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Bao Y, Chen X, Li Y, Yuan S, Han L, Deng X, Ran J. Chronic Low-Grade Inflammation and Brain Structure in the Middle-Aged and Elderly Adults. Nutrients 2024; 16:2313. [PMID: 39064755 PMCID: PMC11280392 DOI: 10.3390/nu16142313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 07/10/2024] [Accepted: 07/11/2024] [Indexed: 07/28/2024] Open
Abstract
Low-grade inflammation (LGI) mainly acted as the mediator of the association of obesity and inflammatory diet with numerous chronic diseases, including neuropsychiatric diseases. However, the evidence about the effect of LGI on brain structure is limited but important, especially in the context of accelerating aging. This study was then designed to close the gap, and we leveraged a total of 37,699 participants from the UK Biobank and utilized inflammation score (INFLA-score) to measure LGI. We built the longitudinal relationships of INFLA-score with brain imaging phenotypes using multiple linear regression models. We further analyzed the interactive effects of specific covariates. The results showed high level inflammation reduced the volumes of the subcortex and cortex, especially the globus pallidus (β [95% confidence interval] = -0.062 [-0.083, -0.041]), thalamus (-0.053 [-0.073, -0.033]), insula (-0.052 [-0.072, -0.032]), superior temporal gyrus (-0.049 [-0.069, -0.028]), lateral orbitofrontal cortex (-0.047 [-0.068, -0.027]), and others. Most significant effects were observed among urban residents. Furthermore, males and individuals with physical frailty were susceptive to the associations. The study provided potential insights into pathological changes during disease progression and might aid in the development of preventive and control targets in an age-friendly city to promote great health and well-being for sustainable development goals.
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Affiliation(s)
- Yujia Bao
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.B.); (X.C.); (Y.L.); (S.Y.)
| | - Xixi Chen
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.B.); (X.C.); (Y.L.); (S.Y.)
| | - Yongxuan Li
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.B.); (X.C.); (Y.L.); (S.Y.)
| | - Shenghao Yuan
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.B.); (X.C.); (Y.L.); (S.Y.)
| | - Lefei Han
- School of Global Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China;
| | - Xiaobei Deng
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.B.); (X.C.); (Y.L.); (S.Y.)
| | - Jinjun Ran
- School of Public Health, University of Hong Kong, Hong Kong SAR, China
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Li K, Wang S, Luo X, Zeng Q, Liu X, Hong L, Li J, Hong H, Xu X, Zhang Y, Jiaerken Y, Zhang R, Xie L, Xu S, Zhang X, Chen Y, Liu Z, Zhang M, Huang P. Associations of Alzheimer's Disease Pathology and Small Vessel Disease With Cerebral White Matter Degeneration: A Tract-Based MR Diffusion Imaging Study. J Magn Reson Imaging 2024; 60:268-278. [PMID: 37737474 DOI: 10.1002/jmri.29022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 09/02/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND White matter (WM) degeneration is a key feature of Alzheimer's disease (AD). However, the underlying mechanism remains unclear. PURPOSE To investigate how amyloid-β (Aβ), tau, and small vascular disease (SVD) jointly affect WM degeneration in subjects along AD continuum. STUDY TYPE Retrospective. SUBJECTS 152 non-demented participants (age: 55.8-91.6, male/female: 66/86) from the ADNI database were included, classified into three groups using the A (Aβ)/T (tau)/N pathological scheme (Group 1: A-T-; Group 2: A+T-; Group 3: A+T+) based on positron emission tomography data. FIELD STRENGTH/SEQUENCE 3T; T1-weighted images, T2-weighted fluid-attenuated inversion recovery images, T2*-weighted images, diffusion-weighted spin-echo echo-planar imaging sequence (54 diffusion directions). ASSESSMENT Free-water diffusion model (generated parameters: free water, FW; tissue fractional anisotropy, FAt; tissue mean diffusivity, MDt); SVD total score; Neuropsychological tests. STATISTICAL TESTS Linear regression analysis was performed to investigate the independent contribution of AD (Aβ and tau) and SVD pathologies to diffusion parameters in each fiber tract, first in the entire population and then in each subgroup. We also investigated associations between diffusion parameters and cognitive functions. The level of statistical significance was set at p < 0.05 (false discovery rate corrected). RESULTS In the entire population, we found that: 1) Increased FW was significantly associated with SVD and tau, while FAt and MDt were significantly associated with Aβ and tau; 2) The spatial pattern of fiber tracts related to a certain pathological marker is consistent with the known distribution of that pathology; 3) Subgroup analysis showed that Group 2 and 3 had more alterations of FAt and MDt associated with Aβ and tau; 4) Diffusion imaging indices showed significant associations with cognitive score in all domains except memory. DATA CONCLUSION WM microstructural injury was associated with both AD and SVD pathologies, showing compartment-specific, tract-specific, and stage-specific WM patterns. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Luwei Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jixuan Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yao Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Linyun Xie
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shan Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinyi Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhirong Liu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Hu Y, Zhu T, Zhang W. The characteristics of brain atrophy prior to the onset of Alzheimer's disease: a longitudinal study. Front Aging Neurosci 2024; 16:1344920. [PMID: 38863784 PMCID: PMC11165148 DOI: 10.3389/fnagi.2024.1344920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 05/02/2024] [Indexed: 06/13/2024] Open
Abstract
Objective We aimed to use the onset time of Alzheimer's disease (AD) as the reference time to longitudinally investigate the atrophic characteristics of brain structures prior to the onset of AD. Materials and methods A total of 328 participants from the ADNI database with clear onset of AD and structural imaging data were included in our study. The time before the onset of AD (abbreviated as BAD) was calculated. We investigated the longitudinal brain changes in 97 regions using multivariate linear mixed effects regression models. Results The average BAD was -28.15 months, with a range from -156 to 0 months. The 54 brain regions showed significant atrophy prior to the onset of AD, and these regions were mainly distributed in the frontal and temporal lobes. The parietal and occipital lobe exhibited relatively less atrophy than the other brain lobes. Sex, age, and magnetic field strength had greater direct impacts on structural indicators than APOE genotype and education. The analysis of interaction effects revealed that the APOE ε4 mutation carriers exhibited more severe structural changes in specific brain regions as the BAD increased. However, sex, age, and education had minimal regulatory influence on the structural changes associated with BAD. Conclusion Longitudinal analysis, with the onset time point of AD as the reference, can accurately describe the features of structural changes preceding the onset of AD and provide a comprehensive understanding of AD development.
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Affiliation(s)
- Ying Hu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Ting Zhu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Wei Zhang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Mental Health Center of West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
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Huang X, Yuan S, Ling Y, Tan S, Xu A, Lyu J. Feelings of tense and risk of incident dementia: A prospective study of 482,360 individuals. J Affect Disord 2024; 351:541-550. [PMID: 38266930 DOI: 10.1016/j.jad.2024.01.156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 10/31/2023] [Accepted: 01/14/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND The relationship between feelings of tense, as a significant emotional distress, and dementia remains unclear. This study aimed to evaluate the association between feelings of tense and dementia. METHODS In UK Biobank, feelings of tense were measured with a standard item. The primary outcome was all cause of dementia (ACD) and its subtypes (Alzheimer's disease (AD), vascular dementia (VD), and other dementia). Cox regression models analyzed the association between feelings of tense and dementia risk, while linear regression examined the correlation with neuroimaging outcomes. The potential association and joint effects of AD and tenseness were evaluated based on the established genetic risk score (GRS). RESULTS During a median follow-up of 12.7 years among 482,360 participants, 7331 dementia cases were identified. Individuals with feelings of tense had a significantly increased risk of ACD (HR, 1.194; 95 % CI: 1.115-1.278), VD (HR, 1.164; 95 % CI: 1.007-1.346), and other dementia (HR, 1.181; 95 % CI: 1.081-1.289), but not AD in multi-adjusted models. This association persisted across various sensitivity analyses and exhibited some heterogeneity in subgroup analyses. Furthermore, feelings of tense are associated with total brain volume shrinkage, higher white matter hyperintensities, and decreased partial subcortical volume, particularly in the hippocampus. No interaction between tenseness and AD genetic susceptibility was observed (P for interaction =0.346). LIMITATIONS Our study only considered feelings of tense measured at a one-time point. CONCLUSIONS Our findings demonstrate a significant association between feeling of tense and elevated dementia risk, indicating that tenseness could serve as a modifiable psychological determinant for dementia.
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Affiliation(s)
- Xiaxuan Huang
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shiqi Yuan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Yitong Ling
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shanyuan Tan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Anding Xu
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China.
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou 510630, China.
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Mak E, Dounavi ME, Operto G, Ziukelis ET, Jones PS, Low A, Swann P, Newton C, Muniz Terrera G, Malhotra P, Koychev I, Falcon C, Mackay C, Lawlor B, Naci L, Wells K, Ritchie C, Ritchie K, Su L, Gispert JD, O’Brien JT. APOE ɛ4 exacerbates age-dependent deficits in cortical microstructure. Brain Commun 2024; 6:fcad351. [PMID: 38384997 PMCID: PMC10881196 DOI: 10.1093/braincomms/fcad351] [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: 05/30/2023] [Revised: 10/20/2023] [Accepted: 02/09/2024] [Indexed: 02/23/2024] Open
Abstract
The apolipoprotein E ɛ4 allele is the primary genetic risk factor for the sporadic type of Alzheimer's disease. However, the mechanisms by which apolipoprotein E ɛ4 are associated with neurodegeneration are still poorly understood. We applied the Neurite Orientation Dispersion Model to characterize the effects of apolipoprotein ɛ4 and its interactions with age and education on cortical microstructure in cognitively normal individuals. Data from 1954 participants were included from the PREVENT-Dementia and ALFA (ALzheimer and FAmilies) studies (mean age = 57, 1197 non-carriers and 757 apolipoprotein E ɛ4 carriers). Structural MRI datasets were processed with FreeSurfer v7.2. The Microstructure Diffusion Toolbox was used to derive Orientation Dispersion Index maps from diffusion MRI datasets. Primary analyses were focused on (i) the main effects of apolipoprotein E ɛ4, and (ii) the interactions of apolipoprotein E ɛ4 with age and education on lobar and vertex-wise Orientation Dispersion Index and implemented using Permutation Analysis of Linear Models. There were apolipoprotein E ɛ4 × age interactions in the temporo-parietal and frontal lobes, indicating steeper age-dependent Orientation Dispersion Index changes in apolipoprotein E ɛ4 carriers. Steeper age-related Orientation Dispersion Index declines were observed among apolipoprotein E ɛ4 carriers with lower years of education. We demonstrated that apolipoprotein E ɛ4 worsened age-related Orientation Dispersion Index decreases in brain regions typically associated with atrophy patterns of Alzheimer's disease. This finding also suggests that apolipoprotein E ɛ4 may hasten the onset age of dementia by accelerating age-dependent reductions in cortical Orientation Dispersion Index.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Grégory Operto
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
| | - Elina T Ziukelis
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Swann
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Coco Newton
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Paresh Malhotra
- Department of Brain Sciences, Imperial College, London W12 0NN, UK
| | - Ivan Koychev
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Carles Falcon
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - Clare Mackay
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Brian Lawlor
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Lorina Naci
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Katie Wells
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Craig Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Karen Ritchie
- Institut National de la Santé et de la Recherche Médicale, U1061 Neuropsychiatrie, Montpellier 34093, France
- Faculty of Medicine, University of Montpellier, Montpellier 34093, France
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - John T O’Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
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Davidson TL, Stevenson RJ. Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction. Int J Mol Sci 2024; 25:1991. [PMID: 38396670 PMCID: PMC10888241 DOI: 10.3390/ijms25041991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024] Open
Abstract
The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.
