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Quintas-Neves M, Teylan MA, Morais-Ribeiro R, Almeida F, Mock CN, Kukull WA, Crary JF, Oliveira TG. Divergent magnetic resonance imaging atrophy patterns in Alzheimer's disease and primary age-related tauopathy. Neurobiol Aging 2022; 117:1-11. [PMID: 35640459 DOI: 10.1016/j.neurobiolaging.2022.04.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 10/18/2022]
Abstract
Our study compared brain MRI with neuropathological findings in patients with primary age-related tauopathy (PART) and Alzheimer's disease (AD), while assessing the relationship between brain atrophy and clinical impairment. We analyzed 233 participants: 32 with no plaques ("definite" PART-BRAAK stage higher than 0 and CERAD 0), and 201 cases within the AD spectrum, with 25 with sparse (CERAD 1), 76 with moderate (CERAD 2), and 100 with severe (CERAD 3) degrees of neuritic plaques. Upon correcting for age, sex, and age difference at MRI and death, there were significantly higher levels of atrophy in CERAD 3 compared to CERAD 1-2 and a trend compared to PART (p = 0.06). In the anterior temporal region, there was a trend for higher levels of atrophy in PART compared to Alzheimer's disease spectrum cases with CERAD 1 (p = 0.08). We then assessed the correlation between regional brain atrophy and CDR sum of boxes score for PART and AD, and found that overall cognition deficits are directly correlated with regional atrophy in the AD continuum, but not in definite PART. We further observed correlations between regional brain atrophy with multiple neuropsychological metrics in AD, with PART showing specific correlations between language deficits and anterior temporal atrophy. Overall, these findings support PART as an independent pathologic process from AD.
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Affiliation(s)
- Miguel Quintas-Neves
- Department of Neuroradiology, Hospital de Braga, Braga, Portugal; Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Merilee A Teylan
- Department of Epidemiology, National Alzheimer's Coordinating Center, University of Washington, Seattle, WA, USA
| | - Rafaela Morais-Ribeiro
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Francisco Almeida
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Charles N Mock
- Department of Epidemiology, National Alzheimer's Coordinating Center, University of Washington, Seattle, WA, USA
| | - Walter A Kukull
- Department of Epidemiology, National Alzheimer's Coordinating Center, University of Washington, Seattle, WA, USA
| | - John F Crary
- Neuropathology Brain Bank & Research Core, Department of Pathology, Nash Family Department of Neuroscience, Department of Artificial Intelligence & Human Health, Friedman Brain Institute, Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tiago Gil Oliveira
- Department of Neuroradiology, Hospital de Braga, Braga, Portugal; Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal.
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102
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Nordestgaard LT, Christoffersen M, Frikke-Schmidt R. Shared Risk Factors between Dementia and Atherosclerotic Cardiovascular Disease. Int J Mol Sci 2022; 23:9777. [PMID: 36077172 PMCID: PMC9456552 DOI: 10.3390/ijms23179777] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 08/21/2022] [Accepted: 08/24/2022] [Indexed: 11/25/2022] Open
Abstract
Alzheimer's disease is the most common form of dementia, and the prodromal phases of Alzheimer's disease can last for decades. Vascular dementia is the second most common form of dementia and is distinguished from Alzheimer's disease by evidence of previous stroke or hemorrhage and current cerebrovascular disease. A compiled group of vascular-related dementias (vascular dementia and unspecified dementia) is often referred to as non-Alzheimer dementia. Recent evidence indicates that preventing dementia by lifestyle interventions early in life with a focus on reducing cardiovascular risk factors is a promising strategy for reducing future risk. Approximately 40% of dementia cases is estimated to be preventable by targeting modifiable, primarily cardiovascular risk factors. The aim of this review is to describe the association between risk factors for atherosclerotic cardiovascular disease and the risk of Alzheimer's disease and non-Alzheimer dementia by providing an overview of the current evidence and to shed light on possible shared pathogenic pathways between dementia and cardiovascular disease. The included risk factors are body mass index (BMI); plasma triglyceride-, high-density lipoprotein (HDL) cholesterol-, low-density lipoprotein (LDL) cholesterol-, and total cholesterol concentrations; hypertension; diabetes; non-alcoholic fatty liver disease (NAFLD); physical inactivity; smoking; diet; the gut microbiome; and genetics. Furthermore, we aim to disentangle the difference between associations of risk factors in midlife as compared with in late life.
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Affiliation(s)
- Liv Tybjærg Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital—Rigshospitalet, 2100 Copenhagen, Denmark
| | - Mette Christoffersen
- Department of Clinical Biochemistry, Copenhagen University Hospital—Rigshospitalet, 2100 Copenhagen, Denmark
| | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Copenhagen University Hospital—Rigshospitalet, 2100 Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
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Singh NA, Graff-Radford J, Machulda MM, Schwarz CG, Baker MC, Rademakers R, Ertekin-Taner N, Lowe VJ, Josephs KA, Whitwell JL. Atypical Alzheimer's disease phenotypes with normal or borderline PET biomarker profiles. J Neurol 2022; 269:6613-6626. [PMID: 36001141 DOI: 10.1007/s00415-022-11330-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/05/2022] [Accepted: 08/07/2022] [Indexed: 01/01/2023]
Abstract
Posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are clinical syndromes that commonly have underlying Alzheimer's disease (AD), although non-AD pathologies have also been reported. PET imaging allows for identification of beta-amyloid (Aβ) and tau in AD, so we aimed to assess these in a large cohort to identify patients that do not have evidence for biomarker-defined AD. Eight-one patients, 47 PCA and 34 LPA, underwent extensive neurological and neuropsychological testing, [11C] Pittsburgh compound B, [18F] flortaucipir and [18F] fluorodeoxyglucose PETs. Global Aβ and tau-PET standardized uptake value ratios (SUVRs) were plotted for all patients and outliers, and patients with abnormally low SUVRs compared to the biomarker-classic cohort were identified. Six (7.4%) biomarker-outlier cases were identified, and three patterns were observed: (i) negative/borderline Aβ-PET and striking widespread tau-PET uptake (two LPA); (ii) negative/borderline Aβ-PET and low tau-PET uptake (three PCA) and (iii) elevated Aβ-PET uptake but mild focal tau-PET uptake (one LPA). Among the unusual patients in group ii, two patients showed no abnormal tau uptake suggesting non-AD pathology, with one developing features of cortico-basal syndrome and the other dementia with Lewy bodies. The remaining patient showed very mild focal tau uptake. This study demonstrates that a small minority (~ 8%) of PCA and LPA patients do not show the typical striking patterns of Aβ and tau PET uptake, with only 2% showing absence of both proteins. These findings will help inform the use of molecular PET in clinical treatment trials that include patients with atypical phenotypes of AD.
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Affiliation(s)
| | | | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Matthew C Baker
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA
| | | | - Jennifer L Whitwell
- Department of Radiology, Mayo Clinic, 200 1st St SW, Rochester, MN, 55905, USA.
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O’Bryant SE, Petersen M, Hall J, Johnson LA. Depression is differentially related to cognitive and biomarker outcomes among Mexican Americans. Front Psychiatry 2022; 13:901403. [PMID: 36081458 PMCID: PMC9445986 DOI: 10.3389/fpsyt.2022.901403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 07/18/2022] [Indexed: 11/26/2022] Open
Abstract
Introduction Despite tremendous advancements in the research of Alzheimer's disease (AD), Mexican Americans, who reflect 65% of the US Hispanic community, remain severely underrepresented in research. Our data demonstrate that risk factors for, and biomarkers of, AD are different among Mexican Americans as compared with non-Hispanic whites. Here, we examined the impact of depressive symptoms on cognitive and AD-relevant biomarker outcomes among the Mexican Americans. Methods Data were examined from 1,633 (852 Mexican Americans and 781 non-Hispanic whites) of the Health and Aging Brain Study-Health Disparities (HABS-HD). Depression was assessed using the Geriatric Depression Scale while cognition was measured using detailed neuropsychological testing. Plasma biomarkers of Aβ40, Aβ42, total tau, and NfL were examined in addition to MRI-based neurodegeneration. PET amyloid data were available in a subset of participants. Results Depressive symptoms were significantly associated with cognitive testing results among both Mexican Americans and non-Hispanic whites. However, depression was only significantly associated with cognitive outcomes and plasma biomarkers among the Mexican American APOEε4 non-carriers. Discussion Depressive symptoms are more commonly endorsed by Mexican Americans and these symptoms are more strongly associated with cognitive and AD-biomarker outcomes among this ethnic group. However, depression scores were only related to AD outcomes among APOEε4 non-carriers within the Mexican American group. These findings can aid in the development of a population-informed precision medicine for treating and preventing cognitive loss among the Mexican Americans.
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Affiliation(s)
- Sid E. O’Bryant
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Melissa Petersen
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, United States
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - James Hall
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Leigh A. Johnson
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, United States
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, United States
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Oberstein TJ, Schmidt MA, Florvaag A, Haas AL, Siegmann EM, Olm P, Utz J, Spitzer P, Doerfler A, Lewczuk P, Kornhuber J, Maler JM. Amyloid-β levels and cognitive trajectories in non-demented pTau181-positive subjects without amyloidopathy. Brain 2022; 145:4032-4041. [PMID: 35973034 DOI: 10.1093/brain/awac297] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/11/2022] [Accepted: 07/24/2022] [Indexed: 11/13/2022] Open
Abstract
Phosphorylated Tau181 (pTau181) in cerebrospinal fluid (CSF) and recently in plasma has been associated with Alzheimer's disease. In the absence of amyloidopathy, individuals with increased total Tau levels and/or temporal lobe atrophy experience no or only mild cognitive decline compared with biomarker-negative controls, leading to the proposal to categorize this constellation as Suspected non-Alzheimer disease pathophysiology (SNAP). We investigated whether the characteristics of SNAP also applied to individuals with increased CSF-pTau181 without amyloidopathy. In this long-term observational study, 285 non-demented individuals, including 76 individuals with subjective cognitive impairment and 209 individuals with mild cognitive impairment, were classified based on their CSF-levels of pTau181 (T), total Tau (N), Amyloid-beta-(Aβ)-42 and Aβ42/Aβ40 ratio (A) into A + T+N±, A + T-N±, A-T + N±, and A-T-N-. The longitudinal analysis included 154 subjects with a follow-up of more than 12 months who were followed to a median of 4.6 years (interquartile range = 4.3 years). We employed linear mixed models on psychometric tests and region of interest analysis of structural MRI data. Cognitive decline and hippocampal atrophy rate were significantly higher in A + T+N ± compared to A-T + N±, whereas there was no difference between A-T + N ± and A-T-N-. Furthermore, there was no significant difference between A-T + N ± and controls in dementia risk (Hazard ratio 0.3, 95% confidence interval [0.1, 1.9]). However, A-T + N ± and A-T-N- could be distinguished based on their Aβ42 and Aβ40 levels. Both Aβ40 and Aβ42 levels were significantly increased in A-T + N ± compared to controls. Long term follow-up of A-T + N ± individuals revealed no evidence that this biomarker constellation was associated with dementia or more severe hippocampal atrophy rates compared to controls. However, because of the positive association of pTau181 with Aβ in the A-T + N ± group, a link to the pathophysiology of Alzheimer´s disease cannot be excluded in this case. We propose to refer to these individuals in the SNAP group as "pTau and Aβ surge with subtle deterioration" (PASSED). The investigation of the circumstances of simultaneous elevation of pTau and Aβ might provide a deeper insight into the process under which Aβ becomes pathological.
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Affiliation(s)
- Timo Jan Oberstein
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel Alexander Schmidt
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Anna Florvaag
- Department of Radiology and Nuclear Medicine, Klinikum Nuremberg, Nuremberg, Germany
| | - Anna Lena Haas
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Eva Maria Siegmann
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Pauline Olm
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Janine Utz
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Philipp Spitzer
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Arnd Doerfler
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Neurodegeneration Diagnostics, Medical University of Bialystok, University Hospital of Bialystok, Bialystok, Poland.,Department of Biochemical Diagnostics, University Hospital of Bialystok, Bialystok, Poland
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Juan Manuel Maler
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Qiu J, Goldstein FC, Hanfelt JJ. An Exploration of Subgroups of Neuropsychiatric Symptoms in Mild Cognitive Impairment and Their Risks of Conversion to Dementia or Death. Am J Geriatr Psychiatry 2022; 30:925-934. [PMID: 35067420 PMCID: PMC9250542 DOI: 10.1016/j.jagp.2021.12.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 01/26/2023]
Abstract
OBJECTIVE To explore the heterogeneity of neuropsychiatric symptom (NPS) complexes in individuals with mild cognitive impairment (MCI) and assess the relative risks of converting to dementia or dying. DESIGN Latent class analysis using 7,971 participants with MCI. SETTING Participants in the Uniform Data Set (UDS) from 39 NIH Alzheimer's Disease Centers. PARTICIPANTS Persons with a diagnosis of MCI at initial visit from each center and with either a Mini-Mental State Examination (MMSE) score of 22 or greater or an equivalent education-adjusted Montreal Cognitive Assessment (MoCA) score of 16 or greater. MEASUREMENTS Neuropsychiatric Inventory Questionnaire (NPI-Q) administered at initial visit. RESULTS In addition to a subgroup with mild or no NPS (relative frequency, 50%), three empirically-based subgroups of NPS were identified: 1) an "affect" or "negative mood" subgroup (27%) with depression, anxiety, apathy, nighttime disturbance, and change in appetite; 2) a "hyperactive" subgroup (14%) with agitation, irritability, and disinhibition; and 3) a "psychotic with additional severe NPS" subgroup (9%) with the highest risk of delusions and hallucinations, as well as highest risk of all other NPS. Each of these three subgroups had significantly higher risk of converting to dementia than the "mild NPS" class, with the "psychotic with additional severe NPS" subgroup possessing a 64% greater risk. The subgroups did not differ in their risks of death without dementia. CONCLUSION Our findings of three NPS subgroups in MCI characterized by affect, hyperactive, or psychotic features are largely consistent with a previous 3-factor model of NPS found in a demented population. The consistency of these findings across studies and samples, coupled with our results on the associated risks of converting to dementia, suggests that the NPS structure is robust, and warrants further consideration in classification models of MCI.
