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Qing Y, Zheng J, Luo Y, Li S, Liu X, Yang S, Du J, Li Y. The impact of metals on cognitive impairment in the elderly and the mediating role of oxidative stress: A cross-sectional study in Shanghai, China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 286:117152. [PMID: 39383823 DOI: 10.1016/j.ecoenv.2024.117152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 09/24/2024] [Accepted: 10/03/2024] [Indexed: 10/11/2024]
Abstract
Cognitive impairment (CI) is a prodrome of many neurodegenerative diseases with complex and unclear pathogenesis. Metal exposure has been found to be associated with CI, but existing population studies are scarce and have the limitations of single outcome and ignoring mixed exposures. This cross-sectional study was conducted in Shanghai, China, enrolling 836 seniors aged over 60 years to investigate the relationship between combined metal exposure (Lead (Pb), cadmium (Cd), and mercury (Hg)) and CI in the elderly and the mediating effect of oxidative stress. It was found that there were significant differences in urinary Pb, Cd, Hg and blood Pb levels between the CI and normal groups. Urinary Pb and Cd levels were significantly negatively correlated with Montreal Cognitive Assessment (MoCA) score, amyloid β42 (Aβ42), and Aβ42/40, while urinary Cd, Hg and blood Hg were significantly positively correlated with phosphorylated tau protein (P-tau). Weighted quantile sum (WQS) regression indicated that combined metal exposure had a more significant effect on CI than individual exposure. Mediation modeling revealed that plasma superoxide dismutase (SOD) was involved in the effects of urinary Cd on Aβ42/40 and P-tau, with mediation effects accounting for 20 % of the total effect. This study emphasized the combined exposure to metals, and the results can help to properly understand the association between mixed metals exposure and CI in the elderly, as well as provide population data and theoretical basis for identifying early environmental risk factors and discovering potential mechanisms of CI.
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Affiliation(s)
- Ying Qing
- Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201300, China; Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | | | - Yingyi Luo
- Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Shichun Li
- Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Xiufen Liu
- Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Shuyu Yang
- Nutrilite Health Institute, Shanghai 201203, China
| | - Jun Du
- Nutrilite Health Institute, Shanghai 201203, China.
| | - Yanfei Li
- Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201300, China.
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Xu L, Ren C, Jing C, Wang G, Wei H, Kong M, Ba M. Predicting amyloid-PET and clinical conversion in apolipoprotein E ε3/ε3 non-demented individuals with multidimensional factors. Eur J Neurosci 2024; 60:3742-3758. [PMID: 38698692 DOI: 10.1111/ejn.16376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 04/14/2024] [Accepted: 04/16/2024] [Indexed: 05/05/2024]
Abstract
The apolipoprotein E (APOE) ε4 is a well-established risk factor of amyloid-β (Aβ) in Alzheimer's disease (AD). However, because of the high prevalence of APOE ε3, there may be a large number of people with APOE ε3/ε3 who are non-demented and have Aβ pathology. There are limited studies on assessing Aβ status and clinical conversion in the APOE ε3/ε3 non-demented population. Two hundred and ninety-three non-demented individuals with APOE ε3/ε3 from ADNI database were divided into Aβ-positron emission tomography (Aβ-PET) positivity (+) and Aβ-PET negativity (-) groups using cut-off value of >1.11. Stepwise regression searched for a single or multidimensional clinical variables for predicting Aβ-PET (+), and the receiver operating characteristic curve (ROC) assessed the accuracy of the predictive models. The Cox regression model explored the risk factors associated with clinical conversion to mild cognitive impairment (MCI) or AD. The results showed that the combination of sex, education, ventricle and white matter hyperintensity (WMH) volume can accurately predict Aβ-PET status in cognitively normal (CN), and the combination of everyday cognition study partner total (EcogSPTotal) score, age, plasma p-tau 181 and WMH can accurately predict Aβ-PET status in MCI individuals. EcogSPTotal score were independent predictors of clinical conversion to MCI or AD. The findings may provide a non-invasive and effective tool to improve the efficiency of screening Aβ-PET (+), accelerate and reduce costs of AD trial recruitment in future secondary prevention trials or help to select patients at high risk of disease progression in clinical trials.
