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Kim J, Suh SI, Park YJ, Kang M, Chung SJ, Lee ES, Jung HN, Eo JS, Koh SB, Oh K, Kang SH. Sarcopenia is a predictor for Alzheimer's continuum and related clinical outcomes. Sci Rep 2024; 14:21074. [PMID: 39256402 DOI: 10.1038/s41598-024-62918-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/22/2024] [Indexed: 09/12/2024] Open
Abstract
Low body mass index is closely related to a high risk of Alzheimer's disease (AD) and related biomarkers including amyloid-β (Aβ) deposition. However, the association between sarcopenia and Aβ-confirmed AD remains controversial. Therefore, we investigated the relationship between sarcopenia and the AD continuum. We explored sarcopenia's association with clinical implications of participants on the AD continuum. We prospectively enrolled 142 participants on the AD continuum (19 with preclinical AD, 96 with mild cognitive impairment due to AD, and 28 with AD dementia) and 58 Aβ-negative cognitively unimpaired participants. Sarcopenia, assessed using dual-energy X-ray absorptiometry and hand grip measurements, was considered a predictor. AD continuum, defined by Aβ deposition on positron emission tomography served as an outcome. Clinical severity in participants on the AD continuum assessed using hippocampal volume, Mini-Mental State Examination (MMSE), Seoul Verbal Learning Test (SVLT), and Clinical Dementia Rating Scale Sum of Boxes Scores (CDR-SOB) were also considered an outcome. Sarcopenia (odds ratio = 4.99, p = 0.004) was associated independently with the AD continuum after controlling for potential confounders. Moreover, sarcopenia was associated with poor downstream imaging markers (decreased hippocampal volume, β = - 0.206, p = 0.020) and clinical outcomes (low MMSE, β = - 1.364, p = 0.025; low SVLT, β = - 1.077, p = 0.025; and high CDR-SOB scores, β = 0.783, p = 0.022) in participants on the AD continuum. Sarcopenia was associated with the AD continuum and poor clinical outcome in individuals with AD continuum. Therefore, our results provide evidence for future studies to confirm whether proper management of sarcopenia can effective strategies are required for sarcopenia management to prevent the AD continuum and its clinical implications.
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Affiliation(s)
- Jeonghun Kim
- Korea Testing Laboratory, Bio and Medical Health Division, Seoul, Korea
| | - Sang-Il Suh
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Yu Jeong Park
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea
| | - Minwoong Kang
- Department of Biomedical Research Center, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Su Jin Chung
- Department of Neurology, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea
| | - Eun Seong Lee
- Department of Nuclear Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Hye Na Jung
- Department of Radiology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Jae Seon Eo
- Department of Nuclear Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea.
| | - Sung Hoon Kang
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, 148 Gurodong-ro, Guro-gu, Seoul, 08308, Korea.
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Park CJ, Park YH, Kwak K, Choi S, Kim HJ, Na DL, Seo SW, Chun MY. Deep learning-based quantification of brain atrophy using 2D T1-weighted MRI for Alzheimer's disease classification. Front Aging Neurosci 2024; 16:1423515. [PMID: 39206118 PMCID: PMC11349618 DOI: 10.3389/fnagi.2024.1423515] [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: 04/26/2024] [Accepted: 07/30/2024] [Indexed: 09/04/2024] Open
Abstract
Background Determining brain atrophy is crucial for the diagnosis of neurodegenerative diseases. Despite detailed brain atrophy assessments using three-dimensional (3D) T1-weighted magnetic resonance imaging, their practical utility is limited by cost and time. This study introduces deep learning algorithms for quantifying brain atrophy using a more accessible two-dimensional (2D) T1, aiming to achieve cost-effective differentiation of dementia of the Alzheimer's type (DAT) from cognitively unimpaired (CU), while maintaining or exceeding the performance obtained with T1-3D individuals and to accurately predict AD-specific atrophy similarity and atrophic changes [W-scores and Brain Age Index (BAI)]. Methods Involving 924 participants (478 CU and 446 DAT), our deep learning models were trained on cerebrospinal fluid (CSF) volumes from 2D T1 images and compared with 3D T1 images. The performance of the models in differentiating DAT from CU was assessed using receiver operating characteristic analysis. Pearson's correlation analyses were used to evaluate the relations between 3D T1 and 2D T1 measurements of cortical thickness and CSF volumes, AD-specific atrophy similarity, W-scores, and BAIs. Results Our deep learning models demonstrated strong correlations between 2D and 3D T1-derived CSF volumes, with correlation coefficients r ranging from 0.805 to 0.971. The algorithms based on 2D T1 accurately distinguished DAT from CU with high accuracy (area under the curve values of 0.873), which were comparable to those of algorithms based on 3D T1. Algorithms based on 2D T1 image-derived CSF volumes showed high correlations in AD-specific atrophy similarity (r = 0.915), W-scores for brain atrophy (0.732 ≤ r ≤ 0.976), and BAIs (r = 0.821) compared with those based on 3D T1 images. Conclusion Deep learning-based analysis of 2D T1 images is a feasible and accurate alternative for assessing brain atrophy, offering diagnostic precision comparable to that of 3D T1 imaging. This approach offers the advantage of the availability of T1-2D imaging, as well as reduced time and cost, while maintaining diagnostic precision comparable to T1-3D.
