1
|
Xu C, Xiao D, Su BB, Saveron JM, Gamez D, Navia RO, Wang N, Roy U, Adjeroh DA, Wang K. Association of APOE gene with longitudinal changes of CSF amyloid beta and tau levels in Alzheimer's disease: racial differences. Neurol Sci 2024; 45:1041-1050. [PMID: 37759100 DOI: 10.1007/s10072-023-07076-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023]
Abstract
BACKGROUND The Apolipoprotein E (APOE) ε4 allele is a risk factor for late-onset Alzheimer's disease (AD). However, no investigation has focused on racial differences in the longitudinal effect of APOE genotypes on CSF amyloid beta (Aβ42) and tau levels in AD. METHODS This study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 222 participants with AD, 264 with cognitive normal (CN), and 692 with mild cognitive impairment (MCI) at baseline and two years follow-up. We used a linear mixed model to investigate the effect of APOE-ε4-genotypes on longitudinal changes in the amyloid beta and tau levels. RESULTS Individuals with 1 or 2 APOE ε4 alleles revealed significantly higher t-Tau and p-Tau, but lower amyloid beta Aβ42 compared with individuals without APOE ε4 alleles. Significantly higher levels of log-t-Tau, log-p-Tau, and low levels of log-Aβ42 were observed in the subjects with older age, being female, and the two diagnostic groups (AD and MCI). The higher p-Tau and Aβ42 values are associated with poor Mini-Mental State Examination (MMSE) performance. Non-Hispanic Africa American (AA) and Hispanic participants were associated with decreased log-t-Tau levels (β = - 0.154, p = 0.0112; β = - 0.207, and p = 0.0016, respectively) as compared to those observed in Whites. Furthermore, Hispanic participants were associated with a decreased log-p-Tau level (β = - 0.224, p = 0.0023) compared to those observed in Whites. There were no differences in Aβ42 level for non-Hispanic AA and Hispanic participants compared with White participants. CONCLUSION Our study, for the first time, showed that the APOE ε4 allele was associated with these biomarkers, however with differing degrees among racial groups.
Collapse
Affiliation(s)
- Chun Xu
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, TX, 78520, USA
| | - Danqing Xiao
- Department of STEM, School of Arts and Sciences, Regis College, Weston, MA, 02493, USA
| | - Brenda Bin Su
- Department of Pediatrics - Allergy and Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Jaime Miguel Saveron
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, TX, 78520, USA
| | - Daniela Gamez
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, TX, 78520, USA
| | - R Osvaldo Navia
- Department of Medicine and Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, 26506, USA
| | - Nianyang Wang
- Department of Health Policy and Management, School of Public Health, University of Maryland, College Park, MD, 20742, USA
| | - Upal Roy
- Department of Health and Biomedical Sciences, College of Health Professions, University of Texas Rio Grande Valley, Brownsville, TX, 78520, USA
| | - Donald A Adjeroh
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, 26506, USA
| | - Kesheng Wang
- Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, WV, 26506, USA.
| |
Collapse
|
2
|
Hwang U, Kim SW, Jung D, Kim S, Lee H, Seo SW, Seong JK, Yoon S. Real-world prediction of preclinical Alzheimer's disease with a deep generative model. Artif Intell Med 2023; 144:102654. [PMID: 37783547 DOI: 10.1016/j.artmed.2023.102654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 08/29/2023] [Accepted: 08/29/2023] [Indexed: 10/04/2023]
Abstract
Amyloid positivity is an early indicator of Alzheimer's disease and is necessary to determine the disease. In this study, a deep generative model is utilized to predict the amyloid positivity of cognitively normal individuals using proxy measures, such as structural MRI scans, demographic variables, and cognitive scores, instead of invasive direct measurements. Through its remarkable efficacy in handling imperfect datasets caused by missing data or labels, and imbalanced classes, the model outperforms previous studies and widely used machine learning approaches with an AUROC of 0.8609. Furthermore, this study illuminates the model's adaptability to diverse clinical scenarios, even when feature sets or diagnostic criteria differ from the training data. We identify the brain regions and variables that contribute most to classification, including the lateral occipital lobes, posterior temporal lobe, and APOE ϵ4 allele. Taking advantage of deep generative models, our approach can not only provide inexpensive, non-invasive, and accurate diagnostics for preclinical Alzheimer's disease, but also meet real-world requirements for clinical translation of a deep learning model, including transferability and interpretability.
Collapse
Affiliation(s)
- Uiwon Hwang
- Division of Digital Healthcare, Yonsei University, Wonju, 26493, Republic of Korea
| | - Sung-Woo Kim
- Department of Bio-convergence Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Dahuin Jung
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, 08826, Republic of Korea
| | - SeungWook Kim
- Department of Bio-convergence Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Hyejoo Lee
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea; Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea; Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Joon-Kyung Seong
- Department of Artificial Intelligence, Korea University, Seoul, 02841, Republic of Korea; School of Biomedical Engineering, Korea University, Seoul, 02841, Republic of Korea; Interdisciplinary Program in Precision Public Health, College of Health Science, Korea University, Seoul, 02841, Republic of Korea.
| | - Sungroh Yoon
- Department of Electrical and Computer Engineering, Seoul National University, Seoul, 08826, Republic of Korea; Interdisciplinary Program in Artificial Intelligence, Seoul National University, Seoul, 08826, Republic of Korea.
| |
Collapse
|
3
|
Duan H, Zhou D, Xu N, Yang T, Wu Q, Wang Z, Sun Y, Li Z, Li W, Ma F, Chen Y, Du Y, Zhang M, Yan J, Sun C, Wang G, Huang G. Association of Unhealthy Lifestyle and Genetic Risk Factors With Mild Cognitive Impairment in Chinese Older Adults. JAMA Netw Open 2023; 6:e2324031. [PMID: 37462970 DOI: 10.1001/jamanetworkopen.2023.24031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/21/2023] Open
Abstract
Importance Apolipoprotein E polymorphism ε4 (APOE ε4) and methylenetetrahydrofolate reductase (MTHFR) TT genotype are genetic risk factors of mild cognitive impairment (MCI), but whether this risk can be changed by modifiable lifestyle factors is unknown. Objective To explore whether unhealthy lifestyle (unhealthy dietary intake, current smoking, nonlimited alcohol consumption, and irregular physical activities) is associated with a higher risk of age-related MCI considering genetic risk. Design, Setting, and Participants This population-based cohort study used data from Tianjin Elderly Nutrition and Cognition (TENC) study participants, recruited from March 1, 2018, through June 30, 2021, and followed up until November 30, 2022. Participants were Chinese adults aged 60 years or older who completed the neuropsychological assessments, general physical examinations, and a personal interview. Exposures Healthy lifestyle was defined according to the Chinese Dietary Guidelines 2022, including healthy diet, regular physical activity, limited alcohol consumption, and no current smoking, categorized into healthy and unhealthy lifestyles according to weighted standardized lifestyle score. Genetic risk was defined by MTHFR TT genotype and APOE ε4, categorized into low and high genetic risk according to weighted standardized genetic risk score. Main Outcomes and Measures The main outcome was newly diagnosed MCI as identified using a modified version of Petersen criteria. Hazard ratios (HRs) and 95% CIs were estimated using Cox proportional hazard regression models. Results A total of 4665 participants were included (mean [SD] age, 67.9 [4.9] years; 2546 female [54.6%] and 2119 male [45.4%]); 653 participants with new-onset MCI (mean [SD] age, 68.4 [5.4] years; 267 female [40.9%] and 386 male [59.1%]) were identified after a median follow-up of 3.11 years (range, 0.82-4.61 years). Individuals with a low genetic risk and an unhealthy lifestyle (HR, 3.01; 95% CI, 2.38-3.79), a high genetic risk and a healthy lifestyle (HR, 2.65; 95% CI, 2.03-3.44), and a high genetic risk and an unhealthy lifestyle (HR, 3.58; 95% CI, 2.73-4.69) had a higher risk of MCI compared with participants with a low genetic risk and a healthy lifestyle. There was a synergistic interaction between lifestyle categories and genetic risk (β = 3.58; 95% CI, 2.73-4.69). Conclusions and Relevance In this cohort study of TENC participants, the findings show that unhealthy lifestyle and high genetic risk were significantly associated with a higher risk of MCI among Chinese older adults. Unhealthy lifestyle factors were associated with a higher risk of MCI regardless of genetic risk, and lifestyle and genetic risk had synergistic interactions. These findings could contribute to the development of dietary guidelines and the prevention of early-stage dementia.
Collapse
Affiliation(s)
- Huilian Duan
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Dezheng Zhou
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Ning Xu
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Tong Yang
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Qi Wu
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Zehao Wang
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Yue Sun
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Zhenshu Li
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Wen Li
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Fei Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Yongjie Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Yue Du
- Department of Social Medicine and Health Management, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Meilin Zhang
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Jing Yan
- Department of Social Medicine and Health Management, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Changqing Sun
- Neurosurgical Department of Baodi Clinical College of Tianjin Medical University, Tianjin, China
| | - Guangshun Wang
- Department of Tumor, Baodi Clinical College of Tianjin Medical University, Tianjin, China
| | - Guowei Huang
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, Tianjin, China
| |
Collapse
|
4
|
APOE Allele Frequency in Southern Greece: Exploring the Role of Geographical Gradient in the Greek Population. Geriatrics (Basel) 2022; 8:geriatrics8010001. [PMID: 36648906 PMCID: PMC9844375 DOI: 10.3390/geriatrics8010001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 12/09/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND the apolipoprotein e4 allele (APOE4) constitutes an established genetic risk factor for Alzheimer's Disease Dementia (ADD). We aimed to explore the frequency of the APOE isoforms in the Greek population of Southern Greece. METHODS peripheral blood from 175 Greek AD patients, 113 with mild cognitive impairment (MCI), and 75 healthy individuals. DNA isolation was performed with a High Pure PCR Template Kit (Roche), followed by amplification with a real-time qPCR kit (TIB MolBiol) in Roche's Light Cycler PCR platform. RESULTS APOE4 allele frequency was 20.57% in the ADD group, 17.69% in the MCI group, and 6.67% in the control group. APOE3/3 homozygosity was the most common genotype, while the frequency of APOE4/4 homozygosity was higher in the AD group (8.60%). APOE4 carrier status was associated with higher odds for ADD and MCI (OR: 4.49, 95% CI: [1.90-10.61] and OR: 3.82, 95% CI: [1.59-9.17], respectively). CONCLUSION this study examines the APOE isoforms and is the first to report a higher APOE frequency in MCI compared with healthy controls in southern Greece. Importantly, we report the occurrence of the APOE4 allele, related to ADD, as amongst the lowest globally reported, even within the nation, thus enhancing the theory of ethnicity and latitude contribution.
Collapse
|
5
|
Kulminski AM, Jain-Washburn E, Loiko E, Loika Y, Feng F, Culminskaya I. Associations of the APOE ε2 and ε4 alleles and polygenic profiles comprising APOE-TOMM40-APOC1 variants with Alzheimer's disease biomarkers. Aging (Albany NY) 2022; 14:9782-9804. [PMID: 36399096 PMCID: PMC9831745 DOI: 10.18632/aging.204384] [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: 08/04/2022] [Accepted: 10/31/2022] [Indexed: 11/19/2022]
Abstract
Capturing the genetic architecture of Alzheimer's disease (AD) is challenging because of the complex interplay of genetic and non-genetic factors in its etiology. It has been suggested that AD biomarkers may improve the characterization of AD pathology and its genetic architecture. Most studies have focused on connections of individual genetic variants with AD biomarkers, whereas the role of combinations of genetic variants is substantially underexplored. We examined the associations of the APOE ε2 and ε4 alleles and polygenic profiles comprising the ε4-encoding rs429358, TOMM40 rs2075650, and APOC1 rs12721046 polymorphisms with cerebrospinal fluid (CSF) and plasma amyloid β (Aβ40 and Aβ42) and tau biomarkers. Our findings support associations of the ε4 alleles with both plasma and CSF Aβ42 and CSF tau, and the ε2 alleles with baseline, but not longitudinal, CSF Aβ42 measurements. We found that the ε4-bearing polygenic profiles conferring higher and lower AD risks are differentially associated with tau but not Aβ42. Modulation of the effect of the ε4 alleles by TOMM40 and APOC1 variants indicates the potential genetic mechanism of differential roles of Aβ and tau in AD pathogenesis.
Collapse
Affiliation(s)
- Alexander M. Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27705, USA
| | - Ethan Jain-Washburn
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27705, USA
| | - Elena Loiko
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27705, USA
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27705, USA
| | - Fan Feng
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27705, USA
| | - Irina Culminskaya
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC 27705, USA
| | | |
Collapse
|
6
|
Dincer A, Chen CD, McKay NS, Koenig LN, McCullough A, Flores S, Keefe SJ, Schultz SA, Feldman RL, Joseph-Mathurin N, Hornbeck RC, Cruchaga C, Schindler SE, Holtzman DM, Morris JC, Fagan AM, Benzinger TLS, Gordon BA. APOE ε4 genotype, amyloid-β, and sex interact to predict tau in regions of high APOE mRNA expression. Sci Transl Med 2022; 14:eabl7646. [PMID: 36383681 PMCID: PMC9912474 DOI: 10.1126/scitranslmed.abl7646] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The apolipoprotein E (APOE) ε4 allele is strongly linked with cerebral β-amyloidosis, but its relationship with tauopathy is less established. We investigated the relationship between APOE ε4 carrier status, regional amyloid-β (Aβ), magnetic resonance imaging (MRI) volumetrics, tau positron emission tomography (PET), APOE messenger RNA (mRNA) expression maps, and cerebrospinal fluid phosphorylated tau (CSF ptau181). Three hundred fifty participants underwent imaging, and 270 had ptau181. We used computational models to evaluate the main effect of APOE ε4 carrier status on regional neuroimaging values and then the interaction of ε4 status and global Aβ on regional tau PET and brain volumes as well as CSF ptau181. Separately, we also examined the additional interactive influence of sex. We found that, for the same degree of Aβ burden, APOE ε4 carriers showed greater tau PET signal relative to noncarriers in temporal regions, but no interaction was present for MRI volumes or CSF ptau181. This potentiation of tau aggregation irrespective of sex occurred in brain regions with high APOE mRNA expression, suggesting local vulnerabilities to tauopathy. There were greater effects of APOE genotype in females, although the interactive sex effects did not strongly mirror mRNA expression. Pathology is not homogeneously expressed throughout the brain but mirrors underlying biological patterns such as gene expression.