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Affiliation(s)
- Terry L. Davidson
- Department of Neuroscience, Center for Neuroscience and Behavior, American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016, USA
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Yang J, Liang L, Wei Y, Liu Y, Li X, Huang J, Zhang Z, Li L, Deng D. Altered cortical and subcortical morphometric features and asymmetries in the subjective cognitive decline and mild cognitive impairment. Front Neurol 2023; 14:1297028. [PMID: 38107635 PMCID: PMC10722314 DOI: 10.3389/fneur.2023.1297028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023] Open
Abstract
Introduction This study aimed to evaluate morphological changes in cortical and subcortical regions and their asymmetrical differences in individuals with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). These morphological changes may provide valuable insights into the early diagnosis and treatment of Alzheimer's disease (AD). Methods We conducted structural MRI scans on a cohort comprising 62 SCD patients, 97 MCI patients, and 70 age-, sex-, and years of education-matched healthy controls (HC). Using Freesurfer, we quantified surface area, thickness, the local gyrification index (LGI) of cortical regions, and the volume of subcortical nuclei. Asymmetry measures were also calculated. Additionally, we explored the correlation between morphological changes and clinical variables related to cognitive decline. Results Compared to HC, patients with MCI exhibited predominantly left-sided surface morphological changes in various brain regions, including the transverse temporal gyrus, superior temporal gyrus, insula, and pars opercularis. SCD patients showed relatively minor surface morphological changes, primarily in the insula and pars triangularis. Furthermore, MCI patients demonstrated reduced volumes in the anterior-superior region of the right hypothalamus, the fimbria of the bilateral hippocampus, and the anterior region of the left thalamus. These observed morphological changes were significantly associated with clinical ratings of cognitive decline. Conclusion The findings of this study suggest that cortical and subcortical morphometric changes may contribute to cognitive impairment in MCI, while compensatory mechanisms may be at play in SCD to preserve cognitive function. These insights have the potential to aid in the early diagnosis and treatment of AD.
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Affiliation(s)
- Jin Yang
- School of Medicine, Guangxi University, Nanning, Guangxi, China
| | - Lingyan Liang
- Department of Radiology, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Yichen Wei
- Department of Radiology, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Ying Liu
- Department of Radiology, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Xiaocheng Li
- Department of Radiology, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Jiazhu Huang
- Department of Radiology, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
| | - Zhiguo Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China
- Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, Guangdong, China
- Peng Cheng Laboratory, Shenzhen, Guangdong, China
| | - Linling Li
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, China
| | - Demao Deng
- School of Medicine, Guangxi University, Nanning, Guangxi, China
- Department of Radiology, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Science, Nanning, Guangxi, China
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Savitz J, Goeckner BD, Ford BN, Kent Teague T, Zheng H, Harezlak J, Mannix R, Tugan Muftuler L, Brett BL, McCrea MA, Meier TB. The effects of cytomegalovirus on brain structure following sport-related concussion. Brain 2023; 146:4262-4273. [PMID: 37070698 PMCID: PMC10545519 DOI: 10.1093/brain/awad126] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 03/06/2023] [Accepted: 03/27/2023] [Indexed: 04/19/2023] Open
Abstract
The neurotrophic herpes virus cytomegalovirus is a known cause of neuropathology in utero and in immunocompromised populations. Cytomegalovirus is reactivated by stress and inflammation, possibly explaining the emerging evidence linking it to subtle brain changes in the context of more minor disturbances of immune function. Even mild forms of traumatic brain injury, including sport-related concussion, are major physiological stressors that produce neuroinflammation. In theory, concussion could predispose to the reactivation of cytomegalovirus and amplify the effects of physical injury on brain structure. However, to our knowledge this hypothesis remains untested. This study evaluated the effect of cytomegalovirus serostatus on white and grey matter structure in a prospective study of athletes with concussion and matched contact-sport controls. Athletes who sustained concussion (n = 88) completed MRI at 1, 8, 15 and 45 days post-injury; matched uninjured athletes (n = 73) completed similar visits. Cytomegalovirus serostatus was determined by measuring serum IgG antibodies (n = 30 concussed athletes and n = 21 controls were seropositive). Inverse probability of treatment weighting was used to adjust for confounding factors between athletes with and without cytomegalovirus. White matter microstructure was assessed using diffusion kurtosis imaging metrics in regions previously shown to be sensitive to concussion. T1-weighted images were used to quantify mean cortical thickness and total surface area. Concussion-related symptoms, psychological distress, and serum concentration of C-reactive protein at 1 day post-injury were included as exploratory outcomes. Planned contrasts compared the effects of cytomegalovirus seropositivity in athletes with concussion and controls, separately. There was a significant effect of cytomegalovirus on axial and radial kurtosis in athletes with concussion but not controls. Cytomegalovirus positive athletes with concussion showed greater axial (P = 0.007, d = 0.44) and radial (P = 0.010, d = 0.41) kurtosis than cytomegalovirus negative athletes with concussion. Similarly, there was a significant association of cytomegalovirus with cortical thickness in athletes with concussion but not controls. Cytomegalovirus positive athletes with concussion had reduced mean cortical thickness of the right hemisphere (P = 0.009, d = 0.42) compared with cytomegalovirus negative athletes with concussion and showed a similar trend for the left hemisphere (P = 0.036, d = 0.33). There was no significant effect of cytomegalovirus on kurtosis fractional anisotropy, surface area, symptoms and C-reactive protein. The results raise the possibility that cytomegalovirus infection contributes to structural brain abnormalities in the aftermath of concussion perhaps via an amplification of concussion-associated neuroinflammation. More work is needed to identify the biological pathways underlying this process and to clarify the clinical relevance of this putative viral effect.
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Affiliation(s)
- Jonathan Savitz
- Laureate Institute for Brain Research, Tulsa, OK 74136, USA
- Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK 74119, USA
| | - Bryna D Goeckner
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Bart N Ford
- Department of Pharmacology and Physiology, Oklahoma State University Center for Health Sciences, Tulsa, OK 74107, USA
| | - T Kent Teague
- Department of Psychiatry, The University of Oklahoma School of Community Medicine, Tulsa, OK 74135, USA
- Department of Surgery, The University of Oklahoma School of Community Medicine, Tulsa, OK 74135, USA
- Department of Pharmaceutical Sciences, University of Oklahoma College of Pharmacy, Tulsa, OK 74135, USA
| | - Haixia Zheng
- Laureate Institute for Brain Research, Tulsa, OK 74136, USA
| | - Jaroslaw Harezlak
- Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA
| | - Rebekah Mannix
- Division of Emergency Medicine, Boston Children’s Hospital, Boston, MA 02115, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - L Tugan Muftuler
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Benjamin L Brett
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Michael A McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Timothy B Meier
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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Chouliaras L, O'Brien JT. The use of neuroimaging techniques in the early and differential diagnosis of dementia. Mol Psychiatry 2023; 28:4084-4097. [PMID: 37608222 PMCID: PMC10827668 DOI: 10.1038/s41380-023-02215-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 07/27/2023] [Accepted: 08/03/2023] [Indexed: 08/24/2023]
Abstract
Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.
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Affiliation(s)
- Leonidas Chouliaras
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Specialist Dementia and Frailty Service, Essex Partnership University NHS Foundation Trust, St Margaret's Hospital, Epping, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK.
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
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10
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Jin P, Xu J, Liao Z, Zhang Y, Wang Y, Sun W, Yu E. A review of current evidence for mild behavioral impairment as an early potential novel marker of Alzheimer's disease. Front Psychiatry 2023; 14:1099333. [PMID: 37293396 PMCID: PMC10246741 DOI: 10.3389/fpsyt.2023.1099333] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 03/31/2023] [Indexed: 06/10/2023] Open
Abstract
Mild behavioral impairment (MBI) is a neurobehavioral syndrome that occurs in the absence of cognitive impairment later in life (≥50 years of age). MBI is widespread in the pre-dementia stage and is closely associated with the progression of cognitive impairment, reflecting the neurobehavioral axis of pre-dementia risk states and complementing the traditional neurocognitive axis. Despite being the most common type of dementia, Alzheimer's disease (AD) does not yet have an effective treatment; therefore, early recognition and intervention are crucial. The Mild Behavioral Impairment Checklist is an effective tool for identifying MBI cases and helps identify people at risk of developing dementia. However, because the concept of MBI is still quite new, the overall understanding of it is relatively insufficient, especially in AD. Therefore, this review examines the current evidence from cognitive function, neuroimaging, and neuropathology that suggests the potential use of MBI as a risk indicator in preclinical AD.
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Affiliation(s)
- Piaopiao Jin
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jiaxi Xu
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhengluan Liao
- Department of Geriatric VIP No. 3 (Department of Clinical Psychology), Rehabilitation Medicine Center, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, China
| | - Yuhan Zhang
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ye Wang
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Wangdi Sun
- Department of Psychiatry, Zhejiang Hospital, Hangzhou, China
| | - Enyan Yu
- Department of Psychiatry, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
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11
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Chen Y, Wang Y, Song Z, Fan Y, Gao T, Tang X. Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review. Ageing Res Rev 2023; 87:101911. [PMID: 36931328 DOI: 10.1016/j.arr.2023.101911] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 03/01/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023]
Abstract
Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.
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Affiliation(s)
- Yu Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yifei Wang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Zeyu Song
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yingwei Fan
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Tianxin Gao
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
| | - Xiaoying Tang
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
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12
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Srivishagan S, Kumaralingam L, Thanikasalam K, Pinidiyaarachchi UAJ, Ratnarajah N. Discriminative patterns of white matter changes in Alzheimer's. Psychiatry Res Neuroimaging 2023; 328:111576. [PMID: 36495726 DOI: 10.1016/j.pscychresns.2022.111576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 11/12/2022] [Accepted: 11/22/2022] [Indexed: 12/02/2022]
Abstract
Changes in structural connectivity of the Alzheimer's brain have not been widely studied utilizing cutting-edge methodologies. This study develops an efficient structural connectome-based convolutional neural network (CNN) to classify the AD and uses explanations of CNNs' choices in classification to pinpoint the discriminative changes in white matter connectivity in AD. A CNN architecture has been developed to classify normal control (NC) and AD subjects from the weighted structural connectome. Then, the CNN classification decision is visually analyzed using gradient-based localization techniques to identify the discriminative changes in white matter connectivity in Alzheimer's. The cortical regions involved in the identified discriminative structural connectivity changes in AD are highly covered in the temporal/subcortical regions. A specific pattern is identified in the discriminative changes in structural connectivity of AD, where the white matter changes are revealed within the temporal/subcortical regions and from the temporal/subcortical regions to the frontal and parietal regions in both left and right hemispheres. The proposed approach has the potential to comprehensively analyze the discriminative structural connectivity differences in AD, change the way of detecting biomarkers, and help clinicians better understand the structural changes in AD and provide them with more confidence in automated diagnostic systems.
