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Li Y, Xiao Q, Chen L, Li G, Li B, Li T, Deng Y, Li F, Yang B, Rong S. Association of the serum levels of saturated fatty acids and mild cognitive impairment: a cross-sectional study. Eur J Clin Nutr 2024; 78:748-756. [PMID: 38926607 DOI: 10.1038/s41430-024-01468-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 06/12/2024] [Accepted: 06/18/2024] [Indexed: 06/28/2024]
Abstract
OBJECTIVES To investigate the association of serum saturated fatty acids (SFAs) and prevalent mild cognitive impairment (MCI) among middle-aged and elderly Chinese. METHODS A total of 607 Chinese adults aged at least 45 years were included in the baseline survey of The Lifestyle and Healthy Aging of Chinese Square Dancer Study. Serum concentrations of individual SFAs including 6 even-chain SFAs (C14:0, C16:0, C18:0, C20:0, C22:0, and C24:0) and 4 odd-chain SFAs (C15:0, C17:0, C21:0, and C23:0), were quantified by Gas chromatography system with a mass spectrometer. According to Petersen's criteria, prevalent MCI was diagnosed by neurologists through uniformed neuropsychological tests, including trail-making test-part B (TMT-B), auditory verbal learning test (AVLT), digit symbol substitution test (DSST), and verbal fluency test (VFT). RESULTS The median age was 62 years with an interquartile range of 57.0 to 67.0 years, and 86 (14.17%) participants were living with MCI. Higher levels of either even-chain or odd-chain individual SFAs were associated with the higher odds of MCI, and their odds ratios (ORs) and 95% confidence intervals (95%CIs) were 2.054 (1.012 to 4.171) for C14:0, 2.246 (1.061 to 4.755) for C16:0, 2.789 (1.321 to 5.886) for C18:0, and 2.329 (1.136 to 4.778) for C15:0, and 2.761 (1.310 to 5.820) for C17:0, respectively. CONCLUSIONS The serum concentration of SFAs was positively related to the odds of MCI in middle-aged and elderly adults. Determining the link between SFAs profiles and MCI may inform a better understanding of the potential role of saturated fat intake on cognitive function.
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Affiliation(s)
- Yuanyuan Li
- Department of Nutrition and Food Hygiene, School of Public Health, Wuhan University; Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan, 430071, China
| | - Qing Xiao
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard, Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - LiangKai Chen
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Guang Li
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard, Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Benchao Li
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard, Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Tingting Li
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard, Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Yan Deng
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard, Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Fengping Li
- Department of Nutrition and Food Hygiene, School of Public Health, Wuhan University; Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan, 430071, China
| | - Bo Yang
- Institute of Lipids Medicine, School of Public Health & Management, Wenzhou Medical University, Wenzhou, 325035, China.
| | - Shuang Rong
- Department of Nutrition and Food Hygiene, School of Public Health, Wuhan University; Research Center of Public Health, Renmin hospital of Wuhan University, Wuhan, 430071, China.
- Academy of Nutrition and Health, Hubei Province Key Laboratory of Occupational Hazard, Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China.
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Kang L, Wang W, Nie Z, Gong Q, Yao L, Xiang D, Zhang N, Tu N, Feng H, Zong X, Bai H, Wang G, Wang F, Bu L, Liu Z. Dysregulated cerebral blood flow, rather than gray matter Volume, exhibits stronger correlations with blood inflammatory and lipid markers in depression. Neuroimage Clin 2024; 41:103581. [PMID: 38430800 PMCID: PMC10944186 DOI: 10.1016/j.nicl.2024.103581] [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: 01/05/2024] [Revised: 02/08/2024] [Accepted: 02/25/2024] [Indexed: 03/05/2024]
Abstract
Arterial spin labeling (ASL) can be used to detect differences in perfusion for multiple brain regions thought to be important in major depressive disorder (MDD). However, the potential of cerebral blood flow (CBF) to predict MDD and its correlations between the blood lipid levels and immune markers, which are closely related to MDD and brain function change, remain unclear. The 451 individuals - 298 with MDD and 133 healthy controls who underwent MRI at a single time point with arterial spin labelling and a high resolution T1-weighted structural scan. A proportion of MDD also provided blood samples for analysis of lipid and immune markers. We performed CBF case-control comparisons, random forest model construction, and exploratory correlation analyses. Moreover, we investigated the relationship between gray matter volume (GMV), blood lipids, and the immune system within the same sample to assess the differences in CBF and GMV. We found that the left inferior parietal but supramarginal and angular gyrus were significantly different between the MDD patients and HCs (voxel-wise P < 0.001, cluster-wise FWE correction). And bilateral inferior temporal (ITG), right middle temporal gyrus and left precentral gyrus CBF predict MDD (the area under the receiver operating characteristic curve of the random forest model is 0.717) and that CBF is a more sensitive predictor of MDD than GMV. The left ITG showed a positive correlation trend with immunoglobulin G (r = 0.260) and CD4 counts (r = 0.283). The right ITG showed a correlation trend with Total Cholesterol (r = -0.249) and tumour necrosis factor-alpha (r = -0.295). Immunity and lipids were closely related to CBF change, with the immunity relationship potentially playing a greater role. The interactions between CBF, plasma lipids and immune index could therefore represent an MDD pathophysiological mechanism. The current findings provide evidence for targeted regulation of CBF or immune properties in MDD.
