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Jiménez-Balado J, Habeck C, Stern Y, Eich T. The relationship between cortical thickness and white matter hyperintensities in mid to late life. Neurobiol Aging 2024; 141:129-139. [PMID: 38909430 DOI: 10.1016/j.neurobiolaging.2024.05.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 06/25/2024]
Abstract
White matter hyperintensities (WMH) are associated with cortical thinning. Although they are primarily detected in older participants, these lesions can appear in younger and midlife individuals. Here, we tested whether WMH are associated with cortical thinning in relatively younger (26-50 years) and relatively older (58-84) participants who were free of dementia, and how these associations are moderated by WMH localization. WMH were automatically quantified and categorized according to the localization of three classes of white matter tracts: association, commissural and projection fibers. Mediation analyses were used to infer whether differences in cortical thickness between younger and older participants were explained by WMH. Our results revealed that total WMH explained between 20.6 % and 65.5 % of the effect of age on cortical thickness in AD-signature regions including the lateral temporal lobes and supramarginal gyrus, among others. This mediation was slightly stronger for projection WMH, although it was still significant for association and commissural WMH. These results suggest that there is an interplay between vascular and AD causes of cognitive impairment that starts at younger ages.
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Affiliation(s)
- Joan Jiménez-Balado
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA USA; Neurovascular Research Group, IMIM-Hospital del Mar Medical Research Institute, Carrer del Dr. Aiguader, 88, Barcelona 08003, Spain
| | - Christian Habeck
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Yaakov Stern
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Teal Eich
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
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Zhao F, Yang H, Gao Z, Liu H, Wu P, Li B, Yu H, Shao J. Novel fabrication of Cu(II)-incorporated chiral d-penicillamine-chitosan nanocomposites enantio-selectively inhibit the induced amyloid β aggregation for Alzheimer's disease therapy. Heliyon 2024; 10:e23563. [PMID: 38223723 PMCID: PMC10784170 DOI: 10.1016/j.heliyon.2023.e23563] [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: 05/04/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 01/16/2024] Open
Abstract
It is well known that the chiral materials combined with metal ion's structure have been identified as promising candidate for the nursing Alzheimer Disease (AD) treatment, particularly to inhibit amyloid (Aβ) due to their significant pharmacological effect on the living bodies. In the present study, Cu(II)/Chitosan nanocomposite caped with chiral penicillamine (Cu@D-PEN/Chitosan) have been synthesized and used as an effective amyloid-β (Aβ) inhibitor. The composite formations of the samples were confirmed from the FTIR and XRD, studies. FE-SEM, TEM and AFM studies have been carried out to depict the morphological analysis of the nanocomposites. The prepared samples have also been subjected to various in vitro studies such as encapsulation efficiency, drug loading capacity, drug release and biodegrading or compatibility of the nanocomposites to support the Aβ aggregation inhibiting ability investigations. It was observed that the increase in the concentration of the Cu@D-PEN/Chitosan enhancing the Aβ inhibiting ability. Thus, the Cu(II)@D-PEN/Chitosan showed improving memory effect suggesting that Cu(II)@D-PEN/Chitosan nanocomposites may be a potential candidate for inhibiting the Aβ aggregation in nursing AD treatment.
