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van der Veere PJ, Hoogland J, Visser LNC, Van Harten AC, Rhodius-Meester HF, Sikkes SAM, Venkatraghavan V, Barkhof F, Teunissen CE, van de Giessen E, Berkhof J, Van Der Flier WM. Predicting Cognitive Decline in Amyloid-Positive Patients With Mild Cognitive Impairment or Mild Dementia. Neurology 2024; 103:e209605. [PMID: 38986053 PMCID: PMC11238942 DOI: 10.1212/wnl.0000000000209605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Cognitive decline rates in Alzheimer disease (AD) vary greatly. Disease-modifying treatments may alter cognitive decline trajectories, rendering their prediction increasingly relevant. We aimed to construct clinically applicable prediction models of cognitive decline in amyloid-positive patients with mild cognitive impairment (MCI) or mild dementia. METHODS From the Amsterdam Dementia Cohort, we selected amyloid-positive participants with MCI or mild dementia and at least 2 longitudinal Mini-Mental State Examination (MMSE) measurements. Amyloid positivity was based on CSF AD biomarker concentrations or amyloid PET. We used linear mixed modeling to predict MMSE over time, describing trajectories using a cubic time curve and interactions between linear time and the baseline predictors age, sex, baseline MMSE, APOE ε4 dose, CSF β-amyloid (Aβ) 1-42 and pTau, and MRI total brain and hippocampal volume. Backward selection was used to reduce model complexity. These models can predict MMSE over follow-up or the time to an MMSE value. MCI and mild dementia were modeled separately. Internal 5-fold cross-validation was performed to calculate the explained variance (R2). RESULTS In total, 961 participants were included (age 65 ± 7 years, 49% female), 310 had MCI (MMSE 26 ± 2) and 651 had mild dementia (MMSE 22 ± 4), with 4 ± 2 measurements over 2 (interquartile range 1-4) years. Cognitive decline rates increased over time for both MCI and mild dementia (model comparisons linear vs squared vs cubic time fit; p < 0.05 favoring a cubic fit). For MCI, backward selection retained age, sex, and CSF Aβ1-42 and pTau concentrations as time-varying effects altering the MMSE trajectory. For mild dementia, retained time-varying effects were Aβ1-42, age, APOE ε4, and baseline MMSE. R2 was 0.15 for the MCI model and 0.26 for mild dementia in internal cross-validation. A hypothetical patient with MCI, baseline MMSE 28, and CSF Aβ1-42 of 925 pg/mL was predicted to reach an MMSE of 20 after 6.0 years (95% CI 5.4-6.7) and after 8.6 years with a hypothetical treatment reducing decline by 30%. DISCUSSION We constructed models for MCI and mild dementia that predict MMSE over time. These models could inform patients about their potential cognitive trajectory and the remaining uncertainty and aid in conversations about individualized potential treatment effects.
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Affiliation(s)
- Pieter J van der Veere
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Jeroen Hoogland
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Leonie N C Visser
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Argonde C Van Harten
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Hanneke F Rhodius-Meester
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Sietske A M Sikkes
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Vikram Venkatraghavan
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Frederik Barkhof
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Charlotte E Teunissen
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Elsmarieke van de Giessen
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Johannes Berkhof
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
| | - Wiesje M Van Der Flier
- From the Alzheimer Center and Department of Neurology (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., S.A.M.S., V.V., W.M.V.D.F.), and Department of Epidemiology and Biostatistics (P.J.v.d.V., J.H., L.N.C.V., J.B., W.M.V.D.F.), Amsterdam Neuroscience, VU University Medical Center; Amsterdam Neuroscience (P.J.v.d.V., L.N.C.V., A.C.V.H., H.F.R.-M., V.V., C.E.T., E.G., W.M.V.D.F.), Neurodegeneration the Netherlands; Division of Clinical Geriatrics (L.N.C.V.), Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Medical Psychology (L.N.C.V.), Amsterdam UMC Location AMC, University of Amsterdam; Amsterdam Public Health (L.N.C.V.), Quality of Care, Personalized Medicine; Internal Medicine (H.F.R.-M.), Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc; Department of Clinical, Neuro and Developmental Psychology (S.A.M.S.), Faculty of Movement and Behavioral Sciences, VU University; Department of Radiology & Nuclear Medicine (F.B., E.G.), Amsterdam UMC, Vrije Universiteit, the Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing (F.B.), University College London, United Kingdom; and Neurochemistry Laboratory and Biobank (C.E.T.), Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, the Netherlands
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Hancock LM, Galioto R, Rhoads T, Ontaneda D, Nakamura K, Ly B, Krishnan K, Miller JB, Hua LH. Comparing Cognitive Profiles in Older Adults With Multiple Sclerosis and Alzheimer Disease: More Similarities Than Differences. Neurol Clin Pract 2024; 14:e200327. [PMID: 38846466 PMCID: PMC11152644 DOI: 10.1212/cpj.0000000000200327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 03/22/2024] [Indexed: 06/09/2024]
Abstract
Background and Objectives Up to 65% of people with multiple sclerosis (MS) experience disease-related cognitive impairment, but even after decades of research, still very little is known about the cognitive issues among older adults with MS (EwMS; individuals aged 60+). To date, few studies have attempted to characterize cognitive impairment in this group or compare EwMS with those with other neurodegenerative diseases. Our goal was to address this knowledge gap by comparing EwMS with individuals experiencing cognitive impairment due to probable Alzheimer disease (AD) with biomarker confirmation. Methods We conducted an observational study of individuals seen for routine clinical care at the Cleveland Clinic. After excluding for potential confounding factors, 6 groups were assembled based on the results of their clinical workup and neuropsychological examination: cognitively normal, cognitively normal with MS, mild neurocognitive disorder (due to MS or AD), and major neurocognitive disorder (due to MS or AD). These groups were compared in terms of cognitive test performance, percentage of the group impaired on specific cognitive skills, and rates of cognitive impairment. Results The sample comprised 140 individuals (64 EwMS and 76 demographically matched individuals from a memory clinic). Among those with mild neurocognitive disorder, differences between MS and AD were marked. However, in those with major neurocognitive disorder, these differences largely disappeared, except persistent performance differences on a measure of rote verbal memory. EwMS outperformed those with AD on memory tests at each level of cognitive impairment. EwMS also exhibited both subcortical and cortical deficits, rather than solely subcortical deficits. Discussion The overall characterization of the cognitive profile of MS may be different than once described, involving both classically cortical and subcortical functions. Clinically, our results suggest that distinguishing between the cognitive effects of MS and AD at more severe levels of cognitive impairment may be less reliable than once thought. Future work to replicate these findings in other samples and deepen the understanding of cognition in older individuals with MS is needed.
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Affiliation(s)
- Laura M Hancock
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Rachel Galioto
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Tasha Rhoads
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Daniel Ontaneda
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Kunio Nakamura
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Brandon Ly
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Kamini Krishnan
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Justin B Miller
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
| | - Le H Hua
- Neurological Institute (LMH, RG, TR), Section of Neuropsychology; Mellen Center for Multiple Sclerosis (RG, DO); Department of Biomedical Engineering (KN), Lerner Research Institute, Cleveland Clinic, OH; Lou Ruvo Center for Brain Health (BL, JBM, LHH), Cleveland Clinic, Las Vegas; College of Osteopathic Medicine (BL), Touro University, Henderson, NV; and Lou Ruvo Center for Brain Health (KK), Cleveland Clinic, OH
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Jiménez‐Huete A, Villino‐Rodríguez R, Ríos‐Rivera MM, Rognoni T, Montoya‐Murillo G, Arrondo C, Zapata C, Rodríguez‐Oroz MC, Riverol M. Clusters of cognitive performance predict long-term cognitive impairment in elderly patients with subjective memory complaints and healthy controls. Alzheimers Dement 2024; 20:4702-4716. [PMID: 38779851 PMCID: PMC11247668 DOI: 10.1002/alz.13903] [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: 10/25/2023] [Accepted: 04/24/2024] [Indexed: 05/25/2024]
Abstract
INTRODUCTION Patients with subjective memory complaints (SMC) may include subgroups with different neuropsychological profiles and risks of cognitive impairment. METHODS Cluster analysis was performed on two datasets (n: 630 and 734) comprising demographic and neuropsychological data from SMC and healthy controls (HC). Survival analyses were conducted on clusters. Bayesian model averaging assessed the predictive utility of clusters and other biomarkers. RESULTS Two clusters with higher and lower than average cognitive performance were detected in SMC and HC. Assignment to the lower performance cluster increased the risk of cognitive impairment in both datasets (hazard ratios: 1.78 and 2.96; Plog-rank: 0.04 and <0.001) and was associated with lower hippocampal volumes and higher tau/amyloid beta 42 ratios in cerebrospinal fluid. The effect of SMC was small and confounded by mood. DISCUSSION This study provides evidence of the presence of cognitive clusters that hold biological significance and predictive value for cognitive decline in SMC and HC. HIGHLIGHTS Patients with subjective memory complaints include two cognitive clusters. Assignment to the lower performance cluster increases risk of cognitive impairment. This cluster shows a pattern of biomarkers consistent with incipient Alzheimer's disease pathology. The same cognitive cluster structure is found in healthy controls. The effect of memory complaints on risk of cognitive decline is small and confounded.
