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Evans TE, Vilor-Tejedor N, Operto G, Falcon C, Hofman A, Ibáñez A, Seshadari S, Tan LC, Weiner M, Alladi S, Anazodo U, Gispert Lopez JD, Adams HHH. Structural brain differences in the Alzheimer's disease continuum: Insights into the heterogeneity from a large multi-site neuroimaging consortium. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00207-6. [PMID: 39084525 DOI: 10.1016/j.bpsc.2024.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 06/08/2024] [Accepted: 07/09/2024] [Indexed: 08/02/2024]
Abstract
INTRODUCTION Neurodegenerative diseases require collaborative, multi-site research to comprehensively grasp their complex and diverse pathological progression, yet there is caution in aggregating global data due to data heterogeneity. The current study investigates brain structure across stages of Alzheimer's disease (AD), and how relationships vary across sources of heterogeneity. METHODS Using 6 international datasets(n>27,000), associations of structural neuroimaging markers were investigated in relation to the AD continuum via meta-analysis. We investigated whether associations varied across elements of MRI acquisition, study design and populations. RESULTS Modest differences in associations were found dependent on how data were acquired, however patterns were similar. Preliminary results suggest neuroimaging marker-AD relationships differ across ethnic groups. DISCUSSION Diversity in data offers unique insights into the neural substrate of AD, however harmonised processing and transparency of data collection is needed. Global collaborations should embrace inherent heterogeneity that exists within the data and quantify its contribution to research findings at the meta-analytical stage.
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Affiliation(s)
- Tavia E Evans
- Department of Clinical Genetics, Erasmus MC, Wytemaweg 80, 3015 CE, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Wytemaweg 80, 3015 CE, Rotterdam, the Netherlands
| | - Natalia Vilor-Tejedor
- Department of Clinical Genetics, Erasmus MC, Wytemaweg 80, 3015 CE, Rotterdam, the Netherlands; Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, 08005 Barcelona, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, C/ del Dr. Aiguader, 88, 08003 Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), C/ del Dr. Aiguader, 88, 08003 Barcelona, Spain
| | - Gregory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, 08005 Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, 08005 Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), C/ del Dr. Aiguader, 88, 08003 Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), C/ del Dr. Aiguader, 88, 08003 Barcelona, Spain
| | - Albert Hofman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, United States
| | - Agustin Ibáñez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Av. Diag. Las Torres 2640, 7941169, Santiago, Peñalolén, Región Metropolitana, Chile; Universidad de San Andrés & Consejo Nacional de Investigaciones Científicas y técnicas (CONICET), Vito Dumas 284, B1644BID Victoria, Provincia de Buenos, Aires, Argentina; Global Brain Health Institute (GBHI), Trinity College Dublin, (TCD), College Green, D02 PN40, Dublin, Ireland
| | - Sudha Seshadari
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, 8300 Floyd Curl Drive, San Antonio, TX, 78229, United States of America
| | - Louis Cs Tan
- Department of Neurology, National Neuroscience Institute, 11 Jln Tan Tock Seng, Level 1, 308433, Singapore, Singapore; Parkinson's Disease and Movement Disorders Centre, International Centre of Excellence, USA Parkinson Foundation, 191 Bishan Street 13, #01-415 Block 191, 570191, Singapore, Singapore
| | - Michael Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, VA Medical Center, 4150 Clement St., 114M, 94121, San Francisco, California, United States of America; Department of Neurology, University of California, 1651 4th St, 94158, San Francisco, California, United States of America
| | - Suverna Alladi
- Department of Neurology, National Institute of Mental Health & Neurosciences, No.29, Hosur Rd, Lakkasandra, Ayappa Garden, Adugodi, 560030, Bengaluru, India
| | - Udunna Anazodo
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 Rue University, H3A 2B4, Montreal, Quebec, Canada
| | - Juan Domingo Gispert Lopez
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, C/ de Wellington, 30, 08005 Barcelona, Spain; Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), C. de Melchor Fernández Almagro, 3, 28029 Madrid, Spain; IMIM (Hospital del Mar Medical Research Institute), C/ del Dr. Aiguader, 88, 08003 Barcelona, Spain; Centro Nacional de Investigaciones Cardiovasculares (CNIC), C. de Melchor Fernández Almagro, 3, 28029, Madrid, Spain
| | - Hieab H H Adams
- Department of Clinical Genetics, Erasmus MC, Wytemaweg 80, 3015 CE, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Wytemaweg 80, 3015 CE, Rotterdam, the Netherlands; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Av. Diag. Las Torres 2640, 7941169, Santiago, Peñalolén, Región Metropolitana, Chile.