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Affiliation(s)
- Jiayue Qiu
- School of Dental Medicine, University of Pennsylvania
| | - Felicia C. Goldstein
- Department of Neurology, Emory University School of Medicine,Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine
| | - John J. Hanfelt
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine,Department of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health
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Alden EC, Lundt ES, Twohy EL, Christianson TJ, Kremers WK, Machulda MM, Jack CR, Knopman DS, Mielke MM, Petersen RC, Stricker NH. Mayo normative studies: A conditional normative model for longitudinal change on the Auditory Verbal Learning Test and preliminary validation in preclinical Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12325. [PMID: 35860792 PMCID: PMC9286327 DOI: 10.1002/dad2.12325] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 04/20/2022] [Accepted: 05/08/2022] [Indexed: 11/09/2022]
Abstract
Introduction The aim of this study was to develop a conditional normative model for Rey's Auditory Verbal Learning Test (AVLT) that accounts for practice effects. Methods In our normative sample, robust conditional norms were derived from 1001 cognitively unimpaired (CU) adults ages 50 to 89 who completed the AVLT up to eight times. Linear mixed-effects models adjusted for baseline performance, prior test exposures, time, demographics, and interaction terms. In our preliminary validation, mean performance on conditional and typical normative scores across two to four completed follow-up tests in preclinical Alzheimer's disease participants at baseline with positive amyloid and tau positron emission (n = 27 CU amyloid [A]+tau[T]+) was compared to biomarker negative individuals (n = 269 CU A-T-). Results AVLT performance using typical norms did not differ across A+T+ and A-T- groups. Conditional norms z-scores were lower in the A+T+ relative to the A-T- group for 30-minute recall (P = .033) and sum of trials (P = .030). Discussion Conditional normative methods that account for practice effects show promise for identifying longitudinal cognitive decline.
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Affiliation(s)
- Eva C. Alden
- Division of Neurocognitive DisordersDepartment of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Emily S. Lundt
- Division of Clinical Trials and BiostatisticsDepartment of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Erin L. Twohy
- Division of Clinical Trials and BiostatisticsDepartment of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Teresa J. Christianson
- Division of Clinical Trials and BiostatisticsDepartment of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Walter K. Kremers
- Division of Clinical Trials and BiostatisticsDepartment of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Mary M. Machulda
- Division of Neurocognitive DisordersDepartment of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | | | | | - Michelle M. Mielke
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
- Division of EpidemiologyDepartment of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | | | - Nikki H. Stricker
- Division of Neurocognitive DisordersDepartment of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
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Coffin C, Suerken CK, Bateman JR, Whitlow CT, Williams BJ, Espeland MA, Sachs BC, Cleveland M, Yang M, Rogers S, Hayden KM, Baker LD, Williamson J, Craft S, Hughes TM, Lockhart SN. Vascular and microstructural markers of cognitive pathology. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12332. [PMID: 35814618 PMCID: PMC9257520 DOI: 10.1002/dad2.12332] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/08/2022] [Accepted: 05/10/2022] [Indexed: 11/16/2022]
Abstract
Introduction Arterial stiffness may play a role in the development of dementia through poorly understood effects on brain microstructural integrity and perfusion. Methods We examined markers of arterial stiffness (carotid-femoral pulse wave velocity [cfPWV]) and elevated systolic blood pressure (SBP) in relation to cognitive function and brain magnetic resonance imaging macrostructure (gray matter [GM] and white matter [WM] volumes), microstructure (diffusion based free water [FW] and fractional anisotropy [FA]), and cerebral blood flow (CBF) in WM and GM in models adjusted for age, race, sex, education, and apolipoprotein E ε4 status. Results Among 460 participants (70 ± 8 years; 44 dementia, 158 mild cognitive impairment, 258 normal cognition), higher cfPWV and SBP were independently associated with higher FW, higher WM hyperintensity volume, and worse cognition (global and executive function). Higher SBP alone was significantly associated with lower WM and GM CBF. Discussion Arterial stiffness is associated with impaired WM microstructure and global and executive cognitive function.
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Affiliation(s)
- Claudia Coffin
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Cynthia K. Suerken
- Department of Biostatistics and Data ScienceDivision of Public Health SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - James R. Bateman
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | - Benjamin J. Williams
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Mark A. Espeland
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
- Department of Biostatistics and Data ScienceDivision of Public Health SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Bonnie C. Sachs
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Maryjo Cleveland
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Mia Yang
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Samantha Rogers
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Kathleen M. Hayden
- Department of Social Sciences and Health PolicyDivision of Public Health SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Laura D. Baker
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jeff Williamson
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Suzanne Craft
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Timothy M. Hughes
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Samuel N. Lockhart
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
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Tosun D, Demir Z, Veitch DP, Weintraub D, Aisen P, Jack CR, Jagust WJ, Petersen RC, Saykin AJ, Shaw LM, Trojanowski JQ, Weiner MW. Contribution of Alzheimer's biomarkers and risk factors to cognitive impairment and decline across the Alzheimer's disease continuum. Alzheimers Dement 2022; 18:1370-1382. [PMID: 34647694 PMCID: PMC9014819 DOI: 10.1002/alz.12480] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 08/10/2021] [Accepted: 08/15/2021] [Indexed: 01/27/2023]
Abstract
INTRODUCTION Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression. METHODS Within 248 Aβ-positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ-positron emission tomography [PET] uptake, regional tau-PET uptake, and regional magnetic resonance imaging-based atrophy) and risk-factors (age, sex, education, apolipoprotein E [APOE], and white-matter lesions) on cross-sectional cognitive impairment and longitudinal cognitive decline. RESULTS Sixteen percent of variance in cross-sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ-tau-atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively. DISCUSSION These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.
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Affiliation(s)
- Duygu Tosun
- San Francisco Veterans Affairs Medical CenterSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Zeynep Demir
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Dallas P. Veitch
- San Francisco Veterans Affairs Medical CenterSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Daniel Weintraub
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute (ATRI)Keck School of MedicineUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | | | - William J. Jagust
- School of Public Health and Helen Wills Neuroscience InstituteUniversity of California, BerkeleyBerkeleyCaliforniaUSA
| | - Ronald C. Petersen
- Division of EpidemiologyDepartment of Health Sciences ResearchMayo ClinicRochesterMinnesotaUSA
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
| | - Andrew J. Saykin
- Center for NeuroimagingDepartment of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer Disease CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - John Q. Trojanowski
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Michael W. Weiner
- San Francisco Veterans Affairs Medical CenterSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
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Lozupone M, Berardino G, Mollica A, Sardone R, Dibello V, Zupo R, Lampignano L, Castellana F, Bortone I, Stallone R, Daniele A, Altamura M, Bellomo A, Solfrizzi V, Panza F. ALZT-OP1: An experimental combination regimen for the treatment of Alzheimer's Disease. Expert Opin Investig Drugs 2022; 31:759-771. [PMID: 35758153 DOI: 10.1080/13543784.2022.2095261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION For Alzheimer's disease (AD) treatment, US FDA granted accelerated approval for aducanumab due to its amyloid-β (Aβ)-lowering effects, notwithstanding the reported poor correlation between amyloid plaque reduction and clinical change for this drug. The diversification of drug targets appears to be the future of the AD field and from this perspective, drugs modulating microglia dysfunction and combination treatment regimens offer some promise. AREAS COVERED The aim of the present article was to provide a comprehensive review of ALZT-OP1 (cromolyn sodium plus ibuprofen), an experimental combination treatment regimen for AD, discussing their mechanisms of action targeting Aβ and neuroinflammation, examining the role of microglia in AD and offering our own insights on the role of present and alternative approaches directed toward neuroinflammation. EXPERT OPINION Enrolling high-risk participants with elevated brain amyloid could help to slow cognitive decline in secondary prevention trials during AD preclinical stages. Long-term follow-up indicated that non-steroidal anti-inflammatory drugs use begun when the brain was still normal may benefit these patients, suggesting that the timing of therapy could be crucial. However, previous clinical failures and the present incomplete understanding of the Aβ pathophysiological role in AD put this novel experimental combination regimen at substantial risk of failure.
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Affiliation(s)
- Madia Lozupone
- Neurodegenerative Disease Unit, Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Giuseppe Berardino
- Psychiatric Unit, Department of Clinical & Experimental Medicine, University of Foggia, Foggia
| | - Anita Mollica
- Psychiatric Unit, Department of Clinical & Experimental Medicine, University of Foggia, Foggia
| | - Rodolfo Sardone
- Unit of Research Methodology and Data Sciences for Population Health, National Institute of Gastroenterology and Research Hospital IRCCS "S. De Bellis" Castellana Grotte, Bari, Italy
| | - Vittorio Dibello
- Department of Orofacial Pain and Dysfunction, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Roberta Zupo
- Unit of Research Methodology and Data Sciences for Population Health, National Institute of Gastroenterology and Research Hospital IRCCS "S. De Bellis" Castellana Grotte, Bari, Italy
| | - Luisa Lampignano
- Unit of Research Methodology and Data Sciences for Population Health, National Institute of Gastroenterology and Research Hospital IRCCS "S. De Bellis" Castellana Grotte, Bari, Italy
| | - Fabio Castellana
- Unit of Research Methodology and Data Sciences for Population Health, National Institute of Gastroenterology and Research Hospital IRCCS "S. De Bellis" Castellana Grotte, Bari, Italy
| | - Ilaria Bortone
- Unit of Research Methodology and Data Sciences for Population Health, National Institute of Gastroenterology and Research Hospital IRCCS "S. De Bellis" Castellana Grotte, Bari, Italy
| | - Roberta Stallone
- Neuroscience and Education, Human Resources Excellence in Research, University of Foggia, Foggia, Italy
| | - Antonio Daniele
- Department of Neuroscience, Catholic University of Sacred Heart, Rome, Italy.,Neurology Unit, IRCCS Fondazione Policlinico Universitario A. Gemelli, Rome, Italy
| | - Mario Altamura
- Psychiatric Unit, Department of Clinical & Experimental Medicine, University of Foggia, Foggia
| | - Antonello Bellomo
- Psychiatric Unit, Department of Clinical & Experimental Medicine, University of Foggia, Foggia
| | - Vincenzo Solfrizzi
- "Cesare Frugoni" Internal and Geriatric Medicine and Memory Unit, University of Bari "Aldo Moro", Bari, Italy
| | - Francesco Panza
- Unit of Research Methodology and Data Sciences for Population Health, National Institute of Gastroenterology and Research Hospital IRCCS "S. De Bellis" Castellana Grotte, Bari, Italy
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Staging of Alzheimer's disease: past, present, and future perspectives. Trends Mol Med 2022; 28:726-741. [PMID: 35717526 DOI: 10.1016/j.molmed.2022.05.008] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 01/01/2023]
Abstract
For many years Alzheimer's disease (AD) was associated with the dementia stage of the disease, the tail end of a pathophysiological process that lasts approximately two decades. Whereas early disease staging assessments focused on progressive deterioration of clinical functioning, brain imaging with positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarker studies highlighted the long preclinical phase of AD in which a cascade of detectable biological abnormalities precede cognitive decline. The recent proliferation of imaging and fluid biomarkers of AD pathophysiology provide an opportunity for the identification of several biological stages in the preclinical phase of AD. We discuss the use of clinical and biomarker information in past, present, and future staging of AD. We highlight potential applications of PET, CSF, and plasma biomarkers for staging AD severity in vivo.
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Therriault J, Pascoal TA, Lussier FZ, Tissot C, Chamoun M, Bezgin G, Servaes S, Benedet AL, Ashton NJ, Karikari TK, Lantero-Rodriguez J, Kunach P, Wang YT, Fernandez-Arias J, Massarweh G, Vitali P, Soucy JP, Saha-Chaudhuri P, Blennow K, Zetterberg H, Gauthier S, Rosa-Neto P. Biomarker modeling of Alzheimer's disease using PET-based Braak staging. NATURE AGING 2022; 2:526-535. [PMID: 37118445 PMCID: PMC10154209 DOI: 10.1038/s43587-022-00204-0] [Citation(s) in RCA: 128] [Impact Index Per Article: 42.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 03/08/2022] [Indexed: 04/30/2023]
Abstract
Gold-standard diagnosis of Alzheimer's disease (AD) relies on histopathological staging systems. Using the topographical information from [18F]MK6240 tau positron-emission tomography (PET), we applied the Braak tau staging system to 324 living individuals. We used PET-based Braak stage to model the trajectories of amyloid-β, phosphorylated tau (pTau) in cerebrospinal fluid (pTau181, pTau217, pTau231 and pTau235) and plasma (pTau181 and pTau231), neurodegeneration and cognitive symptoms. We identified nonlinear AD biomarker trajectories corresponding to the spatial extent of tau-PET, with modest biomarker changes detectable by Braak stage II and significant changes occurring at stages III-IV, followed by plateaus. Early Braak stages were associated with isolated memory impairment, whereas Braak stages V-VI were incompatible with normal cognition. In 159 individuals with follow-up tau-PET, progression beyond stage III took place uniquely in the presence of amyloid-β positivity. Our findings support PET-based Braak staging as a framework to model the natural history of AD and monitor AD severity in living humans.
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Affiliation(s)
- Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada.
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nicholas J Ashton
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- Biomedical Research Unit for Dementia at South London, NIHR Biomedical Research Centre for Mental Health and Maudsley NHS Foundation, London, UK
| | - Thomas K Karikari
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Juan Lantero-Rodriguez
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Peter Kunach
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jaime Fernandez-Arias
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Gassan Massarweh
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Paolo Vitali
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jean-Paul Soucy
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | | | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada.
