PET status than blood samples processed within 24 h (AUC 0.80 versus 0.64; p < 0.001). Age, sex, and APOE ɛ4 carrier status did not the diagnostic performance of plasma Aβ42/Aβ40 to predict amyloid PET positivity in A4 Study participants. CONCLUSION Plasma Aβ42/Aβ40 may serve as a potential biomarker for predicting elevated amyloid in the brain. Utilizing blood testing over PET imaging may improve screening efficiency into clinical trials.
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Affiliation(s)
- Charisse N. Winston
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Oliver Langford
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine University of Southern California, San Diego, CA, USA
| | - Natalie Levin
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Rema Raman
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine University of Southern California, San Diego, CA, USA
| | | | - Tim West
- C2N Diagnostics, St. Louis, MO, USA
| | - Sara Abdel-Latif
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine University of Southern California, San Diego, CA, USA
| | - Michael Donohue
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine University of Southern California, San Diego, CA, USA
| | - Akinori Nakamura
- Department of Biomarker Research, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Kenji Toba
- National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Colin L. Masters
- The Florey Institute, The University of Melbourne, Parkville, VIC, Australia
| | - James Doecke
- The Commonwealth Scientific and Industrial Research Organization, Brisbane, QLD, Australia
| | | | - Paul S. Aisen
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine University of Southern California, San Diego, CA, USA
| | - Robert A. Rissman
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego and VA San Diego Healthcare System, La Jolla, CA, USA
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Wisch JK, Gordon BA, Boerwinkle AH, Luckett PH, Bollinger JG, Ovod V, Li Y, Henson RL, West T, Meyer MR, Kirmess KM, Benzinger TL, Fagan AM, Morris JC, Bateman RJ, Ances BM, Schindler SE. Predicting continuous amyloid PET values with CSF and plasma Aβ42/Aβ40. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12405. [PMID: 36874595 PMCID: PMC9980305 DOI: 10.1002/dad2.12405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 12/14/2022] [Accepted: 01/19/2023] [Indexed: 03/06/2023]
Abstract
Introduction Continuous measures of amyloid burden as measured by positron emission tomography (PET) are being used increasingly to stage Alzheimer's disease (AD). This study examined whether cerebrospinal fluid (CSF) and plasma amyloid beta (Aβ)42/Aβ40 could predict continuous values for amyloid PET. Methods CSF Aβ42 and Aβ40 were measured with automated immunoassays. Plasma Aβ42 and Aβ40 were measured with an immunoprecipitation-mass spectrometry assay. Amyloid PET was performed with Pittsburgh compound B (PiB). The continuous relationships of CSF and plasma Aβ42/Aβ40 with amyloid PET burden were modeled. Results Most participants were cognitively normal (427 of 491 [87%]) and the mean age was 69.0 ± 8.8 years. CSF Aβ42/Aβ40 predicted amyloid PET burden until a relatively high level of amyloid accumulation (69.8 Centiloids), whereas plasma Aβ42/Aβ40 predicted amyloid PET burden until a lower level (33.4 Centiloids). Discussion CSF Aβ42/Aβ40 predicts the continuous level of amyloid plaque burden over a wider range than plasma Aβ42/Aβ40 and may be useful in AD staging. Highlights Cerebrospinal fluid (CSF) amyloid beta (Aβ)42/Aβ40 predicts continuous amyloid positron emission tomography (PET) values up to a relatively high burden.Plasma Aβ42/Aβ40 is a comparatively dichotomous measure of brain amyloidosis.Models can predict regional amyloid PET burden based on CSF Aβ42/Aβ40.CSF Aβ42/Aβ40 may be useful in staging AD.