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Piersson AD, Mohamad M, Suppiah S, Rajab NF. Topographical patterns of whole-brain structural alterations in association with genetic risk, cerebrospinal fluid, positron emission tomography biomarkers of Alzheimer’s disease, and neuropsychological measures. Clin Transl Imaging 2021. [DOI: 10.1007/s40336-021-00440-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Rizzi L, Aventurato ÍK, Balthazar MLF. Neuroimaging Research on Dementia in Brazil in the Last Decade: Scientometric Analysis, Challenges, and Peculiarities. Front Neurol 2021; 12:640525. [PMID: 33790850 PMCID: PMC8005640 DOI: 10.3389/fneur.2021.640525] [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: 12/11/2020] [Accepted: 02/18/2021] [Indexed: 12/12/2022] Open
Abstract
The last years have evinced a remarkable growth in neuroimaging studies around the world. All these studies have contributed to a better understanding of the cerebral outcomes of dementia, even in the earliest phases. In low- and middle-income countries, studies involving structural and functional neuroimaging are challenging due to low investments and heterogeneous populations. Outstanding the importance of diagnosing mild cognitive impairment and dementia, the purpose of this paper is to offer an overview of neuroimaging dementia research in Brazil. The review includes a brief scientometric analysis of quantitative information about the development of this field over the past 10 years. Besides, discusses some peculiarities and challenges that have limited neuroimaging dementia research in this big and heterogeneous country of Latin America. We systematically reviewed existing neuroimaging literature with Brazilian authors that presented outcomes related to a dementia syndrome, published from 2010 to 2020. Briefly, the main neuroimaging methods used were morphometrics, followed by fMRI, and DTI. The major diseases analyzed were Alzheimer's disease, mild cognitive impairment, and vascular dementia, respectively. Moreover, research activity in Brazil has been restricted almost entirely to a few centers in the Southeast region, and funding could be the main driver for publications. There was relative stability concerning the number of publications per year, the citation impact has historically been below the world average, and the author's gender inequalities are not relevant in this specific field. Neuroimaging research in Brazil is far from being developed and widespread across the country. Fortunately, increasingly collaborations with foreign partnerships contribute to the impact of Brazil's domestic research. Although the challenges, neuroimaging researches performed in the native population regarding regional peculiarities and adversities are of pivotal importance.
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Affiliation(s)
- Liara Rizzi
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
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Harrison JR, Mistry S, Muskett N, Escott-Price V. From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review. J Alzheimers Dis 2020; 74:1271-1283. [PMID: 32250305 PMCID: PMC7242840 DOI: 10.3233/jad-191233] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/12/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD. OBJECTIVE This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration. METHODS We searched the literature from July 2008-July 2018 following PRISMA guidelines. RESULTS 57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes. CONCLUSION PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.
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Affiliation(s)
- Judith R. Harrison
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
| | - Sumit Mistry
- MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
| | - Natalie Muskett
- Cardiff University Medical School, University Hospital of Wales, Cardiff, UK
| | - Valentina Escott-Price
- Dementia Research Institute & the MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
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Abstract
Radiogenomics, defined as the integrated analysis of radiologic imaging and genetic data, is a well-established tool shown to augment neuroimaging in the clinical diagnosis, prognostication, and scientific study of late-onset Alzheimer disease (LOAD). Early work using candidate single nucleotide polymorphisms (SNPs) identified genetic variation in APOE, BIN1, CLU, and CR1 as key modifiers of brain structure and function using magnetic resonance imaging (MRI). More recently, polygenic risk scores used in conjunction with MRI and positron emission tomography have shown great promise as a risk-stratification tool for clinical trials and care-management decisions. In addition, recent work using multimodal MRI and positron emission tomography as proxies of LOAD progression has identified novel risk variants that are enhancing our understanding of LOAD pathophysiology and progression. Herein, we highlight key studies and trends in the radiogenomics of LOAD over the past two decades and their implications for clinical practice and scientific research.