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Grants
- Biogen
- Alzheimer's Drug Discovery Foundation
- GE Healthcare
- AbbVie
- Transition Therapeutics
- Cogstate
- NIBIB NIH HHS
- Eli Lilly and Company
- Eisai Inc.
- W81XWH-12-2-0012 Department of Defense
- CIHR
- Alzheimer's Disease Neuroimaging Initiative
- Bristol-Myers Squibb Company
- U01 AG024904 NIA NIH HHS
- Piramal Imaging
- Takeda Pharmaceutical Company
- Johnson & Johnson Pharmaceutical Research & Development LLC; Lumosity
- Genentech, Inc.
- Araclon Biotech
- U01 AG024904 NIH HHS
- Meso Scale Diagnostics, LLC
- Novartis Pharmaceuticals Corporation
- CereSpir, Inc.
- BioClinica, Inc.
- Pfizer Inc.
- Elan Pharmaceuticals, Inc.
- IXICO Ltd.
- EuroImmun; F. Hoffmann-La Roche Ltd
- NeuroRx Research
- Merck & Co., Inc.
- Janssen Alzheimer Immunotherapy Research & Development, LLC
- Fujirebio
- Neurotrack Technologies
- U01 AG024904 NIH HHS
- NIA NIH HHS
- NIBIB NIH HHS
- Alzheimer's Association
- CIHR
- Alzheimer's Disease Neuroimaging Initiative
- National Institutes of Health
- Department of Defense
- National Institute on Aging
- National Institute of Biomedical Imaging and Bioengineering
- AbbVie
- Alzheimer's Association
- Alzheimer's Drug Discovery Foundation
- BioClinica, Inc.
- Biogen
- Bristol‐Myers Squibb Company
- Eli Lilly and Company
- Genentech, Inc.
- Fujirebio
- GE Healthcare
- Merck & Co., Inc.
- Novartis Pharmaceuticals Corporation
- Pfizer Inc.
- Takeda Pharmaceutical Company
- Canadian Institutes of Health Research
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Affiliation(s)
| | | | | | - Teresa Rognoni
- Department of NeurologyClínica Universidad de NavarraMadridSpain
| | | | - Carlota Arrondo
- Department of NeurologyClínica Universidad de NavarraMadridSpain
| | - Carolina Zapata
- Department of NeurologyClínica Universidad de NavarraMadridSpain
- Departament of Psychiatry and Forensic MedicineUniversitat Autònoma de BarcelonaFacultad de Medicina, Avinguda de Can DomènechBarcelonaSpain
| | | | - Mario Riverol
- Department of NeurologyClínica Universidad de NavarraMadridSpain
- Instituto de Investigación Sanitaria de Navarra (IdiSNA)Recinto del Hospital Universitario de NavarraPamplonaSpain
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4
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Dammer EB, Shantaraman A, Ping L, Duong DM, Gerasimov ES, Ravindran SP, Gudmundsdottir V, Frick EA, Gomez GT, Walker KA, Emilsson V, Jennings LL, Gudnason V, Western D, Cruchaga C, Lah JJ, Wingo TS, Wingo AP, Seyfried NT, Levey AI, Johnson ECB. Proteomic analysis of Alzheimer's disease cerebrospinal fluid reveals alterations associated with APOE ε4 and atomoxetine treatment. Sci Transl Med 2024; 16:eadn3504. [PMID: 38924431 DOI: 10.1126/scitranslmed.adn3504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/05/2024] [Indexed: 06/28/2024]
Abstract
Alzheimer's disease (AD) is currently defined by the aggregation of amyloid-β (Aβ) and tau proteins in the brain. Although biofluid biomarkers are available to measure Aβ and tau pathology, few markers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here, we characterized the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals using two different proteomic technologies-tandem mass tag mass spectrometry and SomaScan. Integration of both data types allowed for generation of a robust protein coexpression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen-associated protein kinase signaling, neddylation, and mitochondrial biology and overlapped with a previously described lipoprotein module in serum. Alterations of all three modules in blood were associated with dementia more than 20 years before diagnosis. Analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Clustering of individuals based on their CSF proteomic profiles revealed heterogeneity of pathological changes not fully reflected by Aβ and tau.
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Affiliation(s)
- Eric B Dammer
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Anantharaman Shantaraman
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Lingyan Ping
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Duc M Duong
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Ekaterina S Gerasimov
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | | | - Valborg Gudmundsdottir
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | | | - Gabriela T Gomez
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD 21224, USA
| | - Valur Emilsson
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | | | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Daniel Western
- Department of Psychiatry, Washington University, St. Louis, MO 63108, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO 63108, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63108, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO 63108, USA
| | - James J Lah
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Thomas S Wingo
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Aliza P Wingo
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA 30322, USA
- Division of Mental Health, Atlanta VA Medical Center, Decatur, GA 30033, USA
| | - Nicholas T Seyfried
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Allan I Levey
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Erik C B Johnson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
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5
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Li W, Petersen RC, Algeciras-Schimnich A, Cogswell PM, Bornhorst JA, Kremers WK, Boeve BF, Jones DT, Botha H, Ramanan VK, Knopman DS, Savica R, Josephs KA, Cliatt-Brown C, Andersen E, Day GS, Graff-Radford NR, Ertekin-Taner N, Lachner C, Wicklund M, van Harten A, Woodruff BK, Caselli RJ, Graff-Radford J. Alzheimer Disease Cerebrospinal Fluid Biomarkers in a Tertiary Neurology Practice. Mayo Clin Proc 2024:S0025-6196(24)00031-4. [PMID: 38935019 DOI: 10.1016/j.mayocp.2023.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/04/2023] [Accepted: 12/28/2023] [Indexed: 06/28/2024]
Abstract
OBJECTIVE To evaluate the performance of Alzheimer disease (AD) cerebrospinal fluid (CSF) biomarkers in a tertiary neurology clinic setting with high frequency of non-AD cases, including normal pressure hydrocephalus (NPH). METHODS There were 534 patients who underwent AD CSF biomarkers (Roche Elecsys Aβ42, p-Tau181, total-Tau) from April 1, 2020, through April 23, 2021. A behavioral neurologist blinded to CSF results assigned a clinical diagnosis retrospectively on the basis of consensus criteria, and a neuroradiologist blinded to the diagnosis and CSF studies graded brain magnetic resonance images for indicators of CSF dynamics disorders. Associations between biomarkers, diagnoses, and imaging were assessed by χ2, analysis of covariance, and linear regression methods. RESULTS Median age at time of testing was 67 years (range, 19 to 96 years), median symptom duration was 2 years (range, 0.4 to 28 years), and median Short Test of Mental Status score was 30 (range, 0 to 38). Clinical diagnoses significantly correlated with different CSF biomarker values (χ2=208.3; P=10e-4). p-Tau181/Aβ42 ratios above 0.023 positively correlated with Alzheimer dementia (more than individual measures). This ratio also had the best performance for differentiating Alzheimer dementia from NPH (area under the curve, 0.869). Imaging markers supportive of CSF dynamics disorders correlated with low Aβ42, p-Tau181, and total-Tau. CONCLUSION In a heterogeneous clinical population, abnormal p-Tau181/Aβ42 ratios (>0.023) have the strongest association with Alzheimer dementia and probably represent a comorbid AD pathologic component in persons clearly matching non-AD neurodegenerative syndromes. Altered CSF dynamics were associated with lower concentrations of AD CSF biomarkers regardless of clinical diagnosis, but the ratio compensates for these changes. In the appropriate clinical setting, an isolated abnormal Aβ42 should prompt consideration of NPH.
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Affiliation(s)
- Wentao Li
- Department of Neurology, Mayo Clinic, Rochester, MN; Department of Neurology, Kaiser Permanente South Sacramento, Sacramento, CA
| | | | | | | | - Joshua A Bornhorst
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Walter K Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL
| | | | - Nilüfer Ertekin-Taner
- Department of Neurology, Mayo Clinic, Jacksonville, FL; Department of Neuroscience, Mayo Clinic, Jacksonville, FL
| | | | | | - Argonde van Harten
- Department of Neurology and Alzheimer Center Amsterdam UMC, The Netherlands
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6
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Park Y, KC N, Paneque A, Cole PD. Tau, Glial Fibrillary Acidic Protein, and Neurofilament Light Chain as Brain Protein Biomarkers in Cerebrospinal Fluid and Blood for Diagnosis of Neurobiological Diseases. Int J Mol Sci 2024; 25:6295. [PMID: 38928000 PMCID: PMC11204270 DOI: 10.3390/ijms25126295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 06/01/2024] [Indexed: 06/28/2024] Open
Abstract
Neurological damage is the pathological substrate of permanent disability in various neurodegenerative disorders. Early detection of this damage, including its identification and quantification, is critical to preventing the disease's progression in the brain. Tau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), as brain protein biomarkers, have the potential to improve diagnostic accuracy, disease monitoring, prognostic assessment, and treatment efficacy. These biomarkers are released into the cerebrospinal fluid (CSF) and blood proportionally to the degree of neuron and astrocyte damage in different neurological disorders, including stroke, traumatic brain injury, multiple sclerosis, neurodegenerative dementia, and Parkinson's disease. Here, we review how Tau, GFAP, and NfL biomarkers are detected in CSF and blood as crucial diagnostic tools, as well as the levels of these biomarkers used for differentiating a range of neurological diseases and monitoring disease progression. We also discuss a biosensor approach that allows for the real-time detection of multiple biomarkers in various neurodegenerative diseases. This combined detection system of brain protein biomarkers holds significant promise for developing more specific and accurate clinical tools that can identify the type and stage of human neurological diseases with greater precision.