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Affiliation(s)
- Lijun Kang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wei Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhaowen Nie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Qian Gong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lihua Yao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Dan Xiang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Nan Zhang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ning Tu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Hongyan Feng
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xiaofen Zong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Hanping Bai
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Lihong Bu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan, China.
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China; Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan, China.
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Finkelstein O, Levakov G, Kaplan A, Zelicha H, Meir AY, Rinott E, Tsaban G, Witte AV, Blüher M, Stumvoll M, Shelef I, Shai I, Riklin Raviv T, Avidan G. Deep learning-based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention. Hum Brain Mapp 2024; 45:e26595. [PMID: 38375968 PMCID: PMC10878010 DOI: 10.1002/hbm.26595] [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: 05/01/2023] [Revised: 11/16/2023] [Accepted: 01/03/2024] [Indexed: 02/21/2024] Open
Abstract
Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) tools to explore whether differences in clinical measurements following lifestyle interventions in overweight population could be reflected in brain morphology. In the DIRECT-PLUS clinical trial, participants with criterion for metabolic syndrome underwent an 18-month lifestyle intervention. Structural brain MRIs were acquired before and after the intervention. We utilized an ensemble learning framework to predict Body-Mass Index (BMI) scores, which correspond to adiposity-related clinical measurements from brain MRIs. We revealed that patient-specific reduction in BMI predictions was associated with actual weight loss and was significantly higher in active diet groups compared to a control group. Moreover, explainable AI (XAI) maps highlighted brain regions contributing to BMI predictions that were distinct from regions associated with age prediction. Our DIRECT-PLUS analysis results imply that predicted BMI and its reduction are unique neural biomarkers for obesity-related brain modifications and weight loss.
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Affiliation(s)
- Ofek Finkelstein
- Department of Cognitive and Brain SciencesBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Gidon Levakov
- Department of Cognitive and Brain SciencesBen‐Gurion University of the NegevBeer ShevaIsrael
| | - Alon Kaplan
- The Health & Nutrition Innovative International Research Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
- The Chaim Sheba Medical Center, Tel HashomerRamat‐GanIsrael
| | - Hila Zelicha
- The Health & Nutrition Innovative International Research Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
| | - Anat Yaskolka Meir
- The Health & Nutrition Innovative International Research Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
| | - Ehud Rinott
- The Health & Nutrition Innovative International Research Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
| | - Gal Tsaban
- The Health & Nutrition Innovative International Research Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
- Soroka University Medical CenterBeer ShevaIsrael
| | - Anja Veronica Witte
- Department of Neurology, Max Planck‐Institute for Human Cognitive and Brain Sciences, and Cognitive NeurologyUniversity of Leipzig Medical CenterLeipzigGermany
| | | | | | - Ilan Shelef
- The Health & Nutrition Innovative International Research Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
- Soroka University Medical CenterBeer ShevaIsrael
| | - Iris Shai
- The Health & Nutrition Innovative International Research Center, Faculty of Health SciencesBen Gurion University of the NegevBeer ShevaIsrael
- Department of Nutrition, Harvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Tammy Riklin Raviv
- The School of Electrical and Computer EngineeringBen Gurion University of the NegevBeer ShevaIsrael
| | - Galia Avidan
- Department of PsychologyBen‐Gurion University of the NegevBeer ShevaIsrael