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Affiliation(s)
- Lijuan Xu
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Chao Ren
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Chenxi Jing
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Gang Wang
- School of Ulsan Ship and Ocean College, Ludong University, Yantai, China
| | - Hongchun Wei
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
| | - Min Kong
- Department of Neurology, Yantaishan Hospital, Yantai City, Shandong, China
| | - Maowen Ba
- Department of Neurology, the Affiliated Yantai Yuhuangding Hospital of Qingdao University, Shandong, China
- Yantai Regional Sub Center of National Center for Clinical Medical Research of Neurological Diseases, Shandong, China
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Ruan Y, Zheng D, Guo W, Cao X, Qi W, Yuan Q, Zhang X, Liang X, Zhang D, Xue C, Xiao C. Shared and Specific Changes of Cortico-Striatal Functional Connectivity in Stable Mild Cognitive Impairment and Progressive Mild Cognitive Impairment. J Alzheimers Dis 2024; 98:1301-1317. [PMID: 38517789 DOI: 10.3233/jad-231174] [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] [Indexed: 03/24/2024]
Abstract
Background Mild cognitive impairment (MCI), the prodromal stage of Alzheimer's disease, has two distinct subtypes: stable MCI (sMCI) and progressive MCI (pMCI). Early identification of the two subtypes has important clinical significance. Objective We aimed to compare the cortico-striatal functional connectivity (FC) differences between the two subtypes of MCI and enhance the accuracy of differential diagnosis between sMCI and pMCI. Methods We collected resting-state fMRI data from 31 pMCI patients, 41 sMCI patients, and 81 healthy controls. We chose six pairs of seed regions, including the ventral striatum inferior, ventral striatum superior, dorsal-caudal putamen, dorsal-rostral putamen, dorsal caudate, and ventral-rostral putamen and analyzed the differences in cortico-striatal FC among the three groups, additionally, the relationship between the altered FC within the MCI subtypes and cognitive function was examined. Results Compared to sMCI, the pMCI patients exhibited decreased FC between the left dorsal-rostral putamen and right middle temporal gyrus, the right dorsal caudate and right inferior temporal gyrus, and the left dorsal-rostral putamen and left superior frontal gyrus. Additionally, the altered FC between the right inferior temporal gyrus and right putamen was significantly associated with episodic memory and executive function. Conclusions Our study revealed common and distinct cortico-striatal FC changes in sMCIs and pMCI across different seeds; these changes were associated with cognitive function. These findings can help us understand the underlying pathophysiological mechanisms of MCI and distinguish pMCI and sMCI in the early stage potentially.