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Affiliation(s)
- Yongkyu Park
- Rutgers Cancer Institute of New Jersey, 195 Little Albany St, New Brunswick, NJ 08901, USA; (N.K.); (A.P.)
| | - Nirajan KC
- Rutgers Cancer Institute of New Jersey, 195 Little Albany St, New Brunswick, NJ 08901, USA; (N.K.); (A.P.)
| | - Alysta Paneque
- Rutgers Cancer Institute of New Jersey, 195 Little Albany St, New Brunswick, NJ 08901, USA; (N.K.); (A.P.)
- Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ 08901, USA
| | - Peter D. Cole
- Rutgers Cancer Institute of New Jersey, 195 Little Albany St, New Brunswick, NJ 08901, USA; (N.K.); (A.P.)
- Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ 08901, USA
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7
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Zu L, Wang X, Liu P, Xie J, Zhang X, Liu W, Li Z, Zhang S, Li K, Giannetti A, Bi W, Chiavaioli F, Shi L, Guo T. Ultrasensitive and Multiple Biomarker Discrimination for Alzheimer's Disease via Plasmonic & Microfluidic Sensing Technologies. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308783. [PMID: 38509587 PMCID: PMC11200013 DOI: 10.1002/advs.202308783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 02/03/2024] [Indexed: 03/22/2024]
Abstract
As the population ages, the worldwide prevalence of Alzheimer's disease (AD) as the most common dementia in the elderly is increasing dramatically. However, a long-term challenge is to achieve rapid and accurate early diagnosis of AD by detecting hallmarks such as amyloid beta (Aβ42). Here, a multi-channel microfluidic-based plasmonic fiber-optic biosensing platform is established for simultaneous detection and differentiation of multiple AD biomarkers. The platform is based on a gold-coated, highly-tilted fiber Bragg grating (TFBG) and a custom-developed microfluidics. TFBG excites a high-density, narrow-cladding-mode spectral comb that overlaps with the broad absorption of surface plasmons for high-precision interrogation, enabling ultrasensitive monitoring of analytes. In situ detection and in-parallel discrimination of different forms of Aβ42 in cerebrospinal fluid (CSF) are successfully demonstrated with a detection of limit in the range of ≈30-170 pg mL-1, which is one order of magnitude below the clinical cut-off level in AD onset, providing high detection sensitivity for early diagnosis of AD. The integration of the TFBG sensor with multi-channel microfluidics enables simultaneous detection of multiple biomarkers using sub-µL sample volumes, as well as combining initial binding rate and real-time response time to differentiate between multiple biomarkers in terms of binding kinetics. With the advantages of multi-parameter, low consumption, and highly sensitive detection, the sensor represents an urgently needed potentials for large-scale diagnosis of diseases at early stage.
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Affiliation(s)
- Lijiao Zu
- Institute of Photonics TechnologyJinan UniversityGuangzhou510632China
| | - Xicheng Wang
- Institute of Photonics TechnologyJinan UniversityGuangzhou510632China
| | - Peng Liu
- State Key Laboratory of Bioactive Molecules and Druggability AssessmentJNU‐HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan UniversityGuangzhou510632China
| | - Jiwei Xie
- Institute of Photonics TechnologyJinan UniversityGuangzhou510632China
| | - Xuejun Zhang
- Center for Advanced Biomedical Imaging and Photonics, Division of Gastroenterology, Department of MedicineBeth Israel Deaconess Medical Center, Harvard UniversityBoston02215USA
| | - Weiru Liu
- Institute of Photonics TechnologyJinan UniversityGuangzhou510632China
| | - Zhencheng Li
- Institute of Photonics TechnologyJinan UniversityGuangzhou510632China
| | - Shiqing Zhang
- State Key Laboratory of Bioactive Molecules and Druggability AssessmentJNU‐HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan UniversityGuangzhou510632China
| | - Kaiwei Li
- Institute of Photonics TechnologyJinan UniversityGuangzhou510632China
| | - Ambra Giannetti
- National Research Council of Italy (CNR), Institute of Applied Physics “Nello Carrara” (IFAC)Sesto Fiorentino50019Italy
| | - Wei Bi
- Department of NeurologyThe First Affiliated Hospital of Jinan UniversityGuangzhou510632China
| | - Francesco Chiavaioli
- National Research Council of Italy (CNR), Institute of Applied Physics “Nello Carrara” (IFAC)Sesto Fiorentino50019Italy
| | - Lei Shi
- State Key Laboratory of Bioactive Molecules and Druggability AssessmentJNU‐HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan UniversityGuangzhou510632China
| | - Tuan Guo
- Institute of Photonics TechnologyJinan UniversityGuangzhou510632China
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8
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Algeciras‐Schimnich A, Bornhorst JA. Importance of cerebrospinal fluid (CSF) collection protocol for the accurate diagnosis of Alzheimer's disease when using CSF biomarkers. Alzheimers Dement 2024; 20:3657-3658. [PMID: 38288880 PMCID: PMC11095420 DOI: 10.1002/alz.13721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 05/16/2024]
Affiliation(s)
| | - Joshua A. Bornhorst
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesotaUSA
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9
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Greenberg ABW, Mekbib KY, Mehta NH, Kiziltug E, Duy PQ, Smith HR, Junkkari A, Leinonen V, Hyman BT, Chan D, Curry Jr WT, Arnold SE, Barker II FG, Frosch MP, Kahle KT. Utility of cortical tissue analysis in normal pressure hydrocephalus. Cereb Cortex 2024; 34:bhae001. [PMID: 38275188 PMCID: PMC10839843 DOI: 10.1093/cercor/bhae001] [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: 11/26/2023] [Revised: 12/28/2023] [Accepted: 12/29/2023] [Indexed: 01/27/2024] Open
Abstract
Clinical improvement following neurosurgical cerebrospinal fluid shunting for presumed idiopathic normal pressure hydrocephalus is variable. Idiopathic normal pressure hydrocephalus patients may have undetected Alzheimer's disease-related cortical pathology that confounds diagnosis and clinical outcomes. In this study, we sought to determine the utility of cortical tissue immuno-analysis in predicting shunting outcomes in idiopathic normal pressure hydrocephalus patients. We performed a pooled analysis using a systematic review as well as analysis of a new, original patient cohort. Of the 2707 screened studies, 3 studies with a total of 229 idiopathic normal pressure hydrocephalus patients were selected for inclusion in this meta-analysis alongside our original cohort. Pooled statistics of shunting outcomes for the 229 idiopathic normal pressure hydrocephalus patients and our new cohort of 36 idiopathic normal pressure hydrocephalus patients revealed that patients with Aβ + pathology were significantly more likely to exhibit shunt nonresponsiveness than patients with negative pathology. Idiopathic normal pressure hydrocephalus patients with Alzheimer's disease -related cortical pathology may be at a higher risk of treatment facing unfavorable outcomes following cerebrospinal fluid shunting. Thus, cortical tissue analysis from living patients may be a useful diagnostic and prognostic adjunct for patients with presumed idiopathic normal pressure hydrocephalus and potentially other neurodegenerative conditions affecting the cerebral cortex.
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Affiliation(s)
- Ana B W Greenberg
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06510, United States
| | - Kedous Y Mekbib
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06510, United States
| | - Neel H Mehta
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Emre Kiziltug
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06510, United States
| | - Phan Q Duy
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06510, United States
| | - Hannah R Smith
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Antti Junkkari
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
| | - Ville Leinonen
- Department of Neurosurgery, Kuopio University Hospital, Kuopio 70211, Finland
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Diane Chan
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - William T Curry Jr
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Steven E Arnold
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Frederick G Barker II
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Matthew P Frosch
- Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Kristopher T Kahle
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, United States
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
- Harvard Center for Hydrocephalus and Neurodevelopmental Disorders, Massachusetts General Hospital, Boston, MA 02114, United States
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10
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Figdore DJ, Wiste HJ, Bornhorst JA, Bateman RJ, Li Y, Graff‐Radford J, Knopman DS, Vemuri P, Lowe VJ, Jr CRJ, Petersen RC, Algeciras‐Schimnich A. Performance of the Lumipulse plasma Aβ42/40 and pTau181 immunoassays in the detection of amyloid pathology. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12545. [PMID: 38304322 PMCID: PMC10831129 DOI: 10.1002/dad2.12545] [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: 10/10/2023] [Revised: 12/29/2023] [Accepted: 01/05/2024] [Indexed: 02/03/2024]
Abstract
INTRODUCTION This study evaluated the performance of the Lumipulse plasma beta-amyloid (Aβ) 42/40 and pTau181 compared to other assays to detect an abnormal amyloid-positron emission tomography (PET). METHODS Plasma samples from cognitively unimpaired (N = 179) and MCI/AD dementia (N = 36) individuals were retrospectively evaluated. Plasma Aβ42/40 and pTau181 were measured using the Lumipulse and Simoa immunoassays. An immunoprecipitation mass spectrometry (IP-MS) assay for plasma Aβ42/40 was also evaluated. Amyloid-PET status was the outcome measure. RESULTS Lumipulse and IP-MS Aβ42/40 exhibited the highest diagnostic accuracy for detecting an abnormal amyloid-PET (areas under the curve [AUCs] of 0.81 and 0.84, respectively). The Lumipulse and Simoa pTau181 assays exhibited lower performance (AUCs of 0.74 and 0.72, respectively). The Simoa Aβ42/40 assay demonstrated the lowest diagnostic accuracy (AUC 0.57). Combining Aβ42/40 and pTau181 did not significantly improve performance over Aβ42/40 alone for Lumipulse (AUC 0.83) or over pTau181 alone for Simoa (AUC 0.71). DISCUSSION The Lumipulse Aβ42/40 assay showed similar performance to the IP-MS Aβ42/40 assay for detection of an abnormal amyloid-PET; and both assays performed better than the two p-tau181 immunoassays. The Simoa Aβ42/Aβ40 assay was the least accurate at predicting an abnormal amyloid-PET status. Highlights Lumipulse plasma Aβ42/Aβ40 AUC for abnormal amyloid-PET detection was 0.81.This performance was comparable to previously reported IP-MS and higher than Simoa.Performance of Alzheimer's disease blood biomarkers varies between assays.