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Liu Z, Lin X, Zeng L, Zhang H, Guo W, Lu Q, Huang C, Wang J, Liu P, Chang Q, Zhang M, Huo Y, Wang Y, Wang F, Wu S. Elevated non-HDL-C/HDL-C ratio increases the 1-year risk of recurrent stroke in older patients with non-disabling ischemic cerebrovascular events: results from the Xi'an Stroke Registry Study of China. BMC Geriatr 2023; 23:410. [PMID: 37407911 DOI: 10.1186/s12877-023-04102-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 06/09/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Few studies have explored the prognostic role of nontraditional lipid-related indicators in non-disabling ischemic cerebrovascular events (NICE). In this study, we aimed to investigate the relationship between the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (non-HDL-C/HDL-C) and the1-year risk of recurrent stroke in patients with NICE. METHODS Total cholesterol (TC), HDL-C, and patient information were collected at admission. Recurrent stroke events were followed up 3, 6, and 12 months after onset. Non-HDL-C levels were calculated by subtracting HDL-C from TC. The non-HDL-C/HDL-C ratio was treated as a continuous variable and in quartiles (Q1-Q4). Stratified multivariate Cox regression was used to investigate the relationship between the non-HDL-C/HDL-C ratio and the 1-year risk of recurrent stroke in patients with NICE. RESULTS Overall, 1,659 patients with NICE were enrolled. For each unit increase in the non-HDL-C/HDL-C ratio, the 1-year risk of recurrent stroke in patients aged ≥ 65 years (older patients) with NICE increased by 64% in the adjusted model (hazard ratio [HR]: 1.64, 95%confidence interval [CI]:1.18-2.27, P = 0.003), and the HRs were 3.21 and 4.24 times higher in the Q3 and Q4 groups than that in the Q1 group, which was considered to be the reference (adjusted model Q3: HR: 3.21, 95%CI: 1.05-9.83, P = 0.041; adjusted model Q4: HR: 4.24, 95%CI: 1.30-13.85, P = 0.017). However, there was no significant difference in patients younger than 65 years. Both curve fitting and Kaplan-Meier cumulative risk analysis showed that an elevated non-HDL-C/HDL-C ratio significantly increased the 1-year risk of recurrent stroke in older patients with NICE. The optimal range for the non-HDL-C/HDL-C ratio should be no higher than the Q2 group (2.256-2.939). Stratified Cox regression analysis showed that these results tended to be stable for different comorbidities (all P for interaction > 0.05). CONCLUSIONS Elevated non-HDL-C/HDL-C ratios significantly increased the 1-year risk of recurrent stroke in older patients with NICE. Therefore, clinicians need to pay more attention to this indicator when managing older patients with NICE.
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Affiliation(s)
- Zhongzhong Liu
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Department of Epidemiology and Biostatistics, School of Public Health of Xi'an Jiaotong University Health Science Center, Xi'an, 71006, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Xuemei Lin
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Lingxia Zeng
- Department of Epidemiology and Biostatistics, School of Public Health of Xi'an Jiaotong University Health Science Center, Xi'an, 71006, China
| | - Huan Zhang
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- College of Life Science, Northwest University, Xi'an, 710069, China
| | - Weiyan Guo
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Qingli Lu
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Congli Huang
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
- Department of Traditional Chinese Medicine, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
| | - Jing Wang
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Pei Liu
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Qiaoqiao Chang
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Mi Zhang
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Yan Huo
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Yan Wang
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Fang Wang
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China
| | - Songdi Wu
- Department of Neurology, Xi'an No.1 Hospital, The First Affiliated Hospital of Northwest University, Xi'an, 710002, China.
- College of Life Science, Northwest University, Xi'an, 710069, China.
- Xi'an Key Laboratory for Innovation and Translation of Neuroimmunological Diseases, Xi'an, 710002, China.