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Affiliation(s)
- Chae Jung Park
- Research Institute, National Cancer Center, Goyang, Republic of Korea
| | - Yu Hyun Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Kichang Kwak
- BeauBrain Healthcare, Inc., Seoul, Republic of Korea
| | - Soohwan Choi
- BeauBrain Healthcare, Inc., Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- BeauBrain Healthcare, Inc., Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- BeauBrain Healthcare, Inc., Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Min Young Chun
- Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Republic of Korea
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Li M, Yu Q, Anayyat U, Yang H, Wei Y, Wang X. Rotating magnetic field improved cognitive and memory impairments in a sporadic ad model of mice by regulating microglial polarization. GeroScience 2024:10.1007/s11357-024-01223-y. [PMID: 38904930 DOI: 10.1007/s11357-024-01223-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 05/24/2024] [Indexed: 06/22/2024] Open
Abstract
Neuroinflammation, triggered by aberrantly activated microglia, is widely recognized as a key contributor to the initiation and progression of Alzheimer's disease (AD). Microglial activation in the central nervous system (CNS) can be classified into two distinct phenotypes: the pro-inflammatory M1 phenotype and the anti-inflammatory M2 phenotype. In this study, we investigated the effects of a non-invasive rotating magnetic field (RMF) (0.2T, 4Hz) on cognitive and memory impairments in a sporadic AD model of female Kunming mice induced by AlCl3 and D-gal. Our findings revealed significant improvements in cognitive and memory impairments following RMF treatment. Furthermore, RMF treatment led to reduced amyloid-beta (Aβ) deposition, mitigated damage to hippocampal morphology, prevented synaptic and neuronal loss, and alleviated cell apoptosis in the hippocampus and cortex of AD mice. Notably, RMF treatment ameliorated neuroinflammation, facilitated the transition of microglial polarization from M1 to M2, and inhibited the NF-кB/MAPK pathway. Additionally, RMF treatment resulted in reduced aluminum deposition in the brains of AD mice. In cellular experiments, RMF promoted the M1-M2 polarization transition and enhanced amyloid phagocytosis in cultured BV2 cells while inhibiting the TLR4/NF-кB/MAPK pathway. Collectively, these results demonstrate that RMF improves memory and cognitive impairments in a sporadic AD model, potentially by promoting the M1 to M2 transition of microglial polarization through inhibition of the NF-кB/MAPK signaling pathway. These findings suggest the promising therapeutic applications of RMF in the clinical treatment of AD.
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Affiliation(s)
- Mengqing Li
- Shenzhen University School of Basic Medical Sciences, Shenzhen, 518055, Guangdong, China
| | - Qinyao Yu
- Shenzhen University College of Medicine, Shenzhen, 518055, Guangdong, China
| | - Umer Anayyat
- Shenzhen University School of Basic Medical Sciences, Shenzhen, 518055, Guangdong, China
| | - Hua Yang
- Shenzhen University School of Basic Medical Sciences, Shenzhen, 518055, Guangdong, China
| | - Yunpeng Wei
- Shenzhen University School of Basic Medical Sciences, Shenzhen, 518055, Guangdong, China.
| | - Xiaomei Wang
- Shenzhen University School of Basic Medical Sciences, Shenzhen, 518055, Guangdong, China.
- Shenzhen University International Cancer Center, Shenzhen, 518055, Guangdong, China.
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Lee S, Kim SE, Jang H, Kim JP, Sohn G, Park YH, Ham H, Gu Y, Park CJ, Kim HJ, Na DL, Kim K, Seo SW. Distinct effects of blood pressure parameters on Alzheimer's and vascular markers in 1,952 Asian individuals without dementia. Alzheimers Res Ther 2024; 16:125. [PMID: 38863019 PMCID: PMC11167921 DOI: 10.1186/s13195-024-01483-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 05/15/2024] [Indexed: 06/13/2024]
Abstract
BACKGROUND Risk factors for cardiovascular disease, including elevated blood pressure, are known to increase risk of Alzheimer's disease. There has been increasing awareness of the relationship between long-term blood pressure (BP) patterns and their effects on the brain. We aimed to investigate the association of repeated BP measurements with Alzheimer's and vascular disease markers. METHODS We recruited 1,952 participants without dementia between August 2015 and February 2022. During serial clinic visits, we assessed both systolic BP (SBP) and diastolic BP (DBP), and visit-to-visit BP variability (BPV) was quantified from repeated measurements. In order to investigate the relationship of mean SBP (or DBP) with Alzheimer's and vascular markers and cognition, we performed multiple linear and logistic regression analyses after controlling for potential confounders (Model 1). Next, we investigated the relationship of with variation of SBP (or DBP) with the aforementioned variables by adding it into Model 1 (Model 2). In addition, mediation analyses were conducted to determine mediation effects of Alzheimer's and vascular makers on the relationship between BP parameters and cognitive impairment. RESULTS High Aβ uptake was associated with greater mean SBP (β = 1.049, 95% confidence interval 1.016-1.083). High vascular burden was positively associated with mean SBP (odds ratio = 1.293, 95% CI 1.015-1.647) and mean DBP (1.390, 1.098-1.757). High tau uptake was related to greater systolic BPV (0.094, 0.001-0.187) and diastolic BPV (0.096, 0.007-0.184). High Aβ uptake partially mediated the relationship between mean SBP and the Mini-Mental State Examination (MMSE) scores. Hippocampal atrophy mediated the relationship between diastolic BPV and MMSE scores. CONCLUSIONS Each BP parameter affects Alzheimer's and vascular disease markers differently, which in turn leads to cognitive impairment. Therefore, it is necessary to appropriately control specific BP parameters to prevent the development of dementia. Furthermore, a better understanding of pathways from specific BP parameters to cognitive impairments might enable us to select the managements targeting the specific BP parameters to prevent dementia effectively.
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Affiliation(s)
- Sungjoo Lee
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
| | - Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, 48108, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Gyeongmo Sohn
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, 48108, Republic of Korea
| | - Yu Hyun Park
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Hongki Ham
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Yuna Gu
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Chae Jung Park
- Research Institute, National Cancer Center, Goyang, 10408, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea
| | - Kyunga Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Department of Data Convergence & Future Medicine, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 06351, Republic of Korea.
- Neuroscience Center, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea.
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul, 06351, Republic of Korea.
- Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, 06351, Republic of Korea.
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Kang SH, Yoo H, Cheon BK, Kim JP, Jang H, Kim HJ, Kang M, Oh K, Koh SB, Na DL, Chang Y, Seo SW. Sex-specific relationship between non-alcoholic fatty liver disease and amyloid-β in cognitively unimpaired individuals. Front Aging Neurosci 2023; 15:1277392. [PMID: 37901792 PMCID: PMC10603302 DOI: 10.3389/fnagi.2023.1277392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Background Non-alcoholic fatty liver disease (NAFLD) is known to be associated with a high risk of clinically diagnosed Alzheimer's disease (AD). Additionally, the prevalence of NAFLD and AD is higher in elderly females than in males. However, a sex-specific association between NAFLD and amyloid-beta (Aβ) deposition remains unclear. Therefore, we investigated the sex-specific relationship between NAFLD and Aβ deposition in a large-sized cohort of cognitively unimpaired (CU) individuals. Methods We enrolled 673 (410 [60.9%] females and 263 [39.1%] males) CU individuals aged ≥45 years who underwent Aβ positron emission tomography (PET). The presence of NAFLD, assessed using the hepatic steatosis index, and the severity of NAFLD, assessed using the Fibrosis-4 index, were considered predictors. Aβ deposition on PET was considered as an outcome. Results Females had a higher frequency of NAFLD than males (48 and 23.2%, p < 0.001). Among females, the presence of NAFLD (β = 0.216, p < 0.001) was predictive of increased Aβ deposition, whereas among males, the presence of NAFLD (β = 0.191, p = 0.064) was not associated with Aβ deposition. Among females, the presence of NAFLD with low (β = 0.254, p = 0.039), intermediate (β = 0.201, p = 0.006), and high fibrosis (β = 0.257, p = 0.027) was predictive of increased Aβ deposition. Aβ deposition also increased as the severity of NAFLD increased in females (p for trend = 0.001). Conclusion We highlight the marked influence of NAFLD and its severity on the risk of Aβ deposition in relation to sex. Furthermore, our findings suggest that sex-specific strategies regarding the management of NAFLD are necessary for the prevention of Aβ deposition.