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Shu H, Shi Y, Chen G, Wang Z, Liu D, Yue C, Ward BD, Li W, Xu Z, Chen G, Guo QH, Xu J, Li SJ, Zhang Z. Distinct neural correlates of episodic memory among apolipoprotein E alleles in cognitively normal elderly. Brain Imaging Behav 2019; 13:255-269. [PMID: 29396739 DOI: 10.1007/s11682-017-9818-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The apolipoprotein E (APOE) ε4 and ε2 alleles are acknowledged genetic factors modulating Alzheimer's disease (AD) risk and episodic memory (EM) deterioration in an opposite manner. Mounting neuroimaging studies describe EM-related brain activity differences among APOE alleles but remain limited in elucidating the underlying mechanism. Here, we hypothesized that the APOE ε2, ε3, and ε4 alleles have distinct EM neural substrates, as a manifestation of degeneracy, underlying their modulations on EM-related brain activity and AD susceptibility. To test the hypothesis, we identified neural correlates of EM function by correlating intrinsic hippocampal functional connectivity networks with neuropsychological EM performances in a voxelwise manner, with 129 cognitively normal elderly subjects (36 ε2 carriers, 44 ε3 homozygotes, and 49 ε4 carriers). We demonstrated significantly different EM neural correlates among the three APOE allele groups. Specifically, in the ε3 homozygotes, positive EM neural correlates were characterized in the Papez circuit regions; in the ε4 carriers, positive EM neural correlates involved the lateral temporal cortex, premotor cortex/sensorimotor cortex/superior parietal lobule, and cuneus; and in the ε2 carriers, negative EM neural correlates appeared in the bilateral frontopolar, posteromedial, and sensorimotor cortex. Further, in the ε4 carriers, the interaction between age and EM function occurred in the temporoparietal junction and prefrontal cortex. Our findings suggest that the underlying mechanism of APOE polymorphism modulations on EM function and AD susceptibility is genetically related to the neural degeneracy of EM function across APOE alleles.
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Affiliation(s)
- Hao Shu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Yongmei Shi
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - Gang Chen
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - Duan Liu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - Chunxian Yue
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - B Douglas Ward
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Wenjun Li
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Zhan Xu
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Guangyu Chen
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Qi-Hao Guo
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Jun Xu
- Department of Neurology, Jiangsu Province Geriatric Institute, Nanjing, Jiangsu, 210024, China
| | - Shi-Jiang Li
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China.
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Alzheimer Disease-associated Cortical Atrophy Does not Differ Between Chinese and Whites. Alzheimer Dis Assoc Disord 2019; 33:186-193. [PMID: 31094707 DOI: 10.1097/wad.0000000000000315] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE To assess whether there are differences in Alzheimer disease (AD)-associated atrophy regions in Chinese and white patients with AD versus cognitively normal older adults, and to test whether associations between clinical severity and gray matter volume are similar or different across these ethnic groups in a cross-sectional analysis. MATERIALS AND METHODS Chinese and white patients with AD, individuals with mild cognitive impairment, and cognitively normal controls (46 white and 48 Chinese) were clinically evaluated at an academic center within 1 year of magnetic resonance imaging acquisition. Clinical severity was assessed using the Clinical Dementia Rating Sum of Boxes and cortical atrophy was measured using voxel-based morphometry as well as Freesurfer. Chinese and white cohorts were demographically matched for age, sex, and education. RESULTS Clinical severity by diagnosis was similar across ethnicities. Chinese and white patient groups showed similar amounts of atrophy in the regions most affected in AD after accounting for demographic variables and head size. There was no significant difference between ethnic groups when compared by atrophy and clinical severity. CONCLUSIONS Our study suggests that Chinese and white patients with AD, when matched demographically, are clinically and neuroanatomically similar on normalized measures of cortical atrophy and clinical severity.