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Jiang C, Wang Y, Dong Y, Liu R, Song L, Wang S, Xu Z, Niu S, Ren Y, Han X, Zhao M, Wang J, Li X, Cong L, Hou T, Zhang Q, Du Y, Qiu C. Associations of Microvascular Dysfunction with Mild Cognitive Impairment and Cognitive Function Among Rural-Dwelling Older Adults in China. J Alzheimers Dis 2023:JAD221242. [PMID: 37182877 DOI: 10.3233/jad-221242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND Microvascular dysfunction (MVD) may contribute to cognitive impairment and Alzheimer's disease, but evidence is limited. OBJECTIVE To investigate the association of composite and organ-specific MVD burden with mild cognitive impairment (MCI) and cognition among rural-dwelling Chinese older adults. METHODS In this population-based cross-sectional study, we assessed MVD makers using optical coherence tomographic angiography for retinal microvasculature features, brain magnetic resonance imaging scans for cerebral small vessel disease (CSVD), and serum biomarkers for MVD. A composite MVD score was generated from the aforementioned organ-specific parameters. We used a neuropsychological test battery to assess memory, verbal fluency, attention, executive function, and global cognitive function. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were diagnosed following the Petersen's criteria. Data was analyzed with the linear and logistic regression models. RESULTS Of the 274 dementia-free participants (age≥65 years), 56 were diagnosed with MCI, including 47 with aMCI and 9 with naMCI. A composite MVD score was statistically significantly associated with an odds ratio (OR) of 2.70 (95% confidence interval 1.12-6.53) for MCI and β-coefficient of -0.29 (-0.48--0.10) for global cognitive score after adjustment for socio-demographics, lifestyle factors, APOE genotype, the Geriatric Depression Scale score, serum inflammatory biomarkers, and cardiovascular comorbidity. A composite score of retinal microvascular morphology was associated with a multivariable-adjusted OR of 1.72 (1.09-2.73) for MCI and multivariable-adjusted β-coefficient of -0.11 (-0.22--0.01) for global cognitive score. A composite CSVD score was associated with a lower global cognitive score (β= -0.10; -0.17--0.02). CONCLUSION Microvascular dysfunction, especially in the brain and retina, is associated with MCI and poor cognitive function among rural-dwelling older adults.
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Affiliation(s)
- Chunyan Jiang
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
| | - Yongxiang Wang
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Yi Dong
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Rui Liu
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
| | - Lin Song
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Shanshan Wang
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Zhe Xu
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
| | - Sijie Niu
- Shandong Provincial Key Laboratory of Network based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China
| | - Yifei Ren
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
| | - Xiaodong Han
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
| | - Mingqing Zhao
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
| | - Jiafeng Wang
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
| | - Xiaohui Li
- Shandong Provincial Key Laboratory of Network based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China
| | - Lin Cong
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Tingting Hou
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Qinghua Zhang
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Yifeng Du
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurology, Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P. R. China
- Shandong Provincial Clinical Research Center for Geriatric Neurological Diseases, Jinan, Shandong, P. R. China
| | - Chengxuan Qiu
- Department of Neurology, Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Department of Neurobiology, Aging Research Center and Center for Alzheimer Research, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
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6
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Xu Z, Dong Y, Wang Y, Song L, Niu S, Wang S, Zhao M, Wang J, Cong L, Han X, Hou T, Tang S, Zhang Q, Du Y, Qiu C. Associations of macular microvascular parameters with cerebral small vessel disease in rural older adults: A population-based OCT angiography study. Front Neurol 2023; 14:1133819. [PMID: 37006481 PMCID: PMC10060796 DOI: 10.3389/fneur.2023.1133819] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
ObjectiveTo explore the associations of macular microvascular parameters with cerebral small vessel disease (CSVD) in rural-dwelling older adults in China.MethodsThis population-based cross-sectional study included 195 participants (age ≥ 60 years; 57.4% women) in the optical coherence tomographic angiography (OCTA) sub-study within the Multimodal Interventions to delay Dementia and disability in rural China (MIND-China). Macular microvascular parameters were measured using the OCTA. We automatically estimated volumes of gray matter, white matter, and white matter hyperintensity (WMH), and manually assessed numbers of enlarged perivascular spaces (EPVS) and lacunes on brain magnetic resonance imaging. Data were analyzed with the general linear models.ResultsAdjusting for multiple confounders, lower vessel skeleton density (VSD) and higher vessel diameter index (VDI) were significantly associated with larger WMH volume (P < 0.05). Lower VSD and foveal density-300 (FD-300) of left eye were significantly associated with lower brain parenchymal volume (P < 0.05). In addition, lower areas of foveal avascular zone (FAZ) and FD-300 of left eye were significantly associated with more EPVS (P < 0.05). The associations of abnormal macular microvascular parameters with WMH volume were evident mainly among females. Macular microvascular parameters were not associated with lacunes.ConclusionMacular microvascular signs are associated with WMH, brain parenchymal volume, and EPVS in older adults. The OCTA-assessed macular microvascular parameters can be valuable markers for microvascular lesions in the brain.