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Heejin Yoo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Bo Kyoung Cheon
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Jun Pyo Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Mira Kang
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyungmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yoosoo Chang
- Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea
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Kennedy KG, Islam AH, Karthikeyan S, Metcalfe AWS, McCrindle BW, MacIntosh BJ, Black S, Goldstein BI. Differential association of endothelial function with brain structure in youth with versus without bipolar disorder. J Psychosom Res 2023; 167:111180. [PMID: 36764023 DOI: 10.1016/j.jpsychores.2023.111180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/22/2023] [Accepted: 01/29/2023] [Indexed: 02/04/2023]
Abstract
BACKGROUND Mood symptoms and disorders are associated with impaired endothelial function, a marker of early atherosclerosis. Given the increased vascular burden and neurostructural differences among individuals with mood disorders, we investigated the endothelial function and brain structure interface in relation to youth bipolar disorder (BD). METHODS This cross-sectional case-controlled study included 115 youth, ages 13-20 years (n = 66 BD; n = 49 controls [CG]). Cortical thickness and volume for regions of interest (ROI; insular cortex, ventrolateral prefrontal cortex [vlPFC], temporal lobe) were acquired from FreeSurfer processed T1-weighted MRI images. Endothelial function was assessed using pulse amplitude tonometry, yielding a reactive hyperemia index (RHI). ROI and vertex-wise analyses controlling for age, sex, obesity, and intracranial volume investigated for RHI-neurostructural associations, and RHI-by-diagnosis interactions. RESULTS In ROI analyses, higher RHI (i.e., better endothelial function) was associated with lower thickness in the insular cortex (β = -0.19, pFDR = 0.03), vlPFC (β = -0.30, pFDR = 0.003), and temporal lobe (β = -0.22, pFDR = 0.01); and lower temporal lobe volume (β = -0.16, pFDR = 0.01) in the overall sample. In vertex-wise analyses, higher RHI was associated with lower cortical thickness and volume in the insular cortex, prefrontal cortex (e.g., vlPFC), and temporal lobe. Additionally, higher RHI was associated with lower vlPFC and temporal lobe volume to a greater extent in youth with BD vs. CG. CONCLUSIONS Better endothelial function was associated with lower regional brain thickness and volume, contrasting the hypothesized associations. Additionally, we found evidence that this pattern was exaggerated in youth with BD. Future studies examining the direction of the observed associations and underlying mechanisms are warranted.
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Affiliation(s)
- Kody G Kennedy
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada.
| | - Alvi H Islam
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada; Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Sudhir Karthikeyan
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada.
| | - Arron W S Metcalfe
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada
| | - Brian W McCrindle
- Faculty of Medicine, University of Toronto, Toronto, Canada; Hospital for Sick Children, Toronto, Canada; Labatt Family Heart Centre, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada.
| | - Bradley J MacIntosh
- Hurvitz Brain Sciences, Sunnybrook Research Institute, Toronto, Canada; Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada; Computational Radiology & Artificial Intelligence (CRAI) Unit, Dept of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
| | - Sandra Black
- Faculty of Medicine, University of Toronto, Toronto, Canada; Hurvitz Brain Sciences, Sunnybrook Research Institute, Toronto, Canada; Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Canada.
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada; Faculty of Medicine, University of Toronto, Toronto, Canada.
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Kang SH, Liu M, Park G, Kim SY, Lee H, Matloff W, Zhao L, Yoo H, Kim JP, Jang H, Kim HJ, Jahanshad N, Oh K, Koh SB, Na DL, Gallacher J, Gottesman RF, Seo SW, Kim H. Different effects of cardiometabolic syndrome on brain age in relation to gender and ethnicity. Alzheimers Res Ther 2023; 15:68. [PMID: 36998058 PMCID: PMC10061789 DOI: 10.1186/s13195-023-01215-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 03/20/2023] [Indexed: 04/01/2023]
Abstract
BACKGROUND A growing body of evidence shows differences in the prevalence of cardiometabolic syndrome (CMS) and dementia based on gender and ethnicity. However, there is a paucity of information about ethnic- and gender-specific CMS effects on brain age. We investigated the different effects of CMS on brain age by gender in Korean and British cognitively unimpaired (CU) populations. We also determined whether the gender-specific difference in the effects of CMS on brain age changes depending on ethnicity. METHODS These analyses used de-identified, cross-sectional data on CU populations from Korea and United Kingdom (UK) that underwent brain MRI. After propensity score matching to balance the age and gender between the Korean and UK populations, 5759 Korean individuals (3042 males and 2717 females) and 9903 individuals from the UK (4736 males and 5167 females) were included in this study. Brain age index (BAI), calculated by the difference between the predicted brain age by the algorithm and the chronological age, was considered as main outcome and presence of CMS, including type 2 diabetes mellitus (T2DM), hypertension, obesity, and underweight was considered as a predictor. Gender (males and females) and ethnicity (Korean and UK) were considered as effect modifiers. RESULTS The presence of T2DM and hypertension was associated with a higher BAI regardless of gender and ethnicity (p < 0.001), except for hypertension in Korean males (p = 0.309). Among Koreans, there were interaction effects of gender and the presence of T2DM (p for T2DM*gender = 0.035) and hypertension (p for hypertension*gender = 0.046) on BAI in Koreans, suggesting that T2DM and hypertension are each associated with a higher BAI in females than in males. In contrast, among individuals from the UK, there were no differences in the effects of T2DM (p for T2DM*gender = 0.098) and hypertension (p for hypertension*gender = 0.203) on BAI between males and females. CONCLUSIONS Our results highlight gender and ethnic differences as important factors in mediating the effects of CMS on brain age. Furthermore, these results suggest that ethnic- and gender-specific prevention strategies may be needed to protect against accelerated brain aging.