Collapse
Affiliation(s)
- Aylin Dincer
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Charles D Chen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Nicole S McKay
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Lauren N Koenig
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Austin McCullough
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Shaney Flores
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah J Keefe
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Stephanie A Schultz
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Rebecca L Feldman
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Nelly Joseph-Mathurin
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Russ C Hornbeck
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Carlos Cruchaga
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA.,Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Suzanne E Schindler
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - David M Holtzman
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, Saint Louis, MO, USA
| | - John C Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Anne M Fagan
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA.,Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Tammie LS Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.,Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University School of Medicine, Saint Louis, MO, USA.,Department of Psychological & Brain Sciences, Washington University, Saint Louis, MO, USA
| |
Collapse
|
7
|
|
8
|
Fernández-Calle R, Konings SC, Frontiñán-Rubio J, García-Revilla J, Camprubí-Ferrer L, Svensson M, Martinson I, Boza-Serrano A, Venero JL, Nielsen HM, Gouras GK, Deierborg T. APOE in the bullseye of neurodegenerative diseases: impact of the APOE genotype in Alzheimer’s disease pathology and brain diseases. Mol Neurodegener 2022; 17:62. [PMID: 36153580 PMCID: PMC9509584 DOI: 10.1186/s13024-022-00566-4] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 08/29/2022] [Indexed: 02/06/2023] Open
Abstract
ApoE is the major lipid and cholesterol carrier in the CNS. There are three major human polymorphisms, apoE2, apoE3, and apoE4, and the genetic expression of APOE4 is one of the most influential risk factors for the development of late-onset Alzheimer's disease (AD). Neuroinflammation has become the third hallmark of AD, together with Amyloid-β plaques and neurofibrillary tangles of hyperphosphorylated aggregated tau protein. This review aims to broadly and extensively describe the differential aspects concerning apoE. Starting from the evolution of apoE to how APOE's single-nucleotide polymorphisms affect its structure, function, and involvement during health and disease. This review reflects on how APOE's polymorphisms impact critical aspects of AD pathology, such as the neuroinflammatory response, particularly the effect of APOE on astrocytic and microglial function and microglial dynamics, synaptic function, amyloid-β load, tau pathology, autophagy, and cell–cell communication. We discuss influential factors affecting AD pathology combined with the APOE genotype, such as sex, age, diet, physical exercise, current therapies and clinical trials in the AD field. The impact of the APOE genotype in other neurodegenerative diseases characterized by overt inflammation, e.g., alpha- synucleinopathies and Parkinson's disease, traumatic brain injury, stroke, amyotrophic lateral sclerosis, and multiple sclerosis, is also addressed. Therefore, this review gathers the most relevant findings related to the APOE genotype up to date and its implications on AD and CNS pathologies to provide a deeper understanding of the knowledge in the APOE field.
Collapse
|
9
|
Li L, Yu X, Sheng C, Jiang X, Zhang Q, Han Y, Jiang J. A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives. Transl Neurodegener 2022; 11:42. [PMID: 36109823 PMCID: PMC9476275 DOI: 10.1186/s40035-022-00315-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 08/24/2022] [Indexed: 11/25/2022] Open
Abstract
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.
Collapse
|
10
|
Predictive Scale for Amyloid PET Positivity Based on Clinical and MRI Variables in Patients with Amnestic Mild Cognitive Impairment. J Clin Med 2022; 11:jcm11123433. [PMID: 35743503 PMCID: PMC9224873 DOI: 10.3390/jcm11123433] [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: 04/11/2022] [Revised: 06/11/2022] [Accepted: 06/12/2022] [Indexed: 12/05/2022] Open
Abstract
The presence of amyloid-β (Aβ) deposition is considered important in patients with amnestic mild cognitive impairment (aMCI), since they can progress to Alzheimer’s disease dementia. Amyloid positron emission tomography (PET) has been used for detecting Aβ deposition, but its high cost is a significant barrier for clinical usage. Therefore, we aimed to develop a new predictive scale for amyloid PET positivity using easily accessible tools. Overall, 161 aMCI patients were recruited from six memory clinics and underwent neuropsychological tests, brain magnetic resonance imaging (MRI), apolipoprotein E (APOE) genotype testing, and amyloid PET. Among the potential predictors, verbal and visual memory tests, medial temporal lobe atrophy, APOE genotype, and age showed significant differences between the Aβ-positive and Aβ-negative groups and were combined to make a model for predicting amyloid PET positivity with the area under the curve (AUC) of 0.856. Based on the best model, we developed the new predictive scale comprising integers, which had an optimal cutoff score ≥ 3. The new predictive scale was validated in another cohort of 98 participants and showed a good performance with AUC of 0.835. This new predictive scale with accessible variables may be useful for predicting Aβ positivity in aMCI patients in clinical practice.
Collapse
|
11
|
Wang Y, Pan F, Xie F, He R, Guo Q. Correlation Between Urine Formaldehyde and Cognitive Abilities in the Clinical Spectrum of Alzheimer’s Disease. Front Aging Neurosci 2022; 14:820385. [PMID: 35221998 PMCID: PMC8873387 DOI: 10.3389/fnagi.2022.820385] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 01/13/2022] [Indexed: 12/30/2022] Open
Abstract
Urine-based formaldehyde has been reported to be a potential biomarker for Alzheimer’s disease (AD). However, there is a lack of research about the correlation between urine formaldehyde and cognitive abilities in the clinical spectrum of AD, especially the preclinical period. The relationship of urine formaldehyde with APOE genotype, brain Aβ status and plasma pathological markers in AD are also not clear. This study intends to explore the correlation between urine formaldehyde and cognitive abilities throughout the AD continuum, to evaluate the role of APOE genotype and Aβ accumulation on urine formaldehyde, and further to clarify the relationship between urine formaldehyde level and AD plasma pathological markers. We recruited 72 cognitively normal controls (NC), 110 subjective cognitive decline (SCD), 140 objectively defined subtle cognitive decline (Obj-SCD), 171 mild cognitive impairment (MCI) and 136 AD dementia participants. Next, we collected the data of clinical materials, neuropsychological examination, APOE genotyping, urine formaldehyde concentration, 18F-florbetapir PET imaging and plasma biomarkers. Compared with NC, Obj-SCD and MCI groups, the level of urine formaldehyde was found to be significantly upregulated in SCD group. In addition, the level of urine formaldehyde was significantly higher in AD group compared to both NC and MCI groups. Further subgroup analysis showed that, the level of urine formaldehyde was higher in APOE ε4+ subgroup compared to APOE ε4– subgroup in both NC and AD groups. There was no difference in urine formaldehyde level between the brain Aβ+ subgroup and Aβ– subgroup in each group. In addition, regression analysis showed urine formaldehyde level was correlated with gender, plasma Aβ42 and p-Tau181/T-tau. The dynamic change of urine formaldehyde in the AD continuum could be used as a potential biomarker, and combined with comprehensive cognitive evaluation could become a useful method to distinguish SCD from NC and Obj-SCD, and to distinguish MCI from AD.
Collapse
Affiliation(s)
- Ying Wang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Fengfeng Pan
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Fang Xie
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Rongqiao He
- State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- *Correspondence: Rongqiao He,
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
- Qihao Guo,
| |
Collapse
|
12
|
Gasmi A, Menzel A, Piscopo S, Noor S. Toxic Metals Exposure and APOE4 Gene Variant in Cognitive Decline Disorders. ARCHIVES OF RAZI INSTITUTE 2022; 77:1-10. [PMID: 35891722 PMCID: PMC9288612 DOI: 10.22092/ari.2021.356078.1771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 11/09/2021] [Indexed: 06/15/2023]
Abstract
Neurodegenerative disorders are those which affect cognitive functions. Misfolding of proteins especially apolipoprotein E is a key genetic factor involved in several cognitive impairments. Increasing evidence also described the toxic effects of metals, generated by both nature and humans, on the development of neurological disorders. Understanding of interaction between toxic metals and apolipoprotein E protein in cognitive decline diosrders would provide alternative treatment options. Google Scholar and PubMed database were used to search the articles using different search terms like 'toxic metals', 'cognitive decline', 'Apolipoprotein E', "neurodegenerative disorders" and "metals neurotoxicity". Only those papers were included that discussed the metal exposure-apolipoprotein association in the development of cognitive decline disorders. Heavy metals are particularly recognized as a major source of neurotoxicity. These toxic metals can interact with genetic factors and play important role in disease etiology. Understanding the underlying mechanism of this interaction could provide tremendous benefits to treat cognitive decline disorders. In this study, the role of the apolipoprotein E4 gene in the development of cognitive disease conditions and their phenotypes has been discussed thoroughly which leads to the accumulation of amyloid-beta fibrils. This exploratory study revealed novel hypothetical findings which might contribute to the understanding of the neurotoxic effects of chronic toxic metals exposure and possibly improve our knowledge on the molecular mechanisms linking metal exposure to cognitive decline disorder risk.
Collapse
Affiliation(s)
- A Gasmi
- Société Francophone de Nutrithérapie et de Nutrigénétique Appliquée, Villeurbanne, France
| | - A Menzel
- Laboratoires Réunis, Junglinster, Luxembourg
| | - S Piscopo
- Société Francophone de Nutrithérapie et de Nutrigénétique Appliquée, Villeurbanne, France
| | - S Noor
- Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University Multan, Pakistan
| |
Collapse
|
13
|
Benson GS, Bauer C, Hausner L, Couturier S, Lewczuk P, Peters O, Hüll M, Jahn H, Jessen F, Pantel J, Teipel SJ, Wagner M, Schuchhardt J, Wiltfang J, Kornhuber J, Frölich L. Don’t forget about tau: the effects of ApoE4 genotype on Alzheimer’s disease cerebrospinal fluid biomarkers in subjects with mild cognitive impairment—data from the Dementia Competence Network. J Neural Transm (Vienna) 2022; 129:477-486. [PMID: 35061102 PMCID: PMC9188507 DOI: 10.1007/s00702-022-02461-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 01/06/2022] [Indexed: 11/28/2022]
Abstract
ApoE4, the strongest genetic risk factor for Alzheimer’s disease (AD), has been shown to be associated with both beta-amyloid (Aβ) and tau pathology, with the strongest evidence for effects on Aβ, while the association between ApoE4 and tau pathology remains inconsistent. This study aimed to investigate the associations between ApoE4 with CSF Aβ42, total tau (t-tau), phospho-tau181 (p-tau), and with the progression of decline in a large cohort of MCI subjects, both progressors to AD and other dementias, as well as non-progressors. We analyzed associations of CSF Aβ42, p-tau and t-tau with ApoE4 allele frequency cross-sectionally and longitudinally over 3 years of follow-up in 195 individuals with a diagnosis of MCI-stable, MCI-AD converters and MCI progressing to other dementias from the German Dementia Competence Network. In the total sample, ApoE4 carriers had lower concentrations of CSF Aβ42, and increased concentrations of t-tau and p-tau compared to non-carriers in a gene dose-dependent manner. Comparisons of these associations stratified by MCI-progression groups showed a significant influence of ApoE4 carriership and diagnostic group on all CSF biomarker levels. The effect of ApoE4 was present in MCI-stable individuals but not in the other groups, with ApoE4 + carriers having decreased CSF Aβ 42 levels, and increased concentration of t-tau and p-tau. Longitudinally, individuals with abnormal t-tau and Aβ42 had a more rapid progression of cognitive and clinical decline, independently of ApoE4 genotype. Overall, our results contribute to an emerging framework in which ApoE4 involves mechanisms associated with both CSF amyloid-β burden and tau aggregation at specific time points in AD pathogenesis.
Collapse
|
14
|
Chang HI, Chang YT, Huang CW, Huang KL, Hsu JL, Hsu SW, Tsai SJ, Chang WN, Lee CC, Huang SH, Chang CC. Structural Covariance Network as an Endophenotype in Alzheimer's Disease-Susceptible Single-Nucleotide Polymorphisms and the Correlations With Cognitive Outcomes. Front Aging Neurosci 2022; 13:721217. [PMID: 34975449 PMCID: PMC8719443 DOI: 10.3389/fnagi.2021.721217] [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: 06/06/2021] [Accepted: 11/04/2021] [Indexed: 11/20/2022] Open
Abstract
The cognitive manifestations of Alzheimer’s disease (AD) are related to brain network degeneration, and genetic differences may mediate network degeneration. Several AD-susceptible loci have been reported to involve amyloid or tau cascades; however, their relationships with gray matter (GM) volume and cognitive outcomes have yet to be established. We hypothesized that single-nucleotide polymorphism genotype groups may interact with apolipoprotein E4 (ApoE4) status or independently exert an effect on cognitive outcomes. We also hypothesized that GM structural covariance networks (SCNs) may serve as an endophenotype of the genetic effect, which, in turn, may be related to neurobehavior test scores. Gray matter SCNs were constructed in 324 patients with AD using T1 magnetic resonance imaging with independent component analysis (ICA). We assessed the effects of 15 genetic loci (rs9349407, rs3865444, rs670139, rs744373, rs3851179, rs11136000, rs3764650, rs610932, rs6887649, rs7849530, rs4866650, rs3765728, rs34011, rs6656401, and rs597668) using additive, recessive, and dominant models on cognitive outcomes. Statistical analysis was performed to explore the independent role of each locus, interactions with ApoE4 status, and relationships to GM ICA network intensity score. For outcome measures, we used the Mini-Mental State Examination (MMSE), Cognitive Abilities Screening Instrument (CASI) total score, and short-term memory (STM) subscores, adjusted for the covariates of education, disease duration, and age. Clinically, the CD2AP G allele showed a protective role in MMSE, CASI total, and CASI-STM scores independently or via interactions with non-ApoE4 status, while the CR1 A genotype group was associated with lower STM subscores independent of ApoE4 status. Three loci showed synergic interactions with ApoE4: BIN 1, MS4A6A, and FTMT. Of the 15 meaningful ICA components, 5 SCNs (anterior and posterior hippocampus, right temporal, left thalamus, default mode network) showed relationships with general cognitive performance, in which only the ApoE4 and MS4A6A genotype groups were independently related to the hippocampus network. The genetic loci MS4A6A, BIN1, CLU, CR1, BIN1, PICALM, and FGF1 influenced the networks independently or in synergy. This study suggests that AD-susceptible loci may each exert clinical significance independently through interactions with ApoE4 status or through SCNs as an endophenotype and that this effect is associated with the cognitive outcomes.
Collapse
Affiliation(s)
- Hsin-I Chang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yu-Tzu Chang
- Division of Nephrology, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Chi-Wei Huang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Kuo-Lun Huang
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center and College of Medicine, Neuroscience Research Center, Chang Gung University, Taoyuan City, Taiwan
| | - Jung-Lung Hsu
- Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center and College of Medicine, Neuroscience Research Center, Chang Gung University, Taoyuan City, Taiwan.,Department of Neurology, New Taipei Municipal TuCheng Hospital, New Taipei City, Taiwan.,Graduate Institute of Mind, Brain, and Consciousness, Taipei and Brain and Consciousness Research Center, TMU Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan
| | - Shih-Wei Hsu
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Shih-Jen Tsai
- Psychiatric Department of Taipei Veterans General Hospital, Taipei, Taiwan.,Psychiatric Division, School of Medicine, National Yang-Ming University, Taipei City, Taiwan
| | - Wen-Neng Chang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chen-Chang Lee
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Shu-Hua Huang
- Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chiung-Chih Chang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| |
Collapse
|
15
|
Stage E, Svaldi D, Sokolow S, Risacher SL, Marosi K, Rotter JI, Saykin AJ, Apostolova LG. Prescribing cholinesterase inhibitors in mild cognitive impairment-Observations from the Alzheimer's Disease Neuroimaging Initiative. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2021; 7:e12168. [PMID: 35005201 PMCID: PMC8719350 DOI: 10.1002/trc2.12168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 03/05/2021] [Accepted: 03/14/2021] [Indexed: 11/10/2022]
Abstract
INTRODUCTION Analyses of off-label use of acetylcholinesterase inhibitors (AChEIs) in mild cognitive impairment (MCI) has produced mixed results. Post hoc analyses of observational cohorts, such as the Alzheimer's Disease Neuroimaging Initiative (ADNI), have reported deleterious effects in AChEI-treated subjects (AChEI+). Here, we used neuroimaging biomarkers to determine whether AChEI+ subjects had a greater rate of neurodegeneration than untreated (AChEI-) subjects while accounting for baseline differences. METHODS We selected 121 ADNI MCI AChEI+ subjects and 151 AChEI- subjects with a magnetic resonance imaging (MRI) scan; 82 AChEI+ and 110 AChEI- also had a fluorodeoxyglucose (FDG) scan. A subset (83 AChEI+ and 98 AChEI-) had cerebrospinal fluid (CSF) or amyloid positron emission tomography (PET) assessment for amyloid positivity. Linear regression models were used to compare the effect of treatment on changes in Mini-Mental State Examination and Clinical Dementia Rating-Sum of Boxes scores. We used standard regression in SPM (for baseline) and the SPM toolbox sandwich estimator, SwE (for longitudinal) for comparisons of AChEI+ and AChEI- FDG PET and MRI data. RESULTS At baseline, the AChEI+ group had significantly reduced cortical gray matter density (GMD) and more hypometabolism than AChEI- subjects. The greater rate of atrophy and hypometabolic changes over time in AChEI+ compared to AChEI- subjects did not survive correction for baseline differences. AChEI+ participants were more likely to be amyloid-positive and have lower GMD and FDG standardized uptake value ratio than AChEI- at baseline. AChEI+ subjects showed greater atrophy over time, which remained significant after controlling for amyloid status. DISCUSSION Our data suggest that the observed differences in rates of cognitive decline, atrophy, and hypometabolism are likely the result of significant baseline differences between the groups. Furthermore, the data indicate no treatment effect of AChEI (positive of negative), rather that physicians prescribe AChEI to subjects who present with more severe clinical impairment. This alone may account for the negative effect seen previously in the ADNI population of AChEI use among MCI subjects.