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
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113
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Josephs KA, Weigand SD, Whitwell JL. Characterizing Amyloid-Positive Individuals With Normal Tau PET Levels After 5 Years: An ADNI Study. Neurology 2022; 98:e2282-e2292. [PMID: 35314506 PMCID: PMC9162162 DOI: 10.1212/wnl.0000000000200287] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 02/10/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVE Individuals with biomarker evidence of β-amyloid (Aβ) deposition are increasingly being enrolled in clinical treatment trials but there is a need to identify markers to predict which of these individuals will also develop tau deposition. We aimed to determine whether Aβ-positive individuals can remain tau-negative for at least 5 years and identify characteristics that could distinguish between these individuals and those who develop high tau within this period. METHODS Tau PET positivity was defined using a Gaussian mixture model with log-transformed standard uptake value ratio values from 7 temporal and medial parietal regions using all participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) with flortaucipir PET. Tau PET scans were classified as normal if the posterior probability of elevated tau was less than 1%. Aβ PET positivity was defined based on ADNI cutpoints. We identified all Aβ-positive individuals from ADNI who had normal tau PET more than 5 years after their first abnormal Aβ PET (amyloid with low tau [ALT] group) and all Aβ-positive individuals with abnormal tau PET within 5 years (biomarker AD). In a case-control design, logistic regression was used to model the odds of biomarker AD vs ALT accounting for sex, age, APOE ε4 carriership, Aβ Centiloid, and hippocampal volume. RESULTS We identified 45 individuals meeting criteria for ALT and 157 meeting criteria for biomarker AD. The ALT group had a lower proportion of APOE ε4 carriers, lower Aβ Centiloid, larger hippocampal volumes, and more preserved cognition, and were less likely to develop dementia, than the biomarker AD group. APOE ε4, higher Aβ Centiloid, and hippocampal atrophy were independently associated with increased odds of abnormal tau within 5 years. A Centiloid value of 50 effectively discriminated biomarker AD and ALT with 80% sensitivity and specificity. The majority of the ALT participants did not develop dementia throughout the 5-year interval. DISCUSSION Aβ-positive individuals can remain tau-negative for at least 5 years. Baseline characteristics can help identify these ALT individuals who are less likely to develop dementia. Conservative Aβ cutpoints should be utilized for clinical trials to better capture individuals with high risk of developing biomarker AD.
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Affiliation(s)
- Keith A Josephs
- From the Departments of Neurology (K.A.J.), Health Sciences Research (Division of Biomedical Informatics and Statistics) (S.D.W.), and Radiology (J.W.), Mayo Clinic, Rochester, MN
| | - Stephen D Weigand
- From the Departments of Neurology (K.A.J.), Health Sciences Research (Division of Biomedical Informatics and Statistics) (S.D.W.), and Radiology (J.W.), Mayo Clinic, Rochester, MN
| | - Jennifer L Whitwell
- From the Departments of Neurology (K.A.J.), Health Sciences Research (Division of Biomedical Informatics and Statistics) (S.D.W.), and Radiology (J.W.), Mayo Clinic, Rochester, MN
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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: 1.0] [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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Weigand AJ, Maass A, Eglit GL, Bondi MW. What's the cut-point?: a systematic investigation of tau PET thresholding methods. Alzheimers Res Ther 2022; 14:49. [PMID: 35382866 PMCID: PMC8985353 DOI: 10.1186/s13195-022-00986-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 03/09/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Tau positron emission tomography (PET) is increasing in popularity for biomarker characterization of Alzheimer's disease (AD), and recent frameworks rely on tau PET cut-points to stage individuals along the AD continuum. Given the lack of standardization in tau PET thresholding methods, this study sought to systematically canvass and characterize existing studies that have derived tau PET cut-points and then directly assess different methods of tau PET thresholding in terms of their concurrent validity. METHODS First, a literature search was conducted in PubMed to identify studies of AD and related clinical phenotypes that used the Flortaucipir (AV-1451) tau PET tracer to derive a binary cut-point for tau positivity. Of 540 articles screened and 47 full-texts reviewed, 23 cohort studies met inclusion criteria with a total of 6536 participants. Second, we derived and compared tau PET cut-points in a 2 × 2 × 2 design that systematically varied region (temporal meta-ROI and entorhinal cortex), analytic method (receiver operating characteristics and 2 standard deviations above comparison group), and criterion/comparison variable (amyloid-beta negative cognitively unimpaired or cognitively unimpaired only) using a sample of 453 older adults from the Alzheimer's Disease Neuroimaging Initiative. RESULTS For the systematic review, notable variability in sample characteristics, preprocessing methods, region of interest, and analytic approach were observed, which were accompanied by discrepancy in proposed tau PET cut points. The empirical follow-up indicated the cut-point derived based on 2 standard deviations above a either comparison group in either ROI best differentiated tau positive and negative groups on cerebrospinal fluid phosphorylated tau, Mini-Mental State Examination score, and delayed memory performance. CONCLUSIONS Given the impact of discrepant thresholds on tau positivity rates, biomarker staging, and eligibility for future clinical treatment trials, recommendations are offered to select cut-point derivations based on the unique goals and priorities of different studies.
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Affiliation(s)
- Alexandra J Weigand
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, USA
| | - Anne Maass
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Graham L Eglit
- Research Service, VA San Diego Healthcare System, San Diego, USA
- Department of Psychiatry, University of California, San Diego, USA
| | - Mark W Bondi
- Research Service, VA San Diego Healthcare System, San Diego, USA.
- Department of Psychiatry, University of California, San Diego, USA.
- Neuropsychological Assessment Unit, University of California San Diego School of Medicine, VA San Diego Healthcare System (116B), 3350 La Jolla Village Drive, San Diego, CA, 92161, USA.
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Vassilaki M, Aakre JA, Kremers WK, Mielke MM, Geda YE, Machulda MM, Knopman DS, Vemuri P, Lowe VJ, Jack CR, Roberson ED, Gerstenecker A, Martin RC, Kennedy RE, Marson DC, Petersen RC. Association of Performance on the Financial Capacity Instrument-Short Form With Brain Amyloid Load and Cortical Thickness in Older Adults. Neurol Clin Pract 2022; 12:113-124. [PMID: 35747890 PMCID: PMC9208409 DOI: 10.1212/cpj.0000000000001157] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background and Objectives To investigate the association of the Financial Capacity Instrument-Short Form (FCI-SF) performance and timing total scores with brain β-amyloid and cortical thickness in cognitively unimpaired (CU) (at baseline) older adults. Methods A total of 309 participants (aged 70 years or older) of the Mayo Clinic Study of Aging underwent 11C-Pittsburgh compound B PET amyloid imaging and MRI, and completed the FCI-SF. Abnormal amyloid PET was defined as standardized uptake value ratio ≥1.48 in an Alzheimer disease (AD)-related region of interest and reduced AD signature cortical thickness as ≤2.68 mm (neurodegeneration). A cohort of 218 (of the 309) participants had follow-up visits (every 15 months) with FCI-SF data for longitudinal analysis (number of visits including baseline, median [range]: 2 [2-4]). In the analysis, we used linear regression and mixed-effects models adjusted for age, sex, education, apolipoprotein E ε4 allele status, global cognitive z score, and previous FCI-SF testing. Results Participants' mean age (SD) was 80.2 (4.8) years (56.3% male individuals). In cross-sectional analysis, abnormal amyloid PET (vs normal) was associated with a lower FCI-SF total score and slower total composite time. In longitudinal analysis, FCI-SF total score declined faster (difference in annualized rate of change, beta coefficient [β] [95% confidence interval (CI)] = -1.123 [-2.086 to -0.161]) and FCI-SF total composite time increased faster (difference in annualized rate of change, β [95% CI] = 16.274 [5.951 to 26.597]) for participants with neurodegeneration at baseline (vs those without). Participants who exhibited both abnormal amyloid PET and neurodegeneration at baseline had a greater increase in total composite time when compared with the group without abnormal amyloid and without neurodegeneration (difference in annualized rate of change, β [95% CI] = 16.750 [3.193 to 30.307]). Discussion Performance and processing speed on the FCI-SF were associated with imaging biomarkers of AD pathophysiology in CU (at baseline) older adults. Higher burdens of imaging biomarkers were associated with longitudinal worsening on FCI-SF performance. Additional research is needed to delineate further these associations and their predictive utility at the individual person level.
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Affiliation(s)
- Maria Vassilaki
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Jeremiah A Aakre
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Walter K Kremers
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Michelle M Mielke
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Yonas E Geda
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Mary M Machulda
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - David S Knopman
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Prashanthi Vemuri
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Val J Lowe
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Clifford R Jack
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Erik D Roberson
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Adam Gerstenecker
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Roy C Martin
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Richard E Kennedy
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Daniel C Marson
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
| | - Ronald C Petersen
- Department of Quantitative Health Sciences (MV, JAA, WKK, M.M. Mielke, RCP), and Department of Neurology (M.M. Mielke, DSK, RCP), Mayo Clinic, Rochester, MN; Department of Neurology (YEG), Barrow Neurological Institute, Phoenix, AZ; Department of Psychiatry and Psychology (M.M. Machulda), and Department of Radiology (PV, VJL, CRJ), Mayo Clinic, Rochester, MN; Department of Neurology (EDR, AG, RCM, DCM), Department of Medicine (REK), and Alzheimer's Disease Center (DCM), University of Alabama at Birmingham
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Ebenau JL, Pelkmans W, Verberk IMW, Verfaillie SCJ, van den Bosch KA, van Leeuwenstijn M, Collij LE, Scheltens P, Prins ND, Barkhof F, van Berckel BNM, Teunissen CE, van der Flier WM. Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline. Neurology 2022; 98:e1315-e1326. [PMID: 35110378 PMCID: PMC8967429 DOI: 10.1212/wnl.0000000000200035] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 01/03/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Multiple biomarkers have been suggested to measure neurodegeneration (N) in the AT(N) framework, leading to inconsistencies between studies. We investigated the association of 5 N biomarkers with clinical progression and cognitive decline in individuals with subjective cognitive decline (SCD). METHODS We included individuals with SCD from the Amsterdam Dementia Cohort and SCIENCe project, a longitudinal cohort study (follow-up 4±3 years). We used the following N biomarkers: CSF total tau (t-tau), medial temporal atrophy visual rating on MRI, hippocampal volume (HV), serum neurofilament light (NfL), and serum glial fibrillary acidic protein (GFAP). We determined correlations between biomarkers. We assessed associations between N biomarkers and clinical progression to mild cognitive impairment or dementia (Cox regression) and Mini-Mental State Examination (MMSE) over time (linear mixed models). Models included age, sex, CSF β-amyloid (Aβ) (A), and CSF p-tau (T) as covariates, in addition to the N biomarker. RESULT We included 401 individuals (61±9 years, 42% female, MMSE 28 ± 2, vascular comorbidities 8%-19%). N biomarkers were modestly to moderately correlated (range r -0.28 - 0.58). Serum NfL and GFAP correlated most strongly (r 0.58, p < 0.01). T-tau was strongly correlated with p-tau (r 0.89, p < 0.01), although these biomarkers supposedly represent separate biomarker groups. All N biomarkers individually predicted clinical progression, but only HV, NfL, and GFAP added predictive value beyond Aβ and p-tau (hazard ratio 1.52 [95% CI 1.11-2.09]; 1.51 [1.05-2.17]; 1.50 [1.04-2.15]). T-tau, HV, and GFAP individually predicted MMSE slope (range β -0.17 to -0.11, p < 0.05), but only HV remained associated beyond Aβ and p-tau (β -0.13 [SE 0.04]; p < 0.05). DISCUSSION In cognitively unimpaired older adults, correlations between different N biomarkers were only moderate, indicating they reflect different aspects of neurodegeneration and should not be used interchangeably. T-tau was strongly associated with p-tau (T), which makes it less desirable to use as a measure for N. HV, NfL, and GFAP predicted clinical progression beyond A and T. Our results do not allow to choose one most suitable biomarker for N, but illustrate the added prognostic value of N beyond A and T. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that HV, NfL, and GFAP predicted clinical progression beyond A and T in individuals with SCD.
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Affiliation(s)
- Jarith L Ebenau
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK.
| | - Wiesje Pelkmans
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Inge M W Verberk
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Sander C J Verfaillie
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Karlijn A van den Bosch
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Mardou van Leeuwenstijn
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Lyduine E Collij
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Philip Scheltens
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Niels D Prins
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Frederik Barkhof
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Bart N M van Berckel
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Charlotte E Teunissen
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Wiesje M van der Flier
- From the Alzheimer Center, Departments of Neurology (J.L.E., W.P., I.M.W.V., K.A.v.d.B., M.v.L., P.S., N.D.P., B.N.M.v.B., W.M.V.d.F.) and Radiology & Nuclear Medicine (S.C.J.V., L.E.C., F.B., B.N.M.v.B.), Amsterdam Neuroscience, and Neurochemistry Laboratory, Department of Clinical Chemistry (I.M.W.V., C.E.T.), and Department of Epidemiology & Biostatistics (W.M.v.d.F.), Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
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Calderón-Garcidueñas L, Hernández-Luna J, Mukherjee PS, Styner M, Chávez-Franco DA, Luévano-Castro SC, Crespo-Cortés CN, Stommel EW, Torres-Jardón R. Hemispheric Cortical, Cerebellar and Caudate Atrophy Associated to Cognitive Impairment in Metropolitan Mexico City Young Adults Exposed to Fine Particulate Matter Air Pollution. TOXICS 2022; 10:toxics10040156. [PMID: 35448417 PMCID: PMC9028857 DOI: 10.3390/toxics10040156] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/14/2022] [Accepted: 03/22/2022] [Indexed: 12/16/2022]
Abstract
Exposures to fine particulate matter PM2.5 are associated with Alzheimer's, Parkinson's (AD, PD) and TDP-43 pathology in young Metropolitan Mexico City (MMC) residents. High-resolution structural T1-weighted brain MRI and/or Montreal Cognitive Assessment (MoCA) data were examined in 302 volunteers age 32.7 ± 6.0 years old. We used multivariate linear regressions to examine cortical surface area and thickness, subcortical and cerebellar volumes and MoCA in ≤30 vs. ≥31 years old. MMC residents were exposed to PM2.5 ~ 30.9 µg/m3. Robust hemispheric differences in frontal and temporal lobes, caudate and cerebellar gray and white matter and strong associations between MoCA total and index scores and caudate bilateral volumes, frontotemporal and cerebellar volumetric changes were documented. MoCA LIS scores are affected early and low pollution controls ≥ 31 years old have higher MoCA vs. MMC counterparts (p ≤ 0.0001). Residency in MMC is associated with cognitive impairment and overlapping targeted patterns of brain atrophy described for AD, PD and Fronto-Temporal Dementia (FTD). MMC children and young adult longitudinal studies are urgently needed to define brain development impact, cognitive impairment and brain atrophy related to air pollution. Identification of early AD, PD and FTD biomarkers and reductions on PM2.5 emissions, including poorly regulated heavy-duty diesel vehicles, should be prioritized to protect 21.8 million highly exposed MMC urbanites.