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Affiliation(s)
- Sung Hoon Kang
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Mengting Liu
- School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, China
- Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA, 90033, USA
| | - Gilsoon Park
- Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA, 90033, USA
| | - Sharon Y Kim
- Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA, 90033, USA
| | - Hyejoo Lee
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - William Matloff
- Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA, 90033, USA
| | - Lu Zhao
- Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA, 90033, USA
| | - Heejin Yoo
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jun Pyo Kim
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hyemin Jang
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hee Jin Kim
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Neda Jahanshad
- Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA, 90033, USA
| | - Kyumgmi Oh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Duk L Na
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - John Gallacher
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Rebecca F Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Sang Won Seo
- Departments of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea.
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea.
- Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea.
| | - Hosung Kim
- Keck School of Medicine of University of Southern California, USC Steven Neuroimaging and Informatics Institute, Los Angeles, CA, 90033, USA
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8
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Sex-specific relationships between obesity, physical activity, and gray and white matter volume in cognitively unimpaired older adults. GeroScience 2023:10.1007/s11357-023-00734-4. [PMID: 36781598 PMCID: PMC10400512 DOI: 10.1007/s11357-023-00734-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 01/17/2023] [Indexed: 02/15/2023] Open
Abstract
Independently, obesity and physical activity (PA) influence cerebral structure in aging, yet their interaction has not been investigated. We examined sex differences in the relationships among PA, obesity, and cerebral structure in aging with 340 participants who completed magnetic resonance imaging (MRI) acquisition to quantify grey matter volume (GMV) and white matter volume (WMV). Height and weight were measured to calculate body mass index (BMI). A PA questionnaire was used to estimate weekly Metabolic Equivalents. The relationships between BMI, PA, and their interaction on GMV Regions of Interest (ROIs) and WMV ROIs were examined. Increased BMI was associated with higher GMV in females, an inverse U relationship was found between PA and GMV in females, and the interaction indicated that regardless of BMI greater PA was associated with enhanced GMV. Males demonstrated an inverse U shape between BMI and GMV, and in males with high PA and had normal weight demonstrated greater GMV than normal weight low PA revealed by the interaction. WMV ROIs had a linear relationship with moderate PA in females, whereas in males, increased BMI was associated with lower WMV as well as a positive relationship with moderate PA and WMV. Males and females have unique relationships among GMV, PA and BMI, suggesting sex-aggregated analyses may lead to biased or non-significant results. These results suggest higher BMI, and PA are associated with increased GMV in females, uniquely different from males, highlighting the importance of sex-disaggregated models. Future work should include other imaging parameters, such as perfusion, to identify if these differences co-occur in the same regions as GMV.
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9
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Han G, Kim JS, Park YH, Kang SH, Kim HR, Hwangbo S, Chung TY, Shin HY, Na DL, Seo SW, Lim DH, Kim HJ. Decreased visual acuity is related to thinner cortex in cognitively normal adults: cross-sectional, single-center cohort study. Alzheimers Res Ther 2022; 14:99. [PMID: 35879770 PMCID: PMC9310451 DOI: 10.1186/s13195-022-01045-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 07/13/2022] [Indexed: 11/10/2022]
Abstract
Abstract
Background
Decreased visual acuity (VA) is reported to be a risk factor for dementia. However, the association between VA and cortical thickness has not been established. We investigated the association between VA and cortical thickness in cognitively normal adults.
Method
We conducted a cross-sectional, single-center cohort study with cognitively normal adults (aged ≥ 45) who received medical screening examinations at the Health Promotion Center at Samsung Medical Center. Subjects were categorized as bad (VA ≤ 20/40), fair (20/40 < VA ≤ 20/25), and good (VA > 20/25) VA group by using corrected VA in the Snellen system. Using 3D volumetric brain MRI, cortical thickness was calculated using the Euclidean distance between the linked vertices of the inner and outer surfaces. We analyzed the association between VA and cortical thickness after controlling for age, sex, hypertension, diabetes, dyslipidemia, intracranial volume, and education level.
Results
A total of 2756 subjects were analyzed in this study. Compared to the good VA group, the bad VA group showed overall thinner cortex (p = 0.015), especially in the parietal (p = 0.018) and occipital (p = 0.011) lobes. Topographical color maps of vertex-wise analysis also showed that the bad VA group showed a thinner cortex in the parieto-temporo-occipital area. These results were more robust in younger adults (aged 45 to 65) as decreased VA was associated with thinner cortex in more widespread regions in the parieto-temporo-occipital area.
Conclusion
Our results suggest that a thinner cortex in the visual processing area of the brain is related to decreased visual stimuli.
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10
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Kang SH, Kim JH, Chang Y, Cheon BK, Choe YS, Jang H, Kim HJ, Koh SB, Na DL, Kim K, Seo SW. Independent effect of body mass index variation on amyloid-β positivity. Front Aging Neurosci 2022; 14:924550. [PMID: 35936766 PMCID: PMC9354132 DOI: 10.3389/fnagi.2022.924550] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/04/2022] [Indexed: 11/16/2022] Open
Abstract
Objectives The relationship of body mass index (BMI) changes and variability with amyloid-β (Aβ) deposition remained unclear, although there were growing evidence that BMI is associated with the risk of developing cognitive impairment or AD dementia. To determine whether BMI changes and BMI variability affected Aβ positivity, we investigated the association of BMI changes and BMI variability with Aβ positivity, as assessed by PET in a non-demented population. Methods We retrospectively recruited 1,035 non-demented participants ≥50 years of age who underwent Aβ PET and had at least three BMI measurements in the memory clinic at Samsung Medical Center. To investigate the association between BMI change and variability with Aβ deposition, we performed multivariable logistic regression. Further distinctive underlying features of BMI subgroups were examined by employing a cluster analysis model. Results Decreased (odds ratio [OR] = 1.68, 95% confidence interval [CI] 1.16–2.42) or increased BMI (OR = 1.60, 95% CI 1.11–2.32) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI variability. A greater BMI variability (OR = 1.73, 95% CI 1.07–2.80) was associated with a greater risk of Aβ positivity after controlling for age, sex, APOE e4 genotype, years of education, hypertension, diabetes, baseline BMI, and BMI change. We also identified BMI subgroups showing a greater risk of Aβ positivity. Conclusion Our findings suggest that participants with BMI change, especially those with greater BMI variability, are more vulnerable to Aβ deposition regardless of baseline BMI. Furthermore, our results may contribute to the design of strategies to prevent Aβ deposition with respect to weight control.