Collapse
Affiliation(s)
- Eddie Stage
- Indiana Alzheimer Disease CenterIndianapolisINUSA
- Department of NeurologyIU School of MedicineIndianapolisINUSA
| | - Diana Svaldi
- Department of NeurologyIU School of MedicineIndianapolisINUSA
| | - Sophie Sokolow
- UCLA School of NursingLos AngelesCAUSA
- UCLA Brain Research InsituteLos AngelesCAUSA
- UCLA Clinical and Translational Science InstituteLos AngelesCAUSA
| | - Shannon L. Risacher
- Indiana Alzheimer Disease CenterIndianapolisINUSA
- Department of Radiology and Imaging SciencesIU School of MedicineIndianapolisINUSA
| | | | - Jerome I. Rotter
- The Institute for Translational Genomics and Population SciencesHarbor‐UCLA Medical CenterTorranceCAUSA
- Department of PediatricsHarbor‐UCLA Medical CenterTorranceCAUSA
- The Lundquist Institute for Biomedical InnovationHarbor‐UCLA Medical CenterTorranceCAUSA
| | - Andrew J. Saykin
- Indiana Alzheimer Disease CenterIndianapolisINUSA
- Department of Radiology and Imaging SciencesIU School of MedicineIndianapolisINUSA
| | - Liana G. Apostolova
- Indiana Alzheimer Disease CenterIndianapolisINUSA
- Department of NeurologyIU School of MedicineIndianapolisINUSA
- Department of Radiology and Imaging SciencesIU School of MedicineIndianapolisINUSA
- Department of Medical and Molecular GeneticsIU School of MedicineIndianapolisINUSA
| | | |
Collapse
|
16
|
Apolipoprotein E ɛ4-related effects on cognition are limited to the Alzheimer's disease spectrum. GeroScience 2021; 44:195-209. [PMID: 34591236 PMCID: PMC8811053 DOI: 10.1007/s11357-021-00450-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 08/23/2021] [Indexed: 11/29/2022] Open
Abstract
Whether the deleterious effects of APOE4 are restricted to the Alzheimer’s disease (AD) spectrum or cause cognitive impairment irrespectively of the development of AD is still a matter of debate, and the focus of this study. Our analyses included APOE4 genotype, neuropsychological variables, amyloid-βeta (Aβ) and Tau markers, FDG-PET values, and hippocampal volumetry data derived from the healthy controls sample of the ADNI database. We formed 4 groups of equal size (n = 30) based on APOE4 carriage and amyloid-PET status. Baseline and follow-up (i.e., 48 months post-baseline) results indicated that Aβ-positivity was the most important factor to explain poorer cognitive performance, while APOE4 only exerted a significant effect in Aβ-positive subjects. Additionally, multiple regression analyses evidenced that, within the Aβ-positive sample, hippocampal volumetry explained most of the variability in cognitive performance for APOE4 carriers. These findings represent a strong support for the so-called preclinical/prodromal hypothesis, which states that the reported differences in cognitive performance between healthy carriers and non-carriers are mainly due to the APOE4’s capability to increase the risk of AD. Moreover, our results reinforce the notion that a synergistic interaction of Aβ and APOE4 elicits a neurodegenerative process in the hippocampus that might be the main cause of impaired cognitive performance.
Collapse
|
17
|
Kang SH, Cheon BK, Kim JS, Jang H, Kim HJ, Park KW, Noh Y, Lee JS, Ye BS, Na DL, Lee H, Seo SW. Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment. J Alzheimers Dis 2021; 80:143-157. [PMID: 33523003 DOI: 10.3233/jad-201092] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cost and safety issues. OBJECTIVE We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers. METHODS We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers). RESULTS Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity. CONCLUSION Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.
Collapse
Affiliation(s)
- Sung Hoon Kang
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Bo Kyoung Cheon
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea.,Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Ji-Sun Kim
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Hyemin Jang
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Hee Jin Kim
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A University Medical Center, Dong-A University College of Medicine, Busan, Korea
| | - Young Noh
- Department of Neurology, Gachon University Gil Medical Center, Incheon, Korea
| | - Jin San Lee
- Department of Neurology, Kyung Hee University Hospital, Seoul, Korea
| | - Byoung Seok Ye
- Department of Neurology, Severance hospital, Yonsei University School of Medicine, Seoul, Korea
| | - Duk L Na
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Hyejoo Lee
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea
| | - Sang Won Seo
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Neuroscience Center, Samsung Medical Center, Seoul, Korea.,Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea.,Samsung Alzheimer Research Center and Center for Clinical Epidemiology Medical Center, Seoul, Korea.,Department of Intelligent Precision Healthcare Convergence, SAIHST, Sungkyunkwan University, Seoul, Korea
| |
Collapse
|
18
|
Moore EE, Liu D, Li J, Schimmel SJ, Cambronero FE, Terry JG, Nair S, Pechman KR, Moore ME, Bell SP, Beckman JA, Gifford KA, Hohman TJ, Blennow K, Zetterberg H, Carr JJ, Jefferson AL. Association of Aortic Stiffness With Biomarkers of Neuroinflammation, Synaptic Dysfunction, and Neurodegeneration. Neurology 2021; 97:e329-e340. [PMID: 34031194 PMCID: PMC8362359 DOI: 10.1212/wnl.0000000000012257] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 04/21/2021] [Indexed: 01/19/2023] Open
Abstract
OBJECTIVES To test the hypothesis that increased aortic stiffening is associated with greater CSF evidence of core Alzheimer disease pathology (β-amyloid [Aβ], phosphorylated tau [p-tau]), neurodegeneration (total tau [t-tau]), synaptic dysfunction (neurogranin), neuroaxonal injury (neurofilament light [NFL]), and neuroinflammation (YKL-40, soluble triggering receptor expressed on myeloid cells 2 [sTREM2]), we analyzed pulse wave velocity (PWV) data and CSF data among older adults. METHODS Participants free of stroke and dementia from the Vanderbilt Memory and Aging Project, an observational community-based study, underwent cardiac magnetic resonance to assess aortic PWV (meters per second) and lumbar puncture to obtain CSF. Linear regressions related aortic PWV to CSF Aβ, p-tau, t-tau, neurogranin, NFL, YKL-40, and sTREM2 concentrations after adjustment for age, race/ethnicity, education, apolipoprotein (APOE) ε4 status, Framingham Stroke Risk Profile, and cognitive diagnosis. Models were repeated testing PWV interactions with age, diagnosis, APOE ε4, and hypertension on each biomarker. RESULTS One hundred forty-six participants were examined (age 72 ± 6 years). Aortic PWV interacted with age on p-tau (β = 0.31, p = 0.04), t-tau, (β = 2.67, p = 0.05), neurogranin (β = 0.94, p = 0.04), and sTREM2 (β = 20.4, p = 0.05). Among participants >73 years of age, higher aortic PWV related to higher p-tau (β = 2.4, p = 0.03), t-tau (β = 19.3, p = 0.05), neurogranin (β = 8.4, p = 0.01), and YKL-40 concentrations (β = 7,880, p = 0.005). Aortic PWV had modest interactions with diagnosis on neurogranin (β = -10.76, p = 0.03) and hypertension status on YKL-40 (β = 18,020, p < 0.001). CONCLUSIONS Among our oldest participants, ≥74 years of age, greater aortic stiffening is associated with in vivo biomarker evidence of neuroinflammation, tau phosphorylation, synaptic dysfunction, and neurodegeneration, but not amyloidosis. Central arterial stiffening may lead to cumulative cerebral microcirculatory damage and reduced blood flow delivery to tissue, resulting in neuroinflammation and neurodegeneration in more advanced age.
Collapse
Affiliation(s)
- Elizabeth E Moore
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Dandan Liu
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Judy Li
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Samantha J Schimmel
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Francis E Cambronero
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - James G Terry
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Sangeeta Nair
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Kimberly R Pechman
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Marissa E Moore
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Susan P Bell
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Joshua A Beckman
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Katherine A Gifford
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Timothy J Hohman
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Kaj Blennow
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Henrik Zetterberg
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - John Jeffrey Carr
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK
| | - Angela L Jefferson
- From the Vanderbilt Memory & Alzheimer's Center (E.E.M., D.L., J.L., S.J.S., F.E.C., K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Department of Biostatistics (D.L.), Radiology & Radiological Sciences (J.G.T., S.N., J.J.C.), Department of Neurology (K.R.P., M.E.M., K.A.G., T.J.H., A.L.J.), Division of Cardiovascular Medicine (S.P.B., J.A.B., A.L.J.), Department of Medicine, and Vanderbilt Genetics Institute (T.J.H.), Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Neurochemistry (K.B., H.Z.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg; Clinical Neurochemistry Laboratory (K.B., H.Z.), Sahlgrenska University Hospital, Molndal, Sweden; Department of Neurodegenerative Disease (H.Z.), University College London Institute of Neurology, Queen Square; and United Kingdom Dementia Research Institute at University College London (H.Z.), UK.
| |
Collapse
|
19
|
Nho K, Kueider-Paisley A, Arnold M, MahmoudianDehkordi S, Risacher SL, Louie G, Blach C, Baillie R, Han X, Kastenmüller G, Doraiswamy PM, Kaddurah-Daouk R, Saykin AJ. Serum metabolites associated with brain amyloid beta deposition, cognition and dementia progression. Brain Commun 2021; 3:fcab139. [PMID: 34396103 PMCID: PMC8361396 DOI: 10.1093/braincomms/fcab139] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/30/2021] [Indexed: 11/13/2022] Open
Abstract
Metabolomics in the Alzheimer's Disease Neuroimaging Initiative cohort provides a powerful tool for mapping biochemical changes in Alzheimer's disease, and a unique opportunity to learn about the association between circulating blood metabolites and brain amyloid-β deposition in Alzheimer's disease. We examined 140 serum metabolites and their associations with brain amyloid-β deposition, cognition and conversion from mild cognitive impairment to Alzheimer's disease in the Alzheimer's Disease Neuroimaging Initiative. Processed [18F] Florbetapir PET images were used to perform a voxel-wise statistical analysis of the effect of metabolite levels on amyloid-β accumulation across the whole brain. We performed a multivariable regression analysis using age, sex, body mass index, apolipoprotein E ε4 status and study phase as covariates. We identified nine metabolites as significantly associated with amyloid-β deposition after multiple comparison correction. Higher levels of one acylcarnitine (C3; propionylcarnitine) and one biogenic amine (kynurenine) were associated with decreased amyloid-β accumulation and higher memory scores. However, higher levels of seven phosphatidylcholines (lysoPC a C18:2, PC aa C42:0, PC ae C42:3, PC ae C44:3, PC ae C44:4, PC ae C44:5 and PC ae C44:6) were associated with increased brain amyloid-β deposition. In addition, higher levels of PC ae C44:4 were significantly associated with lower memory and executive function scores and conversion from mild cognitive impairment to Alzheimer's disease dementia. Our findings suggest that dysregulation of peripheral phosphatidylcholine metabolism is associated with earlier pathological changes noted in Alzheimer's disease as measured by brain amyloid-β deposition as well as later clinical features including changes in memory and executive functioning. Perturbations in phosphatidylcholine metabolism may point to issues with membrane restructuring leading to the accumulation of amyloid-β in the brain. Additional studies are needed to explore whether these metabolites play a causal role in the pathogenesis of Alzheimer's disease or if they are biomarkers for systemic changes during preclinical phases of the disease.
Collapse
Affiliation(s)
- Kwangsik Nho
- Department of Radiology and Imaging Sciences, Center for Computational Biology and Bioinformatics, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | | | - Matthias Arnold
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27710, USA
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | | | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Center for Computational Biology and Bioinformatics, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Gregory Louie
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27710, USA
| | - Colette Blach
- Duke Molecular Physiology Institute, Duke University, Durham, NC 27710, USA
| | | | - Xianlin Han
- University of Texas Health Science Center at San Antonio, San Antonio, TX 78249, USA
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg 85764, Germany
- German Center for Diabetes Research (DZD), Neuherberg 85764, Germany
| | - P Murali Doraiswamy
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27710, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA
- Department of Medicine, Duke University, Durham, NC 27710, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27710, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA
- Department of Medicine, Duke University, Durham, NC 27710, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Center for Computational Biology and Bioinformatics, and the Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | | |
Collapse
|
20
|
Yamaguchi T, Tabuchi H, Ito D, Saito N, Yamagata B, Konishi M, Takebayashi M, Ikeda M, Mimura M. Effect of different parietal hypoperfusion on neuropsychological characteristics in mild cognitive impairment. Psychogeriatrics 2021; 21:618-626. [PMID: 34056807 DOI: 10.1111/psyg.12723] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 04/15/2021] [Accepted: 05/09/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND In early-stage amnestic mild cognitive impairment (aMCI), differences in the neuropsychological characteristics of each individual are subtle. We investigated differences in neuropsychological performance between aMCI patients with and without hypoperfusion in the medial parietal regions (MP). We further compared patients with hypoperfusion in the left and right lateral parietal regions. METHODS We examined 165 aMCI patients (mean age: 76.8 ± 5.5 years; 87 women) who had undergone neuropsychological measurement and single-photon emission computed tomography. We classified participants into two subgroups with and without hypoperfusion: MP hypoperfusion (+) and MP hypoperfusion (-); classification was based on Z-scores (calculated by three-dimensional stereotactic surface projection technique) of three regions of interest in the parietal lobes (i.e. MP regions including posterior cingulate cortex and precuneus and left and right inferior parietal lobules (lateral parietal regions)). The MP hypoperfusion (-) group was classified into left lateral parietal hypoperfusion (+) and right lateral parietal hypoperfusion (+) subgroups. We performed either univariate or multivariate ancova to compare neuropsychological scores for continuous variables between groups and examined dichotomous variables using χ2 tests. RESULTS In the overall aMCI sample, scores on logical memory delayed recall in the MP hypoperfusion (+) group were significantly lower than those in the MP hypoperfusion (-) group. Total scores on Rey-Osterrieth Complex Figure Test delayed recall were also marginally lower in the MP hypoperfusion (+) group than in the MP hypoperfusion (-) group. Comparisons of neuropsychological test scores between the left and right lateral parietal hypoperfusion (+) groups revealed no significant differences. CONCLUSIONS The present findings suggest that MP hypoperfusion (+) is associated with more robust memory deficits than MP hypoperfusion (-). Combining neuropsychological tests and single-photon emission computed tomography findings may be useful for early detection of cognitive decline in aMCI.