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Affiliation(s)
- Daniel J. Figdore
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesotaUSA
| | - Heather J. Wiste
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Joshua A. Bornhorst
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesotaUSA
| | - Randall J. Bateman
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
| | - Yan Li
- Department of NeurologyWashington University School of MedicineSt. LouisMissouriUSA
| | | | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
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11
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Dong Q, Li Z, Liu W, Chen K, Su Y, Wu J, Caselli RJ, Reiman EM, Wang Y, Shen J. Correlation studies of Hippocampal Morphometry and Plasma NFL Levels in Cognitively Unimpaired Subjects. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2023; 10:3602-3608. [PMID: 38084365 PMCID: PMC10713345 DOI: 10.1109/tcss.2023.3313819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Alzheimer's disease(AD) is being the burden of society and family. Applying computing-aided strategies to reveal its pathology is one of the research highlights. Plasma neurofilament light (NFL) is an emerging noninvasive and economic biomarker for AD molecular pathology. It is valuable to reveal the correlations between the plasma NFL levels and neurodegeneration, especially hippcampal deformations at the preclinical stage. The negative correlation between plasma NFL levels and hippocampal volumes has been documented. However, the relationship between the plasma NFL levels and the hippocampal morphometry details at the preclinical stage is still elusive. This study seeks to demonstrate the capacity of our proposed surface-based hippocampal morphometry system to discern the plasma NFL positive (NFL+>41.9 pg/L) level and plasma NFL negative (NFL-<41.9pg/L) level and illustrate its superiority to the hippocampal volume measurement by drawing the cohort of 154 CU middle aged and elderly adults. We also apply this morphometry measure and a proposed sparse coding based classification algorithm to classify CU individuals with NFL+ and NFL- levels. Experimental results show that the proposed hippocampal morphometry system offers stronger statistical power to discriminate CU subjects with NFL+ and NFL- levels, comparing with the hippocampal volume measure. Furthermore, this system can discriminate plasma NFL levels in CU individuals (Accuracy=0.86). Both the group level and individual level analysis results indicate that the association between plasma NFL levels and the hippocampal shapes can be mapped at the preclinical stage.
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Affiliation(s)
- Qunxi Dong
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Zhigang Li
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Weijia Liu
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Yi Su
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ, USA
| | | | | | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ, USA
| | - Jian Shen
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
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12
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Dammer EB, Shantaraman A, Ping L, Duong DM, Gerasimov ES, Ravindran SP, Gudmundsdottir V, Frick EA, Gomez GT, Walker KA, Emilsson V, Jennings LL, Gudnason V, Western D, Cruchaga C, Lah JJ, Wingo TS, Wingo AP, Seyfried NT, Levey AI, Johnson EC. Proteomic Network Analysis of Alzheimer's Disease Cerebrospinal Fluid Reveals Alterations Associated with APOE ε4 Genotype and Atomoxetine Treatment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.29.23297651. [PMID: 37961720 PMCID: PMC10635242 DOI: 10.1101/2023.10.29.23297651] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Alzheimer's disease (AD) is currently defined at the research level by the aggregation of amyloid-β (Aβ) and tau proteins in brain. While biofluid biomarkers are available to measure Aβ and tau pathology, few biomarkers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here we describe the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals as assessed by two different proteomic technologies-tandem mass tag (TMT) mass spectrometry and SomaScan. Harmonization and integration of both data types allowed for generation of a robust protein co-expression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen associated protein kinase (MAPK) signaling, neddylation, and mitochondrial biology, and overlapped with a previously described lipoprotein module in serum. Neddylation and oxidant detoxification/MAPK signaling modules had a negative association with APOE ε4 whereas the mitochondrion module had a positive association with APOE ε4. The directions of association were consistent between CSF and blood in two independent longitudinal cohorts, and altered levels of all three modules in blood were associated with dementia over 20 years prior to diagnosis. Dual-proteomic platform analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Individuals who had more severe glycolytic changes at baseline responded better to ATX. Clustering of individuals based on their CSF proteomic network profiles revealed ten groups that did not cleanly stratify by Aβ and tau status, underscoring the heterogeneity of pathological changes not fully reflected by Aβ and tau. AD biofluid proteomics holds promise for the development of biomarkers that reflect diverse pathologies for use in clinical trials and precision medicine.
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Affiliation(s)
- Eric B. Dammer
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Anantharaman Shantaraman
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Lingyan Ping
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Duc M. Duong
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Gabriela T. Gomez
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Keenan A. Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Valur Emilsson
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Daniel Western
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, USA
| | - James J. Lah
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Thomas S. Wingo
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Aliza P. Wingo
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
- Division of Mental Health, Atlanta VA Medical Center, GA, USA
| | - Nicholas T. Seyfried
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I. Levey
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Erik C.B. Johnson
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
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13
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Shaw LM, Galasko D. Assessments of the Utilities of CSF NPTX2 for Disease Progression in Cognitively Normal Individuals Who Progress to Clinical MCI and AD. Ann Neurol 2023; 94:618-619. [PMID: 37614206 DOI: 10.1002/ana.26768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 08/11/2023] [Indexed: 08/25/2023]
Affiliation(s)
- Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Douglas Galasko
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
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14
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Lepinay E, Cicchetti F. Tau: a biomarker of Huntington's disease. Mol Psychiatry 2023; 28:4070-4083. [PMID: 37749233 DOI: 10.1038/s41380-023-02230-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 07/31/2023] [Accepted: 08/11/2023] [Indexed: 09/27/2023]
Abstract
Developing effective treatments for patients with Huntington's disease (HD)-a neurodegenerative disorder characterized by severe cognitive, motor and psychiatric impairments-is proving extremely challenging. While the monogenic nature of this condition enables to identify individuals at risk, robust biomarkers would still be extremely valuable to help diagnose disease onset and progression, and especially to confirm treatment efficacy. If measurements of cerebrospinal fluid neurofilament levels, for example, have demonstrated use in recent clinical trials, other proteins may prove equal, if not greater, relevance as biomarkers. In fact, proteins such as tau could specifically be used to detect/predict cognitive affectations. We have herein reviewed the literature pertaining to the association between tau levels and cognitive states, zooming in on Alzheimer's disease, Parkinson's disease and traumatic brain injury in which imaging, cerebrospinal fluid, and blood samples have been interrogated or used to unveil a strong association between tau and cognition. Collectively, these areas of research have accrued compelling evidence to suggest tau-related measurements as both diagnostic and prognostic tools for clinical practice. The abundance of information retrieved in this niche of study has laid the groundwork for further understanding whether tau-related biomarkers may be applied to HD and guide future investigations to better understand and treat this disease.
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Affiliation(s)
- Eva Lepinay
- Centre de Recherche du CHU de Québec, Axe Neurosciences, Québec, QC, Canada
- Département de Psychiatrie & Neurosciences, Université Laval, Québec, QC, Canada
| | - Francesca Cicchetti
- Centre de Recherche du CHU de Québec, Axe Neurosciences, Québec, QC, Canada.
- Département de Psychiatrie & Neurosciences, Université Laval, Québec, QC, Canada.
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15
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Kerrebijn I, Wainberg M, Zhukovsky P, Chen Y, Davie M, Felsky D, Tripathy SJ. Case-control virtual histology elucidates cell types associated with cortical thickness differences in Alzheimer's disease. Neuroimage 2023; 276:120177. [PMID: 37211192 DOI: 10.1016/j.neuroimage.2023.120177] [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: 10/17/2022] [Revised: 05/08/2023] [Accepted: 05/16/2023] [Indexed: 05/23/2023] Open
Abstract
Many neuropsychiatric disorders are characterised by altered cortical thickness, but the cell types underlying these changes remain largely unknown. Virtual histology (VH) approaches map regional patterns of gene expression with regional patterns of MRI-derived phenotypes, such as cortical thickness, to identify cell types associated with case-control differences in those MRI measures. However, this method does not incorporate valuable information of case-control differences in cell type abundance. We developed a novel method, termed case-control virtual histology (CCVH), and applied it to Alzheimer's disease (AD) and dementia cohorts. Leveraging a multi-region gene expression dataset of AD cases (n = 40) and controls (n = 20), we quantified AD case-control differential expression of cell type-specific markers across 13 brain regions. We then correlated these expression effects with MRI-derived AD case-control cortical thickness differences across the same regions. Cell types with spatially concordant AD-related effects were identified through resampling marker correlation coefficients. Among regions thinner in AD, gene expression patterns identified by CCVH suggested fewer excitatory and inhibitory neurons, and greater proportions of astrocytes, microglia, oligodendrocytes, oligodendrocyte precursor cells, and endothelial cells in AD cases vs. controls. In contrast, original VH identified expression patterns suggesting that excitatory but not inhibitory neuron abundance was associated with thinner cortex in AD, despite the fact that both types of neurons are known to be lost in the disorder. Compared to original VH, cell types identified through CCVH are more likely to directly underlie cortical thickness differences in AD. Sensitivity analyses suggest our results are largely robust to specific analysis choices, like numbers of cell type-specific marker genes used and background gene sets used to construct null models. As more multi-region brain expression datasets become available, CCVH will be useful for identifying the cellular correlates of cortical thickness across neuropsychiatric illnesses.