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Affiliation(s)
- Julie K. Wisch
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Brian A. Gordon
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
- Hope CenterWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Anna H. Boerwinkle
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Patrick H. Luckett
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - James G. Bollinger
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- The Tracy Family SILQ Center for Neurodegenerative BiologySt. LouisMissouriUSA
| | - Vitaliy Ovod
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- The Tracy Family SILQ Center for Neurodegenerative BiologySt. LouisMissouriUSA
| | - Yan Li
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Rachel L. Henson
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
| | - Tim West
- C2N DiagnosticsSt. LouisMissouriUSA
| | | | | | - Tammie L.S. Benzinger
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Anne M. Fagan
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - John C. Morris
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Randall J. Bateman
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- The Tracy Family SILQ Center for Neurodegenerative BiologySt. LouisMissouriUSA
| | - Beau M. Ances
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Department of RadiologyWashington University in Saint LouisSt. LouisMissouriUSA
- Hope CenterWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
| | - Suzanne E. Schindler
- Department of NeurologyWashington University in Saint LouisSt. LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
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5
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Hanon O, Vidal JS, Lehmann S, Bombois S, Allinquant B, Baret-Rose C, Tréluyer JM, Abdoul H, Gelé P, Delmaire C, Blanc F, Mangin JF, Buée L, Touchon J, Hugon J, Vellas B, Galbrun E, Benetos A, Berrut G, Paillaud E, Wallon D, Castelnovo G, Volpe-Gillot L, Paccalin M, Robert P, Godefroy O, Camus V, Belmin J, Vandel P, Novella JL, Duron E, Rigaud AS, Schraen-Maschke S, Gabelle A. Plasma amyloid beta predicts conversion to dementia in subjects with mild cognitive impairment: The BALTAZAR study. Alzheimers Dement 2022; 18:2537-2550. [PMID: 35187794 DOI: 10.1002/alz.12613] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 10/20/2021] [Accepted: 12/10/2021] [Indexed: 01/31/2023]
Abstract
INTRODUCTION Blood-based biomarkers are the next challenge for Alzheimer's disease (AD) diagnosis and prognosis. METHODS Mild cognitive impairment (MCI) participants (N = 485) of the BALTAZAR study, a large-scale longitudinal multicenter cohort, were followed-up for 3 years. A total of 165 of them converted to dementia (95% AD). Associations of conversion and plasma amyloid beta (Aβ)1-42 , Aβ1-40 , Aβ1-42 /Aβ1-40 ratio were analyzed with logistic and Cox models. RESULTS Converters to dementia had lower level of plasma Aβ1-42 (37.1 pg/mL [12.5] vs. 39.2 [11.1] , P value = .03) and lower Aβ1-42 /Aβ1-40 ratio than non-converters (0.148 [0.125] vs. 0.154 [0.076], P value = .02). MCI participants in the highest quartile of Aβ1-42 /Aβ1-40 ratio (>0.169) had a significant lower risk of conversion (hazard ratio adjusted for age, sex, education, apolipoprotein E ε4, hippocampus atrophy = 0.52 (95% confidence interval [0.31-0.86], P value = .01). DISCUSSION In this large cohort of MCI subjects we identified a threshold for plasma Aβ1-42 /Aβ1-40 ratio that may detect patients with a low risk of conversion to dementia within 3 years.