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Bonham LW, Sirkis DW, Fan J, Aparicio RE, Tse M, Ramos EM, Wang Q, Coppola G, Rosen HJ, Miller BL, Yokoyama JS. Identification of a rare coding variant in TREM2 in a Chinese individual with Alzheimer's disease. Neurocase 2017; 23:65-69. [PMID: 28376694 PMCID: PMC5639900 DOI: 10.1080/13554794.2017.1294182] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Rare variation in the TREM2 gene is associated with a broad spectrum of neurodegenerative disorders including Alzheimer's disease (AD). TREM2 encodes a receptor expressed in microglia which is thought to influence neurodegeneration by sensing damage signals and regulating neuroinflammation. Many of the variants reported to be associated with AD, including the rare R47H variant, were discovered in populations of European ancestry and have not replicated in diverse populations from other genetic backgrounds. We utilized a cohort of elderly Chinese individuals diagnosed as cognitively normal, or with mild cognitive impairment or AD to identify a rare variant, A192T, present in a single patient diagnosed with AD. We characterized this variant using biochemical cell surface expression assays and found that it significantly altered cell surface expression of the TREM2 protein. Together these data provide evidence that the A192T variant in TREM2 could contribute risk for AD. This study underscores the increasingly recognized role of immune-related processes in AD and highlights the importance of including diverse populations in research to identify genetic variation that contributes risk for AD and other neurodegenerative disorders.
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Affiliation(s)
- Luke W Bonham
- a Memory and Aging Center, Department of Neurology , University of California, San Francisco , San Francisco , CA , USA
| | - Daniel W Sirkis
- b Department of Molecular and Cell Biology, Howard Hughes Medical Institute , University of California, Berkeley , Berkeley , CA , USA
| | - Jia Fan
- a Memory and Aging Center, Department of Neurology , University of California, San Francisco , San Francisco , CA , USA.,c Department of Neurology , Second Hospital of Jilin University , Changchun , China
| | - Renan E Aparicio
- b Department of Molecular and Cell Biology, Howard Hughes Medical Institute , University of California, Berkeley , Berkeley , CA , USA
| | - Marian Tse
- a Memory and Aging Center, Department of Neurology , University of California, San Francisco , San Francisco , CA , USA
| | - Eliana Marisa Ramos
- d Department of Psychiatry and Semel Institute for Neuroscience and Human Behavior , The David Geffen School of Medicine at University of California Los Angeles , Los Angeles , CA , USA
| | - Qing Wang
- d Department of Psychiatry and Semel Institute for Neuroscience and Human Behavior , The David Geffen School of Medicine at University of California Los Angeles , Los Angeles , CA , USA
| | - Giovanni Coppola
- d Department of Psychiatry and Semel Institute for Neuroscience and Human Behavior , The David Geffen School of Medicine at University of California Los Angeles , Los Angeles , CA , USA
| | - Howard J Rosen
- a Memory and Aging Center, Department of Neurology , University of California, San Francisco , San Francisco , CA , USA
| | - Bruce L Miller
- a Memory and Aging Center, Department of Neurology , University of California, San Francisco , San Francisco , CA , USA
| | - Jennifer S Yokoyama
- a Memory and Aging Center, Department of Neurology , University of California, San Francisco , San Francisco , CA , USA
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Santos PP, Silveira PSD, Souza-Duran FL, Tamashiro-Duran JH, Scazufca M, Menezes PR, Leite CDC, Lotufo PA, Vallada H, Wajngarten M, De Toledo Ferraz Alves TC, Rzezak P, Busatto GF. Prefrontal-Parietal White Matter Volumes in Healthy Elderlies Are Decreased in Proportion to the Degree of Cardiovascular Risk and Related to Inhibitory Control Deficits. Front Psychol 2017; 8:57. [PMID: 28184203 PMCID: PMC5266720 DOI: 10.3389/fpsyg.2017.00057] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 01/10/2017] [Indexed: 01/05/2023] Open
Abstract
Cardiovascular risk (CVR) factors may be associated with poor cognitive functioning in elderlies and impairments in brain structure. Using MRI and voxel-based morphometry (VBM), we assessed regional white matter (WM) volumes in a population-based sample of individuals aged 65–75 years (n = 156), subdivided in three CVR subgroups using the Framingham Risk Score. Cognition was assessed using the Short Cognitive Performance Test. In high-risk subjects, we detected significantly reduced WM volume in the right juxtacortical dorsolateral prefrontal region compared to both low and intermediate CVR subgroups. Findings remained significant after accounting for the presence of the APOEε4 allele. Inhibitory control performance was negatively related to right prefrontal WM volume, proportionally to the degree of CVR. Significantly reduced deep parietal WM was also detected bilaterally in the high CVR subgroup. This is the first large study documenting the topography of CVR-related WM brain volume deficits. The significant association regarding poor response inhibition indicates that prefrontal WM deficits related to CVR are clinically meaningful, since inhibitory control is known to rely on prefrontal integrity.