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Affiliation(s)
- Subaramya Srivishagan
- Department of Physical Science, Faculty of Applied Science, University of Vavuniya, Vavuniya, Sri Lanka; PGIS, University of Peradeniya, Peradeniya, Sri Lanka
| | - Logiraj Kumaralingam
- Department of Computer Science, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - Kokul Thanikasalam
- Department of Computer Science, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - U A J Pinidiyaarachchi
- Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka
| | - Nagulan Ratnarajah
- Department of Physical Science, Faculty of Applied Science, University of Vavuniya, Vavuniya, Sri Lanka.
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13
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Fernández A, Ramírez-Toraño F, Bruña R, Zuluaga P, Esteba-Castillo S, Abásolo D, Moldenhauer F, Shumbayawonda E, Maestú F, García-Alba J. Brain signal complexity in adults with Down syndrome: Potential application in the detection of mild cognitive impairment. Front Aging Neurosci 2022; 14:988540. [PMID: 36337705 PMCID: PMC9631477 DOI: 10.3389/fnagi.2022.988540] [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: 07/07/2022] [Accepted: 09/27/2022] [Indexed: 11/13/2022] Open
Abstract
Background Down syndrome (DS) is considered the most frequent cause of early-onset Alzheimer’s disease (AD), and the typical pathophysiological signs are present in almost all individuals with DS by the age of 40. Despite of this evidence, the investigation on the pre-dementia stages in DS is scarce. In the present study we analyzed the complexity of brain oscillatory patterns and neuropsychological performance for the characterization of mild cognitive impairment (MCI) in DS. Materials and methods Lempel-Ziv complexity (LZC) values from resting-state magnetoencephalography recordings and the neuropsychological performance in 28 patients with DS [control DS group (CN-DS) (n = 14), MCI group (MCI-DS) (n = 14)] and 14 individuals with typical neurodevelopment (CN-no-DS) were analyzed. Results Lempel-Ziv complexity was lowest in the frontal region within the MCI-DS group, while the CN-DS group showed reduced values in parietal areas when compared with the CN-no-DS group. Also, the CN-no-DS group exhibited the expected pattern of significant increase of LZC as a function of age, while MCI-DS cases showed a decrease. The combination of reduced LZC values and a divergent trajectory of complexity evolution with age, allowed the discrimination of CN-DS vs. MCI-DS patients with a 92.9% of sensitivity and 85.7% of specificity. Finally, a pattern of mnestic and praxic impairment was significantly associated in MCI-DS cases with the significant reduction of LZC values in frontal and parietal regions (p = 0.01). Conclusion Brain signal complexity measured with LZC is reduced in DS and its development with age is also disrupted. The combination of both features might assist in the detection of MCI within this population.
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Affiliation(s)
- Alberto Fernández
- Department of Legal Medicine, Psychiatry and Pathology, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), Hospital Universitario San Carlos, Madrid, Spain
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
| | - Federico Ramírez-Toraño
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Radiology, Universidad Complutense de Madrid, Madrid, Spain
- Department of Industrial Engineering & IUNE & ITB, Universidad de La Laguna, San Cristóbal de La Laguna, Spain
| | - Pilar Zuluaga
- Statistics & Operations Research Department, Faculty of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Susanna Esteba-Castillo
- Neurodevelopmental Group, Girona Biomedical Research Institute-IDIBGI, Institute of Health Assistance (IAS), Parc Hospitalari Martí i Julià, Girona, Spain
| | - Daniel Abásolo
- Centre for Biomedical Engineering, School of Mechanical Engineering Sciences, University of Surrey, Guildford, United Kingdom
| | - Fernando Moldenhauer
- Adult Down Syndrome Unit, Internal Medicine Department, Health Research Institute, Hospital Universitario de La Princesa, Madrid, Spain
| | - Elizabeth Shumbayawonda
- Centre for Biomedical Engineering, School of Mechanical Engineering Sciences, University of Surrey, Guildford, United Kingdom
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Javier García-Alba
- Department of Research and Psychology in Education, Universidad Complutense de Madrid, Madrid, Spain
- *Correspondence: Javier García-Alba,
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14
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Thams F, Külzow N, Flöel A, Antonenko D. Modulation of network centrality and gray matter microstructure using multi-session brain stimulation and memory training. Hum Brain Mapp 2022; 43:3416-3426. [PMID: 35373873 PMCID: PMC9248322 DOI: 10.1002/hbm.25857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/15/2022] [Accepted: 03/24/2022] [Indexed: 11/07/2022] Open
Abstract
Neural mechanisms of behavioral improvement induced by repeated transcranial direct current stimulation (tDCS) combined with cognitive training are yet unclear. Previously, we reported behavioral effects of a 3-day visuospatial memory training with concurrent anodal tDCS over the right temporoparietal cortex in older adults. To investigate intervention-induced neural alterations we here used functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) datasets available from 35 participants of this previous study, acquired before and after the intervention. To delineate changes in whole-brain functional network architecture, we employed eigenvector centrality mapping. Gray matter alterations were analyzed using DTI-derived mean diffusivity (MD). Network centrality in the bilateral posterior temporooccipital cortex was reduced after anodal compared to sham stimulation. This focal effect is indicative of decreased functional connectivity of the brain region underneath the anodal electrode and its left-hemispheric homolog with other "relevant" (i.e., highly connected) brain regions, thereby providing evidence for reorganizational processes within the brain's network architecture. Examining local MD changes in these clusters, an interaction between stimulation condition and training success indicated a decrease of MD in the right (stimulated) temporooccipital cluster in individuals who showed superior behavioral training benefits. Using a data-driven whole-brain network approach, we provide evidence for targeted neuromodulatory effects of a combined tDCS-and-training intervention. We show for the first time that gray matter alterations of microstructure (assessed by DTI-derived MD) may be involved in tDCS-enhanced cognitive training. Increased knowledge on how combined interventions modulate neural networks in older adults, will help the development of specific therapeutic interventions against age-associated cognitive decline.
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Affiliation(s)
- Friederike Thams
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
| | - Nadine Külzow
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, Germany.,Neurological Rehabilitation Clinic, Kliniken Beelitz GmbH, Beelitz, Germany
| | - Agnes Flöel
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany.,German Centre for Neurodegenerative Diseases (DZNE) Standort Greifswald, Greifswald, Germany
| | - Daria Antonenko
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
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15
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Dounavi ME, Newton C, Jenkins N, Mak E, Low A, Muniz-Terrera G, Williams GB, Lawlor B, Naci L, Malhotra P, Mackay CE, Koychev I, Ritchie K, Ritchie CW, Su L, O'Brien JT. Macrostructural brain alterations at midlife are connected to cardiovascular and not inherited risk of future dementia: the PREVENT-Dementia study. J Neurol 2022; 269:4299-4309. [PMID: 35279756 PMCID: PMC9294019 DOI: 10.1007/s00415-022-11061-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/28/2022] [Accepted: 03/03/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND Macrostructural brain alterations in the form of brain atrophy or cortical thinning typically occur during the prodromal Alzheimer's disease stage. Mixed findings largely dependent on the age of the examined cohorts have been reported during the preclinical, asymptomatic disease stage. In the present study, our aim was to examine the association of midlife dementia risk with brain macrostructural alterations. METHODS Structural 3T MRI scans were acquired for 647 cognitively normal middle-aged (40-59 years old) participants in the PREVENT-Dementia study. Cortical thickness, volumes of subcortical structures, the hippocampus and hippocampal subfields were quantified using Freesurfer version 7.1. The clarity of the hippocampal molecular layer was evaluated based on T2-weighted hippocampal scans. Associations of structural measures with apolipoprotein ε4 (APOE4) genotype and dementia family history (FHD), were investigated using linear regression. Correlations between the CAIDE dementia risk score (incorporating information about blood pressure, cholesterol, physical activity, body mass index, education, age and sex) and structural measures were further investigated. RESULTS A higher CAIDE score was associated with thinner cortex and a larger hippocampal fissure. APOE4 genotype was associated with reduced molecular layer clarity. CONCLUSIONS Our findings suggest that a higher CAIDE score is associated with widespread cortical thinning. Conversely, APOE4 carriers and participants with FHD do not demonstrate prominent macrostructural alterations at this age range. These findings indicate that cardiovascular and not inherited risk factors for dementia are associated with macrostructural brain alterations at midlife.
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Affiliation(s)
- Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK
| | - Coco Newton
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK
| | - Natalie Jenkins
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | - Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK
| | | | - Guy B Williams
- Department of Clinical Neurosciences and Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Brian Lawlor
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Lorina Naci
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Paresh Malhotra
- Division of Brain Science, Imperial College Healthcare NHS Trust, London, UK
| | | | - Ivan Koychev
- Department of Psychiatry, Oxford University, Oxford, UK
| | - Karen Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
- INM, Univ Montpellier, INSERM, Montpellier, France
| | - Craig W Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK
- Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK.
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16
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Milicic L, Vacher M, Porter T, Doré V, Burnham SC, Bourgeat P, Shishegar R, Doecke J, Armstrong NJ, Tankard R, Maruff P, Masters CL, Rowe CC, Villemagne VL, Laws SM. Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume. GeroScience 2022; 44:1807-1823. [PMID: 35445885 PMCID: PMC9213584 DOI: 10.1007/s11357-022-00558-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 03/30/2022] [Indexed: 12/21/2022] Open
Abstract
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer's Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer's disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.
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Affiliation(s)
- Lidija Milicic
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
| | - Michael Vacher
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Floreat, Western Australia, 6014, Australia
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia
| | - Vincent Doré
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Samantha C Burnham
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
| | - Pierrick Bourgeat
- Australian E-Health Research Centre, CSIRO, Herston, Queensland, 4029, Australia
| | - Rosita Shishegar
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - James Doecke
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Australian E-Health Research Centre, CSIRO, Herston, Queensland, 4029, Australia
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Curtin University, Bentley, Western Australia, Australia
| | - Rick Tankard
- School of Mathematics and Statistics, Murdoch University, Perth, Western Australia, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
- Cogstate Ltd, Melbourne, VIC, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Victor L Villemagne
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia.
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia.