Collapse
Affiliation(s)
- Tatsuya Yamaguchi
- Department of Neuropsychiatry, Graduate School of Medical Science, Kumamoto University, Kumamoto, Japan.,Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Hajime Tabuchi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Daisuke Ito
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
| | - Naho Saito
- Department of Rehabilitation, Keio University School of Medicine, Tokyo, Japan
| | - Bun Yamagata
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Mika Konishi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Minoru Takebayashi
- Department of Neuropsychiatry, Graduate School of Medical Science, Kumamoto University, Kumamoto, Japan.,Department of Neuropsychiatry, Kumamoto University, Faculty of Medical and Pharmaceutical Sciences, Kumamoto, Japan
| | - Manabu Ikeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| |
Collapse
|
21
|
Huang M, Chen X, Yu Y, Lai H, Feng Q. Imaging Genetics Study Based on a Temporal Group Sparse Regression and Additive Model for Biomarker Detection of Alzheimer's Disease. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:1461-1473. [PMID: 33556003 DOI: 10.1109/tmi.2021.3057660] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Imaging genetics is an effective tool used to detect potential biomarkers of Alzheimer's disease (AD) in imaging and genetic data. Most existing imaging genetics methods analyze the association between brain imaging quantitative traits (QTs) and genetic data [e.g., single nucleotide polymorphism (SNP)] by using a linear model, ignoring correlations between a set of QTs and SNP groups, and disregarding the varied associations between longitudinal imaging QTs and SNPs. To solve these problems, we propose a novel temporal group sparsity regression and additive model (T-GSRAM) to identify associations between longitudinal imaging QTs and SNPs for detection of potential AD biomarkers. We first construct a nonparametric regression model to analyze the nonlinear association between QTs and SNPs, which can accurately model the complex influence of SNPs on QTs. We then use longitudinal QTs to identify the trajectory of imaging genetic patterns over time. Moreover, the SNP information of group and individual levels are incorporated into the proposed method to boost the power of biomarker detection. Finally, we propose an efficient algorithm to solve the whole T-GSRAM model. We evaluated our method using simulation data and real data obtained from AD neuroimaging initiative. Experimental results show that our proposed method outperforms several state-of-the-art methods in terms of the receiver operating characteristic curves and area under the curve. Moreover, the detection of AD-related genes and QTs has been confirmed in previous studies, thereby further verifying the effectiveness of our approach and helping understand the genetic basis over time during disease progression.
Collapse
|
22
|
Gellersen HM, Coughlan G, Hornberger M, Simons JS. Memory precision of object-location binding is unimpaired in APOE ε4-carriers with spatial navigation deficits. Brain Commun 2021; 3:fcab087. [PMID: 33987536 PMCID: PMC8108563 DOI: 10.1093/braincomms/fcab087] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/09/2021] [Accepted: 03/29/2021] [Indexed: 12/19/2022] Open
Abstract
Research suggests that tests of memory fidelity, feature binding and spatial navigation are promising for early detection of subtle behavioural changes related to Alzheimer's disease. In the absence of longitudinal data, one way of testing the early detection potential of cognitive tasks is through the comparison of individuals at different genetic risk for Alzheimer's dementia. Most studies have done so using samples aged 70 years or older. Here, we tested whether memory fidelity of long-term object-location binding may be a sensitive marker even among cognitively healthy individuals in their mid-60s by comparing participants at low and higher risk based on presence of the ε4-allele of the apolipoprotein gene (n = 26 ε3ε3, n = 20 ε3ε4 carriers). We used a continuous report paradigm in a visual memory task that required participants to recreate the spatial position of objects in a scene. We employed mixture modelling to estimate the two distinct memory processes that underpin the trial-by-trial variation in localization errors: retrieval success which indexes the proportion of trials where participants recalled any information about an object's position and the precision with which participants retrieved this information. Prior work has shown that these memory paradigms that separate retrieval success from precision are capable of detecting subtle differences in mnemonic fidelity even when retrieval success could not. Nonetheless, Bayesian analyses found good evidence that ε3ε4 carriers did not remember fewer object locations [F(1, 42) = 0.450, P = 0.506, BF01 = 3.02], nor was their precision for the spatial position of objects reduced compared to ε3ε3 carriers [F(1, 42) = 0.12, P = 0.726, BF01 = 3.19]. Because the participants in the sample presented here were a subset of a study on apolipoprotein ε4-carrier status and spatial navigation in the Sea Hero Quest game [Coughlan et al., 2019. PNAS, 116(9)], we obtained these data to contrast genetic effects on the two tasks within the same sample (n = 33). Despite the smaller sample size, wayfinding deficits among ε3ε4 carriers could be replicated [F(1, 33) = 5.60, P = 0.024, BF10 = 3.44]. Object-location memory metrics and spatial navigation scores were not correlated (all r < 0.25, P > 0.1, 0 < BF10 < 3). These findings show spared object-location binding in the presence of a detrimental apolipoprotein ε4 effect on spatial navigation. This suggests that the sensitivity of memory fidelity and binding tasks may not extend to individuals with one ε4-allele in their early to mid-60s. The results provide further support to prior proposals that spatial navigation may be a sensitive marker for the earliest cognitive changes in Alzheimer's disease, even before episodic memory.
Collapse
Affiliation(s)
- Helena M Gellersen
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Gillian Coughlan
- Rotman Research Institute, Baycrest Hospital, Toronto, ON M6A 1W1, Canada
| | | | - Jon S Simons
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| |
Collapse
|
23
|
Brabec JL, Lara MK, Tyler AL, Mahoney JM. System-Level Analysis of Alzheimer's Disease Prioritizes Candidate Genes for Neurodegeneration. Front Genet 2021; 12:625246. [PMID: 33889174 PMCID: PMC8056044 DOI: 10.3389/fgene.2021.625246] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 02/22/2021] [Indexed: 12/11/2022] Open
Abstract
Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder. Since the advent of the genome-wide association study (GWAS) we have come to understand much about the genes involved in AD heritability and pathophysiology. Large case-control meta-GWAS studies have increased our ability to prioritize weaker effect alleles, while the recent development of network-based functional prediction has provided a mechanism by which we can use machine learning to reprioritize GWAS hits in the functional context of relevant brain tissues like the hippocampus and amygdala. In parallel with these developments, groups like the Alzheimer’s Disease Neuroimaging Initiative (ADNI) have compiled rich compendia of AD patient data including genotype and biomarker information, including derived volume measures for relevant structures like the hippocampus and the amygdala. In this study we wanted to identify genes involved in AD-related atrophy of these two structures, which are often critically impaired over the course of the disease. To do this we developed a combined score prioritization method which uses the cumulative distribution function of a gene’s functional and positional score, to prioritize top genes that not only segregate with disease status, but also with hippocampal and amygdalar atrophy. Our method identified a mix of genes that had previously been identified in AD GWAS including APOE, TOMM40, and NECTIN2(PVRL2) and several others that have not been identified in AD genetic studies, but play integral roles in AD-effected functional pathways including IQSEC1, PFN1, and PAK2. Our findings support the viability of our novel combined score as a method for prioritizing region- and even cell-specific AD risk genes.
Collapse
Affiliation(s)
- Jeffrey L Brabec
- Department of Neurological Sciences, University of Vermont, Burlington, VT, United States
| | - Montana Kay Lara
- Department of Neurological Sciences, University of Vermont, Burlington, VT, United States
| | - Anna L Tyler
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - J Matthew Mahoney
- Department of Neurological Sciences, University of Vermont, Burlington, VT, United States.,The Jackson Laboratory, Bar Harbor, ME, United States
| |
Collapse
|
24
|
Yang L, Yan Y, Li Y, Hu X, Lu J, Chan P, Yan T, Han Y. Frequency-dependent changes in fractional amplitude of low-frequency oscillations in Alzheimer's disease: a resting-state fMRI study. Brain Imaging Behav 2021; 14:2187-2201. [PMID: 31478145 DOI: 10.1007/s11682-019-00169-6] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease in elderly individuals. We conducted this study to examine whether alterations in the fractional amplitudes of low-frequency fluctuations (fALFF) in the AD spectrum were frequency-dependent and symptom-relevant. A total of 43 patients with subjective cognitive decline (SCD), 52 with amnestic mild cognitive impairment (aMCI), 44 with Alzheimer's dementia (d-AD) and 55 well-matched controls participated in resting-state functional magnetic resonance imaging (rs-fMRI) scans. The amplitudes were measured using fALFF within the slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands. Repeated-measures analysis of variance was performed on fALFF within two bands and correlated with neuropsychological test scores. The significant main effects of frequency and group on fALFF differed widely across brain regions. There were more varied areas in the slow-5 band than the slow-4 band. The fALFF associated with primary disease effects was mainly distributed in the parietal lobe. Obvious frequency band and group interaction effects were observed in the left angular gyrus, left calcarine fissure and surrounding cortex, left superior cerebellum, left cuneus and right lingual gyrus. Neuropsychological tests scores were significantly correlated with the fALFF magnitude of the left cuneus and right lingual in the slow-5 band. Our results suggested that the AD continuum had abnormal amplitudes in intrinsic brain activity, and these abnormalities were frequency-dependent and mainly associated with the slow-5 band rather than the slow-4 band. This may guide the frequency choice of future rs-fMRI studies and provide new insights into the neuropathophysiology of AD.
Collapse
Affiliation(s)
- Liu Yang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, No.45 Street Changchun, District Xichen, Beijing, 100053, China
| | - Yan Yan
- School of Life Science, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China
| | - Yuxia Li
- Department of Neurology, Xuanwu Hospital of Capital Medical University, No.45 Street Changchun, District Xichen, Beijing, 100053, China
| | - Xiaochen Hu
- Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Piu Chan
- Department of Neurology, Xuanwu Hospital of Capital Medical University, No.45 Street Changchun, District Xichen, Beijing, 100053, China.,Beijing Institute of Geriatrics, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China
| | - Tianyi Yan
- School of Life Science, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, No.45 Street Changchun, District Xichen, Beijing, 100053, China. .,Beijing Institute of Geriatrics, Beijing, China. .,National Clinical Research Center for Geriatric Disorders, Beijing, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
| |
Collapse
|
25
|
2020 update on the clinical validity of cerebrospinal fluid amyloid, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework. Eur J Nucl Med Mol Imaging 2021; 48:2121-2139. [PMID: 33674895 PMCID: PMC8175301 DOI: 10.1007/s00259-021-05258-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/11/2021] [Indexed: 12/15/2022]
Abstract
Purpose In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer’s disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers—encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)—with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology. Methods A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop. Results By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability. Conclusions Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05258-7.
Collapse
|
26
|
Jung M, Apostolova LG, Gao S, Burney HN, Lai D, Foroud T, Saykin AJ, Pressler SJ. Testing influences of APOE and BDNF genes and heart failure on cognitive function. Heart Lung 2021; 50:51-58. [PMID: 32703621 PMCID: PMC8809626 DOI: 10.1016/j.hrtlng.2020.06.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 06/23/2020] [Accepted: 06/29/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND Apolipoprotein E (APOE) ε2, ε4 and brain-derived neurotrophic factor (BDNF) Val66Met alleles have been associated with cognition. Associations of these alleles with cognition in heart failure (HF) and influences of HF across the cognitive spectrum (i.e., cognitively normal to Alzheimer's dementia [AD]) remain unexplored. OBJECTIVES To investigate influences of APOE ε2, ε4, BDNF Met and HF on cognition among participants across the cognitive spectrum. METHODS Genetic association study using national databases (N = 7,166). RESULTS APOE ε2 frequencies were similar across the cognitive spectrum among participants with HF. APOE ε4 frequency was lower among participants with HF and AD than non-HF participants with AD. BDNF Met frequencies did not differ across the spectrum. HF was associated with worse attention and language. In the HF subsample, ε4 was associated with worse memory. CONCLUSION Associations between APOE and cognition may differ in HF but need to be tested in a larger sample.
Collapse
Affiliation(s)
- Miyeon Jung
- Assistant Professor, Indiana University School of Nursing, 600 Barnhill Drive, Indianapolis, IN 46202, USA.
| | - Liana G Apostolova
- Professor, Indiana University School of Medicine, Neurology, Radiology, Medical and Molecular Genetics, 355 West 16th Street, Indianapolis, IN 46202, USA.
| | - Sujuan Gao
- Professor, Indiana University School of Medicine, Department of Biostatistics, 410 West 10th Street, Indianapolis, IN 46202, USA.
| | - Heather N Burney
- Biostatistician, Indiana University School of Medicine, Department of Biostatistics, 410 West 10th Street, Indianapolis, IN 46202, USA.
| | - Dongbing Lai
- Assistant Research Professor, Indiana University School of Medicine, Medical and Molecular Genetics, 410 West 10th Street, Indianapolis, IN 46202, USA.
| | - Tatiana Foroud
- Professor, Indiana University School of Medicine, Medical and Molecular Genetics, 410 West 10th Street, Indianapolis, IN 46202, USA.
| | - Andrew J Saykin
- Professor, Indiana University School of Medicine, Department of Radiology and Imaging Sciences, 355 West 16th street, Indianapolis, IN 46202, USA.
| | - Susan J Pressler
- Professor, Indiana University School of Nursing, 600 Barnhill Drive, Indianapolis, IN 46202, USA.
| |
Collapse
|
27
|
Apolipoprotein E allele 4 effects on Single-Subject Gray Matter Networks in Mild Cognitive Impairment. NEUROIMAGE: CLINICAL 2021; 32:102799. [PMID: 34469849 PMCID: PMC8405842 DOI: 10.1016/j.nicl.2021.102799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 07/23/2021] [Accepted: 08/17/2021] [Indexed: 11/23/2022] Open
Abstract
There is evidence that gray matter networks are disrupted in Mild Cognitive Impairment (MCI) and associated with cognitive impairment and faster disease progression. However, it remains unknown how these alterations are related to the presence of Apolipoprotein E isoform E4 (ApoE4), the most prominent genetic risk factor for late-onset Alzheimer's disease (AD). To investigate this topic at the individual level, we explore the impact of ApoE4 and the disease progression on the Single-Subject Gray Matter Networks (SSGMNets) using the graph theory approach. Our data sample comprised 200 MCI patients selected from the ADNI database, classified as non-Converters and Converters (will progress into AD). Each group included 50 ApoE4-positive ('Carriers', ApoE4 + ) and 50 ApoE4-negative ('non-Carriers', ApoE4-). The SSGMNets were estimated from structural MRIs at two-time points: baseline and conversion. We investigated whether altered network topological measures at baseline and their rate of change (RoC) between baseline and conversion time points were associated with ApoE4 and disease progression. We also explored the correlation of SSGMNets attributes with general cognition score (MMSE), memory (ADNI-MEM), and CSF-derived biomarkers of AD (Aβ42, T-tau, and P-tau). Our results showed that ApoE4 and the disease progression modulated the global topological network properties independently but not in their RoC. MCI converters showed a lower clustering index in several regions associated with neurodegeneration in AD. The SSGMNets' topological organization was revealed to be able to predict cognitive and memory measures. The findings presented here suggest that SSGMNets could indeed be used to identify MCI ApoE4 Carriers with a high risk for AD progression.