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Affiliation(s)
- Zhe Xu
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Yi Dong
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Lin Song
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Sijie Niu
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, Shandong, China
| | - Shanshan Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Mingqing Zhao
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Jiafeng Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Xiaojuan Han
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Shi Tang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
| | - Qinghua Zhang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
- *Correspondence: Qinghua Zhang
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, China
- Yifeng Du
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
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Zhang Q, Huang S, Cao Y, Dong G, Chen Y, Zhu X, Yun W, Zhang M. Remnant cholesterol and mild cognitive impairment: A cross-sectional study. Front Aging Neurosci 2023; 15:1069076. [PMID: 37009458 PMCID: PMC10057110 DOI: 10.3389/fnagi.2023.1069076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 02/23/2023] [Indexed: 03/17/2023] Open
Abstract
ObjectiveEmerging evidence suggests that elevated remnant cholesterol (RC) correlates with several health conditions. To explore the association of plasma RC with MCI incidence and the relationship between plasma RC and different domains of cognition in MCI patients.MethodsThirty-six MCI patients and 38 cognitively healthy controls (HC) were enrolled in the present cross-sectional study. Using total cholesterol (TC) minus high-density lipoprotein cholesterol (HDL-C) minus low-density lipoprotein cholesterol (LDL-C) as the formula for calculating fasting RC. Cognition was assessed using the Chinese version of the Montreal cognitive assessment (MoCA), Auditory Verbal Learning Test (AVLT), Digit Symbol Substitution Test (DSST), Trail Making Test (TMT), and Rey-Osterrieth Complex Figure Test (ROCF).ResultsCompared to healthy controls, MCI patients had a higher level of RC, the median difference in RC levels between these two groups was 8.13 mg/dl (95.0%CI: 0.97–16.1). Concurrently, plasma RC level was positively associated with MCI risk (OR = 1.05, 95%CI: 1.01–1.10). Notably, elevated RC level was correlated with impaired cognition in MCI patients, such as DSST (pr = −0.45, p = 0.008), ROCF- Long Delayed Recall (pr = −0.45, p = 0.008), AVLT-Immediate Recall (pr = −0.38, p = 0.028), and TMT-A (pr = 0.44, p = 0.009). Conversely, no significant correlation was found between RC and the AVLT-Long Delayed Recall test.ConclusionThis study found that plasma remnant cholesterol was associated with MCI. Further large longitudinal studies are needed in the future to confirm the results and clarify the cause-and-effect relationship.
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Affiliation(s)
- Qiaoyang Zhang
- Department of Psychology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Shan Huang
- Department of Neurology, General Hospital of Northern Theatre Command, Shenyang, China
| | - Yin Cao
- Department of Psychology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Guanzhong Dong
- Department of Psychology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Yun Chen
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Xuanyan Zhu
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Wenwei Yun
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
- Wenwei Yun,
| | - Min Zhang
- Department of Neurology, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, Changzhou, China
- *Correspondence: Min Zhang,
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Lam BYK, Cai Y, Akinyemi R, Biessels GJ, van den Brink H, Chen C, Cheung CW, Chow KN, Chung HKH, Duering M, Fu ST, Gustafson D, Hilal S, Hui VMH, Kalaria R, Kim S, Lam MLM, de Leeuw FE, Li ASM, Markus HS, Marseglia A, Zheng H, O'Brien J, Pantoni L, Sachdev PS, Smith EE, Wardlaw J, Mok VCT. The global burden of cerebral small vessel disease in low- and middle-income countries: A systematic review and meta-analysis. Int J Stroke 2023; 18:15-27. [PMID: 36282189 DOI: 10.1177/17474930221137019] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. Previous studies on the prevalence of cSVD are mostly based on single geographically defined cohorts in high-income countries. Studies investigating the prevalence of cSVD in low- and middle-income countries (LMICs) are expanding but have not been systematically assessed. AIM This study aims to systematically review the prevalence of cSVD in LMICs. RESULTS Articles were searched from the Ovid MEDLINE and EMBASE databases from 1 January 2000 to 31 March 2022, without language restrictions. Title/abstract screening, full-text review, and data extraction were performed by two to seven independent reviewers. The prevalence of cSVD and study sample size were extracted by pre-defined world regions and health status. The Risk of Bias for Non-randomized Studies tool was used. The protocol was registered on