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17
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Fractal dimension of the brain in neurodegenerative disease and dementia: A systematic review. Ageing Res Rev 2022; 79:101651. [PMID: 35643264 DOI: 10.1016/j.arr.2022.101651] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 04/26/2022] [Accepted: 05/23/2022] [Indexed: 12/25/2022]
Abstract
Sensitive and specific antemortem biomarkers of neurodegenerative disease and dementia are crucial to the pursuit of effective treatments, required both to reliably identify disease and to track its progression. Atrophy is the structural magnetic resonance imaging (MRI) hallmark of neurodegeneration. However in most cases it likely indicates a relatively advanced stage of disease less susceptible to treatment as some disease processes begin decades prior to clinical onset. Among emerging metrics that characterise brain shape rather than volume, fractal dimension (FD) quantifies shape complexity. FD has been applied in diverse fields of science to measure subtle changes in elaborate structures. We review its application thus far to structural MRI of the brain in neurodegenerative disease and dementia. We identified studies involving subjects who met criteria for mild cognitive impairment, Alzheimer's Disease, Vascular Dementia, Lewy Body Dementia, Frontotemporal Dementia, Amyotrophic Lateral Sclerosis, Parkinson's Disease, Huntington's Disease, Multiple Systems Atrophy, Spinocerebellar Ataxia and Multiple Sclerosis. The early literature suggests that neurodegenerative disease processes are usually associated with a decline in FD of the brain. The literature includes examples of disease-related change in FD occurring independently of atrophy, which if substantiated would represent a valuable advantage over other structural imaging metrics. However, it is likely to be non-specific and to exhibit complex spatial and temporal patterns. A more harmonious methodological approach across a larger number of studies as well as careful attention to technical factors associated with image processing and FD measurement will help to better elucidate the metric's utility.
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18
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Gill S, Wang M, Mouches P, Rajashekar D, Sajobi T, MacMaster FP, Smith EE, Forkert ND, Ismail Z. Neural correlates of the impulse dyscontrol domain of mild behavioral impairment. Int J Geriatr Psychiatry 2021; 36:1398-1406. [PMID: 33778998 PMCID: PMC9292816 DOI: 10.1002/gps.5540] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 03/21/2021] [Indexed: 12/17/2022]
Abstract
OBJECTIVES Agitation and aggression are common in dementia and pre-dementia. The dementia risk syndrome mild behavioral impairment (MBI) includes these symptoms in the impulse dyscontrol domain. However, the neural circuitry associated with impulse dyscontrol in neurodegenerative disease is not well understood. The objective of this work was to investigate if regional micro- and macro-structural brain properties were associated with impulse dyscontrol symptoms in older adults with normal cognition, mild cognitive impairment, and Alzheimer's disease (AD). METHODS Clinical, neuropsychiatric, and T1-weighted and diffusion-tensor magnetic resonance imaging (DTI) data from 80 individuals with and 123 individuals without impulse dyscontrol were obtained from the AD Neuroimaging Initiative. Linear mixed effect models were used to assess if impulse dyscontrol was related to regional DTI and volumetric parameters. RESULTS Impulse dyscontrol was present in 17% of participants with NC, 43% with MCI, and 66% with AD. Impulse dyscontrol was associated with: (1) lower fractional anisotropy (FA), and greater mean, axial, and radial diffusivity in the fornix; (2) lesser FA and greater radial diffusivity in the superior fronto-occipital fasciculus; (3) greater axial diffusivity in the cingulum; (4) greater axial and radial diffusivity in the uncinate fasciculus; (5) gray matter atrophy, specifically, lower cortical thickness in the parahippocampal gyrus. CONCLUSION Our findings provide evidence that well-established atrophy patterns of AD are prominent in the presence of impulse dyscontrol, even when disease status is controlled for, and possibly in advance of dementia. Our findings support the growing evidence for impulse dyscontrol symptoms as an early manifestation of AD.
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Affiliation(s)
- Sascha Gill
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada
| | - Meng Wang
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of Community Health ScienceUniversity of CalgaryCalgaryAlbertaCanada
| | - Pauline Mouches
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of RadiologyUniversity of CalgaryCalgaryAlbertaCanada
| | - Deepthi Rajashekar
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of RadiologyUniversity of CalgaryCalgaryAlbertaCanada
| | - Tolulope Sajobi
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of Community Health ScienceUniversity of CalgaryCalgaryAlbertaCanada
| | - Frank P MacMaster
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of PsychiatryUniversity of CalgaryCalgaryAlbertaCanada,Addiction and Mental Health Strategic Clinical NetworkAlberta Health ServicesAlbertaCanada
| | - Eric E Smith
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada
| | - Nils D Forkert
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada,Department of RadiologyUniversity of CalgaryCalgaryAlbertaCanada
| | - Zahinoor Ismail
- Hotchkiss Brain InstituteCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada,Department of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada,Department of Community Health ScienceUniversity of CalgaryCalgaryAlbertaCanada,Department of PsychiatryUniversity of CalgaryCalgaryAlbertaCanada,O'Brien Institute for Public HealthCumming School of Medicine, University of CalgaryCalgaryAlbertaCanada
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19
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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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20
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Kucikova L, Goerdten J, Dounavi ME, Mak E, Su L, Waldman AD, Danso S, Muniz-Terrera G, Ritchie CW. Resting-state brain connectivity in healthy young and middle-aged adults at risk of progressive Alzheimer's disease. Neurosci Biobehav Rev 2021; 129:142-153. [PMID: 34310975 DOI: 10.1016/j.neubiorev.2021.07.024] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 05/18/2021] [Accepted: 07/21/2021] [Indexed: 11/15/2022]
Abstract
Functional brain connectivity of the resting-state networks has gained recent attention as a possible biomarker of Alzheimer's Disease (AD). In this paper, we review the literature of functional connectivity differences in young adults and middle-aged cognitively intact individuals with non-modifiable risk factors of AD (n = 17). We focus on three main intrinsic resting-state networks: The Default Mode network, Executive network, and the Salience network. Overall, the evidence from the literature indicated early vulnerability of functional connectivity across different at-risk groups, particularly in the Default Mode Network. While there was little consensus on the interpretation on directionality, the topography of the findings showed frequent overlap across studies, especially in regions that are characteristic of AD (i.e., precuneus, posterior cingulate cortex, and medial prefrontal cortex areas). We conclude that while resting-state functional connectivity markers have great potential to identify at-risk individuals, implementing more data-driven approaches, further longitudinal and cross-validation studies, and the analysis of greater sample sizes are likely to be necessary to fully establish the effectivity and utility of resting-state network-based analyses.
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Affiliation(s)
- Ludmila Kucikova
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom.
| | - Jantje Goerdten
- Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Adam D Waldman
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Samuel Danso
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Graciela Muniz-Terrera
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Craig W Ritchie
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
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21
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Hiscox LV, Schwarb H, McGarry MDJ, Johnson CL. Aging brain mechanics: Progress and promise of magnetic resonance elastography. Neuroimage 2021; 232:117889. [PMID: 33617995 PMCID: PMC8251510 DOI: 10.1016/j.neuroimage.2021.117889] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/12/2021] [Accepted: 02/15/2021] [Indexed: 02/07/2023] Open
Abstract
Neuroimaging techniques that can sensitivity characterize healthy brain aging and detect subtle neuropathologies have enormous potential to assist in the early detection of neurodegenerative conditions such as Alzheimer's disease. Magnetic resonance elastography (MRE) has recently emerged as a reliable, high-resolution, and especially sensitive technique that can noninvasively characterize tissue biomechanical properties (i.e., viscoelasticity) in vivo in the living human brain. Brain tissue viscoelasticity provides a unique biophysical signature of neuroanatomy that are representative of the composition and organization of the complex tissue microstructure. In this article, we detail how progress in brain MRE technology has provided unique insights into healthy brain aging, neurodegeneration, and structure-function relationships. We further discuss additional promising technical innovations that will enhance the specificity and sensitivity for brain MRE to reveal considerably more about brain aging as well as its potentially valuable role as an imaging biomarker of neurodegeneration. MRE sensitivity may be particularly useful for assessing the efficacy of rehabilitation strategies, assisting in differentiating between dementia subtypes, and in understanding the causal mechanisms of disease which may lead to eventual pharmacotherapeutic development.
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Affiliation(s)
- Lucy V Hiscox
- Department of Biomedical Engineering, University of Delaware, 150 Academy St. Newark, Newark, DE 19716, United States.
| | - Hillary Schwarb
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States; Interdisciplinary Health Sciences Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | | | - Curtis L Johnson
- Department of Biomedical Engineering, University of Delaware, 150 Academy St. Newark, Newark, DE 19716, United States.
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22
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L'Heureux F, Baril AA, Gagnon K, Soucy JP, Lafond C, Montplaisir J, Gosselin N. Longitudinal changes in regional cerebral blood flow in late middle-aged and older adults with treated and untreated obstructive sleep apnea. Hum Brain Mapp 2021; 42:3429-3439. [PMID: 33939243 PMCID: PMC8249886 DOI: 10.1002/hbm.25443] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/03/2021] [Accepted: 03/29/2021] [Indexed: 12/31/2022] Open
Abstract
Obstructive sleep apnea (OSA) is associated with abnormal cerebral perfusion at wakefulness, but whether these anomalies evolve over time is unknown. Here, we examined longitudinal changes in regional cerebral blood flow (rCBF) distribution in late middle‐aged and older adults with treated or untreated OSA. Twelve controls (64.8 ± 8.0 years) and 23 participants with newly diagnosed OSA (67.8 ± 6.2 years) were evaluated with polysomnography and cerebral 99mTc‐HMPAO single‐photon emission computed tomography during wakeful rest. OSA participants were referred to a sleep apnea clinic and 13 of them decided to start continuous positive airway pressure (CPAP). Participants were tested again after 18 months. Voxel‐based analysis and extracted relative rCBF values were used to assess longitudinal changes. Untreated OSA participants showed decreased relative rCBF in the left hippocampus and the right parahippocampal gyrus over time, while treated participants showed trends for increased relative rCBF in the left hippocampus and the right parahippocampal gyrus. No changes were found over time in controls. Untreated OSA is associated with worsening relative rCBF in specific brain areas over time, while treated OSA shows the opposite. Considering that OSA possibly accelerates cognitive decline in older adults, CPAP treatment could help reduce risk for cognitive impairment.