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Affiliation(s)
- Lilian Calderón-Garcidueñas
- College of Health, The University of Montana, Missoula, MT 59812, USA
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
- Correspondence: ; Tel.: +1-406-243-4785
| | | | - Partha S. Mukherjee
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata 700108, India;
| | - Martin Styner
- Neuro Image Research and Analysis Lab, University of North Carolina, Chapel Hill, NC 27599, USA;
| | - Diana A. Chávez-Franco
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Samuel C. Luévano-Castro
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Celia Nohemí Crespo-Cortés
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Elijah W. Stommel
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA;
| | - Ricardo Torres-Jardón
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico;
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Ge X, Qiao Y, Choi J, Raman R, Ringman JM, Shiand Y. Enhanced Association of Tau Pathology and Cognitive Impairment in Mild Cognitive Impairment Subjects with Behavior Symptoms. J Alzheimers Dis 2022; 87:557-568. [PMID: 35342088 DOI: 10.3233/jad-215555] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Mild cognitive impairment (MCI) individuals with neuropsychiatric symptoms (NPS) are more likely to develop dementia. OBJECTIVE We sought to understand the relationship between neuroimaging markers such as tau pathology and cognitive symptoms both with and without the presence of NPS during the prodromal period of Alzheimer's disease. METHODS A total of 151 MCI subjects with tau positron emission tomographic (PET) scanning with 18F AV-1451, amyloid-β (Aβ) PET scanning with florbetapir or florbetaben, magnetic resonance imaging, and cognitive and behavioral evaluations were selected from the Alzheimer's Disease Neuroimaging Initiative. A 4-group division approach was proposed using amyloid (A-/A+) and behavior (B-/B+) status: A-B-, A-B+, A+B-, and A+B+. Pearson's correlation test was conducted for each group to examine the association between tau deposition and cognitive performance. RESULTS No statistically significant association between tau deposition and cognitive impairment was found for subjects without behavior symptoms in either the A-B-or A+B-groups after correction for false discovery rate. In contrast, tau deposition was found to be significantly associated with cognitive impairment in entorhinal cortex and temporal pole for the A-B+ group and nearly the whole cerebrum for the A+B+ group. CONCLUSION Enhanced associations between tauopathy and cognitive impairment are present in MCI subjects with behavior symptoms, which is more prominent in the presence of elevated amyloid pathology. MCI individuals with NPS may thus be at greater risk for further cognitive decline with the increase of tau deposition in comparison to those without NPS.
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Affiliation(s)
- Xinting Ge
- Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,School of Information Science and Engineering, Shandong Normal University, Jinan, Shandong, China.,School of Medical Imaging, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Yuchuan Qiao
- Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jiyoon Choi
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA
| | - Rema Raman
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA, USA
| | - John M Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yonggang Shiand
- Laboratory of Neuro Imaging (LONI), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Huang S, Wang YJ, Guo J. Biofluid Biomarkers of Alzheimer’s Disease: Progress, Problems, and Perspectives. Neurosci Bull 2022; 38:677-691. [PMID: 35306613 PMCID: PMC9206048 DOI: 10.1007/s12264-022-00836-7] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 11/25/2021] [Indexed: 12/19/2022] Open
Abstract
Since the establishment of the biomarker-based A-T-N (Amyloid/Tau/Neurodegeneration) framework in Alzheimer’s disease (AD), the diagnosis of AD has become more precise, and cerebrospinal fluid tests and positron emission tomography examinations based on this framework have become widely accepted. However, the A-T-N framework does not encompass the whole spectrum of AD pathologies, and problems with invasiveness and high cost limit the application of the above diagnostic methods aimed at the central nervous system. Therefore, we suggest the addition of an “X” to the A-T-N framework and a focus on peripheral biomarkers in the diagnosis of AD. In this review, we retrospectively describe the recent progress in biomarkers based on the A-T-N-X framework, analyze the problems, and present our perspectives on the diagnosis of AD.
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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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Duggan MR, Lu A, Foster TC, Wimmer M, Parikh V. Exosomes in Age-Related Cognitive Decline: Mechanistic Insights and Improving Outcomes. Front Aging Neurosci 2022; 14:834775. [PMID: 35299946 PMCID: PMC8921862 DOI: 10.3389/fnagi.2022.834775] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 02/09/2022] [Indexed: 02/01/2023] Open
Abstract
Aging is the most prominent risk factor for cognitive decline, yet behavioral symptomology and underlying neurobiology can vary between individuals. Certain individuals exhibit significant age-related cognitive impairments, while others maintain intact cognitive functioning with only minimal decline. Recent developments in genomic, proteomic, and functional imaging approaches have provided insights into the molecular and cellular substrates of cognitive decline in age-related neuropathologies. Despite the emergence of novel tools, accurately and reliably predicting longitudinal cognitive trajectories and improving functional outcomes for the elderly remains a major challenge. One promising approach has been the use of exosomes, a subgroup of extracellular vesicles that regulate intercellular communication and are easily accessible compared to other approaches. In the current review, we highlight recent findings which illustrate how the analysis of exosomes can improve our understanding of the underlying neurobiological mechanisms that contribute to cognitive variation in aging. Specifically, we focus on exosome-mediated regulation of miRNAs, neuroinflammation, and aggregate-prone proteins. In addition, we discuss how exosomes might be used to enhance individual patient outcomes by serving as reliable biomarkers of cognitive decline and as nanocarriers to deliver therapeutic agents to the brain in neurodegenerative conditions.
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Affiliation(s)
- Michael R. Duggan
- Department of Psychology and Neuroscience Program, Temple University, Philadelphia, PA, United States
| | - Anne Lu
- Department of Psychology and Neuroscience Program, Temple University, Philadelphia, PA, United States
| | - Thomas C. Foster
- Department of Neuroscience, University of Florida College of Medicine, Gainesville, FL, United States
| | - Mathieu Wimmer
- Department of Psychology and Neuroscience Program, Temple University, Philadelphia, PA, United States
| | - Vinay Parikh
- Department of Psychology and Neuroscience Program, Temple University, Philadelphia, PA, United States
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Grober E, Wang C, Kitner-Triolo M, Lipton RB, Kawas C, Resnick SM. Prognostic Value of Learning and Retention Measures from the Free and Cued Selective Reminding Test to Identify Incident Mild Cognitive Impairment. J Int Neuropsychol Soc 2022; 28:292-299. [PMID: 33745492 PMCID: PMC8455713 DOI: 10.1017/s1355617721000291] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
OBJECTIVE To compare the predictive validity of learning and retention measures from the picture version of the Free and Cued Selective Reminding Test with Immediate Recall (pFCSRT + IR) for identifying incident mild cognitive impairment (MCI). METHODS Learning was defined by the sum of free recall (FR) and retention by delayed free recall (DFR) tested 15-20 min later. Totally, 1422 Baltimore Longitudinal Study of Aging (BLSA) participants (mean age 69.6 years, 54% male, mean 16.7 years of education) without dementia or MCI received the pFCSRT + IR at baseline and were followed longitudinally. Cox proportional hazards models were used to evaluate the effect of baseline learning and retention on risk of MCI. RESULTS In total, 187 participants developed MCI over a median of 8.1 years of follow-up. FR and DFR each predicted incident MCI adjusting for age, sex, and education. Also, each independently predicted incident MCI in the presence of the other with similar effect sizes: around 20% decrease in the hazard of MCI corresponding to one standard deviation increase in FR or DFR. CONCLUSION The practice of preferring retention over learning to predict incident MCI should be reconsidered. The decision to include retention should be guided by time constraints and patient burden.
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Affiliation(s)
- Ellen Grober
- Department of Neurology, Albert Einstein College of
Medicine and Montefiore Medical Center, Bronx, Bronx, NY, USA
| | - Cuiling Wang
- Department of Neurology, Albert Einstein College of
Medicine and Montefiore Medical Center, Bronx, Bronx, NY, USA
| | - Melissa Kitner-Triolo
- Laboratory of Behavioral Neuroscience, National Institute
on Aging, Baltimore, MD, USA
| | - Richard B. Lipton
- Department of Neurology, Albert Einstein College of
Medicine and Montefiore Medical Center, Bronx, Bronx, NY, USA
| | - Claudia Kawas
- Department of Neurology, University of California Irvine,
CA, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute
on Aging, Baltimore, MD, USA
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O'Bryant SE, Zhang F, Petersen M, Hall J, Johnson LA, Yaffe K, Braskie M, Rissman RA, Vig R, Toga AW. Neurodegeneration from the AT(N) framework is different among Mexican Americans compared to non-Hispanic Whites: A Health & Aging Brain among Latino Elders (HABLE) Study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12267. [PMID: 35155729 PMCID: PMC8828994 DOI: 10.1002/dad2.12267] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 07/29/2021] [Accepted: 10/18/2021] [Indexed: 01/18/2023]
Abstract
INTRODUCTION We sought to examine a magnetic resonance imaging (MRI)-based marker of neurodegeneration from the AT(N) (amyloid/tau/neurodegeneration) framework among a multi-ethnic, community-dwelling cohort. METHODS Community-dwelling Mexican Americans and non-Hispanic White adults and elders were recruited. All participants underwent comprehensive assessments including an interview, functional exam, clinical labs, informant interview, neuropsychological testing and 3T MRI of the brain. A neurodegeneration MRI meta-region of interest (ROI) biomarker for the AT(N) framework was calculated. RESULTS Data were examined from n = 1305 participants. Mexican Americans experienced N at significantly younger ages. The N biomarker was significantly associated with cognitive outcomes. N was significantly impacted by cardiovascular factors (e.g., total cholesterol, low-density lipoprotein) among non-Hispanic Whites whereas diabetes (glucose, HbA1c, duration of diabetes) and sociocultural (household income, acculturation) factors were strongly associated with N among Mexican Americans. DISCUSSION The prevalence, progression, timing, and sequence of the AT(N) biomarkers must be examined across diverse populations.
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Affiliation(s)
- Sid E. O'Bryant
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Fan Zhang
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Department of Family MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Melissa Petersen
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Department of Family MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - James Hall
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Department of Pharmacology and NeuroscienceUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Leigh A. Johnson
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Department of Pharmacology and NeuroscienceUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Kristine Yaffe
- Department of Psychiatry, Neurology, and Epidemiology and BiostatisticsUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
- San Francisco VA Medical CenterSan FranciscoCaliforniaUSA
| | - Meredith Braskie
- Imaging Genetics CenterUSC Stevens Neuroimaging and Informatics InstituteKeck School of Medicine of USCUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Robert A. Rissman
- Department of NeurosciencesUniversity of California, San DiegoSan DiegoCaliforniaUSA
- Veterans Affairs San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Rocky Vig
- ImagingMidtown Medical ImagingFort WorthTexasUSA
| | - Arthur W. Toga
- Laboratory of Neuro ImagingUSC Stevens Neuroimaging and Informatics InstituteKeck School of Medicine of USCUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - for the HABLE Study Team
- Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
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Abstract
Recently, Alzheimer's Disease International (ADI) stressed that around 75% of people living with dementia globally are still not receiving a diagnosis. In this commentary, I reflect on how efforts towards better cognitive assessments, particularly of memory, can be aligned and harmonized to contribute to such needs. I highlight some barriers that ongoing collaborations and trials are facing and their potential drivers. I suggest some strategies that can help overcome them and in so doing, integrate research agendas. We need to ignite the debate towards strategies that can help level the playfield to tackle Alzheimer's disease with true global solutions.
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Affiliation(s)
- Mario A Parra
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, Scotland, UK
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126
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Ko CY, Xu JH, Chang YW, Lo YM, Wu JSB, Huang WC, Shen SC. Effects of α-Lipoic Acid on Phagocytosis of Oligomeric Beta-Amyloid1–42 in BV-2 Mouse Microglial Cells. Front Aging Neurosci 2022; 13:788723. [PMID: 35095473 PMCID: PMC8790469 DOI: 10.3389/fnagi.2021.788723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 12/15/2021] [Indexed: 11/20/2022] Open
Abstract
Background and objectives: This study aimed to investigate the enhancing effect of vitamin-like alpha-lipoic acid (ALA) on phagocytosis of oligomeric beta-amyloid (oAβ)1–42 in BV-2 mouse microglial cells. Methods: An in vitro model was established to investigate phagocytosis of oAβ1–42 in BV-2 cells. Transmission electron microscopy images indicated that the morphology of prepared oAβ1–42 was spherical particles. BV-2 cells treated with ALA were incubated with 5(6)-carboxyfluorescein-labeled oAβ1–42 (FAM-oAβ1–42) for 24 h, followed by flow cytometer analysis, western blotting, real-time quantitative PCR, and immunocytochemistry (ICC) analysis to assess the in vitro phagocytosis ability of oAβ1–42. Results: Alpha-lipoic acid significantly increased messenger RNA (mRNA) expression of the CD36 receptor in BV-2 cells. ICC analysis showed that ALA significantly elevated CD36 protein expression in BV-2 cells both with and without oAβ1–42 treatment. Results from the flow cytometry analysis indicated that the CD36 receptor inhibitor significantly attenuated ALA-promoted phagocytosis of FAM-oAβ1–42 in BV-2 cells. Moreover, ICC analysis revealed that ALA caused the translocation of peroxisome proliferator-activated receptor-γ (PPAR-γ), which is known to regulate the expression of CD36 mRNA in BV-2 cells. ALA also elevated both the mRNA and protein expression of cyclooxygenase-2 (COX-2), which is a key enzyme involved in the synthesis of 15-deoxy-Δ12,14-prostaglandin J2 in BV-2 cells. Conclusion: We postulated that ALA enhances oAβ1–42 phagocytosis by upregulating the COX-2/15-deoxy-Δ12,14-prostaglandin J2/PPAR-γ/CD36 pathway in BV-2 cells. Finally, future studies should be conducted with an in vivo study to confirm the findings.