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Affiliation(s)
- Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Jong Hyuk Kim
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Yoosoo Chang
- Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, South Korea
| | - Bo Kyoung Cheon
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Yeong Sim Choe
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences & Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Seong-Beom Koh
- Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
| | - Kyunga Kim
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea
- Department of Data Convergence and Future Medicine, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- *Correspondence: Kyunga Kim,
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, South Korea
- Neuroscience Center, Samsung Medical Center, Seoul, South Korea
- Department of Health Sciences & Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Samsung Alzheimer Research Center, Center for Clinical Epidemiology Medical Center, Seoul, South Korea
- Department of Intelligent Precision Healthcare Convergence, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Sang Won Seo,
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11
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Park J, Kim TJ, Song JH, Jang H, Kim JS, Kang SH, Kim HR, Hwangbo S, Shin HY, Na DL, Seo SW, Kim HJ, Kim JJ. Helicobacter Pylori Infection Is Associated with Neurodegeneration in Cognitively Normal Men. J Alzheimers Dis 2021; 82:1591-1599. [PMID: 34180413 DOI: 10.3233/jad-210119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND An association between Helicobacter pylori (H. pylori) infection and dementia was reported in previous studies; however, the evidence is inconsistent. OBJECTIVE In the present study, the association between H. pylori infection and brain cortical thickness as a biomarker of neurodegeneration was investigated. METHODS A cross-sectional study of 822 men who underwent a medical health check-up, including an esophagogastroduodenoscopy and 3.0 T magnetic resonance imaging, was performed. H. pylori infection status was assessed based on histology. Multiple linear regression analyses were conducted to evaluate the relationship between H. pylori infection and brain cortical thickness. RESULTS Men with H. pylori infection exhibited overall brain cortical thinning (p = 0.022), especially in the parietal (p = 0.008) and occipital lobes (p = 0.050) compared with non-infected men after adjusting for age, educational level, alcohol intake, smoking status, and intracranial volume. 3-dimentional topographical analysis showed that H. pylori infected men had cortical thinning in the bilateral lateral temporal, lateral frontal, and right occipital areas compared with non-infected men with the same adjustments (false discovery rate corrected, Q < 0.050). The association remained significant after further adjusting for inflammatory marker (C-reactive protein) and metabolic factors (obesity, dyslipidemia, fasting glucose, and blood pressure). CONCLUSION Our results indicate H. pylori infection is associated with neurodegenerative changes in cognitive normal men. H. pylori infection may play a pathophysiologic role in the neurodegeneration and further studies are needed to validate this association.
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Affiliation(s)
- Jaehong Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Tae Jun Kim
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Joo Hye Song
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Ji Sun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Sung Hoon Kang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Korea
| | - Hang-Rai Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Neurology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Korea
| | - Song Hwangbo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea
| | - Hee Young Shin
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Health Science and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Health Science and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Korea.,Department of Health Science and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Jae J Kim
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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12
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Min KD, Kim JS, Park YH, Shin HY, Kim C, Seo SW, Kim SY. New assessment for residential greenness and the association with cortical thickness in cognitively healthy adults. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 778:146129. [PMID: 33714817 DOI: 10.1016/j.scitotenv.2021.146129] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 01/26/2021] [Accepted: 02/22/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Recent evidence suggests that neurological health could be improved with the intervention of local green space. A few studies adopted cortical thickness, as an effective biomarker for neurodegenerative disorder, to investigate the association with residential greenness. However, they relied on limited data sources, definitions or applications to assess residential greenness. Our cross-sectional study assessed individual residential greenness using an alternative measure, which provides a more realistic definition of local impact and application based on the type of area, and investigated the association with cortical thickness. METHODS The study population included 2542 subjects who participated in the medical check-up program at the Health Promotion Center of the Samsung Medical Center in Seoul, Korea, from 2008 to 2014. The cortical thickness was calculated by each of the four and global lobes from brain MRI. For greenness, we used the enhanced vegetation index (EVI) that detects canopy structural variation by adjusting background noise based on satellite imagery data. To assess individual exposure to residential greenness, we computed the maximum annual EVI before the date of a medical check-up and averaged it within 750 m from subjects' homes to represent an average walking distance. Finally, we assessed the association with cortical thickness by urban and non-urban populations using multiple linear regression adjusting for individual characteristics. RESULTS The average global cortical thickness and EVI were 3.05 mm (standard deviation = 0.1 mm) and 0.31 (0.1), respectively. An interquartile range increase in EVI was associated with 11 μm (95% confidence interval = 3-20) and 9 μm (1-16) increases in cortical thickness of the parietal and occipital regions among the urban population. We did not find associations in non-urban subjects. CONCLUSIONS Our findings confirm the association between residential greenness and neurological health using alternative exposure assessments, indicating that high exposure to residential greenness can prevent neurological disorders.
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Affiliation(s)
- Kyung-Duk Min
- Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea
| | - Ji Sun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yu Hyun Park
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea; Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hee Young Shin
- Health Promotion Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Changsoo Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea; Neuroscience Center, Samsung Medical Center, Seoul, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
| | - Sun-Young Kim
- Department of Cancer Control and Population Health, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
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13
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Lu R, Aziz NA, Diers K, Stöcker T, Reuter M, Breteler MMB. Insulin resistance accounts for metabolic syndrome-related alterations in brain structure. Hum Brain Mapp 2021; 42:2434-2444. [PMID: 33769661 PMCID: PMC8090787 DOI: 10.1002/hbm.25377] [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: 08/19/2020] [Revised: 01/22/2021] [Accepted: 01/28/2021] [Indexed: 12/26/2022] Open
Abstract
Metabolic syndrome (MetS) is a major public health burden worldwide and associated with brain abnormalities. Although insulin resistance is considered a pivotal feature of MetS, its role in the pathogenesis of MetS‐related brain alterations in the general population is unclear. Therefore, in 973 participants (mean age 52.5 years) of the population‐based Rhineland Study, we assessed brain morphology in relation to MetS and insulin resistance, and evaluated to what extent the pattern of structural brain changes seen in MetS overlap with those associated with insulin resistance. Cortical reconstruction and volumetric segmentation were obtained from high‐resolution brain images at 3 Tesla using FreeSurfer. The relations between metabolic measures and brain structure were assessed through (generalized) linear models. Both MetS and insulin resistance were associated with smaller cortical gray matter volume and thickness, but not with white matter or subcortical gray matter volume. Age‐ and sex‐adjusted vertex‐based brain morphometry demonstrated that MetS and insulin resistance were related to cortical thinning in a similar spatial pattern. Importantly, no independent effect of MetS on cortical gray matter was observed beyond the effect of insulin resistance. Our findings suggest that addressing insulin resistance is critical in the prevention of MetS‐related brain changes in later life.