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Affiliation(s)
- Francis L'Heureux
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montreal, Quebec, Canada.,Department of Neurosciences, Université de Montréal, Montreal, Quebec, Canada
| | - Andrée-Ann Baril
- The Framingham Heart Study, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Katia Gagnon
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montreal, Quebec, Canada.,Department of Psychology, Université du Québec à Montreal, Montreal, Quebec, Canada
| | - Jean-Paul Soucy
- McConnel Brain Imaging Centre, McGill University, Montreal, Quebec, Canada
| | - Chantal Lafond
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montreal, Quebec, Canada
| | - Jacques Montplaisir
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montreal, Quebec, Canada.,Department of Psychiatry, Université de Montréal, Montreal, Quebec, Canada
| | - Nadia Gosselin
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Centre Intégré Universitaire de Santé et de Services Sociaux du Nord de l'Île-de-Montréal, Montreal, Quebec, Canada.,Department of Psychology, Université de Montréal, Montreal, Quebec, Canada
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23
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Hays CC, Zlatar ZZ, Meloy MJ, Osuna J, Liu TT, Galasko DR, Wierenga CE. Anterior Cingulate Structure and Perfusion is Associated with Cerebrospinal Fluid Tau among Cognitively Normal Older Adult APOEɛ4 Carriers. J Alzheimers Dis 2021; 73:87-101. [PMID: 31743999 DOI: 10.3233/jad-190504] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Evidence suggests the ɛ4 allele of the apolipoprotein E (APOE) gene may accelerate an age-related process of cortical thickening and cerebral blood flow (CBF) reduction in the anterior cingulate cortex (ACC). Although the neural basis of this association remains unclear, evidence suggests it might reflect early neurodegenerative processes. However, to date, associations between cerebrospinal fluid (CSF) biomarkers of neurodegeneration, such as CSF tau, and APOE-related alterations in ACC cortical thickness (CTH) and CBF have yet to be explored. The current study explored the interaction of CSF tau and APOE genotype (ɛ4+, ɛ4-) on FreeSurfer-derived CTH and arterial spin labeling MRI-measured resting CBF in the ACC (caudal ACC [cACC] and rostral ACC [rACC]) among a sample of 45 cognitively normal older adults. Secondary analyses also examined associations between APOE, CTH/CBF, and cognitive performance. In the cACC, higher CSF tau was associated with higher CTH and lower CBF in ɛ4+, whereas these relationships were not evident in ɛ4-. In the rACC, higher CSF tau was associated with higher CTH for both ɛ4+ and ɛ4-, and with lower CBF only in ɛ4+. Significant interactions of CSF tau and APOE on CTH/CBF were not observed in two posterior reference regions implicated in Alzheimer's disease. Secondary analyses revealed a negative relationship between cACC CTH and executive functioning in ɛ4+ and a positive relationship in ɛ4-. Findings suggest the presence of an ɛ4-related pattern of increased CTH and reduced CBF in the ACC that is associated with biomarkers of neurodegeneration and subtle decrements in cognition.
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Affiliation(s)
- Chelsea C Hays
- VA San Diego Healthcare System, San Diego, CA, USA.,SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Zvinka Z Zlatar
- Department of Psychiatry, UC San Diego, La Jolla, CA, USA.,SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - M J Meloy
- VA San Diego Healthcare System, San Diego, CA, USA
| | - Jessica Osuna
- VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, UC San Diego, La Jolla, CA, USA
| | - Thomas T Liu
- Department of Radiology, UC San Diego, La Jolla, CA, USA
| | - Douglas R Galasko
- VA San Diego Healthcare System, San Diego, CA, USA.,Department of Neurosciences, UC San Diego, La Jolla, CA, USA
| | - Christina E Wierenga
- VA San Diego Healthcare System, San Diego, CA, USA.,Department of Psychiatry, UC San Diego, La Jolla, CA, USA.,SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
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24
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Mak E, Dounavi ME, Low A, Carter SF, McKiernan E, Williams GB, Jones PS, Carriere I, Muniz GT, Ritchie K, Ritchie C, Su L, O'Brien JT. Proximity to dementia onset and multi-modal neuroimaging changes: The prevent-dementia study. Neuroimage 2021; 229:117749. [PMID: 33454416 DOI: 10.1016/j.neuroimage.2021.117749] [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: 07/31/2020] [Revised: 12/22/2020] [Accepted: 01/08/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND First-degree relatives of people with dementia (FH+) are at increased risk of developing Alzheimer's disease (AD). Here, we investigate "estimated years to onset of dementia" (EYO) as a surrogate marker of preclinical disease progression and assess its associations with multi-modal neuroimaging biomarkers. METHODS 89 FH+ participants in the PREVENT-Dementia study underwent longitudinal MR imaging over 2 years. EYO was calculated as the difference between the parental age of dementia diagnosis and the current age of the participant (mean EYO = 23.9 years). MPRAGE, ASL and DWI data were processed using Freesurfer, FSL-BASIL and DTI-TK. White matter lesion maps were segmented from FLAIR scans. The SPM Sandwich Estimator Toolbox was used to test for the main effects of EYO and interactions between EYO, Time, and APOE-ε4+. Threshold free cluster enhancement and family wise error rate correction (TFCE FWER) was performed on voxelwise statistical maps. RESULTS There were no significant effects of EYO on regional grey matter atrophy or white matter hyperintensities. However, a shorter EYO was associated with lower white matter Fractional Anisotropy and elevated Mean/Radial Diffusivity, particularly in the corpus callosum (TFCEFWERp < 0.05). The influence of EYO on white matter deficits were significantly stronger compared to that of normal ageing. APOE-ε4 carriers exhibited hyperperfusion with nearer proximity to estimated onset in temporo-parietal regions. There were no interactions between EYO and time, suggesting that EYO was not associated with accelerated imaging changes in this sample. CONCLUSIONS Amongst cognitively normal midlife adults with a family history of dementia, a shorter hypothetical proximity to dementia onset may be associated with incipient brain abnormalities, characterised by white matter disruptions and perfusion abnormalities, particularly amongst APOE-ε4 carriers. Our findings also confer biological validity to the construct of EYO as a potential stage marker of preclinical progression in the context of sporadic dementia. Further clinical follow-up of our longitudinal sample would provide critical validation of these findings.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK.
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Stephen F Carter
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Elizabeth McKiernan
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Guy B Williams
- Department of Clinical Neurosciences and Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - P Simon Jones
- Department of Clinical Neurosciences and Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Isabelle Carriere
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | | | - Karen Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK; INSERM and University of Montpellier, Montpellier, France
| | - Craig Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
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25
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Wang X, Huang W, Su L, Xing Y, Jessen F, Sun Y, Shu N, Han Y. Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease. Mol Neurodegener 2020; 15:55. [PMID: 32962744 PMCID: PMC7507636 DOI: 10.1186/s13024-020-00395-3] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 08/07/2020] [Indexed: 12/15/2022] Open
Abstract
Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer’s disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and the Apolipoprotein E (ApoE) ɛ4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility.
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Affiliation(s)
- Xiaoqi Wang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridge, UK.,Sino-Britain Centre for Cognition and Ageing Research, Southwest University, Chongqing, China
| | - Yue Xing
- Radiological Sciences, Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, 50937, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Yu Sun
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China. .,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China. .,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China. .,National Clinical Research Center for Geriatric Disorders, Beijing, China.
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26
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Dou X, Yao H, Feng F, Wang P, Zhou B, Jin D, Yang Z, Li J, Zhao C, Wang L, An N, Liu B, Zhang X, Liu Y. Characterizing white matter connectivity in Alzheimer's disease and mild cognitive impairment: An automated fiber quantification analysis with two independent datasets. Cortex 2020; 129:390-405. [PMID: 32574842 DOI: 10.1016/j.cortex.2020.03.032] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 12/13/2019] [Accepted: 03/31/2020] [Indexed: 12/28/2022]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive dementia. Diffusion tensor imaging (DTI) has been widely used to show structural integrity and delineate white matter (WM) degeneration in AD. The automated fiber quantification (AFQ) method is a fully automated approach that can rapidly and reliably identify major WM fiber tracts and evaluate WM properties. The main aim of this study was to assess WM integrity and abnormities in a cohort of patients with amnestic mild cognitive impairment (aMCI) and AD as well as normal controls (NCs). For this purpose, we first used AFQ to identify 20 major WM tracts and assessed WM integrity and abnormalities in a cohort of 120 subjects (39 NCs, 34 aMCI patients and 47 AD patients) in a discovery dataset and 122 subjects (43 NCs, 37 aMCI patients and 42 AD patients) in a replicated dataset. Pointwise differences along WM tracts were identified in the discovery dataset and simultaneously confirmed in the replicated dataset. Next, we investigated the utility of DTI measures along WM tracts as features to distinguish patients with AD from NCs via multilevel cross validation using a support vector machine. Correlation analysis revealed the identified microstructural WM alterations and classification output to be highly associated with cognitive ability in the patient groups, suggesting that they may be a robust biomarker of AD. This systematic study provides a pipeline to examine WM integrity and its potential clinical application in AD and may be useful for studying other neurological and psychiatric disorders.
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Affiliation(s)
- Xuejiao Dou
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Hongxiang Yao
- Department of Radiology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Feng Feng
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin, 300350, China; Department of Neurology, Nankai University Huanhu Hospital, Tianjin, China
| | - Bo Zhou
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Dan Jin
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Zhengyi Yang
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jin Li
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Cui Zhao
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Luning Wang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Ningyu An
- Department of Radiology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Bing Liu
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Xi Zhang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China.
| | - Yong Liu
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
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27
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Muñoz-Moreno E, Tudela R, López-Gil X, Soria G. Brain connectivity during Alzheimer's disease progression and its cognitive impact in a transgenic rat model. Netw Neurosci 2020; 4:397-415. [PMID: 32537533 PMCID: PMC7286303 DOI: 10.1162/netn_a_00126] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 01/10/2020] [Indexed: 12/12/2022] Open
Abstract
The research of Alzheimer's disease (AD) in its early stages and its progression till symptomatic onset is essential to understand the pathology and investigate new treatments. Animal models provide a helpful approach to this research, since they allow for controlled follow-up during the disease evolution. In this work, transgenic TgF344-AD rats were longitudinally evaluated starting at 6 months of age. Every 3 months, cognitive abilities were assessed by a memory-related task and magnetic resonance imaging (MRI) was acquired. Structural and functional brain networks were estimated and characterized by graph metrics to identify differences between the groups in connectivity, its evolution with age, and its influence on cognition. Structural networks of transgenic animals were altered since the earliest stage. Likewise, aging significantly affected network metrics in TgF344-AD, but not in the control group. In addition, while the structural brain network influenced cognitive outcome in transgenic animals, functional network impacted how control subjects performed. TgF344-AD brain network alterations were present from very early stages, difficult to identify in clinical research. Likewise, the characterization of aging in these animals, involving structural network reorganization and its effects on cognition, opens a window to evaluate new treatments for the disease.
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Affiliation(s)
- Emma Muñoz-Moreno
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Raúl Tudela
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Xavier López-Gil
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Guadalupe Soria
- Experimental 7T MRI Unit, Institut d'Investigacions Bimediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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28
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Volumetric alterations in the hippocampal subfields of subjects at increased risk of dementia. Neurobiol Aging 2020; 91:36-44. [PMID: 32311609 DOI: 10.1016/j.neurobiolaging.2020.03.006] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 03/04/2020] [Accepted: 03/09/2020] [Indexed: 12/12/2022]
Abstract
The hippocampus is one of the first regions to demonstrate atrophy during the prodromal stage of Alzheimer's disease. Volumetric analysis of its individual subfields could provide biomarkers with higher sensitivity than whole hippocampal volume during an earlier disease stage. We quantified the hippocampal subfields volume in a large cohort comprising healthy participants (aged 40-59) with dementia family history (FH) and controls (without FH), examined at 2 time points across 2 years. Subfield volumes were quantified using both a T1-weighted and a high-resolution T2 hippocampal magnetic resonance imaging acquisition with Freesurfer. The participants were stratified based on dementia FH, APOE genotype, and CAIDE (Cardiovascular Risk Factors, Aging and Dementia) risk score. Whole hippocampal volume did not differ between the groups. The volume of the molecular layer was lower in participants with an APOE ε4 genotype, but there were no differences between subjects with and without dementia FH or with an increasing CAIDE score. The molecular layer may be the first hippocampal region to demonstrate volumetric alterations in subjects at risk of dementia.