Collapse
|
28
|
Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging. Mol Psychiatry 2021; 26:309-321. [PMID: 30361487 PMCID: PMC6219464 DOI: 10.1038/s41380-018-0246-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 07/31/2018] [Indexed: 12/25/2022]
Abstract
Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer's disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI using 11C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). Interestingly, after conditioning on APOE*4, 14 SNPs remained significant at P < 0.05 in the APOE region that were not in linkage disequilibrium with APOE*4. Outside the APOE region, the meta-analysis revealed 15 non-APOE loci with P < 1E-05 on nine chromosomes, with two most significant SNPs on chromosomes 8 (P-meta = 4.87E-07) and 3 (P-meta = 9.69E-07). Functional analyses of these SNPs indicate their potential relevance with AD pathogenesis. Top 15 non-APOE SNPs along with APOE*4 explained 25-35% of the amyloid variance in different datasets, of which 14-17% was explained by APOE*4 alone. In conclusion, we have identified novel signals in APOE and non-APOE regions that affect amyloid deposition in the brain. Our data also highlights the presence of yet to be discovered variants that may be responsible for the unexplained genetic variance of amyloid deposition.
Collapse
|
29
|
Peng B, Yao X, Risacher SL, Saykin AJ, Shen L, Ning X. Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data. BMC Med Inform Decis Mak 2020; 20:319. [PMID: 33267852 PMCID: PMC7709267 DOI: 10.1186/s12911-020-01339-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 11/17/2020] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Cognitive assessments represent the most common clinical routine for the diagnosis of Alzheimer's Disease (AD). Given a large number of cognitive assessment tools and time-limited office visits, it is important to determine a proper set of cognitive tests for different subjects. Most current studies create guidelines of cognitive test selection for a targeted population, but they are not customized for each individual subject. In this manuscript, we develop a machine learning paradigm enabling personalized cognitive assessments prioritization. METHOD We adapt a newly developed learning-to-rank approach [Formula: see text] to implement our paradigm. This method learns the latent scoring function that pushes the most effective cognitive assessments onto the top of the prioritization list. We also extend [Formula: see text] to better separate the most effective cognitive assessments and the less effective ones. RESULTS Our empirical study on the ADNI data shows that the proposed paradigm outperforms the state-of-the-art baselines on identifying and prioritizing individual-specific cognitive biomarkers. We conduct experiments in cross validation and level-out validation settings. In the two settings, our paradigm significantly outperforms the best baselines with improvement as much as 22.1% and 19.7%, respectively, on prioritizing cognitive features. CONCLUSIONS The proposed paradigm achieves superior performance on prioritizing cognitive biomarkers. The cognitive biomarkers prioritized on top have great potentials to facilitate personalized diagnosis, disease subtyping, and ultimately precision medicine in AD.
Collapse
Affiliation(s)
- Bo Peng
- The Ohio State University, Columbus, USA
| | - Xiaohui Yao
- University of Pennsylvania, Philadelphia, USA
| | | | | | - Li Shen
- University of Pennsylvania, Philadelphia, USA
| | - Xia Ning
- The Ohio State University, Columbus, USA
| | - for the ADNI
- The Ohio State University, Columbus, USA
- University of Pennsylvania, Philadelphia, USA
- Indiana University, Indianapolis, USA
| |
Collapse
|
30
|
Distribution and clinical impact of apolipoprotein E4 in subjective memory impairment and early mild cognitive impairment. Sci Rep 2020; 10:13365. [PMID: 32770103 PMCID: PMC7414226 DOI: 10.1038/s41598-020-69603-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Accepted: 06/15/2020] [Indexed: 11/24/2022] Open
Abstract
The apolipoprotein E (APOE) e4 allele is the most common genetic variant associated with Alzheimer’s disease (AD). We sought to investigate the distribution of APOE genotypes across the full clinical AD spectrum including AD, late-stage amnestic mild cognitive impairment (L-aMCI), early-stage aMCI (E-aMCI), subjective memory impairment (SMI), and controls. We prospectively recruited 713 AD patients, 735 aMCI patients, 575 SMI patients, and 8,260 individuals as controls. The frequency of the APOE e4 allele revealed an ordered fashion in the AD (30.8%), L-aMCI (24.0%), E-aMCI (15.1%), SMI (11.7%), and control (9.1%) groups. APOE e3/e4 and e4/e4 genotype frequencies also appeared in an ordered fashion in the AD group (39.1% of e3/e4 and 10.9% of e4/e4), as well as the L-aMCI (28.3% and 9.4%), E-aMCI (22.3% and 3.7%), SMI (18.3% and 1.9%), and control (15.1% and 0.8%) groups. In the comparisons of APOE e3/e3 vs. e3/e4 genotypes, all patient groups had a higher frequency of APOE e3/e4 relative to the control group. Relative to the SMI and E-aMCI groups, the AD and L-aMCI groups had higher frequency of the APOE e3/e4 genotype, and the AD group had a higher frequency relative to the L-aMCI group. However, there was no significant difference between the E-aMCI and SMI groups. In our longitudinal data, APOE e4 carrier showed a steeper incline slope in a clinical dementia rating sum of boxes (CDR-SB) score than APOE e4 non-carrier in SMI (B = 0.0066, p = 0.0104), E-aMCI (B = 0.0313, p < 0.0001), and L-aMCI (B = 0.0178, p = 0.0007). APOE e4 carrier showed a steeper decline slope in the CDR-SB than APOE e4 non-carrier in AD (B = − 0.0309, p = 0.0003). These findings suggest that E-aMCI and SMI are associated with a similarly increased frequency of the APOE e4 allele compared to controls, suggesting a greater genetic risk for AD and the importance of monitoring the allele more closely.
Collapse
|
31
|
Stage EC, Svaldi D, Phillips M, Canela VH, Duran T, Goukasian N, Risacher SL, Saykin AJ, Apostolova LG. Neurodegenerative changes in early- and late-onset cognitive impairment with and without brain amyloidosis. Alzheimers Res Ther 2020; 12:93. [PMID: 32758274 PMCID: PMC7409508 DOI: 10.1186/s13195-020-00647-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 06/23/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND A substantial number of patients clinically diagnosed with Alzheimer's disease do not harbor amyloid pathology. We analyzed the presence and extent of tau deposition and neurodegeneration in amyloid-positive (AD) and amyloid-negative (nonAD) ADNI subjects while also taking into account age of onset (< or > 65 years) as we expected that the emerging patterns could vary by age and presence or absence of brain amyloidosis. METHODS One hundred and ten early-onset AD (EOAD), 121 EOnonAD, 364 late-onset AD (LOAD), and 175 LOnonAD mild cognitive impairment (MCI) and dementia (DEM) subjects were compared to 291 ADNI amyloid-negative control subjects using voxel-wise regression in SPM12 with cluster-level family-wise error correction at pFWE < 0.05). A subset of these subjects also received 18F-flortaucipir scans and allowed for analysis of global tau burden. RESULTS As expected, relative to LOAD, EOAD subjects showed more extensive neurodegeneration and tau deposition in AD-relevant regions. EOnonADMCI showed no significant neurodegeneration, while EOnonADDEM showed bilateral medial and lateral temporal, and temporoparietal hypometabolism. LOnonADMCI and LOnonADDEM showed diffuse brain atrophy and a fronto-temporo-parietal hypometabolic pattern. LOnonAD and EOnonAD subjects failed to show significant tau binding. CONCLUSIONS LOnonAD subjects show a fronto-temporal neurodegenerative pattern in the absence of tau binding, which may represent underlying hippocampal sclerosis with TDP-43, also known as limbic-predominant age-related TDP-43 encephalopathy (LATE). The hypometabolic pattern observed in EOnonADDEM seems similar to the one observed in EOADMCI. Further investigation into the underlying etiology of EOnonAD is warranted.
Collapse
Affiliation(s)
- Eddie C Stage
- Department of Neurology, Indiana University School of Medicine, 355 W 16th Street, Suite 4022, Indianapolis, IN, 46202, USA
| | - Diana Svaldi
- Department of Neurology, Indiana University School of Medicine, 355 W 16th Street, Suite 4022, Indianapolis, IN, 46202, USA
- Clinical Imaging, Eli Lilly and Company, Indianapolis, IN, USA
| | - Meredith Phillips
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
| | - Victor Hugo Canela
- Department of Neurology, Indiana University School of Medicine, 355 W 16th Street, Suite 4022, Indianapolis, IN, 46202, USA
| | - Tugce Duran
- Department of Biomedical Sciences Graduate School, Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Naira Goukasian
- University of Vermont College of Medicine, Burlington, VT, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Indianapolis, IN, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, 355 W 16th Street, Suite 4022, Indianapolis, IN, 46202, USA.
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Indianapolis, IN, USA.
| |
Collapse
|
32
|
Moore EE, Liu D, Pechman KR, Acosta LMY, Bell SP, Davis LT, Blennow K, Zetterberg H, Landman BA, Schrag MS, Hohman TJ, Gifford KA, Jefferson AL. Mild Cognitive Impairment Staging Yields Genetic Susceptibility, Biomarker, and Neuroimaging Differences. Front Aging Neurosci 2020; 12:139. [PMID: 32581762 PMCID: PMC7289958 DOI: 10.3389/fnagi.2020.00139] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 04/27/2020] [Indexed: 01/22/2023] Open
Abstract
Introduction While Alzheimer’s disease (AD) is divided into severity stages, mild cognitive impairment (MCI) remains a solitary construct despite clinical and prognostic heterogeneity. This study aimed to characterize differences in genetic, cerebrospinal fluid (CSF), neuroimaging, and neuropsychological markers across clinician-derived MCI stages. Methods Vanderbilt Memory & Aging Project participants with MCI were categorized into 3 severity subtypes at screening based on neuropsychological assessment, functional assessment, and Clinical Dementia Rating interview, including mild (n = 18, 75 ± 8 years), moderate (n = 89 72 ± 7 years), and severe subtypes (n = 18, 78 ± 8 years). At enrollment, participants underwent neuropsychological testing, 3T brain magnetic resonance imaging (MRI), and optional fasting lumbar puncture to obtain CSF. Neuropsychological testing and MRI were repeated at 18-months, 3-years, and 5-years with a mean follow-up time of 3.3 years. Ordinary least square regressions examined cross-sectional associations between MCI severity and apolipoprotein E (APOE)-ε4 status, CSF biomarkers of amyloid beta (Aβ), phosphorylated tau, total tau, and synaptic dysfunction (neurogranin), baseline neuroimaging biomarkers, and baseline neuropsychological performance. Longitudinal associations between baseline MCI severity and neuroimaging and neuropsychological trajectory were assessed using linear mixed effects models with random intercepts and slopes and a follow-up time interaction. Analyses adjusted for baseline age, sex, race/ethnicity, education, and intracranial volume for MRI models. Results Stages differed at baseline on APOE-ε4 status (early < middle = late; p-values < 0.03) and CSF Aβ (early > middle = late), phosphorylated and total tau (early = middle < late; p-values < 0.05), and neurogranin concentrations (early = middle < late; p-values < 0.05). MCI stage related to greater longitudinal cognitive decline, hippocampal atrophy, and inferior lateral ventricle dilation (early < late; p-values < 0.03). Discussion Clinician staging of MCI severity yielded longitudinal cognitive trajectory and structural neuroimaging differences in regions susceptible to AD neuropathology and neurodegeneration. As expected, participants with more severe MCI symptoms at study entry had greater cognitive decline and gray matter atrophy over time. Differences are likely attributable to baseline differences in amyloidosis, tau, and synaptic dysfunction. MCI staging may provide insight into underlying pathology, prognosis, and therapeutic targets.
Collapse
Affiliation(s)
- Elizabeth E Moore
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Dandan Liu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kimberly R Pechman
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Lealani Mae Y Acosta
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Susan P Bell
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - L Taylor Davis
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom.,UK Dementia Research Institute at UCL, London, United Kingdom
| | - Bennett A Landman
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States.,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States.,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Matthew S Schrag
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Timothy J Hohman
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Katherine A Gifford
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Angela L Jefferson
- Vanderbilt Memory & Alzheimer's Center, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States.,Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| |
Collapse
|
33
|
Dibattista M, Pifferi S, Menini A, Reisert J. Alzheimer's Disease: What Can We Learn From the Peripheral Olfactory System? Front Neurosci 2020; 14:440. [PMID: 32508565 PMCID: PMC7248389 DOI: 10.3389/fnins.2020.00440] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 04/09/2020] [Indexed: 01/01/2023] Open
Abstract
The sense of smell has been shown to deteriorate in patients with some neurodegenerative disorders. In Parkinson's disease (PD) and Alzheimer's disease (AD), decreased ability to smell is associated with early disease stages. Thus, olfactory neurons in the nose and olfactory bulb (OB) may provide a window into brain physiology and pathophysiology to address the pathogenesis of neurodegenerative diseases. Because nasal olfactory receptor neurons regenerate throughout life, the olfactory system offers a broad variety of cellular mechanisms that could be altered in AD, including odorant receptor expression, neurogenesis and neurodegeneration in the olfactory epithelium, axonal targeting to the OB, and synaptogenesis and neurogenesis in the OB. This review focuses on pathophysiological changes in the periphery of the olfactory system during the progression of AD in mice, highlighting how the olfactory epithelium and the OB are particularly sensitive to changes in proteins and enzymes involved in AD pathogenesis. Evidence reviewed here in the context of the emergence of other typical pathological changes in AD suggests that olfactory impairments could be used to understand the molecular mechanisms involved in the early phases of the pathology.
Collapse
Affiliation(s)
- Michele Dibattista
- Department of Basic Medical Sciences, Neuroscience and Sensory Organs, University of Bari A. Moro, Bari, Italy
| | - Simone Pifferi
- Neurobiology Group, SISSA, Scuola Internazionale Superiore di Studi Avanzati, Trieste, Italy
| | - Anna Menini
- Neurobiology Group, SISSA, Scuola Internazionale Superiore di Studi Avanzati, Trieste, Italy
| | | |
Collapse
|
34
|
Bernath MM, Bhattacharyya S, Nho K, Barupal DK, Fiehn O, Baillie R, Risacher SL, Arnold M, Jacobson T, Trojanowski JQ, Shaw LM, Weiner MW, Doraiswamy PM, Kaddurah-Daouk R, Saykin AJ. Serum triglycerides in Alzheimer disease: Relation to neuroimaging and CSF biomarkers. Neurology 2020; 94:e2088-e2098. [PMID: 32358220 DOI: 10.1212/wnl.0000000000009436] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 11/19/2019] [Indexed: 01/18/2023] Open
Abstract
OBJECTIVE To investigate the association of triglyceride (TG) principal component scores with Alzheimer disease (AD) and the amyloid, tau, neurodegeneration, and cerebrovascular disease (A/T/N/V) biomarkers for AD. METHODS Serum levels of 84 TG species were measured with untargeted lipid profiling of 689 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, including 190 cognitively normal older adults (CN), 339 with mild cognitive impairment (MCI), and 160 with AD. Principal component analysis with factor rotation was used for dimension reduction of TG species. Differences in principal components between diagnostic groups and associations between principal components and AD biomarkers (including CSF, MRI and [18F]fluorodeoxyglucose-PET) were assessed with a generalized linear model approach. In both cases, the Bonferroni method of adjustment was used to correct for multiple comparisons. RESULTS The 84 TGs yielded 9 principal components, 2 of which, consisting of long-chain, polyunsaturated fatty acid-containing TGs (PUTGs), were significantly associated with MCI and AD. Lower levels of PUTGs were observed in MCI and AD compared to CN. PUTG principal component scores were also significantly associated with hippocampal volume and entorhinal cortical thickness. In participants carrying the APOE ε4 allele, these principal components were significantly associated with CSF β-amyloid1-42 values and entorhinal cortical thickness. CONCLUSION This study shows that PUTG component scores were significantly associated with diagnostic group and AD biomarkers, a finding that was more pronounced in APOE ε4 carriers. Replication in independent larger studies and longitudinal follow-up are warranted.