PROSPERO (CRD42022311133). A meta-analysis of proportion was performed to assess the prevalence of different magnetic resonance imaging markers of cSVD, and a meta-regression was performed to investigate associations between cSVD prevalence and type of study, age, and male: female ratio. Of 2743 studies identified, 42 studies spanning 12 global regions were included in the systematic review. Most of the identified studies were from China (n = 23). The median prevalence of moderate-to-severe white matter hyperintensities (WMHs) was 20.5%, 40.5%, and 58.4% in the community, stroke, and dementia groups, respectively. The median prevalence of lacunes was 0.8% and 33.5% in the community and stroke groups. The median prevalence of cerebral microbleeds (CMBs) was 10.7% and 22.4% in the community and stroke groups. The median prevalence of moderate-to-severe perivascular spaces was 25.0% in the community. Meta-regression analyses showed that the weighted median age (51.4 ± 0.0 years old; range: 36.3-80.2) was a significant predictor of the prevalence of moderate-to-severe WMH and lacunes, while the type of study was a significant predictor of the prevalence of CMB. The heterogeneity of studies was high (>95%). Male participants were overrepresented. CONCLUSIONS This systematic review and meta-analysis provide data on cSVD prevalence in LMICs and demonstrated the high prevalence of the condition. cSVD research in LMICs is being published at an increasing rate, especially between 2010 and 2022. More data are particularly needed from Sub-Saharan Africa and Central Europe, Eastern Europe, and Central Asia.
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Affiliation(s)
- Bonnie Yin Ka Lam
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Gerald Choa Neuroscience Institute, Margaret K.L. Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Shatin, Hong Kong
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Yuan Cai
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Rufus Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Centre for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
- Department of Neurology, University College Hospital, Ibadan, Nigeria
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hilde van den Brink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Christopher Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Chin Wai Cheung
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - King Ngai Chow
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Henry Kwun Hang Chung
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Marco Duering
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Medical Image Analysis Center (MIAC), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Siu Ting Fu
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Deborah Gustafson
- Section for NeuroEpidemiology, Department of Neurology, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Saima Hilal
- Memory Aging and Cognition Centre, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Memory, Aging and Cognition Center, National University Health System, Singapore
- Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore
| | - Vincent Ming Ho Hui
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Gerald Choa Neuroscience Institute, Margaret K.L. Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Rajesh Kalaria
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - SangYun Kim
- Clinical Neuroscience Center, Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, South Korea
| | - Maggie Li Man Lam
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Frank Erik de Leeuw
- Donders Institute for Brain Cognition and Behaviour, Department of Neurology, Radboudumc, Nijmegen, The Netherlands
| | - Ami Sin Man Li
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Gerald Choa Neuroscience Institute, Margaret K.L. Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Hugh Stephen Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Anna Marseglia
- Division of Clinical Geriatrics, Centre for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Huijing Zheng
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Gerald Choa Neuroscience Institute, Margaret K.L. Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - John O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Leonardo Pantoni
- Stroke and Dementia Lab, Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Perminder Singh Sachdev
- School of Psychiatry, Neuropsychiatric Institute, The University of New South Wales, Sydney, NSW, Australia
| | - Eric E Smith
- Division of Neurology, Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, Edinburgh Imaging and UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Vincent Chung Tong Mok
- Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
- Gerald Choa Neuroscience Institute, Margaret K.L. Cheung Research Centre for Management of Parkinsonism, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, Shatin, Hong Kong