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29
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Giorgio J, Landau SM, Jagust WJ, Tino P, Kourtzi Z. Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease. Neuroimage Clin 2020; 26:102199. [PMID: 32106025 PMCID: PMC7044529 DOI: 10.1016/j.nicl.2020.102199] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 01/24/2020] [Accepted: 01/25/2020] [Indexed: 01/13/2023]
Abstract
Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether individuals with MCI will decline (i.e. progressive MCI) or remain stable (i.e. stable MCI) is impeded by patient heterogeneity due to comorbidities that may lead to MCI diagnosis without progression to AD. Despite the importance of early diagnosis of AD for prognosis and personalised interventions, we still lack robust tools for predicting individual progression to dementia. Here, we propose a novel trajectory modelling approach based on metric learning (Generalised Metric Learning Vector Quantization) that mines multimodal data from MCI patients in the Alzheimer's disease Neuroimaging Initiative (ADNI) cohort to derive individualised prognostic scores of cognitive decline due to AD. We develop an integrated biomarker generation- using partial least squares regression- and classification methodology that extends beyond binary patient classification into discrete subgroups (i.e. stable vs. progressive MCI), determines individual profiles from baseline (i.e. cognitive or biological) data and predicts individual cognitive trajectories (i.e. change in memory scores from baseline). We demonstrate that a metric learning model trained on baseline cognitive data (memory, executive function, affective measurements) discriminates stable vs. progressive MCI individuals with high accuracy (81.4%), revealing an interaction between cognitive (memory, executive functions) and affective scores that may relate to MCI comorbidity (e.g. affective disturbance). Training the model to perform the same binary classification on biological data (mean cortical β-amyloid burden, grey matter density, APOE 4) results in similar prediction accuracy (81.9%). Extending beyond binary classifications, we develop and implement a trajectory modelling approach that shows significantly better performance in predicting individualised rate of future cognitive decline (i.e. change in memory scores from baseline), when the metric learning model is trained with biological (r = -0.68) compared to cognitive (r = -0.4) data. Our trajectory modelling approach reveals interpretable and interoperable markers of progression to AD and has strong potential to guide effective stratification of individuals based on prognostic disease trajectories, reducing MCI patient misclassification, that is critical for clinical practice and discovery of personalised interventions.
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Affiliation(s)
- Joseph Giorgio
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA USA
| | - Peter Tino
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom.
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Yiannopoulou KG, Anastasiou AI, Zachariou V, Pelidou SH. Reasons for Failed Trials of Disease-Modifying Treatments for Alzheimer Disease and Their Contribution in Recent Research. Biomedicines 2019; 7:biomedicines7040097. [PMID: 31835422 PMCID: PMC6966425 DOI: 10.3390/biomedicines7040097] [Citation(s) in RCA: 143] [Impact Index Per Article: 28.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 11/29/2019] [Accepted: 12/02/2019] [Indexed: 12/14/2022] Open
Abstract
Despite all scientific efforts and many protracted and expensive clinical trials, no new drug has been approved by FDA for treatment of Alzheimer disease (AD) since 2003. Indeed, more than 200 investigational programs have failed or have been abandoned in the last decade. The most probable explanations for failures of disease-modifying treatments (DMTs) for AD may include late initiation of treatments during the course of AD development, inappropriate drug dosages, erroneous selection of treatment targets, and mainly an inadequate understanding of the complex pathophysiology of AD, which may necessitate combination treatments rather than monotherapy. Clinical trials’ methodological issues have also been criticized. Drug-development research for AD is aimed to overcome these drawbacks. Preclinical and prodromal AD populations, as well as traditionally investigated populations representing all the clinical stages of AD, are included in recent trials. Systematic use of biomarkers in staging preclinical and prodromal AD and of a single primary outcome in trials of prodromal AD are regularly integrated. The application of amyloid, tau, and neurodegeneration biomarkers, including new biomarkers—such as Tau positron emission tomography, neurofilament light chain (blood and Cerebrospinal fluid (CSF) biomarker of axonal degeneration) and neurogranin (CSF biomarker of synaptic functioning)—to clinical trials allows more precise staging of AD. Additionally, use of Bayesian statistics, modifiable clinical trial designs, and clinical trial simulators enrich the trial methodology. Besides, combination therapy regimens are assessed in clinical trials. The above-mentioned diagnostic and statistical advances, which have been recently integrated in clinical trials, are relevant to the recent failures of studies of disease-modifying treatments. Their experiential rather than theoretical origins may better equip potentially successful drug-development strategies.
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Affiliation(s)
- Konstantina G. Yiannopoulou
- Memory Center, Neurological Department, Henry Dunant Hospital Center, 107 Mesogeion Avenue, 11526 Athens, Greece
- Correspondence:
| | | | - Venetia Zachariou
- Icahn School of Medicine at Mount Sinai, Nash family Department of Neurosciences, Department of Pharmacological Sciences, and Friedman Brain Institute, New York, NY 11004, USA;
| | - Sygkliti-Henrietta Pelidou
- Department of Neurology, University of Ioannina, University Hospital of Ioannina, 45500 Ioannina, Greece;
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Potential Fluid Biomarkers for the Diagnosis of Mild Cognitive Impairment. Int J Mol Sci 2019; 20:ijms20174149. [PMID: 31450692 PMCID: PMC6747411 DOI: 10.3390/ijms20174149] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/20/2019] [Accepted: 08/23/2019] [Indexed: 02/07/2023] Open
Abstract
Mild cognitive impairment (MCI) is characterized by a level of cognitive impairment that is lower than normal for a person’s age, but a higher function than that that observed in a demented person. MCI represents a transitional state between normal aging and dementia disorders, especially Alzheimer’s disease (AD). Much effort has been made towards determining the prognosis of a person with MCI who will convert to AD. It is now clear that cerebrospinal fluid (CSF) levels of Aβ40, Aβ42, total tau and phosphorylated tau are useful for predicting the risk of progression from MCI to AD. This review highlights the advantages of the current blood-based biomarkers in MCI, and discusses some of these challenges, with an emphasis on recent studies to provide an overview of the current state of MCI.
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García-Alba J, Ramírez-Toraño F, Esteba-Castillo S, Bruña R, Moldenhauer F, Novell R, Romero-Medina V, Maestú F, Fernández A. Neuropsychological and neurophysiological characterization of mild cognitive impairment and Alzheimer's disease in Down syndrome. Neurobiol Aging 2019; 84:70-79. [PMID: 31518951 DOI: 10.1016/j.neurobiolaging.2019.07.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 07/03/2019] [Accepted: 07/30/2019] [Indexed: 10/26/2022]
Abstract
Down syndrome (DS) has been considered a unique model for the investigation of Alzheimer's disease (AD) but intermediate stages in the continuum are poorly defined. Considering this, we investigated the neurophysiological (i.e., magnetoencephalography [MEG]) and neuropsychological patterns of mild cognitive impairment (MCI) and AD in middle-aged adults with DS. The sample was composed of four groups: Control-DS (n = 14, mean age 44.64 ± 3.30 years), MCI-DS (n = 14, 51.64 ± 3.95 years), AD-DS (n = 13, 53.54 ± 6.58 years), and Control-no-DS (healthy controls, n = 14, 45.21 ± 4.39 years). DS individuals were studied with neuropsychological tests and MEG, whereas the Control-no-DS group completed only the MEG session. Our results showed that the AD-DS group exhibited a significantly poorer performance as compared with the Control-DS group in all tests. Furthermore, this effect was crucially evident in AD-DS individuals when compared with the MCI-DS group in verbal and working memory abilities. In the neurophysiological domain, the Control-DS group showed a widespread increase of theta activity when compared with the Control-no-DS group. With disease progression, this increased theta was substituted by an augmented delta, accompanied with a reduction of alpha activity. Such spectral pattern-specifically observed in occipital, posterior temporal, cuneus, and precuneus regions-correlated with the performance in cognitive tests. This is the first MEG study in the field incorporating both neuropsychological and neurophysiological information, and demonstrating that this combination of markers is sensitive enough to characterize different stages along the AD continuum in DS.
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Affiliation(s)
- Javier García-Alba
- Research and Psychology in Education Department, Complutense University of Madrid, Madrid, Spain; Center for Biomedical Technology, Laboratory of Cognitive and Computational Neuroscience, Technical University of Madrid, Campus Montegancedo, Madrid, Spain.