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Affiliation(s)
- Pedro P Santos
- Laboratory of Psychiatric Neuroimaging, Institute and Department of Psychiatry, Universidade de São PauloSão Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil
| | - Paula S Da Silveira
- Laboratory of Psychiatric Neuroimaging, Institute and Department of Psychiatry, Universidade de São PauloSão Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil
| | - Fabio L Souza-Duran
- Laboratory of Psychiatric Neuroimaging, Institute and Department of Psychiatry, Universidade de São PauloSão Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil
| | - Jaqueline H Tamashiro-Duran
- Laboratory of Psychiatric Neuroimaging, Institute and Department of Psychiatry, Universidade de São PauloSão Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil
| | - Márcia Scazufca
- Department and Institute of Psychiatry, University of São Paulo São Paulo, Brazil
| | - Paulo R Menezes
- Department of Preventive Medicine, Faculty of Medicine, University of São PauloSão Paulo, Brazil; Center of Research in Mental Health Population, University of São PauloSão Paulo, Brazil
| | - Claudia Da Costa Leite
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil; Laboratory of Magnetic Resonance in Neuroradiology, Institute and Department of Radiology, University of São PauloSão Paulo, Brazil
| | - Paulo A Lotufo
- Department of Internal Medicine, Center for Clinical and Epidemiologic Research, University of São Paulo São Paulo, Brazil
| | - Homero Vallada
- Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil; Department and Institute of Psychiatry, University of São PauloSão Paulo, Brazil
| | - Maurício Wajngarten
- Department of Cardiopneumology, Heart Institute, General Hospital of University of São Paulo Medical School São Paulo, Brazil
| | - Tânia C De Toledo Ferraz Alves
- Laboratory of Psychiatric Neuroimaging, Institute and Department of Psychiatry, Universidade de São PauloSão Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil
| | - Patricia Rzezak
- Laboratory of Psychiatric Neuroimaging, Institute and Department of Psychiatry, Universidade de São PauloSão Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil; Laboratory of Clinical Neurophysiology, Institute of Psychiatry, University of São Paulo Medical School (IPq-HC-FMUSP)São Paulo, Brazil
| | - Geraldo F Busatto
- Laboratory of Psychiatric Neuroimaging, Institute and Department of Psychiatry, Universidade de São PauloSão Paulo, Brazil; Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São PauloSão Paulo, Brazil
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Wang S, Zhang Y, Liu G, Phillips P, Yuan TF. Detection of Alzheimer's Disease by Three-Dimensional Displacement Field Estimation in Structural Magnetic Resonance Imaging. J Alzheimers Dis 2016; 50:233-48. [PMID: 26682696 DOI: 10.3233/jad-150848] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Within the past decade, computer scientists have developed many methods using computer vision and machine learning techniques to detect Alzheimer's disease (AD) in its early stages. OBJECTIVE However, some of these methods are unable to achieve excellent detection accuracy, and several other methods are unable to locate AD-related regions. Hence, our goal was to develop a novel AD brain detection method. METHODS In this study, our method was based on the three-dimensional (3D) displacement-field (DF) estimation between subjects in the healthy elder control group and AD group. The 3D-DF was treated with AD-related features. The three feature selection measures were used in the Bhattacharyya distance, Student's t-test, and Welch's t-test (WTT). Two non-parallel support vector machines, i.e., generalized eigenvalue proximal support vector machine and twin support vector machine (TSVM), were then used for classification. A 50 × 10-fold cross validation was implemented for statistical analysis. RESULTS The results showed that "3D-DF+WTT+TSVM" achieved the best performance, with an accuracy of 93.05 ± 2.18, a