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Affiliation(s)
- Feng Zhao
- Department of Neurology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing 210012, China
| | - Hui Yang
- School of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Zehong Gao
- Department of Neurology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing 210012, China
| | - Huamei Liu
- School of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Pingling Wu
- School of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Binbin Li
- School of Nursing, Nanjing University of Chinese Medicine, Nanjing 210023, China
| | - Heming Yu
- Department of Neurology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing 210012, China
| | - Jiahui Shao
- Department of Neurology, Wenling First People's Hospital Affiliated to Wenzhou Medical University, Wenling 317500, China
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Veitch DP, Weiner MW, Miller M, Aisen PS, Ashford MA, Beckett LA, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Nho KT, Nosheny R, Okonkwo O, Perrin RJ, Petersen RC, Rivera Mindt M, Saykin A, Shaw LM, Toga AW, Tosun D. The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022. Alzheimers Dement 2024; 20:652-694. [PMID: 37698424 PMCID: PMC10841343 DOI: 10.1002/alz.13449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 09/13/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Melanie Miller
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Miriam A. Ashford
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Laurel A. Beckett
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | - Robert C. Green
- Division of GeneticsDepartment of MedicineBrigham and Women's HospitalBroad Institute Ariadne Labs and Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | - Kwangsik T. Nho
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Center for Computational Biology and BioinformaticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Rachel Nosheny
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | - Monica Rivera Mindt
- Department of PsychologyLatin American and Latino Studies InstituteAfrican and African American StudiesFordham UniversityNew YorkNew YorkUSA
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Andrew Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine and the PENN Alzheimer's Disease Research CenterCenter for Neurodegenerative ResearchPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro ImagingInstitute of Neuroimaging and InformaticsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
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Parent O, Bussy A, Devenyi GA, Dai A, Costantino M, Tullo S, Salaciak A, Bedford S, Farzin S, Béland ML, Valiquette V, Villeneuve S, Poirier J, Tardif CL, Dadar M, Chakravarty MM. Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging. Brain Commun 2023; 5:fcad279. [PMID: 37953840 PMCID: PMC10636521 DOI: 10.1093/braincomms/fcad279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/05/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
White matter hyperintensities are radiological abnormalities reflecting cerebrovascular dysfunction detectable using MRI. White matter hyperintensities are often present in individuals at the later stages of the lifespan and in prodromal stages in the Alzheimer's disease spectrum. Tissue alterations underlying white matter hyperintensities may include demyelination, inflammation and oedema, but these are highly variable by neuroanatomical location and between individuals. There is a crucial need to characterize these white matter hyperintensity tissue alterations in vivo to improve prognosis and, potentially, treatment outcomes. How different MRI measure(s) of tissue microstructure capture clinically-relevant white matter hyperintensity tissue damage is currently unknown. Here, we compared six MRI signal measures sampled within white matter hyperintensities and their associations with multiple clinically-relevant outcomes, consisting of global and cortical brain morphometry, cognitive function, diagnostic and demographic differences and cardiovascular risk factors. We used cross-sectional data from 118 participants: healthy controls (n = 30), individuals at high risk for Alzheimer's disease due to familial history (n = 47), mild cognitive impairment (n = 32) and clinical Alzheimer's disease dementia (n = 9). We sampled the median signal within white matter hyperintensities on weighted MRI images [T1-weighted (T1w), T2-weighted (T2w), T1w/T2w ratio, fluid-attenuated inversion recovery (FLAIR)] as well as the relaxation times from quantitative T1 (qT1) and T2* (qT2*) images. qT2* and fluid-attenuated inversion recovery signals within white matter hyperintensities displayed different age- and disease-related trends compared to normal-appearing white matter signals, suggesting sensitivity to white matter hyperintensity-specific tissue deterioration. Further, white matter hyperintensity qT2*, particularly in periventricular and occipital white matter regions, was consistently associated with all types of clinically-relevant outcomes in both univariate and multivariate analyses and across two parcellation schemes. qT1 and fluid-attenuated inversion recovery measures showed consistent clinical relationships in multivariate but not univariate analyses, while T1w, T2w and T1w/T2w ratio measures were not consistently associated with clinical variables. We observed that the qT2* signal was sensitive to clinically-relevant microstructural tissue alterations specific to white matter hyperintensities. Our results suggest that combining volumetric and signal measures of white matter hyperintensity should be considered to fully characterize the severity of white matter hyperintensities in vivo. These findings may have implications in determining the reversibility of white matter hyperintensities and the potential efficacy of cardio- and cerebrovascular treatments.
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Affiliation(s)
- Olivier Parent
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Aurélie Bussy
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Gabriel Allan Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Dai
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Manuela Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Stephanie Tullo
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Alyssa Salaciak
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Saashi Bedford
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sarah Farzin
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Marie-Lise Béland
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
| | - Vanessa Valiquette
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Sylvia Villeneuve
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
| | - Judes Poirier
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Center for the Studies in the Prevention of Alzheimer's Disease, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Molecular Neurobiology Unit, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Department of Medicine, McGill University, Montreal, Quebec H4A 3J1, Canada
| | - Christine Lucas Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Quebec H3A 2B4, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec H3A 1A1, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec H3A 2B4, Canada
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