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Affiliation(s)
- Olivier Hanon
- Memory Resource and Research Centre of de Paris-Broca-Ile de France, Université de Paris, EA 4468, APHP, Hopital Broca, Paris, France
| | - Jean-Sébastien Vidal
- Memory Resource and Research Centre of de Paris-Broca-Ile de France, Université de Paris, EA 4468, APHP, Hopital Broca, Paris, France
| | - Sylvain Lehmann
- CHU Montpellier, LBPC, Inserm, Université de Montpellier, Montpellier, France
| | - Stéphanie Bombois
- CHU Lille, U1172-LilNCog, LiCEND, LabEx DISTALZ, Université de Lille, Inserm, Lille, France
| | - Bernadette Allinquant
- UMR-S 1266, Université de Paris, Institute of Psychiatric and Neurosciences, Inserm, Paris, France
| | - Christiane Baret-Rose
- UMR-S 1266, Université de Paris, Institute of Psychiatric and Neurosciences, Inserm, Paris, France
| | - Jean-Marc Tréluyer
- Clinical Research Unit, Université de Paris, APHP, Hôpital Necker, Paris, France
| | - Hendy Abdoul
- Clinical Research Unit, Université de Paris, APHP, Hôpital Necker, Paris, France
| | - Patrick Gelé
- CHU Lille, CRB/CIC1403, Université de Lille, Inserm, Lille, France
| | - Christine Delmaire
- CHU Lille, U1172-LilNCog, LiCEND, LabEx DISTALZ, Université de Lille, Inserm, Lille, France
| | - Fredéric Blanc
- CM2R, pôle de Gériatrie, Laboratoire ICube, FMTS, CNRS, équipe IMIS, Université de Strasbourg, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Jean-François Mangin
- Neurospin, CEA, CNRS, cati-neuroimaging.com, CATI Multicenter Neuroimaging Platform, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Luc Buée
- CHU Lille, U1172-LilNCog, LiCEND, LabEx DISTALZ, Université de Lille, Inserm, Lille, France
| | - Jacques Touchon
- Department of Neurology, Memory Research and Resources Center of Montpellier, Inserm INM NeuroPEPs Team, Excellence Center of Neurodegenerative Disorders, Université de Montpellier, CHU Montpellier, Montpellier, France
| | - Jacques Hugon
- APHP, Groupe Hospitalier Saint Louis-Lariboisière Fernand Widal, Center of Cognitive Neurology, Université de Paris, Paris, France
| | - Bruno Vellas
- Memory Resource and Research Centre of Midi-Pyrénées, Université de Toulouse III, CHU La Grave-Casselardit, Toulouse, France
| | - Evelyne Galbrun
- Department of Gérontology 2, Sorbonne Université, APHP, Centre Hospitalier Dupuytren, Draveil, France
| | - Athanase Benetos
- Memory Resource and Research Centre of Lorraine, Université de Lorraine, CHRU de Nancy, Vandoeuvre-lès-Nancy, France
| | - Gilles Berrut
- Department of Clinical Gerontology, Memory Research Resource Center of Nantes, Université de Nantes, EA 4334 Movement-Interactions-Performance, CHU Nantes, Nantes, France
| | - Elena Paillaud
- Service de Gériatrie, Université de Paris, APHP, Hôpital Europeen Georges Pompidou, Paris, France
| | - David Wallon
- CHU de Rouen, Department of Neurology and CNR-MAJ, Normandy Center for Genomic and Personalized Medicine, CIC-CRB1404, Normandie Univ, UNIROUEN, Inserm U1245, Rouen, France
| | | | - Lisette Volpe-Gillot
- Service de Neuro-Psycho-Gériatrie, Memory Clinic, Hôpital Léopold Bellan, Paris, France
| | - Marc Paccalin
- Memory Resource and Research Centre of Poitiers, CHU de Poitiers, Poitiers, France
| | - Philippe Robert
- Memory Research Resource Center of Nice, CoBTek lab, Université Côte d'Azur, CHU de Nice, Nice, France
| | - Olivier Godefroy
- Memory Resource and Research Centre of Amiens Picardie, CHU d'Amiens-Picardie, Amiens, France
| | - Vincent Camus
- CHRU de Tours, UMR Inserm U1253, Université François-Rabelais de Tours, Tours, France
| | - Joël Belmin
- Service de Gériatrie Ambulatoire, Sorbonne Université, APHP, Hôpitaux Universitaires Pitie-Salpêtrière-Charles Foix, Paris, France
| | - Pierre Vandel
- Laboratoire de Recherches Intégratives en Neurosciences et Psychologie Cognitive, CHU de Besançon, Memory Resource and Research Centre of Besançon Franche-Comté, Université Bourgogne Franche-Comté, Besançon, France
| | - Jean-Luc Novella
- Memory Resource and Research Centre of Champagne-Ardenne, Université de Reims Champagne-Ardenne, EA 3797, CHU de Reims, Reims, France
| | - Emmanuelle Duron
- Département de gériatrie, Équipe MOODS, Inserm 1178, Université Paris-Saclay, APHP, Hôpital Paul Brousse, Villejuif, France
| | - Anne-Sophie Rigaud