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Affiliation(s)
- Yiming Ruan
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Darui Zheng
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wenxuan Guo
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xuan Cao
- Department of Mathematical Sciences, Division of Statistics and Data Science, University of Cincinnati, Cincinnati, OH, USA
| | - Wenzhang Qi
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Qianqian Yuan
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xulian Zhang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xuhong Liang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Da Zhang
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chen Xue
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chaoyong Xiao
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
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Mousa D, Zayed N, Yassine IA. Correlation transfer function analysis as a biomarker for Alzheimer brain plasticity using longitudinal resting-state fMRI data. Sci Rep 2023; 13:21559. [PMID: 38057476 PMCID: PMC10700324 DOI: 10.1038/s41598-023-48693-2] [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: 03/26/2023] [Accepted: 11/29/2023] [Indexed: 12/08/2023] Open
Abstract
Neural plasticity is the ability of the brain to alter itself functionally and structurally as a result of its experience. However, longitudinal changes in functional connectivity of the brain are still unrevealed in Alzheimer's disease (AD). This study aims to discover the significant connections (SCs) between brain regions for AD stages longitudinally using correlation transfer function (CorrTF) as a new biomarker for the disease progression. The dataset consists of: 29 normal controls (NC), and 23, 24, and 23 for early, late mild cognitive impairments (EMCI, LMCI), and ADs, respectively, along three distant visits. The brain was divided into 116 regions using the automated anatomical labeling atlas, where the intensity time series is calculated, and the CorrTF connections are extracted for each region. Finally, the standard t-test and ANOVA test were employed to investigate the SCs for each subject's visit. No SCs, along three visits, were found For NC subjects. The most SCs were mainly directed from cerebellum in case of EMCI and LMCI. Furthermore, the hippocampus connectivity increased in LMCI compared to EMCI whereas missed in AD. Additionally, the patterns of longitudinal changes among the different AD stages compared to Pearson Correlation were similar, for SMC, VC, DMN, and Cereb networks, while differed for EAN and SN networks. Our findings define how brain changes over time, which could help detect functional changes linked to each AD stage and better understand the disease behavior.
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Affiliation(s)
- Doaa Mousa
- Computers and Systems Department, Electronics Research Institute, Cairo, Egypt.
| | - Nourhan Zayed
- Computers and Systems Department, Electronics Research Institute, Cairo, Egypt
- Mechanical Engineering Department, The British University in Egypt, Cairo, Egypt
| | - Inas A Yassine
- Systems and Biomedical Engineering Department, Cairo University, Giza, Egypt
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Deng S, Yi P, Xu M, Yi Q, Feng J. Dysfunctional gene splicing in glucose metabolism may contribute to Alzheimer's disease. Chin Med J (Engl) 2023; 136:666-675. [PMID: 35830275 PMCID: PMC10129079 DOI: 10.1097/cm9.0000000000002214] [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: 12/14/2022] [Indexed: 11/26/2022] Open
Abstract
The glucose metabolism is crucial for sustained brain activity as it provides energy and is a carbon source for multiple biomacromolecules; glucose metabolism decreases dramatically in Alzheimer's disease (AD) and may be a fundamental cause for its development. Recent studies reveal that the alternative splicing events of certain genes effectively regulate several processes in glucose metabolism including insulin receptor, insulin-degrading enzyme, pyruvate kinase M, receptor for advanced glycation endproducts, and others, thereby, influencing glucose uptake, glycolysis, and advanced glycation end-products-mediated signaling pathways. Indeed, the discovery of aberrant alternative splicing that changes the proteomic diversity and protein activity in glucose metabolism has been pivotal in our understanding of AD development. In this review, we summarize the alternative splicing events of the glucose metabolism-related genes in AD pathology and highlight the crucial regulatory roles of splicing factors in the alternative splicing process. We also discuss the emerging therapeutic approaches for targeting splicing factors for AD treatment.
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Affiliation(s)
- Shengfeng Deng
- Laboratory of Anesthesiology, Department of Anesthesiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China
| | - Peng Yi
- Laboratory of Anesthesiology, Department of Anesthesiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China
| | - Mingliang Xu
- Laboratory of Anesthesiology, Department of Anesthesiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China
| | - Qian Yi
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan 646000, China
| | - Jianguo Feng
- Laboratory of Anesthesiology, Department of Anesthesiology, the Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, China
- Affiliated Xinhui Hospital, Southern Medical University (People's Hospital of Xinhui District), Jiangmen, Guangdong 529100, China
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OUP accepted manuscript. Arch Clin Neuropsychol 2022; 37:1502-1514. [DOI: 10.1093/arclin/acac018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
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Corrigendum: Amyloid and tau positive mild cognitive impairment: clinical and biomarker characteristics of dementia progression. Chin Med J (Engl) 2021; 134:2139. [PMID: 34517384 PMCID: PMC8439988 DOI: 10.1097/cm9.0000000000001765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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