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Affiliation(s)
- Ran Lu
- Population Health Sciences, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Kersten Diers
- Image Analysis, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany
| | - Tony Stöcker
- MR Physics, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Martin Reuter
- Image Analysis, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative diseases (DZNE), Bonn, Germany.,Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
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14
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Wani A, Al Rihani SB, Sharma A, Weadick B, Govindarajan R, Khan SU, Sharma PR, Dogra A, Nandi U, Reddy CN, Bharate SS, Singh G, Bharate SB, Vishwakarma RA, Kaddoumi A, Kumar A. Crocetin promotes clearance of amyloid-β by inducing autophagy via the STK11/LKB1-mediated AMPK pathway. Autophagy 2021; 17:3813-3832. [PMID: 33404280 DOI: 10.1080/15548627.2021.1872187] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Alzheimer disease (AD) is usually accompanied by two prominent pathological features, cerebral accumulation of amyloid-β (Aβ) plaques and presence of MAPT/tau neurofibrillary tangles. Dysregulated clearance of Aβ largely contributes to its accumulation and plaque formation in the brain. Macroautophagy/autophagy is a lysosomal degradative process, which plays an important role in the clearance of Aβ. Failure of autophagic clearance of Aβ is currently acknowledged as a contributing factor to increased accumulation of Aβ in AD brains. In this study, we have identified crocetin, a pharmacologically active constituent from the flower stigmas of Crocus sativus, as a potential inducer of autophagy in AD. In the cellular model, crocetin induced autophagy in N9 microglial and primary neuron cells through STK11/LKB1 (serine/threonine kinase 11)-mediated AMP-activated protein kinase (AMPK) pathway activation. Autophagy induction by crocetin significantly increased Aβ clearance in N9 cells. Moreover, crocetin crossed the blood-brain barrier and induced autophagy in the brains' hippocampi of wild-type male C57BL/6 mice. Further studies in transgenic male 5XFAD mice, as a model of AD, revealed that one-month treatment with crocetin significantly reduced Aβ levels and neuroinflammation in the mice brains and improved memory function by inducing autophagy that was mediated by AMPK pathway activation. Our findings support further development of crocetin as a pharmacological inducer of autophagy to prevent, slow down progression, and/or treat AD.
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Affiliation(s)
- Abubakar Wani
- Division of PK-PD-Toxicology and Formulation, CSIR-Indian Institute of Integrative Medicine, Jammu, India.,Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India.,Department of Neurology, Washington University, St. Louis, Missouri, USA
| | - Sweilem B Al Rihani
- Department of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, Alabama, USA
| | - Ankita Sharma
- Division of PK-PD-Toxicology and Formulation, CSIR-Indian Institute of Integrative Medicine, Jammu, India.,Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India
| | - Brenna Weadick
- Division of Pharmaceutics and Pharmaceutical Chemistry, College of Pharmacy, Ohio State University, Columbus, Ohio, USA
| | - Rajgopal Govindarajan
- Division of Pharmaceutics and Pharmaceutical Chemistry, College of Pharmacy, Ohio State University, Columbus, Ohio, USA
| | - Sameer U Khan
- Division of PK-PD-Toxicology and Formulation, CSIR-Indian Institute of Integrative Medicine, Jammu, India.,Division of Cancer Pharmacology, CSIR-Indian Institute of Integrative Medicine, Jammu, India
| | - Parduman R Sharma
- Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India.,Division of Cancer Pharmacology, CSIR-Indian Institute of Integrative Medicine, Jammu, India
| | - Ashish Dogra
- Division of PK-PD-Toxicology and Formulation, CSIR-Indian Institute of Integrative Medicine, Jammu, India.,Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India
| | - Utpal Nandi
- Division of PK-PD-Toxicology and Formulation, CSIR-Indian Institute of Integrative Medicine, Jammu, India.,Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India
| | - Chilakala N Reddy
- Preformulation Laboratory, PK-PD Toxicology and Formulation Division, CSIR- Indian Institute of Integrative Medicine, Jammu, India
| | - Sonali S Bharate
- Preformulation Laboratory, PK-PD Toxicology and Formulation Division, CSIR- Indian Institute of Integrative Medicine, Jammu, India.,Shobhaben Pratapbhai Patel School of Pharmacy & Technology Management, SVKM's NMIMS, Mumbai, India
| | - Gurdarshan Singh
- Division of PK-PD-Toxicology and Formulation, CSIR-Indian Institute of Integrative Medicine, Jammu, India.,Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India
| | - Sandip B Bharate
- Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India.,Division of Medicinal Chemistry, CSIR-Indian Institute of Integrative Medicine, Jammu, India
| | - Ram A Vishwakarma
- Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India.,Division of Medicinal Chemistry, CSIR-Indian Institute of Integrative Medicine, Jammu, India
| | - Amal Kaddoumi
- Department of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, Alabama, USA
| | - Ajay Kumar
- Division of PK-PD-Toxicology and Formulation, CSIR-Indian Institute of Integrative Medicine, Jammu, India.,Academy of Scientific and Innovative Research (Acsir), Ghaziabad, India
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15
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Shin J, Pelletier S, Richer L, Pike GB, Gaudet D, Paus T, Pausova Z. Adiposity-related insulin resistance and thickness of the cerebral cortex in middle-aged adults. J Neuroendocrinol 2020; 32:e12921. [PMID: 33340164 PMCID: PMC8132297 DOI: 10.1111/jne.12921] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 11/13/2020] [Accepted: 11/13/2020] [Indexed: 12/14/2022]
Abstract
The thickness of the cerebral cortex decreases with ageing. Recent research suggests that obesity and type 2 diabetes mellitus may accelerate this cortical thinning, and that obesity-related insulin resistance may be a shared mechanistic pathway. Ageing of the cerebral cortex demonstrates sex-specific trajectories, with a gradual shift towards accelerated thinning beginning in midlife. Here, we investigated whether adiposity-related insulin resistance is associated with lower thickness of the human cerebral cortex in a community-based sample of middle-aged adults. We studied 533 adult participants (36-65 years) from the Saguenay Youth Study. Adiposity was assessed with bioimpedance, and insulin resistance was evaluated from a fasting blood sample with the homeostatic model assessment of insulin resistance (HOMA-IR). Associations between adiposity-related insulin resistance (adiposity/IR) and cortical thickness were assessed with linear models, separately in males and females younger or older than 50 years. Potential biological underpinnings were investigated with virtual histology. Adiposity/IR was associated with lower cortical thickness in females older than 50 years but not in males or younger females. The strength of the association varied across the cerebral cortex, with regions of the lateral frontal and parietal cortices and the superior temporal cortex demonstrating most pronounced thinning. Based on virtual histology, adiposity/IR-related cortical thinning may involve neurones, astrocytes, oligodendrocytes and ependymal cells acting so that they lower the cortical potential for synaptogenesis, formation of dendritic spines, production of extracellular matrix and myelination. Adiposity-related insulin resistance is associated with lower cortical thickness in middle-aged women older than 50 years. This aspect of thinning may involve neuronal and glial cells in a way that lowers the capacity of the cerebral cortex for neuronal plasticity and maintenance of myelination.