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Affiliation(s)
- Chih-Yuan Ko
- Department of Clinical Nutrition, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
- School of Public Health, Fujian Medical University, Fuzhou, China
- Respiratory Medicine Center of Fujian Province, Quanzhou, China
| | - Jian-Hua Xu
- Department of Tumor Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China
| | - Yu-Wei Chang
- Graduate Program of Nutrition Science, National Taiwan Normal University, Taipei, Taiwan
| | | | - James Swi-Bea Wu
- Graduate Institute of Food Science and Technology, National Taiwan University, Taipei, Taiwan
| | - Wen-Chung Huang
- Graduate Institute of Health Industry Technology, Chang Gung University of Science and Technology, Taoyuan, Taiwan
| | - Szu-Chuan Shen
- Graduate Program of Nutrition Science, National Taiwan Normal University, Taipei, Taiwan
- *Correspondence: Szu-Chuan Shen,
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Lydon EA, Nguyen LT, Shende SA, Chiang HS, Spence JS, Mudar RA. EEG theta and alpha oscillations in early versus late mild cognitive impairment during a semantic Go/NoGo task. Behav Brain Res 2022; 416:113539. [PMID: 34416304 DOI: 10.1016/j.bbr.2021.113539] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 11/02/2022]
Abstract
Amnestic mild cognitive impairment (aMCI) is marked by episodic memory deficits, which can be used to classify individuals into early MCI (EMCI) and late MCI (LMCI). Although mounting evidence suggests that individuals with aMCI have additional cognitive alterations including deficits in cognitive control, few have examined if EMCI and LMCI differ on processes other than episodic memory. Using a semantic Go/NoGo task, we examined differences in cognitive control between EMCI and LMCI on behavioral (accuracy and reaction time) and neural (scalp-recorded event-related oscillations in theta and alpha band) measures. Although no behavioral differences were observed between the EMCI and LMCI groups, differences in neural oscillations were observed. The LMCI group had higher theta synchronization on Go trials at central electrodes compared to the EMCI group. In addition, the EMCI group showed differences in theta power at central electrodes and alpha power at central and centro-parietal electrodes between Go and NoGo trials, while the LMCI group did not exhibit such differences. These findings suggest that while behavioral differences may not be observable, neural changes underlying cognitive control processes may differentiate EMCI and LMCI stages and may be useful to understand the trajectory of aMCI in future studies.
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Affiliation(s)
- Elizabeth A Lydon
- Department of Speech and Hearing Science, University of Illinois Urbana-Champaign, 901 South 6th Street, Champaign, IL, 61820, United States
| | - Lydia T Nguyen
- Neuroscience Program, University of Illinois Urbana-Champaign, 405 North Mathews Avenue, Urbana, IL, 61801, United States
| | - Shraddha A Shende
- Department of Speech and Hearing Science, University of Illinois Urbana-Champaign, 901 South 6th Street, Champaign, IL, 61820, United States
| | - Hsueh-Sheng Chiang
- Department of Neurology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, United States; School of Behavioral and Brain Sciences, The University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, United States
| | - Jeffrey S Spence
- Center for BrainHealth, The University of Texas at Dallas, 2200 West Mockingbird Ln, Dallas, TX, United States
| | - Raksha A Mudar
- Department of Speech and Hearing Science, University of Illinois Urbana-Champaign, 901 South 6th Street, Champaign, IL, 61820, United States; Neuroscience Program, University of Illinois Urbana-Champaign, 405 North Mathews Avenue, Urbana, IL, 61801, United States.
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Duara R, Barker W. Heterogeneity in Alzheimer's Disease Diagnosis and Progression Rates: Implications for Therapeutic Trials. Neurotherapeutics 2022; 19:8-25. [PMID: 35084721 PMCID: PMC9130395 DOI: 10.1007/s13311-022-01185-z] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/05/2022] [Indexed: 01/03/2023] Open
Abstract
The clinical presentation and the pathological processes underlying Alzheimer's disease (AD) can be very heterogeneous in severity, location, and composition including the amount and distribution of AB deposition and spread of neurofibrillary tangles in different brain regions resulting in atypical clinical patterns and the existence of distinct AD variants. Heterogeneity in AD may be related to demographic factors (such as age, sex, educational and socioeconomic level) and genetic factors, which influence underlying pathology, the cognitive and behavioral phenotype, rate of progression, the occurrence of neuropsychiatric features, and the presence of comorbidities (e.g., vascular disease, neuroinflammation). Heterogeneity is also manifest in the individual resilience to the development of neuropathology (brain reserve) and the ability to compensate for its cognitive and functional impact (cognitive and functional reserve). The variability in specific cognitive profiles and types of functional impairment may be associated with different progression rates, and standard measures assessing progression may not be equivalent for individual cognitive and functional profiles. Other factors, which may govern the presence, rate, and type of progression of AD, include the individuals' general medical health, the presence of specific systemic conditions, and lifestyle factors, including physical exercise, cognitive and social stimulation, amount of leisure activities, environmental stressors, such as toxins and pollution, and the effects of medications used to treat medical and behavioral conditions. These factors that affect progression are important to consider while designing a clinical trial to ensure, as far as possible, well-balanced treatment and control groups.
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Affiliation(s)
- Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
- Departments of Neurology, University of Florida College of Medicine, Gainesville, FL, USA
- Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
| | - Warren Barker
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA.
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Vogt NM, Hunt JFV, Adluru N, Ma Y, Van Hulle CA, Dean DC, Kecskemeti SR, Chin NA, Carlsson CM, Asthana S, Johnson SC, Kollmorgen G, Batrla R, Wild N, Buck K, Zetterberg H, Alexander AL, Blennow K, Bendlin BB. Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults. Alzheimers Dement 2022; 18:65-76. [PMID: 33984184 PMCID: PMC8589921 DOI: 10.1002/alz.12364] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 03/31/2021] [Accepted: 04/12/2021] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aβ)42 /Aβ40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS We observed a significant CSF Aβ42 /Aβ40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.
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Affiliation(s)
- Nicholas M. Vogt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Jack F. V. Hunt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Steven R. Kecskemeti
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | | | - Richard Batrla
- Roche Diagnostics International AG, Rotkreuz, Switzerland
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Andrew L. Alexander
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Vassilaki M, Crowson CS, Davis III JM, Duong SQ, Jones DT, Nguyen A, Mielke MM, Vemuri P, Myasoedova E. Rheumatoid Arthritis, Cognitive Impairment, and Neuroimaging Biomarkers: Results from the Mayo Clinic Study of Aging. J Alzheimers Dis 2022; 89:943-954. [PMID: 35964191 PMCID: PMC9535562 DOI: 10.3233/jad-220368] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/14/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Observational studies suggested that dementia risk in patients with rheumatoid arthritis (RA) is higher than in the general population. OBJECTIVE To examine the associations of RA with cognitive decline and dementia, and neuroimaging biomarkers of aging, Alzheimer's disease, and vascular pathology in adult participants in the Mayo Clinic Study of Aging (MCSA). METHODS Participants with RA were matched 1:3 on age, sex, education, and baseline cognitive diagnosis to participants without RA. RA cases with MRI were also matched with non-cases with available MRI. All available imaging studies (i.e., amyloid and FDG PET, sMRI, and FLAIR) were included. The study included 104 participants with RA and 312 without RA (mean age (standard deviation, SD) 75.0 (10.4) years, 33% male and average follow-up (SD) 4.2 (3.8) years). RESULTS Groups were similar in cognitive decline and risk of incident dementia. Among participants with neuroimaging, participants with RA (n = 33) and without RA (n = 98) had similar amyloid burden and neurodegeneration measures, including regions sensitive to aging and dementia, but greater mean white matter hyperintensity volume relative to the total intracranial volume (mean (SD)% : 1.12 (0.57)% versus 0.76 (0.69)% of TIV, p = 0.01), and had higher mean (SD) number of cortical infarctions (0.24 (0.44) versus 0.05 (0.33), p = 0.02). CONCLUSION Although cognitive decline and dementia risk were similar in participants with and without RA, participants with RA had more abnormal cerebrovascular pathology on neuroimaging. Future studies should examine the mechanisms underlying these changes and potential implications for prognostication and prevention of cognitive decline in RA.
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Affiliation(s)
- Maria Vassilaki
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Cynthia S. Crowson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Stephanie Q. Duong
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Aivi Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | - Elena Myasoedova
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Division of Rheumatology, Mayo Clinic, Rochester, MN, USA
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O’Bryant SE, Zhang F, Petersen M, Hall JR, Johnson LA, Yaffe K, Braskie M, Vig R, Toga AW, Rissman RA. Proteomic Profiles of Neurodegeneration Among Mexican Americans and Non-Hispanic Whites in the HABS-HD Study. J Alzheimers Dis 2022; 86:1243-1254. [PMID: 35180110 PMCID: PMC9376967 DOI: 10.3233/jad-210543] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND Hispanics are expected to experience the largest increase in Alzheimer's disease (AD) and AD related dementias over the next several decades. However, few studies have examined biomarkers of AD among Mexican Americans, the largest segment of the U.S. Hispanic population. OBJECTIVE We sought to examine proteomic profiles of an MRI-based marker of neurodegeneration from the AT(N) framework among a multi-ethnic, community-dwelling cohort. METHODS Community-dwelling Mexican Americans and non-Hispanic white adults and elders were recruited. All participants underwent comprehensive assessments including an interview, functional exam, clinical labs, informant interview, neuropsychological testing, and 3T MRI of the brain. A neurodegeneration MRI meta-ROI biomarker for the AT(N) framework was calculated. RESULTS Data was examined from n = 1,291 participants. Proteomic profiles were highly accurate for detecting neurodegeneration (i.e., N+) among both Mexican Americans (AUC = 1.0) and non-Hispanic whites (AUC = 0.98). The proteomic profile of N + was different between ethnic groups. Further analyses revealed that the proteomic profiles of N + varied by diagnostic status (control, MCI, dementia) and ethnicity (Mexican American versus non-Hispanic whites) though diagnostic accuracy was high for all classifications. CONCLUSION A proteomic profile of neurodegeneration has tremendous value and point towards novel diagnostic and intervention opportunities. The current findings demonstrate that the underlying biological factors associated with neurodegeneration are different between Mexican Americans versus non-Hispanic whites as well as at different levels of disease progression.
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Affiliation(s)
- Sid E. O’Bryant
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Fan Zhang
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Melissa Petersen
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - James R. Hall
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Leigh A. Johnson
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Kristine Yaffe
- Department of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Meredith Braskie
- Imaging Genetics Center, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Rocky Vig
- Imaging, Midtown Medical Imaging, Fort Worth, Texas, USA; Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Robert A. Rissman
- Department of Neurosciences, University of California, San Diego, La Jolla, CA and Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
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Jiang C, Wang Q, Xie S, Chen Z, Fu L, Peng Q, Liang Y, Guo H, Guo T. OUP accepted manuscript. Brain Commun 2022; 4:fcac084. [PMID: 35441134 PMCID: PMC9014538 DOI: 10.1093/braincomms/fcac084] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 12/21/2021] [Accepted: 03/29/2022] [Indexed: 11/14/2022] Open
Affiliation(s)
- Chenyang Jiang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Qingyong Wang
- Department of Neurology, University of Chinese Academy of Sciences-Shenzhen Hospital, Shenzhen 518107, China
| | - Siwei Xie
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Zhicheng Chen
- Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Liping Fu
- Department of Nuclear Medicine, China-Japan Friendship Hospital, 2 Yinghuayuan Dongjie, Beijing 100029, China
| | - Qiyu Peng
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
| | - Ying Liang
- Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - Hongbo Guo
- Department of Neurosurgery, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518132, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Correspondence to: Tengfei Guo, PhD Institute of Biomedical Engineering Shenzhen Bay Laboratory, No.5 Kelian Road Shenzhen 518132, China E-mail:
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O’Bryant SE, Petersen M, Hall J, Johnson LA, Barber R, Phillips N, Braskie MN, Yaffe K, Rissman R, Toga A. Characterization of Mild Cognitive Impairment and Dementia among Community-Dwelling Mexican Americans and Non-Hispanic Whites. J Alzheimers Dis 2022; 90:905-915. [PMID: 36189588 PMCID: PMC10117692 DOI: 10.3233/jad-220300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Despite tremendous advancements in the field, our understanding of mild cognitive impairment (MCI) and Alzheimer's disease (AD) among Mexican Americans remains limited. OBJECTIVE The aim of this study was to characterize MCI and dementia among Mexican Americans and non-Hispanic whites. METHODS Baseline data were analyzed from n = 1,705 (n = 890 Mexican American; n = 815 non-Hispanic white) participants enrolled in the Health and Aging Brain Study-Health Disparities (HABS-HD). RESULTS Among Mexican Americans, age (OR = 1.07), depression (OR = 1.09), and MRI-based neurodegeneration (OR = 0.01) were associated with dementia, but none of these factors were associated with MCI. Among non-Hispanic whites, male gender (OR = 0.33), neighborhood deprivation (OR = 1.34), depression (OR = 1.09), and MRI-based neurodegeneration (OR = 0.03) were associated with MCI, while depression (OR = 1.09) and APOEɛ4 genotype (OR = 4.38) were associated with dementia. CONCLUSION Findings from this study revealed that the demographic, clinical, sociocultural and biomarker characteristics of MCI and dementia are different among Mexican Americans as compared to non-Hispanic whites.