- Memory Resource and Research Centre of de Paris-Broca-Ile de France, Université de Paris, EA 4468, APHP, Hopital Broca, Paris, France
| | | | - Audrey Gabelle
- Department of Neurology, Memory Research and Resources Center of Montpellier, Inserm INM NeuroPEPs Team, Excellence Center of Neurodegenerative Disorders, Université de Montpellier, CHU Montpellier, Montpellier, France
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6
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Biomarkers of Neurodegenerative Diseases: Biology, Taxonomy, Clinical Relevance, and Current Research Status. Biomedicines 2022; 10:biomedicines10071760. [PMID: 35885064 PMCID: PMC9313182 DOI: 10.3390/biomedicines10071760] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/18/2022] [Accepted: 07/19/2022] [Indexed: 01/02/2023] Open
Abstract
The understanding of neurodegenerative diseases, traditionally considered to be well-defined entities with distinguishable clinical phenotypes, has undergone a major shift over the last 20 years. The diagnosis of neurodegenerative diseases primarily requires functional brain imaging techniques or invasive tests such as lumbar puncture to assess cerebrospinal fluid. A new biological approach and research efforts, especially in vivo, have focused on biomarkers indicating underlying proteinopathy in cerebrospinal fluid and blood serum. However, due to the complexity and heterogeneity of neurodegenerative processes within the central nervous system and the large number of overlapping clinical diagnoses, identifying individual proteinopathies is relatively difficult and often not entirely accurate. For this reason, there is an urgent need to develop laboratory methods for identifying specific biomarkers, understand the molecular basis of neurodegenerative disorders and classify the quantifiable and readily available tools that can accelerate efforts to translate the knowledge into disease-modifying therapies that can improve and simplify the areas of differential diagnosis, as well as monitor the disease course with the aim of estimating the prognosis or evaluating the effects of treatment. The aim of this review is to summarize the current knowledge about clinically relevant biomarkers in different neurodegenerative diseases.
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7
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Rippon B, Palta P, Tahmi M, Sherwood G, Soto L, Cespedes S, Mesen Y, He H, Laing K, Moreno H, Teresi J, Razlighi Q, Brickman AM, Zetterberg H, Luchsinger JA. Plasma Amyloid and in vivo Brain Amyloid in Late Middle-Aged Hispanics. J Alzheimers Dis 2022; 87:1229-1238. [PMID: 35466933 PMCID: PMC10361456 DOI: 10.3233/jad-210391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Determining amyloid positivity is possible with cerebrospinal fluid and brain imaging of amyloid, but these methods are invasive and expensive. OBJECTIVE To relate plasma amyloid-β (Aβ), measured using Single-molecule array (Simoatrademark) assays, to in vivo brain Aβ, measured using positron emission tomography (PET), examine the accuracy of plasma Aβ to predict brain Aβ positivity, and the relation of APOE ɛ4 with plasma Aβ. METHODS We performed a cross-sectional analysis in a cohort of 345 late middle-aged Hispanic men and women (age 64 years, 72% women). Our primary plasma variable was Aβ42/Aβ40 ratio measured with Simoa. Brain Aβ burden was measured as global SUVR with 18F-Florbetaben PET examined continuously and categorically. RESULTS Plasma Aβ42/Aβ40 ratio was inversely associated with global Aβ SUVR (β= -0.13, 95% Confidence Interval (CI): -0.23, -0.03; p = 0.013) and Aβ positivity (Odds Ratio: 0.59, 95% CI: 0.38, 0.91; p = 0.016), independent of demographics and APOE ɛ4. ROC curves (AUC = 0.73, 95% CI: 0.64, 0.82; p < 0.0001) showed that the optimal threshold for plasma Aβ42/Aβ40 ratio in relation to brain Aβ positivity was 0.060 with a sensitivity of 82.4% and specificity of 62.8%. APOE ɛ4 carriers had lower Aβ42/Aβ40 ratio and a higher Aβ positivity determined with the Aβ42/Aβ40 ratio threshold of 0.060. CONCLUSION Plasma Aβ42/Aβ40 ratio assayed using Simoa is weakly correlated with in vivo brain amyloid and has limited accuracy in screening for amyloid positivity and for studying risk factors of brain amyloid burden when in vivo imaging is not feasible.