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Affiliation(s)
- Jean Shin
- The Hospital for Sick Children, University of Toronto, Toronto, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada
| | - Stephanie Pelletier
- The Hospital for Sick Children, University of Toronto, Toronto, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada
| | - Louis Richer
- Department of Health Sciences, Université du Québec à Chicoutimi, Chicoutimi, Canada
| | - G. Bruce Pike
- Department of Radiology and Clinical Neurosciences, University of Calgary, Calgary, Canada
| | - Daniel Gaudet
- Lipidology Unit, Community Genomic Medicine Centre and ECOGENE-21, Department of Medicine, Université de Montréal, Saguenay, Canada
| | - Tomas Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada
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16
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Calderón-Garcidueñas L, Torres-Solorio AK, Kulesza RJ, Torres-Jardón R, González-González LO, García-Arreola B, Chávez-Franco DA, Luévano-Castro SC, Hernández-Castillo A, Carlos-Hernández E, Solorio-López E, Crespo-Cortés CN, García-Rojas E, Mukherjee PS. Gait and balance disturbances are common in young urbanites and associated with cognitive impairment. Air pollution and the historical development of Alzheimer's disease in the young. ENVIRONMENTAL RESEARCH 2020; 191:110087. [PMID: 32890478 PMCID: PMC7467072 DOI: 10.1016/j.envres.2020.110087] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/10/2020] [Accepted: 08/11/2020] [Indexed: 05/03/2023]
Abstract
To determine whether gait and balance dysfunction are present in young urbanites exposed to fine particular matter PM2.5 ≥ annual USEPA standard, we tested gait and balance with Tinetti and Berg tests in 575 clinically healthy subjects, age 21.0 ± 5.7 y who were residents in Metropolitan Mexico City, Villahermosa and Reynosa. The Montreal Cognitive Assessment was also applied to an independent cohort n:76, age 23.3 ± 9.1 y. In the 575 cohort, 75.4% and 34.4% had abnormal total Tinetti and Berg scores and high risk of falls in 17.2% and 5.7% respectively. BMI impacted negatively Tinetti and Berg performance. Gait dysfunction worsen with age and males performed worse than females. Gait and balance dysfunction were associated with mild cognitive impairment MCI (19.73%) and dementia (55.26%) in 57/76 and 19 cognitively intact subjects had gait and balance dysfunction. Seventy-five percent of urbanites exposed to PM2.5 had gait and balance dysfunction. For MMC residents-with historical documented Alzheimer disease (AD) and CSF abnormalities, these findings suggest Alzheimer Continuum is in progress. Early development of a Motoric Cognitive Risk Syndrome ought to be considered in city dwellers with normal cognition and gait dysfunction. The AD research frame in PM2.5 exposed young urbanites should include gait and balance measurements. Multicity teens and young adult cohorts are warranted for quantitative gait and balance measurements and neuropsychological and brain imaging studies in high vs low PM2.5 exposures. Early identification of gait and balance impairment in young air pollution-exposed urbanites would facilitate multidisciplinary prevention efforts for modifying the course of AD.
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Affiliation(s)
| | | | - Randy J Kulesza
- Auditory Research Center, Lake Erie College of Osteopathic Medicine, Erie, PA, 16509, USA
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17
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Choi J, Kwon LN, Lim H, Chun HW. Gender-Based Analysis of Risk Factors for Dementia Using Senior Cohort. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E7274. [PMID: 33027971 PMCID: PMC7579641 DOI: 10.3390/ijerph17197274] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 09/23/2020] [Accepted: 09/28/2020] [Indexed: 12/11/2022]
Abstract
Globally, one of the biggest problems with the increase in the elderly population is dementia. However, dementia still has no fundamental cure. Therefore, it is important to predict and prevent dementia early. For early prediction of dementia, it is crucial to find dementia risk factors that increase a person's risk of developing dementia. In this paper, the subject of dementia risk factor analysis and discovery studies were limited to gender, because it is assumed that the difference in the prevalence of dementia in men and women will lead to differences in the risk factors for dementia among men and women. This study analyzed the Korean National Health Information System-Senior Cohort using machine-learning techniques. By using the machine-learning technique, it was possible to reveal a very small causal relationship between data that are ignored using existing statistical techniques. By using the senior cohort, it was possible to analyze 6000 data that matched the experimental conditions out of 558,147 sample subjects over 14 years. In order to analyze the difference in dementia risk factors between men and women, three machine-learning-based dementia risk factor analysis models were constructed and compared. As a result of the experiment, it was found that the risk factors for dementia in men and women are different. In addition, not only did the results include most of the known dementia risk factors, previously unknown candidates for dementia risk factors were also identified. We hope that our research will be helpful in finding new dementia risk factors.