sensitivity of 92.57 ± 3.80, a specificity of 93.18 ± 3.35, and a precision of 79.51 ± 2.86. This method also exceled in 13 state-of-the-art approaches. Additionally, we were able to detect 17 regions related to AD by using the pure computer-vision technique. These regions include sub-gyral, inferior parietal lobule, precuneus, angular gyrus, lingual gyrus, supramarginal gyrus, postcentral gyrus, third ventricle, superior parietal lobule, thalamus, middle temporal gyrus, precentral gyrus, superior temporal gyrus, superior occipital gyrus, cingulate gyrus, culmen, and insula. These regions were reported in recent publications. CONCLUSIONS The 3D-DF is effective in AD subject and related region detection.
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Affiliation(s)
- Shuihua Wang
- School of Computer Science and Technology & School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China.,School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, China.,Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China
| | - Yudong Zhang
- School of Computer Science and Technology & School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China.,Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China
| | - Ge Liu
- Translational Imaging Division & MRI Unit, Columbia University & New York State Psychiatric Institute, New York, NY, USA
| | - Preetha Phillips
- School of Natural Sciences and Mathematics, Shepherd University, Shepherdstown, WV, USA
| | - Ti-Fei Yuan
- School of Computer Science and Technology & School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China
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Zhang Y, Wang S. Detection of Alzheimer's disease by displacement field and machine learning. PeerJ 2015; 3:e1251. [PMID: 26401461 PMCID: PMC4579022 DOI: 10.7717/peerj.1251] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2015] [Accepted: 08/29/2015] [Indexed: 12/26/2022] Open
Abstract
Aim. Alzheimer's disease (AD) is a chronic neurodegenerative disease. Recently, computer scientists have developed various methods for early detection based on computer vision and machine learning techniques. Method. In this study, we proposed a novel AD detection method by displacement field (DF) estimation between a normal brain and an AD brain. The DF was treated as the AD-related features, reduced by principal component analysis (PCA), and finally fed into three classifiers: support vector machine (SVM), generalized eigenvalue proximal SVM (GEPSVM), and twin SVM (TSVM). The 10-fold cross validation repeated 50 times. Results. The results showed the "DF + PCA + TSVM" achieved the accuracy of 92.75 ± 1.77, sensitivity of 90.56 ± 1.15, specificity of 93.37 ± 2.05, and precision of 79.61 ± 2.21. This result is better than or comparable with not only the other proposed two methods, but also ten state-of-the-art methods. Besides, our method discovers the AD is related to following brain regions disclosed in recent publications: Angular Gyrus, Anterior Cingulate, Cingulate Gyrus, Culmen, Cuneus, Fusiform Gyrus, Inferior Frontal Gyrus, Inferior Occipital Gyrus, Inferior Parietal Lobule, Inferior Semi-Lunar Lobule, Inferior Temporal Gyrus, Insula, Lateral Ventricle, Lingual Gyrus, Medial Frontal Gyrus, Middle Frontal Gyrus, Middle Occipital Gyrus, Middle Temporal Gyrus, Paracentral Lobule, Parahippocampal Gyrus, Postcentral Gyrus, Posterior Cingulate, Precentral Gyrus, Precuneus, Sub-Gyral, Superior Parietal Lobule, Superior Temporal Gyrus, Supramarginal Gyrus, and Uncus. Conclusion. The displacement filed is effective in detection of AD and related brain-regions.
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Affiliation(s)
- Yudong Zhang
- School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China
- Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China
| | - Shuihua Wang
- School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu, China
- Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing, Nanjing, Jiangsu, China
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