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Affiliation(s)
- Isabel Kerrebijn
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Michael Wainberg
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Peter Zhukovsky
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Yuxiao Chen
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Melanie Davie
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Daniel Felsky
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto ON, Canada
| | - Shreejoy J Tripathy
- The Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Department of Physiology, University of Toronto, Toronto, ON, Canada.
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16
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Schmidt-Morgenroth I, Michaud P, Gasparini F, Avrameas A. Central and Peripheral Inflammation in Mild Cognitive Impairment in the Context of Alzheimer's Disease. Int J Mol Sci 2023; 24:10523. [PMID: 37445700 DOI: 10.3390/ijms241310523] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 06/05/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023] Open
Abstract
Mild cognitive impairment (MCI) is characterized by an abnormal decline in mental and cognitive function compared with normal cognitive aging. It is an underlying condition of Alzheimer's disease (AD), an irreversible neurodegenerative disease. In recent years, neuroinflammation has been investigated as a new leading target that contributes to MCI progression into AD. Understanding the mechanism underlying inflammatory processes involved in the early onset of the disease could help find a safe and effective way to diagnose and treat patients. In this article, we assessed over twenty different blood and cerebrospinal fluid (CSF) inflammatory biomarker concentrations with immunoassay methods in patients with MCI (mild cognitive impairment), non-impaired control (NIC), and serum healthy control (HC). We performed group comparisons and analyzed in-group correlations between the biomarkers. We included 107 participants (mean age: 64.7 ± 7.8, women: 58.9%). CSF osteopontin and YKL-40 were significantly increased in the MCI group, whereas serum C-reactive protein and interleukin-6 were significantly higher (p < 0.001) in the NIC group compared with the MCI and HC groups. Stronger correlations between interleukin-1β and inflammasome markers were observed in the serum of the MCI group. We confirmed specific inflammatory activation in the central nervous system and interleukin-1β pathway upregulation in the serum of the MCI cohort.
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Affiliation(s)
- Inès Schmidt-Morgenroth
- Novartis Institutes for Biomedical Research (NIBR), Translational Medicine, 4056 Basel, Switzerland
- Institut Pascal, Université Clermont Auvergne, CNRS, Clermont Auvergne INP, 63000 Clermont-Ferrand, France
| | - Philippe Michaud
- Institut Pascal, Université Clermont Auvergne, CNRS, Clermont Auvergne INP, 63000 Clermont-Ferrand, France
| | - Fabrizio Gasparini
- Novartis Institutes for Biomedical Research (NIBR), Translational Medicine, 4056 Basel, Switzerland
| | - Alexandre Avrameas
- Novartis Institutes for Biomedical Research (NIBR), Translational Medicine, 4056 Basel, Switzerland
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17
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Gibson M, Nicolazzo J, Cavuoto M, Rowsthorn E, Cribb L, Bransby L, Buckley R, Yassi N, Yiallourou S, Brodtmann A, Velakoulis D, Eratne D, Hamilton GS, Naughton MT, Lim YY, Pase MP. Short sleep duration is associated with lower cerebrospinal fluid amyloid beta 42 levels in midlife: a preliminary report. Sleep 2023; 46:zsac307. [PMID: 36534943 PMCID: PMC10091085 DOI: 10.1093/sleep/zsac307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Indexed: 12/23/2022] Open
Affiliation(s)
- Madeline Gibson
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Jessica Nicolazzo
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Marina Cavuoto
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Ella Rowsthorn
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Lachlan Cribb
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Lisa Bransby
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Rachel Buckley
- Melbourne School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Nawaf Yassi
- Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Stephanie Yiallourou
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Amy Brodtmann
- Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia
- Department of Neurology, Austin Health, Melbourne, Victoria, Australia
- Eastern Cognitive Disorders Clinic, Eastern Health, Monash University, Clayton, Victoria, Australia
| | - Dennis Velakoulis
- Neuropsychiatry at The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Dhamidhu Eratne
- Neuropsychiatry at The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Garun S Hamilton
- Monash Lung, Sleep, Allergy and Immunology, Monash Health, Clayton, Victoria, Australia
- School of Clinical Sciences, Monash University, Clayton, Victoria, Australia
| | - Matthew T Naughton
- Department of Respiratory Medicine, Alfred Health and Central Clinical School, Melbourne, Victoria, Australia
| | - Yen Ying Lim
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
| | - Matthew P Pase
- The Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria, Australia
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
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18
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Zou Y, Yu S, Ma X, Ma C, Mao C, Mu D, Li L, Gao J, Qiu L. How far is the goal of applying β-amyloid in cerebrospinal fluid for clinical diagnosis of Alzheimer's disease with standardization of measurements? Clin Biochem 2023; 112:33-42. [PMID: 36473516 DOI: 10.1016/j.clinbiochem.2022.11.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 11/02/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
Cerebrospinal fluid (CSF) β-amyloid (Aβ) is important for early diagnosis of Alzheimer's disease (AD). However, the cohort distributions and cut-off values have large variation across different analytical assays, kits, and laboratories. In this review, we summarize the cut-off values and diagnostic performance for CSF Aβ1-42 and Aβ1-42/Aβ1-40, and explore the important effect factors. Based on the Alzheimer's Association external quality control program (AAQC program), the peer group coefficient of variation of manual ELISA assays for CSF Aβ1-42 was unsatisfied (>20%). Fully automated platforms with better performance have recently been developed, but still not widely applied. In 2020, the certified reference material (CRM) for CSF Aβ1-42 was launched; however, the AAQC 2021-round results did not show effective improvements. Thus, further development and popularization of CRM for CSF Aβ1-42 and Aβ1-40 are urgently required. Standardizing the diagnostic procedures of AD and related status and the pre-analytical protocols of CSF samples, improving detection performance of analytical assays, and popularizing the application of fully automated platforms are also important for the establishment of uniform cut-off values. Moreover, each laboratory should verify the applicability of uniform cut-off values, and evaluate whether it is necessary to establish its own population- and assay-specific cut-off values.
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Affiliation(s)
- Yutong Zou
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Songlin Yu
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Xiaoli Ma
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China; Medical Science Research Center, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Chaochao Ma
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Chenhui Mao
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Danni Mu
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Lei Li
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Jing Gao
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China.
| | - Ling Qiu
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China; State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China.
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19
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Abildgaard A, Parkner T, Knudsen CS, Gottrup H, Klit H. Diagnostic Cut-offs for CSF β-amyloid and tau proteins in a Danish dementia clinic. Clin Chim Acta 2023; 539:244-249. [PMID: 36572135 DOI: 10.1016/j.cca.2022.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 12/21/2022] [Indexed: 12/25/2022]
Abstract
BACKGROUND Analysis of beta-amyloid 1-42 (Aβ42), total tau (t-tau) and phosphorylated-tau 181 (p-tau) in the cerebrospinal fluid (CSF) is often performed as a part of the diagnostic work-up in case of suspected Alzheimer's dementia (AD). Unfortunately, studies on optimal CSF biomarker cut-offs in a real-world clinical setting are scarce. METHODS We retrospectively evaluated the biomarker levels of 264 consecutive patients referred to our dementia clinic. The biomarkers were analysed with the Elecsys(R) assays. Diagnoses were based on all available clinical information, including FDG-PET scans. RESULTS In total, we identified 233 patients diagnosed with dementia. The median MMSE score was 22 (IQR 18-25). AD pathophysiology was suspected in 156 patients, and the corresponding cut-offs based on the Youden index were: Aβ42: 903 ng/L (ROC-AUC 0.78); t-tau: 272 ng/L (ROC-AUC 0.78); p-tau: 24 ng/L (ROC-AUC 0.85); t-tau/Aβ42 ratio: 0.34 (ROC-AUC 0.91); p-tau/Aβ42 ratio: 0.029 (ROC-AUC 0.92). CONCLUSIONS We found the tau/Aβ42 ratios to possess the best diagnostic performance, but our estimated cut-off values for the ratios were somewhat higher than previously reported. Consequently, if the CSF analyses are used to support a diagnosis of AD in a heterogeneous high-prevalence cohort, adjustment of the cut-offs may be warranted.