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Affiliation(s)
- Jaekue Choi
- Convergence Research Center for Diagnosis, Treatment and Care System of Dementia, Korea Institute of Science and Technology, Seoul 02792, Korea; (J.C.); (L.-N.K.)
- Future Information Research Center, Korea Institute of Science and Technology Information, Seoul 02456, Korea
- Department of Computer Science and Engineering, Korea University, Seoul 02855, Korea;
| | - Lee-Nam Kwon
- Convergence Research Center for Diagnosis, Treatment and Care System of Dementia, Korea Institute of Science and Technology, Seoul 02792, Korea; (J.C.); (L.-N.K.)
- Future Information Research Center, Korea Institute of Science and Technology Information, Seoul 02456, Korea
| | - Heuiseok Lim
- Department of Computer Science and Engineering, Korea University, Seoul 02855, Korea;
| | - Hong-Woo Chun
- Convergence Research Center for Diagnosis, Treatment and Care System of Dementia, Korea Institute of Science and Technology, Seoul 02792, Korea; (J.C.); (L.-N.K.)
- Future Information Research Center, Korea Institute of Science and Technology Information, Seoul 02456, Korea
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18
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Lu WH, de Souto Barreto P, Rolland Y, Rodríguez-Mañas L, Bouyahia A, Fischer C, Mangin JF, Giudici KV, Vellas B. Cross-sectional and prospective associations between cerebral cortical thickness and frailty in older adults. Exp Gerontol 2020; 139:111018. [PMID: 32663588 DOI: 10.1016/j.exger.2020.111018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/16/2020] [Accepted: 07/03/2020] [Indexed: 11/15/2022]
Abstract
BACKGROUND Several neurodegenerative markers measured by magnetic resonance imaging (MRI) have shown to be related with frailty. While most studies have focused on surrogates of cerebral vascular damage such as increased white matter lesions, the associations between cortical atrophy and frailty were less often investigated. OBJECTIVES To investigate the cross-sectional and prospective associations between cortical thickness and frailty evolution in older adults. METHODS We enrolled 484 community-dwelling adults aged ≥70 years, participants from the Multidomain Alzheimer Preventive Trial (MAPT), with data on cerebral cortical thickness and frailty. Cortical thickness was acquired by MRI for whole-brain and regional cortices. Two function-specific regions of interest, i.e., mobility-related regions and Alzheimer's disease (AD) signature, were selected on the basis of previous studies. Frailty status was assessed by the Fried frailty phenotype (i.e., weakness, slowness, involuntary weight loss, fatigue and low physical activity level) at baseline, after 6 months and every year until the end of the 5-year follow-up. RESULTS Older adults with higher global cortical thickness were less likely to be pre-frail and frail at baseline (adjusted OR: 0.13, 95% CI: 0.03-0.65, p = 0.013). In addition, higher cortical thickness in mobility-related and AD-signature regions were associated with lower likelihood of being pre-frail and frail. Similar associations were observed for having weakness and slowness. However, neither global nor region-specific cortical thickness showed prospective associations with future frailty onset. CONCLUSIONS The global and regional cortical thickness cross-sectionally associated with frailty in older adults, but no prospective associations with incident frailty were found. The longitudinal relationship between cortical thickness and frailty evolution requires further investigation.
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Affiliation(s)
- Wan-Hsuan Lu
- Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), Toulouse, France.
| | - Philipe de Souto Barreto
- Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), Toulouse, France; UPS/Inserm UMR1027, University of Toulouse III, Toulouse, France
| | - Yves Rolland
- Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), Toulouse, France; UPS/Inserm UMR1027, University of Toulouse III, Toulouse, France
| | - Leocadio Rodríguez-Mañas
- CIBER of Frailty and Healthy Aging (CIBERFES), Madrid, Spain; Geriatric Department, Hospital Universitario de Getafe, Getafe, Spain
| | - Ali Bouyahia
- CATI Multicenter Neuroimaging Platform, Neurospin, CEA, Gif-sur-Yvette, France
| | - Clara Fischer
- CATI Multicenter Neuroimaging Platform, Neurospin, CEA, Gif-sur-Yvette, France; Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, France
| | - Jean-François Mangin
- CATI Multicenter Neuroimaging Platform, Neurospin, CEA, Gif-sur-Yvette, France; Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, France
| | - Kelly Virecoulon Giudici
- Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), Toulouse, France
| | - Bruno Vellas
- Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), Toulouse, France; UPS/Inserm UMR1027, University of Toulouse III, Toulouse, France
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Gamache J, Yun Y, Chiba-Falek O. Sex-dependent effect of APOE on Alzheimer's disease and other age-related neurodegenerative disorders. Dis Model Mech 2020; 13:dmm045211. [PMID: 32859588 PMCID: PMC7473656 DOI: 10.1242/dmm.045211] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The importance of apolipoprotein E (APOE) in late-onset Alzheimer's disease (LOAD) has been firmly established, but the mechanisms through which it exerts its pathogenic effects remain elusive. In addition, the sex-dependent effects of APOE on LOAD risk and endophenotypes have yet to be explained. In this Review, we revisit the different aspects of APOE involvement in neurodegeneration and neurological diseases, with particular attention to sex differences in the contribution of APOE to LOAD susceptibility. We discuss the role of APOE in a broader range of age-related neurodegenerative diseases, and summarize the biological factors linking APOE to sex hormones, drawing on supportive findings from rodent models to identify major mechanistic themes underlying the exacerbation of LOAD-associated neurodegeneration and pathology in the female brain. Additionally, we list sex-by-genotype interactions identified across neurodegenerative diseases, proposing APOE variants as a shared etiology for sex differences in the manifestation of these diseases. Finally, we present recent advancements in 'omics' technologies, which provide a new platform for more in-depth investigations of how dysregulation of this gene affects the development and progression of neurodegenerative diseases. Collectively, the evidence summarized in this Review highlights the interplay between APOE and sex as a key factor in the etiology of LOAD and other age-related neurodegenerative diseases. We emphasize the importance of careful examination of sex as a contributing factor in studying the underpinning genetics of neurodegenerative diseases in general, but particularly for LOAD.
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Affiliation(s)
- Julia Gamache
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, Durham, NC 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708, USA
| | - Young Yun
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, Durham, NC 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708, USA
| | - Ornit Chiba-Falek
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, Durham, NC 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708, USA
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