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Affiliation(s)
- Sid E. O’Bryant
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Melissa Petersen
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - James Hall
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Leigh A Johnson
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, Texas, USA
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Robert Barber
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Nicole Phillips
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, Texas, USA
| | - Meredith N. Braskie
- Imaging Genetics Center, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Kristine Yaffe
- Department of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Robert Rissman
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
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Clark AL, Haley AP, Duarte A, O’Bryant S. Fatty Acid-Binding Protein 3 Is a Marker of Neurodegeneration and White Matter Hyperintensity Burden in Mexican American Older Adults. J Alzheimers Dis 2022; 90:61-68. [PMID: 36093702 PMCID: PMC11234903 DOI: 10.3233/jad-220524] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We examined ethnoracial differences in fatty acid binding protein (FABP)-a family of intracellular lipid carriers-and clarified FABP3 associations with gray and white matter. Relative to Mexican Americans (MAs), FABP3 was higher in Non-Hispanic Whites (NHWS, p < 0.001). Regressions revealed, independent of traditional AD markers, FABP3 was associated with neurodegeneration (B = -0.08, p = 0.003) and WMH burden (B = 0.18, p = 0.03) in MAs, but not in NHWs (ps > 0.18). Findings suggest FABP3 is related to neural health within MAs and highlight its potential as a prognostic marker of brain health in ethnoracially diverse older adults.
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Affiliation(s)
- Alexandra L. Clark
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
| | - Andreanna P. Haley
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
| | - Audrey Duarte
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
| | - Sid O’Bryant
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
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Amyloid and tau PET-positive cognitively unimpaired individuals are at high risk for future cognitive decline. Nat Med 2022; 28:2381-2387. [PMID: 36357681 PMCID: PMC9671808 DOI: 10.1038/s41591-022-02049-x] [Citation(s) in RCA: 199] [Impact Index Per Article: 66.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 09/21/2022] [Indexed: 11/12/2022]
Abstract
A major unanswered question in the dementia field is whether cognitively unimpaired individuals who harbor both Alzheimer's disease neuropathological hallmarks (that is, amyloid-β plaques and tau neurofibrillary tangles) can preserve their cognition over time or are destined to decline. In this large multicenter amyloid and tau positron emission tomography (PET) study (n = 1,325), we examined the risk for future progression to mild cognitive impairment and the rate of cognitive decline over time among cognitively unimpaired individuals who were amyloid PET-positive (A+) and tau PET-positive (T+) in the medial temporal lobe (A+TMTL+) and/or in the temporal neocortex (A+TNEO-T+) and compared them with A+T- and A-T- groups. Cox proportional-hazards models showed a substantially increased risk for progression to mild cognitive impairment in the A+TNEO-T+ (hazard ratio (HR) = 19.2, 95% confidence interval (CI) = 10.9-33.7), A+TMTL+ (HR = 14.6, 95% CI = 8.1-26.4) and A+T- (HR = 2.4, 95% CI = 1.4-4.3) groups versus the A-T- (reference) group. Both A+TMTL+ (HR = 6.0, 95% CI = 3.4-10.6) and A+TNEO-T+ (HR = 7.9, 95% CI = 4.7-13.5) groups also showed faster clinical progression to mild cognitive impairment than the A+T- group. Linear mixed-effect models indicated that the A+TNEO-T+ (β = -0.056 ± 0.005, T = -11.55, P < 0.001), A+TMTL+ (β = -0.024 ± 0.005, T = -4.72, P < 0.001) and A+T- (β = -0.008 ± 0.002, T = -3.46, P < 0.001) groups showed significantly faster longitudinal global cognitive decline compared to the A-T- (reference) group (all P < 0.001). Both A+TNEO-T+ (P < 0.001) and A+TMTL+ (P = 0.002) groups also progressed faster than the A+T- group. In summary, evidence of advanced Alzheimer's disease pathological changes provided by a combination of abnormal amyloid and tau PET examinations is strongly associated with short-term (that is, 3-5 years) cognitive decline in cognitively unimpaired individuals and is therefore of high clinical relevance.
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136
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Teng E, Manser PT, Sanabria Bohorquez S, Wildsmith KR, Pickthorn K, Baker SL, Ward M, Kerchner GA, Weimer RM. Baseline [ 18F]GTP1 tau PET imaging is associated with subsequent cognitive decline in Alzheimer's disease. Alzheimers Res Ther 2021; 13:196. [PMID: 34852837 PMCID: PMC8638526 DOI: 10.1186/s13195-021-00937-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 11/16/2021] [Indexed: 12/14/2022]
Abstract
Background The role and implementation of tau PET imaging for predicting subsequent cognitive decline in Alzheimer’s disease (AD) remains uncertain. This study was designed to evaluate the relationship between baseline [18F]GTP1 tau PET and subsequent longitudinal change across multiple cognitive measures over 18 months. Methods Our analyses incorporated data from 67 participants, including cognitively normal controls (n = 10) and β-amyloid (Aβ)-positive individuals ([18F] florbetapir Aβ PET) with prodromal (n = 26), mild (n = 16), or moderate (n = 15) AD. Baseline measurements included cortical volume (MRI), tau burden ([18F]GTP1 tau PET), and cognitive assessments [Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR), 13-item version of the Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog13), and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)]. Cognitive assessments were repeated at 6-month intervals over an 18-month period. Associations between baseline [18F]GTP1 tau PET indices and longitudinal cognitive performance were assessed via univariate (Spearman correlations) and multivariate (linear mixed effects models) approaches. The utility of potential prognostic tau PET cut points was assessed with ROC curves. Results Univariate analyses indicated that greater baseline [18F]GTP1 tau PET signal was associated with faster rates of subsequent decline on the MMSE, CDR, and ADAS-Cog13 across regions of interest (ROIs). In multivariate analyses adjusted for baseline age, cognitive performance, cortical volume, and Aβ PET SUVR, the prognostic performance of [18F]GTP1 SUVR was most robust in the whole cortical gray ROI. When AD participants were dichotomized into low versus high tau subgroups based on baseline [18F]GTP1 PET standardized uptake value ratios (SUVR) in the temporal (cutoff = 1.325) or whole cortical gray (cutoff = 1.245) ROIs, high tau subgroups demonstrated significantly more decline on the MMSE, CDR, and ADAS-Cog13. Conclusions Our results suggest that [18F]GTP1 tau PET represents a prognostic biomarker in AD and are consistent with data from other tau PET tracers. Tau PET imaging may have utility for identifying AD patients at risk for more rapid cognitive decline and for stratification and/or enrichment of participant selection in AD clinical trials. Trial registration ClinicalTrials.gov NCT02640092. Registered on December 28, 2015 Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00937-x.
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Affiliation(s)
- Edmond Teng
- Early Clinical Development, Genentech, Inc., South San Francisco, CA, USA.
| | - Paul T Manser
- Clinical Biostatistics, Genentech, Inc., South San Francisco, CA, USA
| | | | | | - Karen Pickthorn
- Early Clinical Development, Genentech, Inc., South San Francisco, CA, USA
| | - Suzanne L Baker
- Clinical Imaging Group, Genentech, Inc., South San Francisco, CA, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Michael Ward
- Early Clinical Development, Genentech, Inc., South San Francisco, CA, USA.,Current Address: Alector, Inc., South San Francisco, CA, USA
| | - Geoffrey A Kerchner
- Early Clinical Development, Genentech, Inc., South San Francisco, CA, USA.,Current Address: F. Hoffmann-La Roche AG, Basel, Switzerland
| | - Robby M Weimer
- Biomedical Imaging, Genentech, Inc., South San Francisco, CA, USA
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Baker SL, Provost K, Thomas W, Whitman AJ, Janabi M, Schmidt ME, Timmers M, Kolb HC, Rabinovici GD, Jagust WJ. Evaluation of [ 18F]-JNJ-64326067-AAA tau PET tracer in humans. J Cereb Blood Flow Metab 2021; 41:3302-3313. [PMID: 34259071 PMCID: PMC8669274 DOI: 10.1177/0271678x211031035] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The [18F]-JNJ-64326067-AAA ([18F]-JNJ-067) tau tracer was evaluated in healthy older controls (HCs), mild cognitive impairment (MCI), Alzheimer's disease (AD), and progressive supranuclear palsy (PSP) participants. Seventeen subjects (4 HCs, 5 MCIs, 5 ADs, and 3 PSPs) received a [11C]-PIB amyloid PET scan, and a tau [18F]-JNJ-067 PET scan 0-90 minutes post-injection. Only MCIs and ADs were amyloid positive. The simplified reference tissue model, Logan graphical analysis distribution volume ratio, and SUVR were evaluated for quantification. The [18F]-JNJ-067 tau signal relative to the reference region continued to increase to 90 min, indicating the tracer had not reached steady state. There was no significant difference in any bilateral ROIs for MCIs or PSPs relative to HCs; AD participants showed elevated tracer relative to controls in most cortical ROIs (P < 0.05). Only AD participants showed elevated retention in the entorhinal cortex. There was off-target signal in the putamen, pallidum, thalamus, midbrain, superior cerebellar gray, and white matter. [18F]-JNJ-067 significantly correlated (p < 0.05) with Mini-Mental State Exam in entorhinal cortex and temporal meta regions. There is clear binding of [18F]-JNJ-067 in AD participants. Lack of binding in HCs, MCIs and PSPs suggests [18F]-JNJ-067 may not bind to low levels of AD-related tau or 4 R tau.
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Affiliation(s)
- Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Karine Provost
- Memory and Aging Center, Department of Neurology, University of California, Berkeley, CA, USA
| | - Wesley Thomas
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - A J Whitman
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Mustafa Janabi
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Mark E Schmidt
- Janssen Research and Development, A Division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Maarten Timmers
- Janssen Research and Development, A Division of Janssen Pharmaceutica NV, Beerse, Belgium
| | | | - Gil D Rabinovici
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Memory and Aging Center, Department of Neurology, University of California, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.,Department of Radiology and Biomedical Imaging, University of California, Berkeley, CA, USA
| | - William J Jagust
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
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138
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Plasma phosphorylated-tau181 as a predictive biomarker for Alzheimer's amyloid, tau and FDG PET status. Transl Psychiatry 2021; 11:585. [PMID: 34775468 PMCID: PMC8590691 DOI: 10.1038/s41398-021-01709-9] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/17/2021] [Accepted: 10/26/2021] [Indexed: 12/13/2022] Open
Abstract
Plasma phosphorylated-tau181 (p-tau181) showed the potential for Alzheimer's diagnosis and prognosis, but its role in detecting cerebral pathologies is unclear. We aimed to evaluate whether it could serve as a marker for Alzheimer's pathology in the brain. A total of 1189 participants with plasma p-tau181 and PET data of amyloid, tau or FDG PET were included from ADNI. Cross-sectional relationships of plasma p-tau181 with PET biomarkers were tested. Longitudinally, we further investigated whether different p-tau181 levels at baseline predicted different progression of Alzheimer's pathological changes in the brain. We found plasma p-tau181 significantly correlated with brain amyloid (Spearman ρ = 0.45, P < 0.0001), tau (0.25, P = 0.0003), and FDG PET uptakes (-0.37, P < 0.0001), and increased along the Alzheimer's continuum. Individually, plasma p-tau181 could detect abnormal amyloid, tau pathologies and hypometabolism in the brain, similar with or even better than clinical indicators. The diagnostic accuracy of plasma p-tau181 elevated significantly when combined with clinical information (AUC = 0.814 for amyloid PET, 0.773 for tau PET, and 0.708 for FDG PET). Relationships of plasma p-tau181 with brain pathologies were partly or entirely mediated by the corresponding CSF biomarkers. Besides, individuals with abnormal plasma p-tau181 level (>18.85 pg/ml) at baseline had a higher risk of pathological progression in brain amyloid (HR: 2.32, 95%CI 1.32-4.08) and FDG PET (3.21, 95%CI 2.06-5.01) status. Plasma p-tau181 may be a sensitive screening test for detecting brain pathologies, and serve as a predictive biomarker for Alzheimer's pathophysiology.
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139
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Brodtmann A, Werden E, Khlif MS, Bird LJ, Egorova N, Veldsman M, Pardoe H, Jackson G, Bradshaw J, Darby D, Cumming T, Churilov L, Donnan G. Neurodegeneration Over 3 Years Following Ischaemic Stroke: Findings From the Cognition and Neocortical Volume After Stroke Study. Front Neurol 2021; 12:754204. [PMID: 34744989 PMCID: PMC8570373 DOI: 10.3389/fneur.2021.754204] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 09/27/2021] [Indexed: 12/15/2022] Open
Abstract
Background: Stroke survivors are at high risk of dementia, associated with increasing age and vascular burden and with pre-existing cognitive impairment, older age. Brain atrophy patterns are recognised as signatures of neurodegenerative conditions, but the natural history of brain atrophy after stroke remains poorly described. We sought to determine whether stroke survivors who were cognitively normal at time of stroke had greater total brain (TBV) and hippocampal volume (HV) loss over 3 years than controls. We examined whether stroke survivors who were cognitively impaired (CI) at 3 months following their stroke had greater brain volume loss than cognitively normal (CN) stroke participants over the next 3 years. Methods: Cognition And Neocortical Volume After Stroke (CANVAS) study is a multi-centre cohort study of first-ever or recurrent adult ischaemic stroke participants compared to age- and sex-matched community controls. Participants were followed with MRI and cognitive assessments over 3 years and were free of a history of cognitive impairment or decline at inclusion. Our primary outcome measure was TBV change between 3 months and 3 years; secondary outcomes were TBV and HV change comparing CI and CN participants. We investigated associations between group status and brain volume change using a baseline-volume adjusted linear regression model with robust standard error. Results: Ninety-three stroke (26 women, 66.7 ± 12 years) and 39 control participants (15 women, 68.7 ± 7 years) were available at 3 years. TBV loss in stroke patients was greater than controls: stroke mean (M) = 20.3 cm3 ± SD 14.8 cm3; controls M = 14.2 cm3 ± SD 13.2 cm3; [adjusted mean difference 7.88 95%CI (2.84, 12.91) p-value = 0.002]. TBV decline was greater in those stroke participants who were cognitively impaired (M = 30.7 cm3; SD = 14.2 cm3) at 3 months (M = 19.6 cm3; SD = 13.8 cm3); [adjusted mean difference 10.42; 95%CI (3.04, 17.80), p-value = 0.006]. No statistically significant differences in HV change were observed. Conclusions: Ischaemic stroke survivors exhibit greater neurodegeneration compared to stroke-free controls. Brain atrophy is greater in stroke participants who were cognitively impaired early after their stroke. Early cognitive impairment was associated greater subsequent atrophy, reflecting the combined impacts of stroke and vascular brain burden. Atrophy rates could serve as a useful biomarker for trials testing interventions to reduce post-stroke secondary neurodegeneration. Clinical Trail Registration:http://www.clinicaltrials.gov, identifier: NCT02205424.