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Li Y, Wang M, Cong L, Hou T, Song L, Wang X, Shi L, Dekhtyar S, Wang Y, Du Y, Qiu C. Lifelong Cognitive Reserve, Imaging Markers of Brain Aging, and Cognitive Function in Dementia-Free Rural Older Adults: A Population-Based Study. J Alzheimers Dis 2023; 92:261-272. [PMID: 36710675 PMCID: PMC10041437 DOI: 10.3233/jad-220864] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/28/2022] [Indexed: 01/28/2023]
Abstract
BACKGROUND Cognitive reserve (CR) partly explains cognitive variability in the presence of pathological brain aging. OBJECTIVE We investigated the interplay of lifelong CR with age, sex, and brain aging markers in cognitive phenotypes among older adults with very limited education. METHODS This population-based cross-sectional study included 179 dementia-free participants (age ≥65 years; 39.7% women; 67.0% had no or elementary education) examined in 2014-2016. We assessed lacunes and volumes of hippocampus, ventricles, grey matter, white matter (WM), and white matter hyperintensities. Lifelong CR score was generated from six lifespan intellectual factors (e.g., education and social support). We used Mini-Mental State Examination (MMSE) score to assess cognition and Petersen's criteria to define mild cognitive impairment (MCI). Data were analyzed using general linear and logistic models. RESULTS The association of higher lifelong CR score (range: -4.0-5.0) with higher MMSE score was stronger in women (multivariable-adjusted β-coefficient and 95% CI: 1.75;0.99-2.51) than in men (0.68;0.33-1.03) (pinteraction = 0.006). The association of higher CR with MCI (multivariable-adjusted odds ratio and 95% CI: 0.77;0.60-0.99) did not vary by age or sex. Among participants with low CR (<1.4[median]), greater hippocampal and WM volumes were related to higher MMSE scores with multivariable-adjusted β-coefficients being 1.77(0.41-3.13) and 0.44(0.15-0.74); the corresponding figures in those with high CR were 0.15(-0.76-1.07) and -0.17(-0.41-0.07) (pinteraction <0.01). There was no statistical interaction of CR with MRI markers on MCI. CONCLUSION Greater lifelong CR capacity is associated with better late-life cognition among people with limited education, possibly by compensating for impact of neurodegeneration.
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Affiliation(s)
- Yuanjing Li
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Mingqi Wang
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Lin Song
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Xiang Wang
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, P.R. China
| | - Serhiy Dekhtyar
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P.R. China
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
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Han X, Song L, Li Y, Dong Y, Liu R, Han Q, Wang X, Mao M, Cong L, Tang S, Hou T, Zhang Q, Liu C, Han X, Shi L, Nyberg L, Launer LJ, Wang Y, Du Y, Qiu C. Accelerometer-Measured Sedentary Behavior Patterns, Brain Structure, and Cognitive Function in Dementia-Free Older Adults: A Population-Based Study. J Alzheimers Dis 2023; 96:657-668. [PMID: 37840495 PMCID: PMC10657675 DOI: 10.3233/jad-230575] [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] [Accepted: 08/29/2023] [Indexed: 10/17/2023]
Abstract
BACKGROUND Sedentary behavior is associated with cognitive impairment, but the neuropathological mechanisms underlying their associations are poorly understood. OBJECTIVE To investigate the associations of accelerometer-measured sedentary behavior patterns with brain structure and cognition, and further to explore the potential mechanisms. METHODS This community-based study included 2,019 older adults (age≥60 years, 59% women) without dementia derived from participants in the baseline examination of MIND-China (2018-2020). We assessed sedentary parameters using an accelerometer and cognitive function using a neuropsychological test battery. Structural brain markers were assessed on the structural brain MRI scans in a subsample (n = 1,009). Data were analyzed using the general linear, isotemporal substitution, and mediation models. RESULTS In the total sample (n = 2,019), adjusting for multiple covariates and moderate-to-vigorous-intensity physical activity, longer mean sedentary bout duration was linearly related with lower z-scores of global cognition, verbal fluency, and memory (ptrend < 0.05), whereas greater total sedentary time was linearly associated with lower z-scores of global cognition, verbal fluency, and memory only among individuals with long sedentary time (>10 h/day) (ptrend < 0.05); Breaking up sedentary time with same amount of light-intensity physical activity was significantly associated with higher verbal fluency and memory z-scores (p < 0.05). In the MRI subsample (n = 1,009), separately entering structural brain MRI markers into the mediation models substantially attenuated the associations of mean sedentary bout duration with global cognition, verbal fluency, and memory z-scores. CONCLUSION Prolonged uninterrupted sedentary time is associated with poor global cognition, memory, and verbal fluency among rural older adults, and structural brain markers could partially mediate the association.