Collapse
Affiliation(s)
- Megan M Bernath
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Sudeepa Bhattacharyya
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Kwangsik Nho
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Dinesh Kumar Barupal
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Oliver Fiehn
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Rebecca Baillie
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Shannon L Risacher
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Matthias Arnold
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Tanner Jacobson
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - John Q Trojanowski
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Leslie M Shaw
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Michael W Weiner
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - P Murali Doraiswamy
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Rima Kaddurah-Daouk
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC
| | - Andrew J Saykin
- From the Department of Radiology and Imaging Sciences (M.M.B., K.N., S.L.R., T.J., A.J.S.), Center for Neuroimaging, Indiana Alzheimer Disease Center (M.M.B., K.N., S.L.R., T.J., A.J.S.), Medical and Molecular Genetics Department (M.M.B., T.J., A.J.S.), and Medical Scientist Training Program (M.M.B.), Indiana University School of Medicine, Indianapolis; Department of Pediatrics (S.B.), University of Arkansas for Medical Sciences, Little Rock; Department of Environmental Medicine and Public Health (D.K.B.), Icahn School of Medicine at Mt Sinai, New York; NIH-West Coast Metabolomics Center (D.K.B., O.F.), University of California, Davis; Rosa & Co LLC (R.B.), San Carlos, CA; Institute of Bioinformatics and Systems Biology (M.A.), Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Department of Pathology & Laboratory Medicine (J.Q.T., L.M.S.), University of Pennsylvania, Philadelphia; Department of Radiology (M.W.W.), Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco; and Department of Psychiatry and Behavioral Sciences (M.A., P.M.D., R.K.-D.), Duke Institute of Brain Sciences (R.K.-D.), and Department of Medicine (R.K.-D.), Duke University, Durham, NC.
| | | |
Collapse
|
35
|
Rodriguez-Vieitez E, Nielsen HM. Associations Between APOE Variants, Tau and α-Synuclein. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1184:177-186. [PMID: 32096038 DOI: 10.1007/978-981-32-9358-8_15] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Neurodegenerative diseases are characterized by the aggregation and deposition of misfolded proteins in the brain, most prominently amyloid-β (Aβ), tau and α-synuclein (α-syn), and are thus referred to as proteinopathies. While tau is a hallmark of Alzheimer's disease (AD) and other non-AD tauopathies, and α-synuclein is the pathological feature of the spectrum of synucleinopathies including Parkinson's disease (PD), Parkinson's disease with dementia (PDD) and dementia with Lewy bodies (DLB), the presence of co-pathologies is very frequent in all these diseases. Positive and synergistic associations between the different types of protein deposits have been reported, leading to worse prognosis and cognitive decline. A large variation in phenotypic clinical presentation of these diseases, largely due to the frequent presence of co-pathologies, makes differential diagnosis challenging. The observed clinico-pathological overlaps suggest common underlying mechanisms, in part due to shared genetic risk factors. The ε4 allele of the apolipoprotein (APOE) gene is one of the major genetic risk factors for the sporadic forms of proteinopathies, but the biological mechanisms linking APOE, tau and α-syn are not fully understood. This chapter describes current experimental evidence on the relationships between APOE variants, tau and α-syn, from clinical studies on fluid biomarkers and positron emission tomography (PET) imaging, and from basic experimental studies in cellular/molecular biology and animal models. The chapter focuses on recent advances and identifies knowledge gaps. In particular, no PET tracer for assessment of brain α-syn deposits is yet available, although it is subject of intense research and development, therefore experimental evidence on in vivo α-syn levels is based on measures in the cerebrospinal fluid (CSF) and plasma. Moreover, tau PET imaging studies comparing the patterns of tracer retention in synucleinopathies versus in other proteinopathies are scarce and much is still unknown regarding the relationships between APOE variants and fluid and/or imaging biomarkers of tau and α-syn. Further research incorporating multimodal imaging, fluid biomarkers and genetic factors will help elucidate the biological mechanisms underlying these proteinopathies, and contribute to differential diagnosis and patient stratification for clinical trials.
Collapse
Affiliation(s)
- Elena Rodriguez-Vieitez
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Henrietta M Nielsen
- Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
| |
Collapse
|
36
|
Coughlin JM, Rubin LH, Du Y, Rowe SP, Crawford JL, Rosenthal HB, Frey SM, Marshall ES, Shinehouse LK, Chen A, Speck CL, Wang Y, Lesniak WG, Minn I, Bakker A, Kamath V, Smith GS, Albert MS, Azad BB, Dannals RF, Horti A, Wong DF, Pomper MG. High Availability of the α7-Nicotinic Acetylcholine Receptor in Brains of Individuals with Mild Cognitive Impairment: A Pilot Study Using 18F-ASEM PET. J Nucl Med 2020; 61:423-426. [PMID: 31420499 PMCID: PMC9374031 DOI: 10.2967/jnumed.119.230979] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 07/23/2019] [Indexed: 01/05/2023] Open
Abstract
Emerging evidence supports a hypothesized role for the α7-nicotinic acetylcholine receptor (α7-nAChR) in the pathophysiology of Alzheimer's disease. 18F-ASEM (3-(1,4-diazabicyclo[3.2.2]nonan-4-yl)-6-18F-fluorodibenzo[b,d]thiophene 5,5-dioxide) is a radioligand for estimating the availability of α7-nAChR in the brain in vivo with PET. Methods: In this cross-sectional study, 14 patients with mild cognitive impairment (MCI), a prodromal stage to dementia, and 17 cognitively intact, elderly controls completed 18F-ASEM PET. For each participant, binding in each region of interest was estimated using Logan graphical analysis with a metabolite-corrected arterial input function. Results: Higher 18F-ASEM binding was observed in MCI patients than in controls across all regions, supporting higher availability of α7-nAChR in MCI. 18F-ASEM binding was not associated with verbal memory in this small MCI sample. Conclusion: These data support use of 18F-ASEM PET to examine further the relationship between α7-nAChR availability and MCI.
Collapse
Affiliation(s)
- Jennifer M Coughlin
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Leah H Rubin
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Neurology, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Medical Institutions, Baltimore, Maryland; and
| | - Yong Du
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Steven P Rowe
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Jeffrey L Crawford
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Hailey B Rosenthal
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Sarah M Frey
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Erica S Marshall
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Laura K Shinehouse
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Allen Chen
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Caroline L Speck
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Yuchuan Wang
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Wojciech G Lesniak
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Il Minn
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Arnold Bakker
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Vidyulata Kamath
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Gwenn S Smith
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Babak Behnam Azad
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Robert F Dannals
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Andrew Horti
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Dean F Wong
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Neurology, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Neuroscience, Johns Hopkins Medical Institutions, Baltimore, Maryland
| | - Martin G Pomper
- Department of Psychiatry, Johns Hopkins Medical Institutions, Baltimore, Maryland
- Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland
| |
Collapse
|
37
|
Zhang C, Kong M, Wei H, Zhang H, Ma G, Ba M. The effect of ApoE ε 4 on clinical and structural MRI markers in prodromal Alzheimer's disease. Quant Imaging Med Surg 2020; 10:464-474. [PMID: 32190571 PMCID: PMC7063277 DOI: 10.21037/qims.2020.01.14] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 01/15/2020] [Indexed: 12/18/2022]
Abstract
BACKGROUND Apolipoprotein E (ApoE) ε 4 has been identified as the strongest genetic risk factor for Alzheimer's disease (AD). However, the importance of ApoE ε 4 on clinical and biological heterogeneity of AD is still to be determined, particularly at the prodromal stage. Here, we evaluate the association of ApoE ε 4 with clinical cognition and neuroimaging regions in mild cognitive impairment (MCI) participants based on the AT (N) system, which is increasingly essential for developing a precise assessment of AD. METHODS We stratified 178 A+T+MCI participants (prodromal AD) into ApoE ε 4 (+) and ApoE ε 4 (-) according to ApoE genotype from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We determined Aβ-positivity (A+) by the standardized uptake values ratios (SUVR) means of florbetapir-PET-AV45 (the cut-off value of 1.1) and fibrillar tau-positivity (T+) by cerebrospinal fluid (CSF) phosphorylated-tau at threonine 181 position (p-Tau) (cut-off value of 23 pg/mL). We evaluated the effect of ApoE ε 4 status on cognitive conditions and brain atrophy from structural magnetic resonance imaging (MRI) scans. A multivariate analysis of variance was used to compare the differences of cognitive scores and brain atrophy from structural MRI regions of interest (ROIs) between both groups. Furthermore, we performed a linear regression model to assess the correlation between signature ROIs of structural MRI and cognitive scores in the prodromal AD participants. RESULTS ApoE ε 4 (+) prodromal AD participants had lower levels of CSF Aβ 1-42, higher levels of t-Tau, more memory and global cognitive impairment, and faster decline of global cognition, compared to ApoE ε 4 (-) prodromal AD. ApoE ε 4 (+) prodromal AD participants had a thinner cortical thickness of bilateral entorhinal, smaller subcortical volume of the left amygdala, bilateral hippocampus, and left ventral diencephalon (DC) relative to ApoE ε 4 (-) prodromal AD. Furthermore, the cortical thickness average of bilateral entorhinal was highly correlated with memory and global cognition. CONCLUSIONS ApoE ε 4 status in prodromal AD participants has an important effect on clinical cognitive domains. After ascertaining the ApoE ε 4 status, specific MRI regions can be correlated to the cognitive domain and will be helpful for precise assessment in prodromal AD.
Collapse
Affiliation(s)
- Chunhua Zhang
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, China
| | - Min Kong
- Department of Neurology, Yantaishan Hospital, Yantai 264000, China
| | - Hongchun Wei
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, China
| | - Hua Zhang
- Department of Neurology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Guozhao Ma
- Department of Neurology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| | - Maowen Ba
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, China
| | - for the Alzheimer’s Disease Neuroimaging Initiative
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, China
- Department of Neurology, Yantaishan Hospital, Yantai 264000, China
- Department of Neurology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
- Department of Neurology, East Hospital, Tongji University School of Medicine, Shanghai 200120, China
| |
Collapse
|
38
|
Phillips ML, Stage EC, Lane KA, Gao S, Risacher SL, Goukasian N, Saykin AJ, Carrillo MC, Dickerson BC, Rabinovici GD, Apostolova LG. Neurodegenerative Patterns of Cognitive Clusters of Early-Onset Alzheimer's Disease Subjects: Evidence for Disease Heterogeneity. Dement Geriatr Cogn Disord 2020; 48:131-142. [PMID: 31901905 PMCID: PMC7031037 DOI: 10.1159/000504341] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 10/24/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND/AIMS Alzheimer's disease (AD) with onset before 65 (early-onset AD [EOAD]) occurs in approximately 6% of cases and can affect nonmemory domains. Here, we analyze patterns of impairment in amnestic EOAD individuals using data-driven statistical analyses. METHODS Cognitive data of 146 EOAD subjects were Z-normalized to 395 cognitively normal (CN) individuals. Domain-averaged Z-scores were adjusted for age, sex, and education followed by Wald cluster analysis of residuals. Magnetic resonance imaging and positron emission tomography comparisons of EOAD clusters to age-matched CN were done using Statistic Parametric Mapping 8. Cluster-level-family-wise error (p < 0.05) correction was applied. Mixed-effect models were used to compute longitudinal change across clusters. RESULTS Scree plot using the pseudo-T-squared suggested a 4-cluster solution. Cluster 1 (memory-predominant impairment) showed atrophy/hypometabolism in medial/lateral temporal, lateral parietal, and posterior cingulate regions. Cluster 2 (memory/visuospatial-predominant) showed atrophy/hypometabolism of medial temporal, temporoparietal, and frontal cortices. Cluster 3 (memory, language, and executive function) and Cluster 4 (globally impaired) manifested atrophy and hypometabolism throughout the brain. Longitudinally between-cluster differences in the visuospatial and language/executive domains were significant, suggesting phenotypic variation. CONCLUSION We observed significant heterogeneity in cognitive presentation among amnestic EOAD subjects and patterns of atrophy/hypometabolism in each cluster in agreement with the observed cognitive phenotype.
Collapse
Affiliation(s)
- Meredith L Phillips
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, Indiana, USA,
| | - Eddie C Stage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kathleen A Lane
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sujuan Gao
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Shannon L Risacher
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Andrew J Saykin
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana University Network Science Institute, Indianapolis, Indiana, USA
| | | | | | - Gil D Rabinovici
- University of California San Francisco, San Francisco, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Indiana University Network Science Institute, Indianapolis, Indiana, USA
| |
Collapse
|
39
|
Marizzoni M, Ferrari C, Babiloni C, Albani D, Barkhof F, Cavaliere L, Didic M, Forloni G, Fusco F, Galluzzi S, Hensch T, Jovicich J, Marra C, Molinuevo JL, Nobili F, Parnetti L, Payoux P, Ranjeva JP, Ribaldi F, Rolandi E, Rossini PM, Salvatore M, Soricelli A, Tsolaki M, Visser PJ, Wiltfang J, Richardson JC, Bordet R, Blin O, Frisoni GB. CSF cutoffs for MCI due to AD depend on APOEε4 carrier status. Neurobiol Aging 2019; 89:55-62. [PMID: 32029236 DOI: 10.1016/j.neurobiolaging.2019.12.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 12/20/2019] [Accepted: 12/21/2019] [Indexed: 12/14/2022]
Abstract
Amyloid and tau pathological accumulation should be considered for Alzheimer's disease (AD) definition and before subjects' enrollment in disease-modifying trials. Although age, APOEε4, and sex influence cerebrospinal fluid (CSF) biomarker levels, none of these variables are considered by current normality/abnormality cutoffs. Using baseline CSF data from 2 independent cohorts (PharmaCOG/European Alzheimer's Disease Neuroimaging Initiative and Alzheimer's Disease Neuroimaging Initiative), we investigated the effect of age, APOEε4 status, and sex on CSF Aβ42/P-tau distribution and cutoff extraction by applying mixture models with covariates. The Aβ42/P-tau distribution revealed the presence of 3 subgroups (AD-like, intermediate, control-like) and 2 cutoffs. The identification of the intermediate subgroup and of the higher cutoff was APOEε4 dependent in both cohorts. APOE-specific classification (higher cutoff for APOEε4+, lower cutoff for APOEε4-) showed higher diagnostic accuracy in identifying MCI due to AD compared to single Aβ42 and Aβ42/P-tau cutoffs. APOEε4 influences amyloid and tau CSF markers and AD progression in MCI patients supporting i) the use of APOE-specific cutoffs to identify MCI due to AD and ii) the utility of considering APOE genotype for early AD diagnosis.