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Affiliation(s)
- Amy Brodtmann
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.,Melbourne Dementia Research Centre, Florey Institute and University of Melbourne, Parkville, VIC, Australia.,Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia
| | - Emilio Werden
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Mohamed Salah Khlif
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Laura J Bird
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Natalia Egorova
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.,Melbourne Dementia Research Centre, Florey Institute and University of Melbourne, Parkville, VIC, Australia.,Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Michele Veldsman
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.,Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Heath Pardoe
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
| | - Graeme Jackson
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.,Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia
| | - Jennifer Bradshaw
- Department of Clinical Neuropsychology, Austin Health, Heidelberg, VIC, Australia
| | - David Darby
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.,Melbourne Dementia Research Centre, Florey Institute and University of Melbourne, Parkville, VIC, Australia
| | - Toby Cumming
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Leonid Churilov
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.,Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia
| | - Geoffrey Donnan
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.,Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia
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Kumar A, Nemeroff CB, Cooper JJ, Widge A, Rodriguez C, Carpenter L, McDonald WM. Amyloid and Tau in Alzheimer's Disease: Biomarkers or Molecular Targets for Therapy? Are We Shooting the Messenger? Am J Psychiatry 2021; 178:1014-1025. [PMID: 34734743 DOI: 10.1176/appi.ajp.2021.19080873] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
Alzheimer's disease is a neuropsychiatric disorder with devastating clinical and socioeconomic consequences. Since the original description of the neuropathological correlates of the disorder, neuritic plaques and neurofibrillary tangles have been presumed to be critical to the underlying pathophysiology of the illness. The authors review the clinical and neuropathological origins of Alzheimer's disease and trace the evolution of modern biomarkers from their historical roots. They describe how technological innovations such as neuroimaging and biochemical assays have been used to measure and quantify key proteins and lipids in the brain, cerebrospinal fluid, and blood and advance their role as biomarkers of Alzheimer's disease. Together with genomics, these approaches have led to the development of a thematic and focused science in the area of degenerative disorders. The authors conclude by drawing distinctions between legitimate biomarkers of disease and molecular targets for therapeutic intervention and discuss future approaches to this complex neurobehavioral illness.
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Affiliation(s)
- Anand Kumar
- Department of Psychiatry, University of Illinois at Chicago (Kumar, Cooper); Department of Psychiatry and Behavioral Sciences, University of Texas Dell Medical School in Austin, and Mulva Clinic for the Neurosciences, UT Health Austin (Nemeroff); Department of Psychiatry, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif. (Rodriguez); Department of Psychiatry and Human Behavior, Warren Alpert Medical School at Brown University, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald)
| | - Charles B Nemeroff
- Department of Psychiatry, University of Illinois at Chicago (Kumar, Cooper); Department of Psychiatry and Behavioral Sciences, University of Texas Dell Medical School in Austin, and Mulva Clinic for the Neurosciences, UT Health Austin (Nemeroff); Department of Psychiatry, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif. (Rodriguez); Department of Psychiatry and Human Behavior, Warren Alpert Medical School at Brown University, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald)
| | - Joseph J Cooper
- Department of Psychiatry, University of Illinois at Chicago (Kumar, Cooper); Department of Psychiatry and Behavioral Sciences, University of Texas Dell Medical School in Austin, and Mulva Clinic for the Neurosciences, UT Health Austin (Nemeroff); Department of Psychiatry, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif. (Rodriguez); Department of Psychiatry and Human Behavior, Warren Alpert Medical School at Brown University, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald)
| | - Alik Widge
- Department of Psychiatry, University of Illinois at Chicago (Kumar, Cooper); Department of Psychiatry and Behavioral Sciences, University of Texas Dell Medical School in Austin, and Mulva Clinic for the Neurosciences, UT Health Austin (Nemeroff); Department of Psychiatry, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif. (Rodriguez); Department of Psychiatry and Human Behavior, Warren Alpert Medical School at Brown University, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald)
| | - Carolyn Rodriguez
- Department of Psychiatry, University of Illinois at Chicago (Kumar, Cooper); Department of Psychiatry and Behavioral Sciences, University of Texas Dell Medical School in Austin, and Mulva Clinic for the Neurosciences, UT Health Austin (Nemeroff); Department of Psychiatry, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif. (Rodriguez); Department of Psychiatry and Human Behavior, Warren Alpert Medical School at Brown University, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald)
| | - Linda Carpenter
- Department of Psychiatry, University of Illinois at Chicago (Kumar, Cooper); Department of Psychiatry and Behavioral Sciences, University of Texas Dell Medical School in Austin, and Mulva Clinic for the Neurosciences, UT Health Austin (Nemeroff); Department of Psychiatry, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif. (Rodriguez); Department of Psychiatry and Human Behavior, Warren Alpert Medical School at Brown University, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald)
| | - William M McDonald
- Department of Psychiatry, University of Illinois at Chicago (Kumar, Cooper); Department of Psychiatry and Behavioral Sciences, University of Texas Dell Medical School in Austin, and Mulva Clinic for the Neurosciences, UT Health Austin (Nemeroff); Department of Psychiatry, University of Minnesota, Minneapolis (Widge); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, Calif. (Rodriguez); Department of Psychiatry and Human Behavior, Warren Alpert Medical School at Brown University, Providence, R.I. (Carpenter); Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta (McDonald)
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141
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Yang J, Zhao X, Sui H, Liu X. High Prevalence and Low Awareness of Mild Cognitive Impairment in a Suburban Community in Shanghai. Neurol India 2021; 69:1693-1700. [PMID: 34979671 DOI: 10.4103/0028-3886.333524] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND The prevalence of mild cognitive impairment (MCI), herein China, was without involving the suburban communities, where the awareness of MCI still remains extremely weak. OBJECTIVE The objective of this study is to investigate the prevalence of MCI in the Chinese residents aged ≥65 in the suburban communities of Shanghai, China, and study the awareness of MCI in terms of its symptom, prevention, and intervention. METHODS A total of 925 suburban community residents aged ≥65 were evaluated with a series of clinical examinations and scale questionnaire, and 600 participated in a five-dimension questionnaire survey pertaining to the awareness of MCI. RESULTS The prevalence of MCI was up to 29.8% and of dementia was 11.1%, respectively. A difference was observed among the three groups of dementia, MCI, and normal in each dimension of age, gender, education, being widowed, and living with the next generation (P < 0.05). The degree of cognitive impairment was linearly correlated with age (P < 0.001). The prevalence of MCI was higher in the females (P < 0.001), in the group of low educational level (P < 0.001), in the widowed residents (P < 0.01), and in those who did not live with their next generations (P < 0.01). The family's concern for MCI symptoms in the elderly accounted for 60%; the awareness rate of MCI symptoms, 25.5%; the awareness rate of MCI prevention, 15.5%; and the rate of taking MCI seniors to the doctor, 32%. CONCLUSIONS The prevalence of MCI in the suburban communities of Shanghai was high but the awareness of MCI was low.
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Affiliation(s)
- Juan Yang
- Department of Neurology,Shanghai Tenth People's Hospital, School of Medicine, Tongji University; Department of Neurology, Shanghai Pudong New Area People's Hospital, Shanghai, 201299, China
| | - Xiaohui Zhao
- Department of Neurology, Shanghai Pudong New Area People's Hospital, Shanghai, 201299, China
| | - Haijing Sui
- Department of Image, Shanghai Pudong New Area People's Hospital, Shanghai, 201299, China
| | - Xueyuan Liu
- Department of Neurology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
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142
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Ezzati A, Abdulkadir A, Jack CR, Thompson PM, Harvey DJ, Truelove-Hill M, Sreepada LP, Davatzikos C, Lipton RB. Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia. Alzheimers Dement 2021; 17:1855-1867. [PMID: 34870371 PMCID: PMC8842842 DOI: 10.1002/alz.12491] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 07/15/2021] [Accepted: 09/07/2021] [Indexed: 01/18/2023]
Abstract
We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 415) we assessed predictive performance of ATN classification using empirical knowledge-based cut-offs for each component of ATN and compared it to two data-driven approaches, logistic regression and RUSBoost machine learning classifiers, which used continuous clinical or biomarker scores. In data-driven approaches, we identified ATN features that distinguish normals from individuals with dementia and used them to classify persons with MCI into dementia-like and normal groups. Both data-driven classification methods performed better than the empirical cut-offs for ATN biomarkers in predicting conversion to dementia. Classifiers that used clinical features performed as well as classifiers that used ATN biomarkers for prediction of progression to dementia. We discuss that data-driven modeling approaches can improve our ability to predict disease progression and might have implications in future clinical trials.
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Affiliation(s)
- Ali Ezzati
- Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical center, Bronx, New York, USA
| | - Ahmed Abdulkadir
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Danielle J. Harvey
- Department of Public Health Sciences, University of California-Davis, Davis, California, USA
| | - Monica Truelove-Hill
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lasya P. Sreepada
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Richard B. Lipton
- Department of Neurology, Albert Einstein College of Medicine and Montefiore Medical center, Bronx, New York, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
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143
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Guo T, Landau SM, Jagust WJ. Age, vascular disease, and Alzheimer's disease pathologies in amyloid negative elderly adults. ALZHEIMERS RESEARCH & THERAPY 2021; 13:174. [PMID: 34654465 PMCID: PMC8520216 DOI: 10.1186/s13195-021-00913-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 10/03/2021] [Indexed: 02/04/2023]
Abstract
Background We recently reported that CSF phosphorylated tau (p-Tau181) relative to Aβ40 (CSF p-Tau/Aβ40 ratio) was less noisy and increased associations with Alzheimer’s disease (AD) biomarkers compared to CSF p-Tau181 alone. While elevations of CSF p-Tau/Aβ40 can occur in amyloid-β (Aβ) negative (Aβ-) individuals, the factors associated with these elevations and their role in neurodegeneration and cognitive decline are unknown. We aim to explore factors associated with elevated tau in CSF, and how these elevated tau are related to neurodegeneration and cognitive decline in the absence of Aβ positivity. Methods We examined relationships between CSF p-Tau/Aβ40, and CSF Aβ42/Aβ40, Aβ PET, and white matter hyperintensities (WMH) as well as vascular risk factors in 149 cognitively unimpaired and 52 impaired individuals who were presumably not on the Alzheimer’s disease (AD) pathway due to negative Aβ status on both CSF and PET. Subgroups had 18F-fluorodeoxyglucose (FDG) PET and adjusted hippocampal volume (aHCV), and longitudinal measures of CSF, aHCV, FDG PET, and cognition data, so we examined CSF p-Tau/Aβ40 associations with these measures as well. Results Elevated CSF p-Tau/Aβ40 was associated with older age, male sex, greater WMH, and hypertension as well as a pattern of hippocampal atrophy and temporoparietal hypometabolism characteristic of AD. Lower CSF Aβ42/Aβ40, higher WMH, and hypertension but not age, sex, Aβ PET, APOE-ε4 status, body mass index, smoking, and hyperlipidemia at baseline predicted CSF p-Tau/Aβ40 increases over approximately 5 years of follow-up. The relationship between CSF p-Tau/Aβ40 and subsequent cognitive decline was partially or fully explained by neurodegenerative measurements. Conclusions These data provide surprising clues as to the etiology and significance of tau pathology in the absence of Aβ. It seems likely that, in addition to age, both cerebrovascular disease and subthreshold levels of Aβ are related to this tau accumulation. Crucially, this phenotype of CSF tau elevation in amyloid-negative individuals share features with AD such as a pattern of metabolic decline and regional brain atrophy. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00913-5.
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Affiliation(s)
- Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, 94720, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
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Barker W, Quinonez C, Greig MT, Behar R, Chirinos C, Rodriguez RA, Rosselli M, Rodriguez MJ, Cid RC, Rundek T, McFarland K, Hanson K, Smith G, DeKosky S, Vaillancourt D, Adjouadi M, Marsiske M, Ertekin-Taner N, Golde T, Loewenstein DA, Duara R. Utility of Plasma Neurofilament Light in the 1Florida Alzheimer's Disease Research Center (ADRC). J Alzheimers Dis 2021; 79:59-70. [PMID: 33216030 PMCID: PMC7902971 DOI: 10.3233/jad-200901] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background: Plasma NfL (pNfL) levels are elevated in many neurological disorders. However, the utility of pNfL in a clinical setting has not been established. Objective: In a cohort of diverse older participants, we examined: 1) the association of pNfL to age, sex, Hispanic ethnicity, diagnosis, and structural and amyloid imaging biomarkers; and 2) its association to baseline and longitudinal cognitive and functional performance. Methods: 309 subjects were classified at baseline as cognitively normal (CN) or with cognitive impairment. Most subjects had structural MRI and amyloid PET scans. The most frequent etiological diagnosis was Alzheimer’s disease (AD), but other neurological and neuropsychiatric disorders were also represented. We assessed the relationship of pNfL to cognitive and functional status, primary etiology, imaging biomarkers, and to cognitive and functional decline. Results: pNfL increased with age, degree of hippocampal atrophy, and amyloid load, and was higher in females among CN subjects, but was not associated with Hispanic ethnicity. Compared to CN subjects, pNfL was elevated among those with AD or FTLD, but not those with neuropsychiatric or other disorders. Hippocampal atrophy, amyloid positivity and higher pNfL levels each added unique variance in predicting greater functional impairment on the CDR-SB at baseline. Higher baseline pNfL levels also predicted greater cognitive and functional decline after accounting for hippocampal atrophy and memory scores at baseline. Conclusion: pNfL may have a complementary and supportive role to brain imaging and cognitive testing in a memory disorder evaluation, although its diagnostic sensitivity and specificity as a stand-alone measure is modest. In the absence of expensive neuroimaging tests, pNfL could be used for differentiating neurodegenerative disease from neuropsychiatric disorders.