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Affiliation(s)
- Xiaolei Han
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Lin Song
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Yuanjing Li
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Yi Dong
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Rui Liu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Qi Han
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Xiaojie Wang
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Ming Mao
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Shi Tang
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Qinghua Zhang
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Cuicui Liu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Xiaodong Han
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Lin Shi
- BrainNow Research Institute, Shenzhen, Guangdong, China
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Lars Nyberg
- Department of Radiation Sciences, Radiology, Umeå University, Umeå, Sweden
| | - Lenore J. Launer
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
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Lin Y, Peng X, Lin X, Deng X, Liu F, Tao H, Dong R, Wang B, Bi Y. Potential Value of Serum Lipid in the Identication of Postoperative Delirium Undergoing Knee/Hip Arthroplasty: The Perioperative Neurocognitive Disorder and Biomarker Lifestyle Study. Front Psychiatry 2022; 13:870317. [PMID: 35492710 PMCID: PMC9039337 DOI: 10.3389/fpsyt.2022.870317] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 03/18/2022] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE We aimed to investigate the relationship between preoperative lipid level and postoperative delirium (POD) and explore whether lipid's effect on POD is mediated by POD core protein. METHODS A total of 635 patients who were planned to undergo knee/hip arthroplasty under combined spinal-epidural anesthesia, regardless of gender, were selected. The patients were aged 40-90 years with American Society of Anesthesiologists physical status I II. The Mini-Mental State Examination (MMSE) was completed 1 day before the operation. Five milliliter elbow venous blood was taken from the patients before anesthesia, and serum levels of total cholesterol (TG), triglyceride (TC), low-density lipoprotein (LDL-C), and high-density lipoprotein (HDL-C) were detected. Cerebrospinal fluid (CSF) was extracted after successful spinal-epidural combined puncture, and amyloid beta40 (Aβ40), amyloid beta42 (Aβ42), total Tau (t-Tau), and phosphorylated Tau (p-Tau) in the CSF were measured by enzyme-linked immunosorbent assays (ELISA). After the operation, the occurrence and severity of POD were assessed using the Confusion Assessment Method and the Memorial Delirium Assessment Scale (MDAS), respectively. Patients were categorized into POD group and NPOD group. Logistic regression was used to analyze the relationship between POD and TC, TG, LDL-C, and HDL-C, and the mediating effect was used to analyze the role of POD core proteins in the relationship between lipid and MDAS. We used the receiver operating characteristic (ROC) and the precision-recall curve (PRC) analysis to assess the ability of TC, TG, LDL-C, and HDL-C ability to predict POD. Finally, we performed a sensitivity analysis to assess the stability of the results. RESULTS A total of 562 patients were finally enrolled in this study, and 66 patients developed POD, with an incidence of 11.7%. Logistic regression analysis showed that high concentration of TC (OR = 3.148, 95%CI 1.858∼5.333, P < 0.001), TG (OR = 2.483, 95%CI 1.573∼3.918, P < 0.001), and LDL-C (OR = 2.469, 95%CI 1.310∼4.656, P = 0.005) in serum were risk factors for POD. A high concentration of HDL-C (OR = 0.258, 95%CI 0.112∼0.594, P = 0.001) was a protective factor for POD after adjusted for age, sex, education, and MMSE score. ROC curves showed that HDL-C have the highest sensitivity and specificity in predicting POD. For these four lipid markers, the PRC range from 0.602 to 0.731, respectively. The mediating analysis showed that POD core proteins could partially mediate the relationship between lipid and POD (effect value: 16.19∼91.04%). The results were barely changed in the sensitivity analysis, and the sensitivity analysis has shown that the results were stable. CONCLUSION The increase of serum TG, TC, and LDL-C concentration is a risk factor for POD development, while high HDL-C concentration is a protective factor for POD, and the occurrence of POD is caused by hyperlipidemia may be caused by POD core proteins. CLINICAL TRIAL REGISTRATION [www.ClinicalTrials.gov], identifier [Chictr200033439].
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Affiliation(s)
- Yanan Lin
- Department of Anesthesiology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Xiaoyan Peng
- Department of Anesthesiology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Xu Lin
- Department of Anesthesiology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Xiyuan Deng
- Department of Anesthesiology, Dalian Medical University, Dalian, China
| | - Fanghao Liu
- Department of Anesthesiology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - He Tao
- Department of Anesthesiology, Dalian Medical University, Dalian, China
| | - Rui Dong
- Department of Anesthesiology, Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, China
| | - Bin Wang
- Department of Anesthesiology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
| | - Yanlin Bi
- Department of Anesthesiology, Qingdao Municipal Hospital Affiliated to Qingdao University, Qingdao, China
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