Collapse
Affiliation(s)
- Moira Marizzoni
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "V. Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino (FR), Cassino, Italy
| | - Diego Albani
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands; Institutes of Neurology and Healthcare Engineering, UCL, London, UK
| | - Libera Cavaliere
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Mira Didic
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone, Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Federica Fusco
- Neuroscience Department, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy
| | - Samantha Galluzzi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig, Leipzig, Germany
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Camillo Marra
- Department of Gerontology, Neurosciences & Orthopedics, Catholic University, Rome, Italy
| | - José Luis Molinuevo
- Alzheimer's Disease Unit and Other Cognitive Disorders Unit, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Flavio Nobili
- Dept. of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy; Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Lucilla Parnetti
- Clinica Neurologica, Università di Perugia, Ospedale Santa Maria della Misericordia, Perugia, Italy
| | - Pierre Payoux
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, INSERM, Marseille, France; Service de Neurologie et Neuropsychologie, APHM Hôpital Timone Adultes, Marseille, France
| | - Federica Ribaldi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Elena Rolandi
- Laboratory of Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Marco Salvatore
- SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy
| | | | - Magda Tsolaki
- 1st University Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Makedonia, Greece
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Centre, VU Medical Centre, Amsterdam, the Netherlands
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, LVR-Hospital Essen, Faculty of Medicine, University of Duisburg-Essen, Essen, Germany; Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Goettingen, Germany; Medical Sciences Department, iBiMED, University of Aveiro, Aveiro, Portugal
| | | | - Régis Bordet
- University of Lille, Inserm, CHU, Lille, France; U1171 - Degenerative and Vascular Cognitive Disorders, Lille, France
| | - Olivier Blin
- Aix Marseille University, UMR-INSERM 1106, Service de Pharmacologie Clinique, APHM, Marseille, France
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| |
Collapse
|
40
|
Lin SY, Lin KJ, Lin PC, Huang CC, Chang CC, Lee YC, Hsiao IT, Yen TC, Huang WS, Yang BH, Wang PN. Plasma amyloid assay as a pre-screening tool for amyloid positron emission tomography imaging in early stage Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2019; 11:111. [PMID: 31881963 PMCID: PMC6933740 DOI: 10.1186/s13195-019-0566-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 12/05/2019] [Indexed: 11/10/2022]
Abstract
INTRODUCTION Due to the high cost and high failure rate of ascertaining amyloid positron emission tomography positivity (PET+) in patients with earlier stage Alzheimer's disease (AD), an effective pre-screening tool for amyloid PET scans is needed. METHODS Patients with mild cognitive impairment (n = 33, 24.2% PET+, 42% females, age 74.4 ± 7.5, MMSE 26.8 ± 1.9) and mild dementia (n = 19, 63.6% PET+, 36.3% females, age 73.0 ± 9.3, MMSE 22.6 ± 2.0) were recruited. Amyloid PET imaging, Apolipoprotein E (APOE) genotyping, and plasma amyloid β (Aβ)1-40, Aβ1-42, and total tau protein quantification by immunomagnetic reduction (IMR) method were performed. Receiver operating characteristics (ROC) analysis and Youden's index were performed to identify possible cut-off points, clinical sensitivities/specificities, and areas under the curve (AUCs). RESULTS Amyloid PET+ participants had lower plasma Aβ1-42 levels than amyloid PET-negative (PET-) subjects. APOE ε4 carriers had higher plasma Aβ1-42 than non-carriers. We developed an algorithm involving the combination of plasma Aβ1-42 and APOE genotyping. The success rate for detecting amyloid PET+ patients effectively increased from 42.3 to 70.4% among clinically suspected MCI and mild dementia patients. CONCLUSIONS Our results demonstrate the possibility of utilizing APOE genotypes in combination with plasma Aβ1-42 levels as a pre-screening tool for predicting the positivity of amyloid PET findings in early stage dementia patients.
Collapse
Affiliation(s)
- Szu-Ying Lin
- Department of Neurology, Taipei Municipal Gan-Dau Hospital, Taipei, Taiwan
| | - Kun-Ju Lin
- Department of Nuclear Medicine and Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Tao-Yuan, Taiwan. .,Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan.
| | - Po-Chen Lin
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chin-Chang Huang
- Department of Neurology, Linkou Chang Gung Memorial Hospital and University, Tao-Yuan, Taiwan
| | - Chiung-Chih Chang
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yi-Chung Lee
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan.,Brain Research Center, National Yang-Ming University, Taipei, Taiwan
| | - Ing-Tsung Hsiao
- Department of Nuclear Medicine and Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Tao-Yuan, Taiwan.,Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
| | - Tzu-Chen Yen
- Department of Nuclear Medicine and Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Tao-Yuan, Taiwan.,Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
| | - Wen-Sheng Huang
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Bang-Hung Yang
- Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, School of Medicine, National Yang-Ming University, Taipei, Taiwan. .,Brain Research Center, National Yang-Ming University, Taipei, Taiwan. .,Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan. .,Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.
| |
Collapse
|
41
|
Horgusluoglu-Moloch E, Risacher SL, Crane PK, Hibar D, Thompson PM, Saykin AJ, Nho K. Genome-wide association analysis of hippocampal volume identifies enrichment of neurogenesis-related pathways. Sci Rep 2019; 9:14498. [PMID: 31601890 PMCID: PMC6787090 DOI: 10.1038/s41598-019-50507-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 09/09/2019] [Indexed: 01/04/2023] Open
Abstract
Adult neurogenesis occurs in the dentate gyrus of the hippocampus during adulthood and contributes to sustaining the hippocampal formation. To investigate whether neurogenesis-related pathways are associated with hippocampal volume, we performed gene-set enrichment analysis using summary statistics from a large-scale genome-wide association study (N = 13,163) of hippocampal volume from the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium and two year hippocampal volume changes from baseline in cognitively normal individuals from Alzheimer's Disease Neuroimaging Initiative Cohort (ADNI). Gene-set enrichment analysis of hippocampal volume identified 44 significantly enriched biological pathways (FDR corrected p-value < 0.05), of which 38 pathways were related to neurogenesis-related processes including neurogenesis, generation of new neurons, neuronal development, and neuronal migration and differentiation. For genes highly represented in the significantly enriched neurogenesis-related pathways, gene-based association analysis identified TESC, ACVR1, MSRB3, and DPP4 as significantly associated with hippocampal volume. Furthermore, co-expression network-based functional analysis of gene expression data in the hippocampal subfields, CA1 and CA3, from 32 normal controls showed that distinct co-expression modules were mostly enriched in neurogenesis related pathways. Our results suggest that neurogenesis-related pathways may be enriched for hippocampal volume and that hippocampal volume may serve as a potential phenotype for the investigation of human adult neurogenesis.
Collapse
Grants
- UL1 TR001108 NCATS NIH HHS
- R01 CA129769 NCI NIH HHS
- R35 CA197289 NCI NIH HHS
- P50 GM115318 NIGMS NIH HHS
- R01 AG019771 NIA NIH HHS
- P30 AG010133 NIA NIH HHS
- R03 AG054936 NIA NIH HHS
- U01 AG024904 NIA NIH HHS
- UL1 TR002369 NCATS NIH HHS
- R01 LM011360 NLM NIH HHS
- U54 EB020403 NIBIB NIH HHS
- K01 AG049050 NIA NIH HHS
- R01 LM012535 NLM NIH HHS
- CIHR
- NLM R01 LM012535, NIA R03 AG054936, NIA R01 AG19771, NIA P30 AG10133, NLM R01 LM011360, NSF IIS-1117335, DOD W81XWH-14-2-0151, NCAA 14132004, NIGMS P50GM115318, NCATS UL1 TR001108, NIA K01 AG049050, the Alzheimer’s Association, the Indiana Clinical and Translational Science Institute, and the IU Health-IU School of Medicine Strategic Neuroscience Research Initiative.
- ENIGMA was supported in part by a Consortium grant (U54EB020403 to PMT) from the NIH Institutes contributing to the Big Data to Knowledge (BD2K) Initiative, including the NIBIB and NCI.
- Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. Additional support for data analysis was provided by NLM R01 LM012535, NIA R03 AG054936, NIA R01 AG19771, NIA P30 AG10133, NLM R01 LM011360, NSF IIS-1117335, DOD W81XWH-14-2-0151, NCAA 14132004, NIGMS P50GM115318, NCATS UL1 TR001108, NIA K01 AG049050, the Alzheimer’s Association, the Indiana Clinical and Translational Science Institute, and the IU Health-IU School of Medicine Strategic Neuroscience Research Initiative.
Collapse
Affiliation(s)
- Emrin Horgusluoglu-Moloch
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Paul K Crane
- Department of Medicine, University of Washington, School of Medicine, Seattle, WA, USA
| | - Derrek Hibar
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, USC Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Neuroscience Biomarkers, Janssen Research and Development, LLC, San Diego, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, USC Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrew J Saykin
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Kwangsik Nho
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
| |
Collapse
|
42
|
Kim SE, Woo S, Kim SW, Chin J, Kim HJ, Lee BI, Park J, Park KW, Kang DY, Noh Y, Ye BS, Yoo HS, Lee JS, Kim Y, Kim SJ, Cho SH, Na DL, Lockhart SN, Jang H, Seo SW. A Nomogram for Predicting Amyloid PET Positivity in Amnestic Mild Cognitive Impairment. J Alzheimers Dis 2019; 66:681-691. [PMID: 30320571 DOI: 10.3233/jad-180048] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Most clinical trials focus on amyloid-β positive (Aβ+) amnestic mild cognitive impairment (aMCI), but screening failures are high because only a half of patients with aMCI are positive on Aβ PET. Therefore, it becomes necessary for clinicians to predict which patients will have Aβ biomarker. OBJECTIVE We aimed to compare clinical factors, neuropsychological (NP) profiles, and apolipoprotein E (APOE) genotype between Aβ+ aMCI and Aβ-aMCI and to develop a clinically useful prediction model of Aβ positivity on PET (PET-Aβ+) in aMCI using a nomogram. METHODS We recruited 523 aMCI patients who underwent Aβ PET imaging in a nation-wide multicenter cohort. The results of NP measures were divided into following subgroups: 1) Stage (Early and Late-stage), 2) Modality (Visual, Verbal, and Both), 3) Recognition failure, and 4) Multiplicity (Single and Multiple). A nomogram for PET-Aβ+ in aMCI patients was constructed using a logistic regression model. RESULTS PET-Aβ+ had significant associations with NP profiles for several items, including high Clinical Dementia Rating Scale Sum of Boxes score (OR 1.47, p = 0.013) and impaired memory modality (impaired both visual and verbal memories compared with visual only, OR 3.25, p = 0.001). Also, presence of APOEɛ4 (OR 4.14, p < 0.001) was associated with PET-Aβ+. These predictors were applied to develop the nomogram, which showed good prediction performance (C-statistics = 0.79). Its prediction performances were 0.77/0.74 in internal/external validation. CONCLUSIONS The nomogram consisting of NP profiles, especially memory domain, and APOEɛ4 genotype may provide a useful predictive model of PET-Aβ+ in patients with aMCI.
Collapse
Affiliation(s)
- Si Eun Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Sookyoung Woo
- Statistics and Data Center, Samsung Medical Center, Seoul, Korea
| | - Seon Woo Kim
- Statistics and Data Center, Samsung Medical Center, Seoul, Korea
| | - Juhee Chin
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Hee Jin Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Byung In Lee
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Jinse Park
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A University College of Medicine, Dong-A University Medical Center, Busan, Korea
| | - Do-Young Kang
- Department of Nuclear Medicine, Dong-A University College of Medicine, Dong-A University Medical Center, Busan, Korea
| | - Young Noh
- Department of Neurology, Gachon University Gil Medical Center, Incheon, Korea
| | - Byoung Seok Ye
- Department of Neurology, Yonsei University School of Medicine, Severance hospital, Seoul, Korea
| | - Han Soo Yoo
- Department of Neurology, Yonsei University School of Medicine, Severance hospital, Seoul, Korea
| | - Jin San Lee
- Department of Neurology, Kyung Hee University Hospital, Seoul, Korea
| | - Yeshin Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Kangwon National University College of Medicine, Chuncheon-si, Gangwon-do, Korea
| | - Seung Joo Kim
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Soo Hyun Cho
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Duk L Na
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Samuel N Lockhart
- Department of Internal Medicine, Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Hyemin Jang
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| | - Sang Won Seo
- Department of Neurology, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Korea
| |
Collapse
|
43
|
Peng B, Yao X, Risacher SL, Saykin AJ, Shen L, Ning X. Prioritization of Cognitive Assessments in Alzheimer's Disease via Learning to Rank using Brain Morphometric Data. ... IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS. IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS 2019; 2019. [PMID: 31934686 DOI: 10.1109/bhi.2019.8834618] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
We propose an innovative machine learning paradigm enabling precision medicine for prioritizing cognitive assessments according to their relevance to Alzheimer's disease at the individual patient level. The paradigm tailors the cognitive biomarker discovery and cognitive assessment selection process to the brain morphometric characteristics of each individual patient. We implement this paradigm using a newly developed learning-to-rank method PLTR. Our empirical study on the ADNI data yields promising results to identify and prioritize individual-specific cognitive biomarkers as well as cognitive assessment tasks based on the individual's structural MRI data. The resulting top ranked cognitive biomarkers and assessment tasks have the potential to aid personalized diagnosis and disease subtyping.
Collapse
Affiliation(s)
- Bo Peng
- Computer & Information Science IUPUI, Indianapolis, IN
| | - Xiaohui Yao
- Biostatistics, Epidemiology & Informatics University of Pennsylvania, Philadelphia, PA
| | | | - Andrew J Saykin
- Radiology & Imaging Sciences Indiana University, Indianapolis, IN
| | - Li Shen
- Biostatistics, Epidemiology & Informatics University of Pennsylvania, Philadelphia, PA
| | - Xia Ning
- Biomedical Informatics Ohio State University, Columbus, OH
| |
Collapse
|
44
|
Kang DW, Lim HK, Joo SH, Lee NR, Lee CU. Differential Associations Between Volumes of Atrophic Cortical Brain Regions and Memory Performances in Early and Late Mild Cognitive Impairment. Front Aging Neurosci 2019; 11:245. [PMID: 31551759 PMCID: PMC6738351 DOI: 10.3389/fnagi.2019.00245] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 08/20/2019] [Indexed: 11/13/2022] Open
Abstract
Background Early and late mild cognitive impairment (MCI) patients have been reported to have a distinctive prognosis of converting to Alzheimer’s disease. Objective To evaluate the difference in gray matter volume and assess the association between cognitive function evaluated by comprehensive cognitive function test, and cortical thickness across healthy controls (HCs) (n = 37), early (n = 30), and late MCI patients (n = 35). Methods Differences in gray matter volume were evaluated by whole brain voxel-based morphometry across the groups. Multiple regression analysis was used to analyze group by memory performance interactions for the normalized gray matter volume. Results The early MCI group showed reduced gray matter volume in the right middle temporal gyrus in comparison to the HC group. The late MCI group displayed atrophy in the left parahippocampal gyrus in comparison to the HC group. Late MCI patients exhibited a decreased gray matter volume in the left fusiform gyrus in comparison to patients in the early MCI group (Monte Carlo simulation corrected p < 0.01, Tukey post hoc tests). Furthermore, there was a significant group (HC vs. early MCI) by memory performance interaction for the normalized cortical volume of the right middle temporal gyrus. Additionally, a significant group (early MCI vs. late MCI) by memory performance interaction was found for the normalized gray matter volume of the left fusiform gyrus (p < 0.001). Conclusion Early and late MCI patients showed distinctive associations of gray matter volumes in compensatory brain regions with memory performances. The findings can contribute to a better understanding of the structural changes in compensatory brain regions to elucidate memory decline in the trajectory of the subdivided prodromal stages of the Alzheimer’s disease (AD).