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Affiliation(s)
- Warren Barker
- Wien Center for Alzheimer's Disease and Memory Disorder, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Carlos Quinonez
- Wien Center for Alzheimer's Disease and Memory Disorder, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Maria T Greig
- Wien Center for Alzheimer's Disease and Memory Disorder, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Raquel Behar
- Wien Center for Alzheimer's Disease and Memory Disorder, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Cesar Chirinos
- Wien Center for Alzheimer's Disease and Memory Disorder, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Rosemarie A Rodriguez
- Wien Center for Alzheimer's Disease and Memory Disorder, Mount Sinai Medical Center, Miami Beach, FL, USA
| | - Monica Rosselli
- Florida Atlantic University, Department of Psychology, Charles E. Schmidt College of Science, Davie, FL, USA
| | | | - Rosie Curiel Cid
- Department of Psychiatry and Behavioral Sciences and Neurology, Miller School of Medicine, University of Miami, FL, USA
| | - Tatjana Rundek
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | | | - Kevin Hanson
- Florida ADRC, University of Florida, Gainesville, FL, USA
| | - Glenn Smith
- Florida ADRC, University of Florida, Gainesville, FL, USA
| | - Steven DeKosky
- Florida ADRC, University of Florida, Gainesville, FL, USA
| | | | - Malek Adjouadi
- College of Engineering and Computing, Florida International University, Miami, Florida, USA
| | | | - Nilufer Ertekin-Taner
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL, USA.,Mayo Clinic Florida, Department of Neurology, Jacksonville, FL, USA
| | - Todd Golde
- Florida ADRC, University of Florida, Gainesville, FL, USA
| | - David A Loewenstein
- Department of Psychiatry and Behavioral Sciences and Neurology, Miller School of Medicine, University of Miami, FL, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorder, Mount Sinai Medical Center, Miami Beach, FL, USA
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145
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Ebenau JL, van der Lee SJ, Hulsman M, Tesi N, Jansen IE, Verberk IM, van Leeuwenstijn M, Teunissen CE, Barkhof F, Prins ND, Scheltens P, Holstege H, van Berckel BN, van der Flier WM. Risk of dementia in APOE ε4 carriers is mitigated by a polygenic risk score. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12229. [PMID: 34541285 PMCID: PMC8438688 DOI: 10.1002/dad2.12229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/09/2021] [Accepted: 06/28/2021] [Indexed: 12/22/2022]
Abstract
INTRODUCTION We investigated relationships among genetic determinants of Alzheimer's disease (AD), amyloid/tau/neurodegenaration (ATN) biomarkers, and risk of dementia. METHODS We studied cognitively normal individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort and SCIENCe project. We examined associations between genetic variants and ATN biomarkers, and evaluated their predictive value for incident dementia. A polygenic risk score (PRS) was calculated based on 39 genetic variants. The APOE gene was not included in the PRS and was analyzed separately. RESULTS The PRS and APOE ε4 were associated with amyloid-positive ATN profiles, and APOE ε4 additionally with isolated increased tau (A-T+N-). A high PRS and APOE ε4 separately predicted AD dementia. Combined, a high PRS increased while a low PRS attenuated the risk associated with ε4 carriers. DISCUSSION Genetic variants beyond APOE are clinically relevant and contribute to the pathophysiology of AD. In the future, a PRS might be used in individualized risk profiling.
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Affiliation(s)
- Jarith L. Ebenau
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Sven J. van der Lee
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
| | - Marc Hulsman
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Niccolò Tesi
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Iris E. Jansen
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Complex Trait GeneticsCenter for Neurogenomics and Cognitive ResearchAmsterdam NeuroscienceVU UniversityAmsterdamthe Netherlands
| | - Inge M.W. Verberk
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Mardou van Leeuwenstijn
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Niels D. Prins
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Philip Scheltens
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Henne Holstege
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Bart N.M. van Berckel
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Epidemiology and BiostatisticsAmsterdam UMCAmsterdamthe Netherlands
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146
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Dartora CM, Borelli WV, Koole M, Marques da Silva AM. Cognitive Decline Assessment: A Review From Medical Imaging Perspective. Front Aging Neurosci 2021; 13:704661. [PMID: 34489675 PMCID: PMC8416532 DOI: 10.3389/fnagi.2021.704661] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/19/2021] [Indexed: 11/13/2022] Open
Abstract
Aging is a complex process that involves changes at both molecular and morphological levels. However, our understanding of how aging affects brain anatomy and function is still poor. In addition, numerous biomarkers and imaging markers, usually associated with neurodegenerative diseases such as Alzheimer's disease (AD), have been clinically used to study cognitive decline. However, the path of cognitive decline from healthy aging to a mild cognitive impairment (MCI) stage has been studied only marginally. This review presents aspects of cognitive decline assessment based on the imaging differences between individuals cognitively unimpaired and in the decline spectrum. Furthermore, we discuss the relationship between imaging markers and the change in their patterns with aging by using neuropsychological tests. Our goal is to delineate how aging has been studied by using medical imaging tools and further explore the aging brain and cognitive decline. We find no consensus among the biomarkers to assess the cognitive decline and its relationship with the cognitive decline trajectory. Brain glucose hypometabolism was found to be directly related to aging and indirectly to cognitive decline. We still need to understand how to quantify an expected hypometabolism during cognitive decline during aging. The Aβ burden should be longitudinally studied to achieve a better consensus on its association with changes in the brain and cognition decline with aging. There exists a lack of standardization of imaging markers that highlight the need for their further improvement. In conclusion, we argue that there is a lot to investigate and understand cognitive decline better and seek a window for a suitable and effective treatment strategy.
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Affiliation(s)
- Caroline Machado Dartora
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil
| | - Wyllians Vendramini Borelli
- Neurology Department, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Brain Institute of Rio Grande do Sul, BraIns, Porto Alegre, Brazil
| | - Michel Koole
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Ana Maria Marques da Silva
- School of Medicine, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil.,Brain Institute of Rio Grande do Sul, BraIns, Porto Alegre, Brazil.,Medical Image Computing Laboratory, School of Technology, Pontifical Catholic University of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil
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147
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Huang W, Li X, Li H, Wang W, Chen K, Xu K, Zhang J, Chen Y, Wei D, Shu N, Zhang Z. Accelerated Brain Aging in Amnestic Mild Cognitive Impairment: Relationships with Individual Cognitive Decline, Risk Factors for Alzheimer Disease, and Clinical Progression. Radiol Artif Intell 2021; 3:e200171. [PMID: 34617021 PMCID: PMC8489444 DOI: 10.1148/ryai.2021200171] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Revised: 05/06/2021] [Accepted: 06/07/2021] [Indexed: 06/13/2023]
Abstract
PURPOSE To determine whether a brain age prediction model could quantify individual deviations from a healthy brain-aging trajectory (predicted age difference [PAD]) in patients with amnestic mild cognitive impairment (aMCI) and to determine if PAD was associated with individual cognitive impairment. MATERIALS AND METHODS In this retrospective study, a machine learning approach was trained to determine brain age based on T1-weighted MRI scans. Two datasets were used for model training and testing-the Beijing Aging Brain Rejuvenation Initiative (BABRI) (616 healthy controls and 80 patients with aMCI, 2010-2018) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (589 healthy controls and 144 patients with aMCI, 2010-2018). A total of 974 healthy controls were used for model training (490 from BABRI and 484 from ADNI; age range, 49-95 years). The trained model was then tested on both healthy controls (126 from BABRI and 105 from ADNI) and patients with aMCI (80 from BABRI and 144 from ADNI) to estimate PAD (predicted age - actual age). Furthermore, the associations between PAD with cognitive impairment, genetic risk factors and pathologic markers of Alzheimer disease (AD), and clinical progression in patients with aMCI were examined using a partial correlation analysis, a two-way analysis of covariance, and a general linear model, respectively. RESULTS Based on the prediction model, patients with aMCI were found to have higher PADs than those of healthy controls (BABRI: 2.65 ± 4.91 [standard deviation] vs 0.18 ± 4.79 [P < .001]; ADNI: 1.68 ± 5.28 vs 0.05 ± 4.41 [P < .001]). Moreover, the PAD was significantly associated with individual cognitive impairment in several cognitive domains in patients with aMCI (P < .05, corrected). When considering different AD-related risk factors, apolipoprotein E ε4 allele carriers were observed to have higher PADs than noncarriers (3.76 ± 4.82 vs 0.10 ± 5.05; P = .017), and patients with amyloid-positive aMCI were observed to have higher PADs than patients with amyloid-negative status (2.40 ± 5.25 vs 0.93 ± 5.20; P = .003). Finally, PAD combined with other markers of AD at baseline for differentiating between progressive and stable aMCI resulted in an area under the curve value of 0.87. CONCLUSION The PAD is a sensitive imaging marker related to individual cognitive differences in patients with aMCI.Keywords: MR Imaging, Brain/Brain Stem, Brain Age, Machine Learning, Mild Cognitive Impairment, Structural MRI Supplemental material is available for this article. © RSNA, 2021.
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Developing the ATX(N) classification for use across the Alzheimer disease continuum. Nat Rev Neurol 2021; 17:580-589. [PMID: 34239130 DOI: 10.1038/s41582-021-00520-w] [Citation(s) in RCA: 190] [Impact Index Per Article: 47.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/28/2021] [Indexed: 02/06/2023]
Abstract
Breakthroughs in the development of highly accurate fluid and neuroimaging biomarkers have catalysed the conceptual transformation of Alzheimer disease (AD) from the traditional clinical symptom-based definition to a clinical-biological construct along a temporal continuum. The AT(N) system is a symptom-agnostic classification scheme that categorizes individuals using biomarkers that chart core AD pathophysiological features, namely the amyloid-β (Aβ) pathway (A), tau-mediated pathophysiology (T) and neurodegeneration (N). This biomarker matrix is now expanding towards an ATX(N) system, where X represents novel candidate biomarkers for additional pathophysiological mechanisms such as neuroimmune dysregulation, synaptic dysfunction and blood-brain barrier alterations. In this Perspective, we describe the conceptual framework and clinical importance of the existing AT(N) system and the evolving ATX(N) system. We provide a state-of-the-art summary of the potential contexts of use of these systems in AD clinical trials and future clinical practice. We also discuss current challenges related to the validation, standardization and qualification process and provide an outlook on the real-world application of the AT(N) system.
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Bontempi P, Podda R, Daducci A, Sonato N, Fattoretti P, Fiorini S, Tambalo S, Mosconi E, Merigo F, Balietti M, Marzola P. MRI characterization of rat brain aging at structural and functional level: Clues for translational applications. Exp Gerontol 2021; 152:111432. [DOI: 10.1016/j.exger.2021.111432] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/10/2021] [Accepted: 05/27/2021] [Indexed: 12/18/2022]
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Lim YY, Ayton D, Perin S, Lavale A, Yassi N, Buckley R, Barton C, Bruns L, Morello R, Pirotta S, Rosenich E, Rajaratnam SMW, Sinnott R, Brodtmann A, Bush AI, Maruff P, Churilov L, Barker A, Pase MP. An Online, Person-Centered, Risk Factor Management Program to Prevent Cognitive Decline: Protocol for A Prospective Behavior-Modification Blinded Endpoint Randomized Controlled Trial. J Alzheimers Dis 2021; 83:1603-1622. [PMID: 34420970 DOI: 10.3233/jad-210589] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Several modifiable risk factors for dementia have been identified, although the extent to which their modification leads to improved cognitive outcomes remains unclear. OBJECTIVE The primary aim is to test the hypothesis that a behavior modification intervention program targeting personalized risk factors prevents cognitive decline in community-dwelling, middle-aged adults with a family history of dementia. METHODS This is a prospective, risk factor management, blinded endpoint, randomized, controlled trial, where 1510 cognitively normal, community-dwelling adults aged 40-70 years old will be recruited. Participants will be screened for risk factors related to vascular health (including physical inactivity), mental health, sleep, and cognitive/social engagement. The intervention is an online person-centered risk factor management program: BetterBrains. Participants randomized to intervention will receive telehealth-based person-centered goal setting, motivational interviewing, and follow-up support, health care provider communication and community linkage for management of known modifiable risk factors of dementia. Psychoeducational health information will be provided to both control and intervention groups. RESULTS The primary outcome is favorable cognitive performance at 24-months post-baseline, defined as the absence of decline on one or more of the following cognitive tests: (a) Cogstate Detection, (b) Cogstate One Card Learning, (c) Cogstate One Back, and (d) Cognitive Function Instrument total score. CONCLUSION We will test the hypothesis that the BetterBrains intervention program can prevent cognitive decline. By leveraging existing community services and using a risk factor management pathway that tailors the intervention to each participant, we maximize likelihood for engagement, long-term adherence, and for preserving cognitive function in at-risk individuals.
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Affiliation(s)
- Yen Ying Lim
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Darshini Ayton
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Stephanie Perin
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Alexandra Lavale
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Nawaf Yassi
- Department of Medicine and Neurology, Melbourne Brain Centre at The Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.,Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Rachel Buckley
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia.,Melbourne School of Psychological Sciences, University of Melbourne, Parkville, VIC 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
| | - Christopher Barton
- Department of General Practice, School of Primary and Allied Health Care, Monash University, Clayton, VIC, Australia
| | - Loren Bruns
- School of Computing and Information Systems, University of Melbourne, Parkville, VIC, Australia
| | - Renata Morello
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Stephanie Pirotta
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Emily Rosenich
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Shantha M W Rajaratnam
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Richard Sinnott
- School of Computing and Information Systems, University of Melbourne, Parkville, VIC, Australia
| | - Amy Brodtmann
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Ashley I Bush
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia.,Cogstate Ltd., Melbourne, VIC, Australia
| | - Leonid Churilov
- Melbourne Medical School, University of Melbourne, Parkville, VIC, Australia
| | - Anna Barker
- Health and Social Care Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia.,Harvard T.H. Chan School of Public Health, Boston, MA, USA
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