| | - Federico Ramírez-Toraño
- Center for Biomedical Technology, Laboratory of Cognitive and Computational Neuroscience, Technical University of Madrid, Campus Montegancedo, Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid, Campus de Somosaguas, Pozuelo de Alarcón, Madrid, Spain
| | - Susanna Esteba-Castillo
- Specialized Department in Mental Health and Intellectual Disability, Parc Hospitalari Martí i Julià - Institut d'Assistència Sanitària, Institut d'Assistència Sanitària (IAS), Girona, Spain; Neurodevelopment group [Girona Biomedical Research Institute]-IDIBGI, Institute of Health Assistance (IAS), Parc Hospitalari Martí i Julià, Girona, Spain
| | - Ricardo Bruña
- Center for Biomedical Technology, Laboratory of Cognitive and Computational Neuroscience, Technical University of Madrid, Campus Montegancedo, Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid, Campus de Somosaguas, Pozuelo de Alarcón, Madrid, Spain; Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Fernando Moldenhauer
- Internal Medicine Department, Adult Down Syndrome Unit, La Princesa University Hospital, Health Research Institute, Madrid, Spain
| | - Ramón Novell
- Specialized Department in Mental Health and Intellectual Disability, Parc Hospitalari Martí i Julià - Institut d'Assistència Sanitària, Institut d'Assistència Sanitària (IAS), Girona, Spain; Neurodevelopment group [Girona Biomedical Research Institute]-IDIBGI, Institute of Health Assistance (IAS), Parc Hospitalari Martí i Julià, Girona, Spain
| | - Verónica Romero-Medina
- Center for Biomedical Technology, Laboratory of Cognitive and Computational Neuroscience, Technical University of Madrid, Campus Montegancedo, Madrid, Spain
| | - Fernando Maestú
- Center for Biomedical Technology, Laboratory of Cognitive and Computational Neuroscience, Technical University of Madrid, Campus Montegancedo, Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid, Campus de Somosaguas, Pozuelo de Alarcón, Madrid, Spain; Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Alberto Fernández
- Center for Biomedical Technology, Laboratory of Cognitive and Computational Neuroscience, Technical University of Madrid, Campus Montegancedo, Madrid, Spain; Department of Legal Medicine, Psychiatry and Pathology, Complutense University of Madrid, Spain, Madrid, Spain
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Zhao W, Wang X, Yin C, He M, Li S, Han Y. Trajectories of the Hippocampal Subfields Atrophy in the Alzheimer's Disease: A Structural Imaging Study. Front Neuroinform 2019; 13:13. [PMID: 30983985 PMCID: PMC6450438 DOI: 10.3389/fninf.2019.00013] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 02/19/2019] [Indexed: 11/13/2022] Open
Abstract
Background The hippocampus and hippocampal subfields have been found to be diversely affected in Alzheimer's Disease (AD) and early stages of Alzheimer's disease by neuroimaging studies. However, our knowledge is still lacking about the trajectories of the hippocampus and hippocampal subfields atrophy with the progression of Alzheimer's disease. Objective To identify which subfields of the hippocampus differ in the trajectories of Alzheimer's disease by magnetic resonance imaging (MRI) and to determine whether individual differences on memory could be explained by structural volumes of hippocampal subfields. Methods Four groups of participants including 41 AD patients, 43 amnestic mild cognitive impairment (aMCI) patients, 35 subjective cognitive decline (SCD) patients and 42 normal controls (NC) received their structural MRI brain scans. Structural MR images were processed by the FreeSurfer 6.0 image analysis suite to extract the hippocampus and its subfields. Furthermore, we investigated relationships between hippocampal subfield volumes and memory test variables (AVLT-immediate recall, AVLT-delayed recall, AVLT-recognition) and the regression model analyses were controlled for age, gender, education and eTIV. Results CA1, subiculum, presubiculum, molecular layer and fimbria showed the trend toward significant volume reduction among four groups with the progression of Alzheimer's disease. Volume of left subiculum was most strongly and actively correlated with performance across AVLT measures. Conclusion The trend changes in the hippocampus subfields and further illustrates that SCD is the preclinical stage of AD earlier than aMCI. Future studies should aim to associate the atrophy of the hippocampal subfields in SCD with possible conversion to aMCI or AD with longitudinal design.
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Affiliation(s)
- Weina Zhao
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.,Department of Neurology, Mudanjiang Medical University Affiliated Hongqi Hospital, Mudanjiang, China
| | - Xuetong Wang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Changhao Yin
- Department of Neurology, Mudanjiang Medical University Affiliated Hongqi Hospital, Mudanjiang, China
| | - Mengfei He
- Department of Neurology, Mudanjiang Medical University Affiliated Hongqi Hospital, Mudanjiang, China
| | - Shuyu Li
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.,Institute of Alzheimer Disease, Beijing Institute for Brain Disorders, Beijing, China.,Institute of Geriatrics, Beijing Hospital, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
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34
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Peraza LR, Díaz-Parra A, Kennion O, Moratal D, Taylor JP, Kaiser M, Bauer R. Structural connectivity centrality changes mark the path toward Alzheimer's disease. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:98-107. [PMID: 30723773 PMCID: PMC6350419 DOI: 10.1016/j.dadm.2018.12.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Introduction The pathophysiological process of Alzheimer's disease is thought to begin years before clinical decline, with evidence suggesting prion-like spreading processes of neurofibrillary tangles and amyloid plaques. Methods Using diffusion magnetic resonance imaging data from the Alzheimer's Disease Neuroimaging Initiative database, we first identified relevant features for dementia diagnosis. We then created dynamic models with the Nathan Kline Institute-Rockland Sample database to estimate the earliest detectable stage associated with dementia in the simulated disease progression. Results A classifier based on centrality measures provides informative predictions. Strength and closeness centralities are the most discriminative features, which are associated with the medial temporal lobe and subcortical regions, together with posterior and occipital brain regions. Our model simulations suggest that changes associated with dementia begin to manifest structurally at early stages. Discussion Our analyses suggest that diffusion magnetic resonance imaging–based centrality measures can offer a tool for early disease detection before clinical dementia onset.
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Affiliation(s)
- Luis R Peraza
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Antonio Díaz-Parra
- Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain
| | - Oliver Kennion
- Interdisciplinary Computing and Complex Biosystems Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - David Moratal
- Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Marcus Kaiser
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom.,Interdisciplinary Computing and Complex Biosystems Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Roman Bauer
- Interdisciplinary Computing and Complex Biosystems Research Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.,Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
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35
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The Lifespan Human Connectome Project in Aging: An overview. Neuroimage 2018; 185:335-348. [PMID: 30332613 DOI: 10.1016/j.neuroimage.2018.10.009] [Citation(s) in RCA: 168] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 09/21/2018] [Accepted: 10/04/2018] [Indexed: 12/31/2022] Open
Abstract
The original Human Connectome Project yielded a rich data set on structural and functional connectivity in a large sample of healthy young adults using improved methods of data acquisition, analysis, and sharing. More recent efforts are extending this approach to include infants, children, older adults, and brain disorders. This paper introduces and describes the Human Connectome Project in Aging (HCP-A), which is currently recruiting 1200 + healthy adults aged 36 to 100+, with a subset of 600 + participants returning for longitudinal assessment. Four acquisition sites using matched Siemens Prisma 3T MRI scanners with centralized quality control and data analysis are enrolling participants. Data are acquired across multimodal imaging and behavioral domains with a focus on factors known to be altered in advanced aging. MRI acquisitions include structural (whole brain and high resolution hippocampal) plus multiband resting state functional (rfMRI), task fMRI (tfMRI), diffusion MRI (dMRI), and arterial spin labeling (ASL). Behavioral characterization includes cognitive (such as processing speed and episodic memory), psychiatric, metabolic, and socioeconomic measures as well as assessment of systemic health (with a focus on menopause via hormonal assays). This dataset will provide a unique resource for examining how brain organization and connectivity changes across typical aging, and how these differences relate to key characteristics of aging including alterations in hormonal status and declining memory and general cognition. A primary goal of the HCP-A is to make these data freely available to the scientific community, supported by the Connectome Coordination Facility (CCF) platform for data quality assurance, preprocessing and basic analysis, and shared via the NIMH Data Archive (NDA). Here we provide the rationale for our study design and sufficient details of the resource for scientists to plan future analyses of these data. A companion paper describes the related Human Connectome Project in Development (HCP-D, Somerville et al., 2018), and the image acquisition protocol common to both studies (Harms et al., 2018).
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Mak E, Bethlehem RA, Romero-Garcia R, Cervenka S, Rittman T, Gabel S, Surendranathan A, Bevan-Jones RW, Passamonti L, Vázquez Rodríguez P, Su L, Arnold R, Williams GB, Hong YT, Fryer TD, Aigbirhio FI, Rowe JB, O'Brien JT. In vivo coupling of tau pathology and cortical thinning in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2018; 10:678-687. [PMID: 30426064 PMCID: PMC6222030 DOI: 10.1016/j.dadm.2018.08.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
INTRODUCTION The deposition of neurofibrillary tangles in neurodegenerative disorders is associated with neuronal loss on autopsy; however, their in vivo associations with atrophy across the continuum of Alzheimer's disease (AD) remain unclear. METHODS We estimated cortical thickness, tau ([18F]-AV-1451), and amyloid β (Aβ) status ([11C]-PiB) in 47 subjects who were stratified into Aβ- (14 healthy controls and six mild cognitive impairment-Aβ-) and Aβ+ (14 mild cognitive impairment-Aβ+ and 13 AD) groups. RESULTS Compared with the Aβ- group, tau was increased in widespread regions whereas cortical thinning was restricted to the temporal cortices. Increased tau binding was associated with cortical thinning in each Aβ group. Locally, regional tau was associated with temporoparietal atrophy. DISCUSSION These findings position tau as a promising therapeutic target. Further studies are needed to elucidate the casual relationships between tau pathology and trajectories of atrophy in AD.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | | | - Simon Cervenka
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm County Council, Stockholm, Sweden
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Silvy Gabel
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory for Cognitive Neurology, University of Leuven, Leuven, Belgium
| | | | | | - Luca Passamonti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- China-UK Centre for Cognition and Ageing Research, Southwest University, Chongqing, China
| | - Robert Arnold
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Guy B. Williams
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Young T. Hong
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Tim D. Fryer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Franklin I. Aigbirhio
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - James B. Rowe
- Medical Research Council, and Brain Sciences Unit, Cambridge, UK
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - John T. O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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Mak E, Donaghy PC, McKiernan E, Firbank MJ, Lloyd J, Petrides GS, Thomas AJ, O'Brien JT. Beta amyloid deposition maps onto hippocampal and subiculum atrophy in dementia with Lewy bodies. Neurobiol Aging 2018; 73:74-81. [PMID: 30339962 DOI: 10.1016/j.neurobiolaging.2018.09.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Revised: 09/05/2018] [Accepted: 09/06/2018] [Indexed: 10/28/2022]
Abstract
Although dementia with Lewy bodies (DLB) is a synucleinopathy, it is frequently accompanied by beta amyloid (Aβ) accumulation. Elucidating the relationships of Aβ with gray matter atrophy in DLB may yield insights regarding the contributions of comorbid Alzheimer's disease to its disease progression. Twenty healthy controls and 25 DLB subjects underwent clinical assessment, [18F]-Florbetapir, and 3T magnetic resonance imaging. FreeSurfer was used to estimate cortical thickness and subcortical volumes, and PetSurfer was used to quantify [18F]-Florbetapir standardized uptake value ratio. Principal component analysis was used to identify the dominant Aβ component for correlations with regional cortical thickness, hippocampal subfields, and subcortical structures. Relative to healthy controls, the DLB group demonstrated increased Aβ in widespread regions encompassing the frontal and temporoparietal cortices, whereas cortical thinning was restricted to the temporal lobe. Among DLB subjects, the Aβ component was significantly associated with more severe hippocampal and subiculum atrophy. These findings may reflect an early process of superimposed AD-like atrophy in DLB, thereby conferring support for the therapeutic potential of anti-Aβ interventions in people with DLB.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Paul C Donaghy
- Institute for Ageing and Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | | | - Michael J Firbank
- Institute for Ageing and Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Jim Lloyd
- Nuclear Medicine Department, Newcastle Upon Tyne Hospitals, NHS Foundation Trust, Newcastle upon Tyne, UK
| | - George S Petrides
- Nuclear Medicine Department, Newcastle Upon Tyne Hospitals, NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Alan J Thomas
- Institute for Ageing and Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
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Corlier F, Hafzalla G, Faskowitz J, Kuller LH, Becker JT, Lopez OL, Thompson PM, Braskie MN. Systemic inflammation as a predictor of brain aging: Contributions of physical activity, metabolic risk, and genetic risk. Neuroimage 2018; 172:118-129. [PMID: 29357308 PMCID: PMC5954991 DOI: 10.1016/j.neuroimage.2017.12.027] [Citation(s) in RCA: 66] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 12/01/2017] [Accepted: 12/11/2017] [Indexed: 12/17/2022] Open
Abstract
Inflammatory processes may contribute to risk for Alzheimer's disease (AD) and age-related brain degeneration. Metabolic and genetic risk factors, and physical activity may, in turn, influence these inflammatory processes. Some of these risk factors are modifiable, and interact with each other. Understanding how these processes together relate to brain aging will help to inform future interventions to treat or prevent cognitive decline. We used brain magnetic resonance imaging (MRI) to scan 335 older adult humans (mean age 77.3 ± 3.4 years) who remained non-demented for the duration of the 9-year longitudinal study. We used structural equation modeling (SEM) in a subset of 226 adults to evaluate whether measures of baseline peripheral inflammation (serum C-reactive protein levels; CRP), mediated the baseline contributions of genetic and metabolic risk, and physical activity, to regional cortical thickness in AD-relevant brain regions at study year 9. We found that both baseline metabolic risk and AD risk variant apolipoprotein E ε4 (APOE4), modulated baseline serum CRP. Higher baseline CRP levels, in turn, predicted thinner regional cortex at year 9, and mediated an effect between higher metabolic risk and thinner cortex in those regions. A higher polygenic risk score composed of variants in immune-associated AD risk genes (other than APOE) was associated with thinner regional cortex. However, CRP levels did not mediate this effect, suggesting that other mechanisms may be responsible for the elevated AD risk. We found interactions between genetic and environmental factors and structural brain health. Our findings support the role of metabolic risk and peripheral inflammation in age-related brain decline.