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Affiliation(s)
- Brady Rippon
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA
| | - Priya Palta
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA.,Department of Epidemiology, Joseph P. Mailman School of Public Health, CUIMC, New York, NY, USA
| | - Mouna Tahmi
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA
| | - Greysi Sherwood
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA
| | - Luisa Soto
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA
| | - Sandino Cespedes
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA
| | - Yanette Mesen
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA
| | - Hengda He
- Department of Neurology, College of Physicians and Surgeons, CUIMC, New York, NY, USA
| | - Krystal Laing
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, CUIMC, New York, NY, USA
| | - Herman Moreno
- Department of Neurology and Pharmacology/Physiology, SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - Jeanne Teresi
- Research Division, Hebrew Home in Riverdale, Bronx, NY, USA
| | - Qolamreza Razlighi
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Adam M Brickman
- Department of Neurology, College of Physicians and Surgeons, CUIMC, New York, NY, USA.,Taub Institute for Research on Alzheimer's Disease and the Aging Brain, CUIMC, New York, NY, USA.,Gertrude H. Sergievsky Center, CUIMC, New York, NY, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - José A Luchsinger
- Department of Medicine, College of Physicians and Surgeons, Columbia University Irving Medical Center (CUIMC), New York, NY, USA.,Department of Epidemiology, Joseph P. Mailman School of Public Health, CUIMC, New York, NY, USA
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8
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Chen TB, Lin KJ, Lin SY, Lee YJ, Lin YC, Wang CY, Chen JP, Wang PN. Prediction of Cerebral Amyloid Pathology Based on Plasma Amyloid and Tau Related Markers. Front Neurol 2021; 12:619388. [PMID: 34671305 PMCID: PMC8520900 DOI: 10.3389/fneur.2021.619388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 09/07/2021] [Indexed: 11/26/2022] Open
Abstract
Background and Purpose: Pyroglutamate-modified β-amyloid peptide (AβpE) is crucial for AD pathophysiological process. The potential associations of plasma AβpE and total tau (t-tau) with brain Aβ burden and cognitive performance remain to be clarified. Methods: Forty-six subjects with unimpaired cognition, mild cognitive impairment, or very mild dementia were enrolled. Plasma levels of AβpE3−40, t-tau, and Aβ42 were quantified by immunomagnetic reduction (IMR) assays. We analyzed individual and combined biomarker correlations with neuropsychological scores and Aβ positivity determined by 18F-florbetapir positron emission tomography (PET). Results: Both plasma AβpE3−40 levels and AβpE3−40/t-tau ratios correlated negatively with short-term memory and global cognition scores, while correlating positively with PET standardized uptake value ratios (SUVRs). Among the biomarkers analyzed, the combination of AβpE3−40 in a ratio with t-tau had the best discriminatory ability for Aβ PET positivity. Likewise, logistic regression analysis showed that AβpE3−40/t-tau was a highly robust predictor of Aβ PET positivity after controlling for relevant demographic covariates. Conclusion: Plasma AβpE3−40/t-tau ratios correlate with cognitive function and cerebral Aβ burden. The suitability of AβpE3−40/t-tau as a candidate clinical biomarker of AD pathology in the brain should be examined further in larger studies.