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Affiliation(s)
- Anders Abildgaard
- Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark.
| | - Tina Parkner
- Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
| | - Cindy Soendersoe Knudsen
- Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
| | - Hanne Gottrup
- Department of Neurology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
| | - Henriette Klit
- Department of Neurology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, Denmark
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20
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Shir D, Mielke MM, Hofrenning EI, Lesnick TG, Knopman DS, Petersen RC, Jack CR, Algeciras-Schimnich A, Vemuri P, Graff-Radford J. Associations of Neurodegeneration Biomarkers in Cerebrospinal Fluid with Markers of Alzheimer's Disease and Vascular Pathology. J Alzheimers Dis 2023; 92:887-898. [PMID: 36806507 PMCID: PMC10193844 DOI: 10.3233/jad-221015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
BACKGROUND The National Institute on Aging-Alzheimer's Association Research Framework proposes defining Alzheimer's disease by grouping imaging and fluid biomarkers by their respective pathologic processes. The AT(N) structure proposes several neurodegenerative fluid biomarkers (N) including total tau (t-tau), neurogranin (Ng), and neurofilament light chain (NfL). However, pathologic drivers influencing each biomarker remain unclear. OBJECTIVE To determine whether cerebrospinal fluid (CSF)-neurodegenerative biomarkers (N) map differentially to Alzheimer's disease pathology measured by Aβ42 (an indicator of amyloidosis, [A]), p-tau (an indicator of tau deposition, [T]), and MRI vascular pathology indicators (measured by white-matter integrity, infarcts, and microbleeds [V]). METHODS Participants were from Mayo Clinic Study of Aging (MCSA) with CSF measures of NfL, Ng, t-tau, Aβ42, and p-tau and available MRI brain imaging. Linear models assessed associations between CSF neurodegeneration (N) markers, amyloid markers (A), tau (T), and vascular pathology (V). RESULTS Participants (n = 408) had a mean age of 69.2±10.7; male, 217 (53.2%); cognitively unimpaired, 359 (88%). All three neurodegeneration biomarkers correlated with age (p < 0.001 for NfL and t-tau, p = 0.018 for Ng). Men had higher CSF-NfL levels; women had higher Ng (p < 0.001). NfL and t-tau levels correlated with infarcts (p = 0.009, p = 0.034 respectively); no biomarkers correlated with white-matter integrity. N biomarkers correlated with p-tau levels (T, p < 0.001). Higher Aβ42 levels associated with higher N-biomarker levels but only among cognitively unimpaired (A, p < 0.001). CONCLUSION The influence of vascular pathology in the general population on CSF (N) biomarkers is modest, with greater influence of infarcts than white-matter disruption. Neurodegeneration markers more closely correlated with tau than amyloid markers.
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Affiliation(s)
- Dror Shir
- Department of Neurology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota 55905, USA
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, 27101
| | | | - Timothy G. Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - David S. Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic, Rochester, Minnesota 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Clifford R. Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | | | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905, USA
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21
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Singh S A, Suresh S, Singh A, Chandran L, Vellapandian C. Perspectives of ozone induced neuropathology and memory decline in Alzheimer's disease: A systematic review of preclinical evidences. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 313:120136. [PMID: 36089140 DOI: 10.1016/j.envpol.2022.120136] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 09/02/2022] [Accepted: 09/05/2022] [Indexed: 06/15/2023]
Abstract
This systematic review aims to discover the plausible mechanism of Ozone in A.D., to boost translational research. The main focus of our review lies in understanding the effects of ozone pollution on the human brain and causing degenerative disease. Owing to the number of works carried out as preclinical evidence in association with oxidative stress and Alzheimer's disease and the lack of systematic review or meta-analysis prompted us to initiate a study on Alzheimer's risk due to ground-level ozone. We found relevant studies from PubMed, ScienceDirect, Proquest, DOAJ, and Scopus, narrowing to animal studies and the English language without any time limit. The searches will be re-run before the final analysis. This work was registered in Prospero with Reg ID CRD42022319360, followed the PRISMA-P framework, and followed the PICO approach involving Population, Intervention/Exposure, Comparison, and Outcomes data. Bibliographic details of 16 included studies were studied for Exposure dose of ozone, duration, exposure, and frequency with control and exposure groups. Primary and secondary outcomes were assessed based on pathology significance, and results were significant in inducing Alzheimer-like pathology by ozone. In conclusion, ozone altered oxidative stress, metabolic pathway, and amyloid plaque accumulation besides endothelial stress response involving mitochondria as the critical factor in ATP degeneration, caspase pathway, and neuronal damage. Thus, ozone is a criteria pollutant to be focused on in mitigating Alzheimer's Disease pathology.
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Affiliation(s)
- Ankul Singh S
- Department of Pharmacology, SRM College of Pharmacy, SRMIST, SRM Nagar, Kattankulathur, Kancheepuram, 603 203, Tamil Nadu, India.
| | - Swathi Suresh
- Department of Pharmacology, SRM College of Pharmacy, SRMIST, SRM Nagar, Kattankulathur, Kancheepuram, 603 203, Tamil Nadu, India
| | - Anuragh Singh
- Department of Pharmacology, SRM College of Pharmacy, SRMIST, SRM Nagar, Kattankulathur, Kancheepuram, 603 203, Tamil Nadu, India
| | - Lakshmi Chandran
- Department of Pharmacy Practice, SRM College of Pharmacy, SRMIST, SRM Nagar, Kattankulathur, Kancheepuram, 603 203, Tamil Nadu, India
| | - Chitra Vellapandian
- Department of Pharmacology, SRM College of Pharmacy, SRMIST, SRM Nagar, Kattankulathur, Kancheepuram, 603 203, Tamil Nadu, India.
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22
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Knopman DS. Can CSF Biomarkers Decode Contributions of Combined Aβ Plaque, Tau Tangle, and α-Synuclein Pathology? Neurology 2022; 99:877-878. [PMID: 36307221 DOI: 10.1212/wnl.0000000000201287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 08/10/2022] [Indexed: 11/15/2022] Open
Affiliation(s)
- David S Knopman
- From the Department of Neurology, Mayo Clinic, Rochester, MN.
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23
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Chang BK, Day GS, Graff-Radford J, McKeon A, Flanagan EP, Algeciras-Schimnich A, Mielke MM, Nguyen A, Jones DT, Toledano M, Kremers WK, Knopman DS, Petersen RC, Li W. Alzheimer's disease cerebrospinal fluid biomarkers differentiate patients with Creutzfeldt-Jakob disease and autoimmune encephalitis. Eur J Neurol 2022; 29:2905-2912. [PMID: 35735602 PMCID: PMC9463096 DOI: 10.1111/ene.15469] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 06/10/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND PURPOSE Autoimmune encephalitis (AE) is a potentially treatable cause of rapidly progressive dementia that may mimic Creutzfeldt-Jakob disease (CJD). Alzheimer disease (AD) cerebrospinal fluid (CSF) biomarkers may discriminate CJD from AD, but utility in discriminating CJD and AE is unclear. This study compared AD CSF biomarkers in CJD and AE. METHODS Patients with probable or definite CJD and probable or definite AE who underwent Roche Elecsys AD CSF biomarker testing at Mayo Clinic from March 2020 through April 2021 were included. Total-tau, phosphorylated181 tau and amyloid-β42 levels were compared. RESULTS Of 11 CJD cases, four were autopsy proven; the rest had positive real-time quaking-induced conversion testing. Disease-associated autoantibodies were detected in 8/15 cases of AE: leucine-rich glioma-inactivated 1 and neuronal intermediate filaments (two cases each), and N-methyl-d-aspartate receptor, contactin-associated protein-like 2, dipeptidyl-peptidase-like protein 6 and immunoglobulin-like cell adhesion molecule IgLON family member 5. Total-tau provided excellent discrimination between CJD and AE in a univariate model (odds ratio 1.46 per 100 pg/ml, 95% confidence interval 1.17-2.11, p < 0.05, c = 0.93). Total-tau was elevated in 91% of CJD cases (median > 1300, range 236->1300 pg/ml), of which 55% were above the limit of assay measurement (>1300 pg/ml). Total-tau was elevated in 20% of AE cases (median 158, range 80->1300 pg/ml). CONCLUSION Total-tau was greater in CJD than AE. Given that amyloid-β42 and phosphorylated181 tau were comparable, the ratio differences were probably driven by elevated total-tau in CJD. This study supports the role for AD biomarker testing in patients with rapidly progressive dementia.
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Affiliation(s)
| | | | | | - Andrew McKeon
- Department of Neurology, Mayo Clinic, Rochester, MN
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Eoin P. Flanagan
- Department of Neurology, Mayo Clinic, Rochester, MN
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Michelle M. Mielke
- Department of Neurology, Mayo Clinic, Rochester, MN
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Aivi Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | | | - Walter K. Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | | | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
| | - Wentao Li
- Department of Neurology, Mayo Clinic, Rochester, MN
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24
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Klafki HW, Vogelgsang J, Manuilova E, Bauer C, Jethwa A, Esselmann H, Jahn-Brodmann A, Osterloh D, Lachmann I, Breitling B, Rauter C, Hansen N, Bouter C, Palme S, Schuchhardt J, Wiltfang J. Diagnostic performance of automated plasma amyloid-β assays combined with pre-analytical immunoprecipitation. Alzheimers Res Ther 2022; 14:127. [PMID: 36071505 PMCID: PMC9450259 DOI: 10.1186/s13195-022-01071-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 08/28/2022] [Indexed: 11/10/2022]
Abstract
Abstract
Background
Measurements of the amyloid-β (Aβ) 42/40 ratio in blood plasma may support the early diagnosis of Alzheimer’s disease and aid in the selection of suitable participants in clinical trials. Here, we compared the diagnostic performance of fully automated prototype plasma Aβ42/40 assays with and without pre-analytical sample workup by immunoprecipitation.