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Affiliation(s)
- Fabian Corlier
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA
| | - George Hafzalla
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA
| | - Joshua Faskowitz
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA
| | - Lewis H Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - James T Becker
- Departments of Neurology, Psychiatry, and Psychology, University of Pittsburgh, Pittsburgh, PA 15139, USA
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA; Depts. of Neurology, Psychiatry, Engineering, Radiology, & Ophthalmology, Keck/USC School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Meredith N Braskie
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA.
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Chouliaras L, Pishva E, Haapakoski R, Zsoldos E, Mahmood A, Filippini N, Burrage J, Mill J, Kivimäki M, Lunnon K, Ebmeier KP. Peripheral DNA methylation, cognitive decline and brain aging: pilot findings from the Whitehall II imaging study. Epigenomics 2018; 10:585-595. [PMID: 29692214 PMCID: PMC6021930 DOI: 10.2217/epi-2017-0132] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: The present study investigated the link between peripheral DNA methylation (DNAm), cognitive impairment and brain aging. Methods: We tested the association between blood genome-wide DNAm profiles using the Illumina 450K arrays, cognitive dysfunction and brain MRI measures in selected participants of the Whitehall II imaging sub-study. Results: Eight differentially methylated regions were associated with cognitive impairment. Accelerated aging based on the Hannum epigenetic clock was associated with mean diffusivity and global fractional anisotropy. We also identified modules of co-methylated loci associated with white matter hyperintensities. These co-methylation modules were enriched among pathways relevant to β-amyloid processing and glutamatergic signaling. Conclusion: Our data support the notion that blood DNAm changes may have utility as a biomarker for cognitive dysfunction and brain aging.
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Affiliation(s)
- Leonidas Chouliaras
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.,Current: Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Ehsan Pishva
- University of Exeter Medical School, RILD, University of Exeter, Barrack Road, Exeter, UK.,Department of Psychiatry & Neuropsychology, School for Mental Health & Neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
| | - Rita Haapakoski
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.,Department of Epidemiology & Public Health, University College London, London, UK
| | - Eniko Zsoldos
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Abda Mahmood
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Nicola Filippini
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Joe Burrage
- University of Exeter Medical School, RILD, University of Exeter, Barrack Road, Exeter, UK
| | - Jonathan Mill
- University of Exeter Medical School, RILD, University of Exeter, Barrack Road, Exeter, UK
| | - Mika Kivimäki
- Department of Epidemiology & Public Health, University College London, London, UK.,Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Katie Lunnon
- University of Exeter Medical School, RILD, University of Exeter, Barrack Road, Exeter, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
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A longitudinal study of brain anatomy changes preceding dementia in Down syndrome. NEUROIMAGE-CLINICAL 2018; 18:160-166. [PMID: 29868444 PMCID: PMC5984600 DOI: 10.1016/j.nicl.2018.01.024] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 12/18/2017] [Accepted: 01/18/2018] [Indexed: 12/21/2022]
Abstract
Background We longitudinally assessed Down syndrome individuals at the age of risk of developing dementia to measure changes in brain anatomy and their relationship to cognitive impairment progression. Methods Forty-two Down syndrome individuals were initially included, of whom 27 (mean age 46.8 years) were evaluable on the basis of completing the 2-year follow-up and success in obtaining good quality MRI exams. Voxel-based morphometry was used to estimate regional brain volumes at baseline and follow-up on 3D anatomical images. Longitudinal volume changes for the group and their relationship with change in general cognitive status and specific cognitive domains were mapped. Results As a group, significant volume reduction was identified in the substantia innominata region of the basal forebrain, hippocampus, lateral temporal cortex and left arcuate fasciculus. Volume reduction in the substantia innominata and hippocampus was more prominent in individuals whose clinical status changed from cognitively stable to mild cognitive impairment or dementia during the follow-up. Relevantly, longitudinal memory score change was specifically associated with volume change in the hippocampus, prospective memory with prefrontal lobe and verbal comprehension with language-related brain areas. Conclusions Results are notably concordant with the well-established anatomical changes signaling the progression to dementia in Alzheimer's disease, despite the dense baseline pathology that developmentally accumulates in Down syndrome. This commonality supports the potential value of Down syndrome as a genetic model of Alzheimer's neurodegeneration and may serve to further support the view that Down syndrome patients are best candidates to benefit from treatment research in Alzheimer's disease.
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Mito R, Raffelt D, Dhollander T, Vaughan DN, Tournier JD, Salvado O, Brodtmann A, Rowe CC, Villemagne VL, Connelly A. Fibre-specific white matter reductions in Alzheimer’s disease and mild cognitive impairment. Brain 2018; 141:888-902. [DOI: 10.1093/brain/awx355] [Citation(s) in RCA: 159] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 11/08/2017] [Indexed: 12/13/2022] Open
Affiliation(s)
- Remika Mito
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3084, Australia
| | - David Raffelt
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, 3084, Australia
| | - Thijs Dhollander
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, 3084, Australia
| | - David N Vaughan
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3084, Australia
- Department of Neurology, Austin Health, Heidelberg, Victoria, 3084, Australia
| | - J-Donald Tournier
- Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, WC2R 2LS, UK
- Centre for the Developing Brain, King’s College London, London, WC2R 2LS, UK
| | - Olivier Salvado
- CSIRO, Health and Biosecurity, The Australian eHealth Research Centre, Brisbane, Queensland, 4029, Australia
| | - Amy Brodtmann
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3084, Australia
- Eastern Clinical Research Unit, Monash University, Box Hill Hospital, Melbourne, Victoria, 3128, Australia
| | - Christopher C Rowe
- Department of Medicine, Austin Health, University of Melbourne, Heidelberg, Victoria, 3084, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Victoria, 3084, Australia
| | - Victor L Villemagne
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, 3084, Australia
- Department of Medicine, Austin Health, University of Melbourne, Heidelberg, Victoria, 3084, Australia
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Victoria, 3084, Australia
| | - Alan Connelly
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3084, Australia
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Castrillo JI, Lista S, Hampel H, Ritchie CW. Systems Biology Methods for Alzheimer’s Disease Research Toward Molecular Signatures, Subtypes, and Stages and Precision Medicine: Application in Cohort Studies and Trials. Methods Mol Biol 2018; 1750:31-66. [PMID: 29512064 DOI: 10.1007/978-1-4939-7704-8_3] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Juan I Castrillo
- Genetadi Biotech S.L. Parque Tecnológico de Bizkaia, Derio, Bizkaia, Spain.
| | - Simone Lista
- AXA Research Fund & UPMC Chair, F-75013, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France
| | - Harald Hampel
- AXA Research Fund & UPMC Chair, F-75013, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France
| | - Craig W Ritchie
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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Mak E, Su L, Williams GB, Firbank MJ, Lawson RA, Yarnall AJ, Duncan GW, Mollenhauer B, Owen AM, Khoo TK, Brooks DJ, Rowe JB, Barker RA, Burn DJ, O'Brien JT. Longitudinal whole-brain atrophy and ventricular enlargement in nondemented Parkinson's disease. Neurobiol Aging 2017; 55:78-90. [PMID: 28431288 PMCID: PMC5454799 DOI: 10.1016/j.neurobiolaging.2017.03.012] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Revised: 03/05/2017] [Accepted: 03/08/2017] [Indexed: 11/28/2022]
Abstract
We investigated whole-brain atrophy and ventricular enlargement over 18 months in nondemented Parkinson's disease (PD) and examined their associations with clinical measures and baseline CSF markers. PD subjects (n = 100) were classified at baseline into those with mild cognitive impairment (MCI; PD-MCI, n = 36) and no cognitive impairment (PD-NC, n = 64). Percentage of whole-brain volume change (PBVC) and ventricular expansion over 18 months were assessed with FSL-SIENA and ventricular enlargement (VIENA) respectively. PD-MCI showed increased global atrophy (-1.1% ± 0.8%) and ventricular enlargement (6.9 % ± 5.2%) compared with both PD-NC (PBVC: -0.4 ± 0.5, p < 0.01; VIENA: 2.1% ± 4.3%, p < 0.01) and healthy controls. In a subset of 35 PD subjects, CSF levels of tau, and Aβ42/Aβ40 ratio were correlated with PBVC and ventricular enlargement respectively. The sample size required to demonstrate a 20% reduction in PBVC and VIENA was approximately 1/15th of that required to detect equivalent changes in cognitive decline. These findings suggest that longitudinal MRI measurements have potential to serve as surrogate markers to complement clinical assessments for future disease-modifying trials in PD.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
| | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
| | - Guy B Williams
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridgeshire, UK
| | - Michael J Firbank
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Rachael A Lawson
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Alison J Yarnall
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Gordon W Duncan
- Medicine of the Elderly, Western General Hospital, Edinburgh, UK
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany; University Medical Center Goettingen, Institute of Neuropathology, Goettingen, Germany
| | - Adrian M Owen
- Brain and Mind Institute, University of Western Ontario, London, Canada; Department of Psychology, University of Western Ontario, London, Canada
| | - Tien K Khoo
- Menzies Health Institute, Queensland and School of Medicine, Griffith University, Gold Coast, Australia
| | - David J Brooks
- Division of Neuroscience, Imperial College London, London, UK; Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Medical Research Council, Cognition and Brain Sciences Unit, Cambridge, UK; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Roger A Barker
- John van Geest Centre for Brain Repair, University of Cambridge, Cambridge, UK
| | - David J Burn
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridgeshire, UK.
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