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Affiliation(s)
- Ting-Bin Chen
- Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, Taichung, Taiwan.,Dementia Center, Taichung Veterans General Hospital, Taichung, Taiwan.,Center for Geriatrics and Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Kun-Ju Lin
- Department of Nuclear Medicine and Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan.,Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Szu-Ying Lin
- Taipei Municipal Gan-Dau Hospital, Taipei, Taiwan
| | - Yi-Jung Lee
- Division of Neurology, Department of Medicine, Taipei City Hospital Renai Branch, Taipei, Taiwan
| | - Yi-Cheng Lin
- Taipei Municipal Gan-Dau Hospital, Taipei, Taiwan.,School of Life Sciences, Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan
| | - Chen-Yu Wang
- Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Jun-Peng Chen
- Biostatistics Task Force of Taichung Veterans General Hospital, Taichung, Taiwan
| | - Pei-Ning Wang
- Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.,Faculty of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
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9
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Hadjidemetriou M, Rivers-Auty J, Papafilippou L, Eales J, Kellett KAB, Hooper NM, Lawrence CB, Kostarelos K. Nanoparticle-Enabled Enrichment of Longitudinal Blood Proteomic Fingerprints in Alzheimer's Disease. ACS NANO 2021; 15:7357-7369. [PMID: 33730479 PMCID: PMC8155389 DOI: 10.1021/acsnano.1c00658] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Blood-circulating biomarkers have the potential to detect Alzheimer's disease (AD) pathology before clinical symptoms emerge and to improve the outcomes of clinical trials for disease-modifying therapies. Despite recent advances in understanding concomitant systemic abnormalities, there are currently no validated or clinically used blood-based biomarkers for AD. The extremely low concentration of neurodegeneration-associated proteins in blood necessitates the development of analytical platforms to address the "signal-to-noise" issue and to allow an in-depth analysis of the plasma proteome. Here, we aimed to discover and longitudinally track alterations of the blood proteome in a transgenic mouse model of AD, using a nanoparticle-based proteomics enrichment approach. We employed blood-circulating, lipid-based nanoparticles to extract, analyze and monitor AD-specific protein signatures and to systemically uncover molecular pathways associated with AD progression. Our data revealed the existence of multiple proteomic signals in blood, indicative of the asymptomatic stages of AD. Comprehensive analysis of the nanoparticle-recovered blood proteome by label-free liquid chromatography-tandem mass spectrometry resulted in the discovery of AD-monitoring signatures that could discriminate the asymptomatic phase from amyloidopathy and cognitive deterioration. While the majority of differentially abundant plasma proteins were found to be upregulated at the initial asymptomatic stages, the abundance of these molecules was significantly reduced as a result of amyloidosis, suggesting a disease-stage-dependent fluctuation of the AD-specific blood proteome. The potential use of the proposed nano-omics approach to uncover information in the blood that is directly associated with brain neurodegeneration was further exemplified by the recovery of focal adhesion cascade proteins. We herein propose the integration of nanotechnology with already existing proteomic analytical tools in order to enrich the identification of blood-circulating signals of neurodegeneration, reinvigorating the potential clinical utility of the blood proteome at predicting the onset and kinetics of the AD progression trajectory.
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Affiliation(s)
- Marilena Hadjidemetriou
- Nanomedicine
Lab, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PT, United Kingdom
- (M.H.)
| | - Jack Rivers-Auty
- Division
of Neuroscience and Experimental Psychology, School of Biological
Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science
Centre, Manchester M13 9PT, United Kingdom
| | - Lana Papafilippou
- Nanomedicine
Lab, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - James Eales
- Division
of Cardiovascular Sciences, School of Medical Sciences, Faculty of
Biology, Medicine and Health, The University
of Manchester M13 9PT, Manchester, United Kingdom
| | - Katherine A. B. Kellett
- Division
of Neuroscience and Experimental Psychology, School of Biological
Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science
Centre, Manchester M13 9PT, United Kingdom
| | - Nigel M. Hooper
- Division
of Neuroscience and Experimental Psychology, School of Biological
Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science
Centre, Manchester M13 9PT, United Kingdom
| | - Catherine B. Lawrence
- Division
of Neuroscience and Experimental Psychology, School of Biological
Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science
Centre, Manchester M13 9PT, United Kingdom
| | - Kostas Kostarelos
- Nanomedicine
Lab, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PT, United Kingdom
- (K.K.)
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10
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Toombs J, Zetterberg H. In the blood: biomarkers for amyloid pathology and neurodegeneration in Alzheimer's disease. Brain Commun 2020; 2:fcaa054. [PMID: 32954304 PMCID: PMC7425323 DOI: 10.1093/braincomms/fcaa054] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Affiliation(s)
- Jamie Toombs
- Centre for Discovery Brain Sciences, UK Dementia Research Institute, The University of Edinburgh, UK
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, London, UK.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,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
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