Methods
A pre-selected clinical sample comprising 42 subjects with normal and 38 subjects with low cerebrospinal fluid (CSF) Aβ42/40 ratios was studied. The plasma Aβ42/40 ratios were determined with fully automated prototype Elecsys® immunoassays (Roche Diagnostics GmbH, Penzberg, Germany) by direct measurements in EDTA plasma or after pre-analytical Aβ immunoprecipitation. The diagnostic performance for the detection of abnormal CSF Aβ42/40 was analyzed by receiver operating characteristic (ROC) analysis. In an additional post hoc analysis, a biomarker-supported clinical diagnosis was used as a second endpoint.
Results
Pre-analytical immunoprecipitation resulted in a significant increase in the area under the ROC curve (AUC) from 0.73 to 0.88 (p = 0.01547) for identifying subjects with abnormal CSF Aβ42/40. A similar improvement in the diagnostic performance by pre-analytical immunoprecipitation was also observed when a biomarker-supported clinical diagnosis was used as a second endpoint (AUC increase from 0.77 to 0.92, p = 0.01576).
Conclusions
Our preliminary observations indicate that pre-analytical Aβ immunoprecipitation can improve the diagnostic performance of plasma Aβ assays for detecting brain amyloid pathology. The findings may aid in the further development of blood-based immunoassays for Alzheimer’s disease ultimately suitable for screening and routine use.
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25
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Das Saha N, Pradhan S, Sasmal R, Sarkar A, Berač CM, Kölsch JC, Pahwa M, Show S, Rozenholc Y, Topçu Z, Alessandrini V, Guibourdenche J, Tsatsaris V, Gagey-Eilstein N, Agasti SS. Cucurbit[7]uril Macrocyclic Sensors for Optical Fingerprinting: Predicting Protein Structural Changes to Identifying Disease-Specific Amyloid Assemblies. J Am Chem Soc 2022; 144:14363-14379. [PMID: 35913703 DOI: 10.1021/jacs.2c05969] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In a three-dimensional (3D) representation, each protein molecule displays a specific pattern of chemical and topological features, which are altered during its misfolding and aggregation pathway. Generating a recognizable fingerprint from such features could provide an enticing approach not only to identify these biomolecules but also to gain clues regarding their folding state and the occurrence of pathologically lethal misfolded aggregates. We report here a universal strategy to generate a fluorescent fingerprint from biomolecules by employing the pan-selective molecular recognition feature of a cucurbit[7]uril (CB[7]) macrocyclic receptor. We implemented a direct sensing strategy by covalently tethering CB[7] with a library of fluorescent reporters. When CB[7] recognizes the chemical and geometrical features of a biomolecule, it brings the tethered fluorophore into the vicinity, concomitantly reporting the nature of its binding microenvironment through a change in their optical signature. The photophysical properties of the fluorophores allow a multitude of probing modes, while their structural features provide additional binding diversity, generating a distinct fluorescence fingerprint from the biomolecule. We first used this strategy to rapidly discriminate a diverse range of protein analytes. The macrocyclic sensor was then applied to probe conformational changes in the protein structure and identify the formation of oligomeric and fibrillar species from misfolded proteins. Notably, the sensor system allowed us to differentiate between different self-assembled forms of the disease-specific amyloid-β (Aβ) aggregates and segregated them from other generic amyloid structures with a 100% identification accuracy. Ultimately, this sensor system predicted clinically relevant changes by fingerprinting serum samples from a cohort of pregnant women.
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Affiliation(s)
- Nilanjana Das Saha
- New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India.,Chemistry & Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India
| | - Soumen Pradhan
- Chemistry & Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India
| | - Ranjan Sasmal
- New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India
| | - Aritra Sarkar
- New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India
| | - Christian M Berač
- Department of Chemistry, Johannes Gutenberg-University Mainz, Duesbergweg 10-14, 55128 Mainz, Germany.,Graduate School of Materials Science in Mainz, Staudingerweg 9, 55128 Mainz, Germany
| | - Jonas C Kölsch
- Department of Chemistry, Johannes Gutenberg-University Mainz, Duesbergweg 10-14, 55128 Mainz, Germany
| | - Meenakshi Pahwa
- Chemistry & Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India
| | - Sushanta Show
- New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India
| | - Yves Rozenholc
- UR 7537 BioSTM, Université Paris Cité, 4 avenue de l'Observatoire, 75006 Paris, France
| | - Zeki Topçu
- UR 7537 BioSTM, Université Paris Cité, 4 avenue de l'Observatoire, 75006 Paris, France
| | - Vivien Alessandrini
- INSERM UMR-S 1139, Université Paris Cité, 4 avenue de l'Observatoire, 75006 Paris, France.,Department of Obstetrics, Cochin Hospital, AP-HP, Université Paris Cité, FHU PREMA, 123 Bd Port-Royal, 75014 Paris, France
| | - Jean Guibourdenche
- INSERM UMR-S 1139, Université Paris Cité, 4 avenue de l'Observatoire, 75006 Paris, France.,Department of Obstetrics, Cochin Hospital, AP-HP, Université Paris Cité, FHU PREMA, 123 Bd Port-Royal, 75014 Paris, France
| | - Vassilis Tsatsaris
- INSERM UMR-S 1139, Université Paris Cité, 4 avenue de l'Observatoire, 75006 Paris, France.,Department of Obstetrics, Cochin Hospital, AP-HP, Université Paris Cité, FHU PREMA, 123 Bd Port-Royal, 75014 Paris, France
| | | | - Sarit S Agasti
- New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India.,Chemistry & Physics of Materials Unit, Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Bangalore, Karnataka 560064, India
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26
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Ramanan VK, Heckman MG, Lesnick TG, Przybelski SA, Cahn EJ, Kosel ML, Murray ME, Mielke MM, Botha H, Graff-Radford J, Jones DT, Lowe VJ, Machulda MM, Jack CR, Knopman DS, Petersen RC, Ross OA, Vemuri P. Tau polygenic risk scoring: a cost-effective aid for prognostic counseling in Alzheimer's disease. Acta Neuropathol 2022; 143:571-583. [PMID: 35412102 PMCID: PMC9109940 DOI: 10.1007/s00401-022-02419-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/07/2022] [Accepted: 04/07/2022] [Indexed: 11/28/2022]
Abstract
Tau deposition is one of two hallmark features of biologically defined Alzheimer's disease (AD) and is more closely related to cognitive decline than amyloidosis. Further, not all amyloid-positive individuals develop tauopathy, resulting in wide heterogeneity in clinical outcomes across the population with AD. We hypothesized that a polygenic risk score (PRS) based on tau PET (tau PRS) would capture the aggregate inherited susceptibility/resistance architecture influencing tau accumulation, beyond solely the measurement of amyloid-β burden. Leveraging rich multimodal data from a population-based sample of older adults, we found that this novel tau PRS was a strong surrogate of tau PET deposition and captured a significant proportion of the variance in tau PET levels as compared with amyloid PET burden, APOE (apolipoprotein E) ε4 (the most common risk allele for AD), and a non-APOE PRS of clinical case-control AD risk variants. In independent validation samples, the tau PRS was associated with cerebrospinal fluid phosphorylated tau levels in one cohort and with postmortem Braak neurofibrillary tangle stage in another. We also observed an association of the tau PRS with longitudinal cognitive trajectories, including a statistical interaction of the tau PRS with amyloid burden on cognitive decline. Although additional study is warranted, these findings demonstrate the potential utility of a tau PRS for capturing the collective genetic background influencing tau deposition in the general population. In the future, a tau PRS could be leveraged for cost-effective screening and risk stratification to guide trial enrollment and clinical interventions in AD.
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Affiliation(s)
- Vijay K Ramanan
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Michael G Heckman
- Department of Quantitative Health Sciences, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Elliot J Cahn
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Matthew L Kosel
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jonathan Graff-Radford
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
- Department of Clinical Genomics, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Prashanthi Vemuri
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA.
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
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27
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Brum WS, de Bastiani MA, Bieger A, Therriault J, Ferrari‐Souza JP, Benedet AL, Saha‐Chaudhuri P, Souza DO, Ashton NJ, Zetterberg H, Pascoal TA, Karikari T, Blennow K, Rosa‐Neto P, Zimmer ER. A three-range approach enhances the prognostic utility of CSF biomarkers in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12270. [PMID: 35310530 PMCID: PMC8918110 DOI: 10.1002/trc2.12270] [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: 10/13/2021] [Revised: 01/10/2022] [Accepted: 01/21/2022] [Indexed: 12/02/2022]
Abstract
Introduction Alzheimer's disease consensus recommends biomarker dichotomization, a practice with well-described clinical strengths and methodological limitations. Although neuroimaging studies have explored alternative biomarker interpretation strategies, a formally defined three-range approach and its prognostic impact remains under-explored for cerebrospinal fluid (CSF) biomarkers . Methods With two-graph receiver-operating characteristics based on different reference schemes, we derived three-range cut-points for CSF Elecsys biomarkers. According to baseline CSF status, we assessed the prognostic utility of this in predicting risk of clinical progression and longitudinal trajectories of cognitive decline and amyloid-beta (Aβ) positron emission tomography (PET) accumulation in non-demented individuals (Alzheimer's Disease Neuroimaging Initiative [ADNI]; n = 1246). In all analyses, we compared herein-derived three-range CSF cut-points to previously described binary ones. Results In our main longitudinal analyses, we highlight CSF p-tau181/Aβ1-42 three-range cut-points derived based on the cognitively normal Aβ-PET negative versus dementia Aβ-PET positive reference scheme for best depicting a prognostically relevant biomarker abnormality range. Longitudinally, our approach revealed a divergent intermediate cognitive trajectory undetected by dichotomization and a clearly abnormal group at higher risk for cognitive decline, with power analyses suggesting the latter group as potential trial enrichment candidates. Furthermore, we demonstrate that individuals with intermediate-range CSF status have similar rates of Aβ deposition to those in the clearly abnormal group. Discussion The proposed approach can refine clinico-biological prognostic assessment and potentially enhance trial recruitment, as it captures faster biomarker-related cognitive decline in comparison to binary cut-points. Although this approach has implications for trial recruitment and observational studies, further discussion is needed regarding clinical practice applications.