Collapse
Affiliation(s)
- Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Hyun Kook Lim
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Soo-Hyun Joo
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Na Rae Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Chang Uk Lee
- Department of Psychiatry, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| |
Collapse
|
45
|
Clark DO, Xu H, Moser L, Adeoye P, Lin AW, Tangney CC, Risacher SL, Saykin AJ, Considine RV, Unverzagt FW. MIND food and speed of processing training in older adults with low education, the MINDSpeed Alzheimer's disease prevention pilot trial. Contemp Clin Trials 2019; 84:105814. [PMID: 31326523 PMCID: PMC6721976 DOI: 10.1016/j.cct.2019.105814] [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] [Received: 01/22/2019] [Revised: 07/11/2019] [Accepted: 07/16/2019] [Indexed: 11/18/2022]
Abstract
BACKGROUND Multiple national organizations and leaders have called for increased attention to dementia prevention in those most vulnerable, for example persons with limited formal education. Prevention recommendations have included calls for multicomponent interventions that have the potential to improve both underlying neurobiological health and the ability to function despite neurobiological pathology, or what has been termed cognitive reserve. OBJECTIVES Test feasibility, treatment modifier, mechanism, and cognitive function effects of a multicomponent intervention consisting of foods high in polyphenols (i.e., MIND foods) to target neurobiological health, and speed of processing training to enhance cognitive reserve. We refer to this multicomponent intervention as MINDSpeed. DESIGN MINDSpeed is being evaluated in a 2 × 2 randomized factorial design with 180 participants residing independently in a large Midwestern city. Qualifying participants are 60 years of age or older with no evidence of dementia, and who have completed 12 years or less of education. All participants receive a study-issued iPad to access the custom study application that enables participants, depending on randomization, to select either control or MIND food, and to play online cognitive games, either speed of processing or control games. METHODS All participants complete informed consent and baseline assessment, including urine and blood samples. Additionally, up to 90 participants will complete neuroimaging. Assessments are repeated immediately following 12 weeks of active intervention, and at 24 weeks post-randomization. The primary outcome is an executive cognitive composite score. Secondary outcomes include oxidative stress, pro-inflammatory cytokines, and neuroimaging-captured structural and functional metrics of the hippocampus and cortical brain regions. SUMMARY MINDSpeed is the first study to evaluate the multicomponent intervention of high polyphenol intake and speed of processing training. It is also one of the first dementia prevention trials to target older adults with low education. The results of the study will guide future dementia prevention efforts and trials in high risk populations.
Collapse
Affiliation(s)
- Daniel O Clark
- Indiana University Center for Aging Research, Indianapolis, IN, United States of America; Regenstrief Institute, Inc., Indianapolis, IN, United States of America; Department of Medicine, Division of General Internal Medicine and Geriatrics, Indiana University School of Medicine, Indianapolis, IN, United States of America.
| | - Huiping Xu
- Indiana University Center for Aging Research, Indianapolis, IN, United States of America; Regenstrief Institute, Inc., Indianapolis, IN, United States of America; Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, United States of America
| | - Lyndsi Moser
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States of America
| | - Philip Adeoye
- Indiana University Center for Aging Research, Indianapolis, IN, United States of America; Regenstrief Institute, Inc., Indianapolis, IN, United States of America
| | - Annie W Lin
- Department of Preventive Medicine, Northwestern University, Chicago, IL, United States of America
| | - Christy C Tangney
- Department of Clinical Nutrition, Rush University Medical Center, Chicago, IL, United States of America
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States of America
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States of America
| | - Robert V Considine
- Department of Medicine, Division of Endocrinology, Indiana University School of Medicine, Indianapolis, IN, United States of America
| | - Frederick W Unverzagt
- Indiana University Center for Aging Research, Indianapolis, IN, United States of America; Regenstrief Institute, Inc., Indianapolis, IN, United States of America; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States of America
| |
Collapse
|
46
|
Moscoso A, Silva-Rodríguez J, Aldrey JM, Cortés J, Fernández-Ferreiro A, Gómez-Lado N, Ruibal Á, Aguiar P. Staging the cognitive continuum in prodromal Alzheimer's disease with episodic memory. Neurobiol Aging 2019; 84:1-8. [PMID: 31479859 DOI: 10.1016/j.neurobiolaging.2019.07.014] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 07/23/2019] [Accepted: 07/24/2019] [Indexed: 11/26/2022]
Abstract
It is unclear whether episodic memory is an appropriate descriptor of the cognitive continuum in mild cognitive impairment (MCI). Here, we investigated the ability of episodic memory to track cognitive changes in patients with MCI with biomarker evidence of Alzheimer's disease (AD). We examined 387 MCI amyloid-positive subjects, cognitively staged as "early" or "late" on the basis of episodic memory impairment. Cross-sectional and longitudinal comparisons between these 2 groups were performed for each amyloid, tau, and neurodegeneration (AT(N)) profile. Cross-sectional analyses indicate that "early" MCI represents a transitional phase between normal cognition and "late" MCI in the AD biomarker pathway. After adjusting by confounders and levels of A, T, and (N), "late" MCI progressed significantly faster than "early" MCI only in profiles with both abnormal amyloid and tau markers (A+T+(N)- p < 0.05, A+T+(N)+ p < 0.001). Episodic memory staging is useful for describing symptoms in prodromal AD and complements the AT(N) profiles. Our findings might have implications for the Numeric Clinical staging scheme of the National Institute on Aging and Alzheimer's Association research framework.
Collapse
Affiliation(s)
- Alexis Moscoso
- Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Santiago de Compostela, Spain
| | - Jesús Silva-Rodríguez
- Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Santiago de Compostela, Spain
| | - Jose Manuel Aldrey
- Neurology Department, University Hospital CHUS-IDIS, Santiago de Compostela, Spain
| | - Julia Cortés
- Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Santiago de Compostela, Spain
| | - Anxo Fernández-Ferreiro
- Pharmacy Department and Pharmacology group, University Hospital CHUS-IDIS, Santiago de Compostela, Spain
| | - Noemí Gómez-Lado
- Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Santiago de Compostela, Spain
| | - Álvaro Ruibal
- Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Santiago de Compostela, Spain; Department of Radiology, Molecular Imaging Group, Faculty of Medicine, University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Spain; Fundación Tejerina, Madrid, Spain
| | - Pablo Aguiar
- Nuclear Medicine Department and Molecular Imaging Group, University Hospital CHUS-IDIS, Santiago de Compostela, Spain; Department of Radiology, Molecular Imaging Group, Faculty of Medicine, University of Santiago de Compostela (USC), Campus Vida, Santiago de Compostela, Spain.
| | | |
Collapse
|
47
|
Stockburger C, Eckert S, Eckert GP, Friedland K, Müller WE. Mitochondrial Function, Dynamics, and Permeability Transition: A Complex Love Triangle as A Possible Target for the Treatment of Brain Aging and Alzheimer's Disease. J Alzheimers Dis 2019; 64:S455-S467. [PMID: 29504539 DOI: 10.3233/jad-179915] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Because of the failure of all amyloid-β directed treatment strategies for Alzheimer's disease (AD), the concept of mitochondrial dysfunction as a major pathomechanism of the cognitive decline in aging and AD has received substantial support. Accordingly, improving mitochondrial function as an alternative strategy for new drug development became of increasing interest and many different compounds have been identified which improve mitochondrial function in preclinical in vitro and in vivo experiments. However, very few if any have been investigated in clinical trials, representing a major drawback of the mitochondria directed drug development. To overcome these problems, we used a top-down approach by investigating several older antidementia drugs with clinical evidence of therapeutic efficacy. These include EGb761® (standardized ginkgo biloba extract), piracetam, and Dimebon. All improve experimentally many aspects of mitochondrial dysfunction including mitochondrial dynamics and also improve cognition and impaired neuronal plasticity, the functionally most relevant consequences of mitochondrial dysfunction. All partially inhibit opening events of the mitochondrial permeability transition pore (mPTP) which previously has mainly been discussed as a mechanism relevant for the induction of apoptosis. However, as more recent work suggests the mPTP as a master regulator of many mitochondrial functions, our data suggest the mPTP as a possible relevant drug target within the love triangle between mPTP regulation, mitochondrial dynamics, and mitochondrial function including regulation of neuronal plasticity. Drugs interfering with mPTP function will improve not only mitochondrial impairment in aging and AD but also will have beneficial effects on impaired neuronal plasticity, the pathomechanism which correlates best with functional deficits (cognition, behavior) in aging and AD.
Collapse
Affiliation(s)
- Carola Stockburger
- Department of Pharmacology, University of Frankfurt/M, Biocenter, Frankfurt/Main, Germany
| | - Schamim Eckert
- Department of Pharmacology, University of Frankfurt/M, Biocenter, Frankfurt/Main, Germany
| | - Gunter P Eckert
- Department of Nutritional Sciences, University of Giessen, Giessen, Germany
| | - Kristina Friedland
- Department of Molecular and Clinical Pharmacy, University of Erlangen, Erlangen, Germany
| | - Walter E Müller
- Department of Pharmacology, University of Frankfurt/M, Biocenter, Frankfurt/Main, Germany
| |
Collapse
|
48
|
Wang L, Pan X, Fei G, Wang C, Wan W, Sang S, Wang H, Wang Z, Zhong C. Decreased Function of Delayed Recall in Non-demented Elderly Subjects With Apolipoprotein E ε4 Allele. Front Aging Neurosci 2019; 11:71. [PMID: 30983990 PMCID: PMC6450220 DOI: 10.3389/fnagi.2019.00071] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 03/12/2019] [Indexed: 01/01/2023] Open
Abstract
Apolipoprotein E (APOE) is the major genetic risk factor for late-onset Alzheimer's disease (AD). Inconsistent results about the role of APOE ε4 alleles on cognitive decline of community non-dementia elderly have been reported. This study aimed to examine the relationship between APOE ε4 allele and cognitive abilities in the subjects aged 60 years or above from a community in Shanghai, China. A total of 1445 participants voluntarily accepted the analysis of APOE genotype and global cognitive assay using the Mini Mental Status Evaluation (MMSE). There were no significant differences in total MMSE scores between APOE ε4 carriers and non-carriers. In addition, the performances of orientation, registration, attention, calculation, and language had no significant differences between subjects with and without APOE ε4 allele. However, stratified analysis showed that the performance of delayed recall in subjects with APOE ε4 allele was inferior to that in non-ε4 carriers (p = 0.041). Further, the multiple linear regression analysis showed the significant correlations between the presence of APOE ε4 allele and the scores of the delayed memory subdomain if age, gender, and education were adjusted but no significant correlations if the related factors were not adjusted. The results indicate that significant impact of APOE ε4 allele only on the delay memory but not on global or other sub-domains of cognitive abilities.
Collapse
Affiliation(s)
- Lijun Wang
- Department of Neurology, Zhongshan Hospital, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Xiaoli Pan
- Department of Neurology, Zhongshan Hospital, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Guoqiang Fei
- Department of Neurology, Zhongshan Hospital, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Changpeng Wang
- Department of Neurology, Zhongshan Hospital, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Wenbin Wan
- Department of Neurology, Zhongshan Hospital, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Shaoming Sang
- Department of Neurology, Zhongshan Hospital, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| | - Hui Wang
- Regional Health Service Center of Xujiahui, Shanghai, China
| | - Zhiliang Wang
- Regional Health Service Center of Xujiahui, Shanghai, China
| | - Chunjiu Zhong
- Department of Neurology, Zhongshan Hospital, State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, Fudan University, Shanghai, China
| |
Collapse
|
49
|
The Contribution of Genetic Factors to Cognitive Impairment and Dementia: Apolipoprotein E Gene, Gene Interactions, and Polygenic Risk. Int J Mol Sci 2019; 20:ijms20051177. [PMID: 30866553 PMCID: PMC6429136 DOI: 10.3390/ijms20051177] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 02/26/2019] [Indexed: 12/19/2022] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease. Although it has been studied for years, the pathogenesis of AD is still controversial. Genetic factors may play an important role in pathogenesis, with the apolipoprotein E (APOE) gene among the greatest risk factors for AD. In this review, we focus on the influence of genetic factors, including the APOE gene, the interaction between APOE and other genes, and the polygenic risk factors for cognitive function and dementia. The presence of the APOE ε4 allele is associated with increased AD risk and reduced age of AD onset. Accelerated cognitive decline and abnormal internal environment, structure, and function of the brain were also found in ε4 carriers. The effect of the APOE promoter on cognition and the brain was confirmed by some studies, but further investigation is still needed. We also describe the effects of the associations between APOE and other genetic risk factors on cognition and the brain that exhibit a complex gene⁻gene interaction, and we consider the importance of using a polygenic risk score to investigate the association between genetic variance and phenotype.
Collapse
|
50
|
Müller WE, Eckert A, Eckert GP, Fink H, Friedland K, Gauthier S, Hoerr R, Ihl R, Kasper S, Möller HJ. Therapeutic efficacy of the Ginkgo special extract EGb761 ® within the framework of the mitochondrial cascade hypothesis of Alzheimer's disease. World J Biol Psychiatry 2019; 20:173-189. [PMID: 28460580 DOI: 10.1080/15622975.2017.1308552] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
OBJECTIVES The mitochondrial cascade hypothesis of dementia assumes mitochondrial dysfunction as an important common pathomechanism for the whole spectrum of age-associated memory disorders from cognitive symptoms in the elderly over mild cognitive impairment to Alzheimer's dementia. Thus, a drug such as the Ginkgo special extract EGb 761® which improves mitochondrial function should be able to ameliorate cognitive deficits over the whole aging spectrum. METHODS We review the most relevant publications about effects of EGb 761® on cognition and synaptic deficits in preclinical studies as well as on cognitive deficits in man from aging to dementia. RESULTS EGb 761® improves mitochondrial dysfunction and cognitive impairment over the whole spectrum of age-associated cognitive disorders in relevant animal models and in vitro experiments, and also shows clinical efficacy in improving cognition over the whole range from aging to Alzheimer's or even vascular dementia. CONCLUSIONS EGb 761® shows clinical efficacy in the treatment of cognitive deficits over the whole spectrum of age-associated memory disorders. Thus, EGb 761® can serve as an important pharmacological argument for the mitochondrial cascade hypothesis of dementia.
Collapse
Affiliation(s)
- Walter E Müller
- a Department of Pharmacology , Biocenter, Goethe-University , Frankfurt/M , Germany
| | - Anne Eckert
- b Neurobiological laboratory, Department of Psychiatry , Basel , Switzerland
| | - Gunter P Eckert
- c Department of Nutritional Sciences , Justus-Liebig University , Giessen , Germany
| | - Heidrun Fink
- d Department of Pharmacology and Toxicology , Free University , Berlin , Germany
| | - Kristina Friedland
- e Department of Molecular and Clinical Pharmacy , University Erlangen , Erlangen , Germany
| | - Serge Gauthier
- f McGill Center for Studies in Aging , Montreal , Canada
| | - Robert Hoerr
- g Dr.Willmar Schwabe GmbH & Co. KG , Karlsruhe , Germany
| | - Ralf Ihl
- h Alexianer Hospital, Clinic of Geriatric Psychiatry , Krefeld , Germany
| | - Siegfried Kasper
- i Department of Psychiatry , Medical University , Vienna , Austria
| | - Hans-Jürgen Möller
- j Department of Psychiatry , Ludwig-Maximilian University , Munich , Germany
| |
Collapse
|