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Affiliation(s)
- Wagner S. Brum
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil
- Department of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
| | - Marco Antônio de Bastiani
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil
| | - Andrei Bieger
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil
| | - Joseph Therriault
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingLaSalle BoulevardVerdunCanada
- Department of Neurology and NeurosurgeryMcGill UniversityMontrealCanada
| | - João P. Ferrari‐Souza
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil
- Department of Neurology and PsychiatryUniversity of PittsburghPittsburghUSA
| | - Andréa L. Benedet
- Department of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingLaSalle BoulevardVerdunCanada
- Department of Neurology and NeurosurgeryMcGill UniversityMontrealCanada
| | | | - Diogo O. Souza
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil
- Department of BiochemistryUFRGSPorto AlegreBrazil
| | - Nicholas J. Ashton
- Department of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Department of Old Age PsychiatryInstitute of PsychiatryPsychology & NeuroscienceKing's College LondonLondonUK
- Wallenberg Centre for Molecular and Translational MedicineUniversity of GothenburgGothenburgSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalGothenburgSweden
- Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCLLondonUK
| | - Tharick A. Pascoal
- Department of Neurology and PsychiatryUniversity of PittsburghPittsburghUSA
| | - Thomas Karikari
- Department of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Department of Neurology and PsychiatryUniversity of PittsburghPittsburghUSA
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalGothenburgSweden
| | - Pedro Rosa‐Neto
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingLaSalle BoulevardVerdunCanada
- Department of Neurology and NeurosurgeryMcGill UniversityMontrealCanada
| | - Eduardo R. Zimmer
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do Sul (UFRGS)Porto AlegreBrazil
- Department of PharmacologyUFRGSPorto AlegreBrazil
- Graduate Program in Biological Sciences: Pharmacology and TherapeuticsUFRGSPorto AlegreBrazil
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28
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Fowler CJ, Stoops E, Rainey‐Smith SR, Vanmechelen E, Vanbrabant J, Dewit N, Mauroo K, Maruff P, Rowe CC, Fripp J, Li Q, Bourgeat P, Collins SJ, Martins RN, Masters CL, Doecke JD. Plasma p‐tau181/Aβ
1‐42
ratio predicts Aβ‐PET status and correlates with CSF‐p‐tau181/Aβ
1‐42
and future cognitive decline. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2022; 14:e12375. [DOI: 10.1002/dad2.12375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 09/28/2022] [Indexed: 11/26/2022]
Affiliation(s)
| | | | - Stephanie R. Rainey‐Smith
- School of Medical and Health Sciences Centre of Excellence for Alzheimer's Disease Research & Care Edith Cowan University Joondalup Western Australia Australia
| | | | | | | | | | | | - Christopher C. Rowe
- The Florey Institute of Neuroscience and Mental Health Melbourne Victoria Australia
- Austin Health, Molecular Imaging Research and The Florey Department of Neuroscience University of Melbourne Melbourne Victoria Australia
| | - Jurgen Fripp
- Australian E‐Health Research Centre CSIRO Herston Queensland Australia
| | - Qiao‐Xin Li
- The Florey Institute of Neuroscience and Mental Health Melbourne Victoria Australia
| | - Pierrick Bourgeat
- Australian E‐Health Research Centre CSIRO Herston Queensland Australia
| | - Steven J. Collins
- Department of Medicine (RMH) The University of Melbourne Melbourne Victoria Australia
| | - Ralph N. Martins
- School of Medical and Health Sciences Centre of Excellence for Alzheimer's Disease Research & Care Edith Cowan University Joondalup Western Australia Australia
- Department of Biological Sciences Macquarie University North Ryde New South Wales Australia
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental Health Melbourne Victoria Australia
| | - James D. Doecke
- Australian E‐Health Research Centre CSIRO Herston Queensland Australia
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29
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Weinshel S, Irwin DJ, Zhang P, Weintraub D, Shaw LM, Siderowf A, Xie SX. Appropriateness of Applying Cerebrospinal Fluid Biomarker Cutoffs from Alzheimer's Disease to Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:1155-1167. [PMID: 35431261 PMCID: PMC9934950 DOI: 10.3233/jpd-212989] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND While cutoffs for abnormal levels of the cerebrospinal fluid (CSF) biomarkers amyloid-β 1-42 (Aβ142), total tau (t-tau), phosphorylated tau (p-tau), and the ratios of t-tau/Aβ142 and p-tau/Aβ142, have been established in Alzheimer's disease (AD), biologically relevant cutoffs have not been studied extensively in Parkinson's disease (PD). OBJECTIVE Assess the suitability and diagnostic accuracy of established AD-derived CSF biomarker cutoffs in the PD population. METHODS Baseline and longitudinal data on CSF biomarkers, cognitive diagnoses, and PET amyloid imaging in 423 newly diagnosed patients with PD from the Parkinson's Progression Markers Initiative (PPMI) cohort were used to evaluate established AD biomarker cutoffs compared with optimal cutoffs derived from the PPMI cohort. RESULTS Using PET amyloid imaging as the gold standard for AD pathology, the optimal cutoff of Aβ142 was higher than the AD cutoff, the optimal cutoffs of t-tau/Aβ142 and p-tau/Aβ142 were lower than the AD cutoffs, and their confidence intervals (CIs) did not overlap with the AD cutoffs. Optimal cutoffs for t-tau and p-tau to predict cognitive impairment were significantly lower than the AD cutoffs, and their CIs did not overlap with the AD cutoffs. CONCLUSION Optimal cutoffs for the PPMI cohort for Aβ142, t-tau/Aβ142, and p-tau/Aβ142 to predict amyloid-PET positivity and for t-tau and p-tau to predict cognitive impairment differ significantly from cutoffs derived from AD populations. The presence of additional pathologies such as alpha-synuclein in PD may lead to disease-specific CSF biomarker characteristics.
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Affiliation(s)
- Sarah Weinshel
- Swarthmore College, Swarthmore, PA, USA;,Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David J. Irwin
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Panpan Zhang
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Weintraub
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA;,Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA;,Michael J. Crescenz VA Medical Center, Parkinson’s Disease Research, Education, and Clinical Center, Philadelphia, PA, USA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew Siderowf
- Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sharon X. Xie
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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30
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Cummings J, Aisen P, Apostolova LG, Atri A, Salloway S, Weiner M. Aducanumab: Appropriate Use Recommendations. J Prev Alzheimers Dis 2021; 8:398-410. [PMID: 34585212 PMCID: PMC8835345 DOI: 10.14283/jpad.2021.41] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Aducanumab has been approved by the US Food and Drug Administration for treatment of Alzheimer's disease (AD). Clinicians require guidance on the appropriate use of this new therapy. An Expert Panel was assembled to construct Appropriate Use Recommendations based on the participant populations, conduct of the pivotal trials of aducanumab, updated Prescribing Information, and expert consensus. Aducanumab is an amyloid-targeting monoclonal antibody delivered by monthly intravenous infusions. The pivotal trials included patients with early AD (mild cognitive impairment due to AD and mild AD dementia) who had confirmed brain amyloid using amyloid positron tomography. The Expert Panel recommends that use of aducanumab be restricted to this population in which efficacy and safety have been studied. Aducanumab is titrated to a dose of 10 mg/kg over a 6-month period. The Expert Panel recommends that the aducanumab be titrated to the highest dose to maximize the opportunity for efficacy. Aducanumab can substantially increase the incidence of amyloid-related imaging abnormalities (ARIA) with brain effusion or hemorrhage. Dose interruption or treatment discontinuation is recommended for symptomatic ARIA and for moderate-severe ARIA. The Expert Panel recommends MRIs prior to initiating therapy, during the titration of the drug, and at any time the patient has symptoms suggestive of ARIA. Recommendations are made for measures less cumbersome than those used in trials for the assessment of effectiveness in the practice setting. The Expert Panel emphasized the critical importance of engaging in a process of patient-centered informed decision-making that includes comprehensive discussions and clear communication with the patient and care partner regarding the requirements for therapy, the expected outcome of therapy, potential risks and side effects, and the required safety monitoring, as well as uncertainties regarding individual responses and benefits.
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Affiliation(s)
- J Cummings
- Jeffrey Cummings, MD, ScD, 1380 Opal Valley Street, Henderson, NV 89052, , T: 702-902-3939
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