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Xu J, Tan S, Wen J, Zhang M, Xu X. Progression of hippocampal subfield atrophy and asymmetry in Alzheimer's disease. Eur J Neurosci 2024; 60:6091-6106. [PMID: 39308012 DOI: 10.1111/ejn.16543] [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: 04/06/2024] [Revised: 07/25/2024] [Accepted: 08/29/2024] [Indexed: 10/17/2024]
Abstract
Alzheimer's disease (AD) affects the hippocampus during its progression, but the specific observable changes of hippocampal subfields during disease progression remain poorly understood. In this study, we employed an event-based model (EBM) to determine the sequence of occurrence of hippocampal subfield atrophy in mild cognitive impairment (MCI) and AD cohorts. Subjects (207) were included: 86 MCI, 53 AD, and 68 healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent structural magnetic resonance imaging (MRI) scans to analyse the hippocampal subfields. We assigned each patient to a specific EBM stage, based on the number of their abnormal subfields. A combination of 2-year follow-up MRI scans were applied to demonstrate the longitudinal consistency and utility of the model's staging system. The model estimated that the earliest atrophy occurs in the hippocampal fissure, then spreading to other subregions in both MCI and AD. We identified a marked divergence between the sequences of left and right hippocampal subfields atrophy, so inter-hemispheric asymmetry pattern was further analysed. The sequence of asymmetry index (AI) increases beginning in the molecular and granule cell layers of the dentate gyrus (GC-ML-DG), cornus ammonis (CA) 4, and the molecular layer (ML). Longitudinal analysis confirms the efficacy of the model. In addition, the model stages were significantly correlated with patients' memory scores (p < .05). Collectively, we used a data-driven method to provide new insight into AD hippocampal progression. The present model could aid in understanding of the disease stages, as well as tracking memory decline.
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Affiliation(s)
- Jingjing Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine. No.88 Jiefang Road, Hangzhou, China
| | - Sijia Tan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine. No.88 Jiefang Road, Hangzhou, China
| | - Jiaqi Wen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine. No.88 Jiefang Road, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine. No.88 Jiefang Road, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine. No.88 Jiefang Road, Hangzhou, China
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2
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Wu Y, Gao M, Lv L, Yan Y, Gao L, Geng Z, Zhou S, Zhu W, Yu Y, Tian Y, Ji G, Hu P, Wu X, Wang K. Brain functional specialization and cooperation in Alzheimer's disease. Brain Behav 2024; 14:e3550. [PMID: 38841739 PMCID: PMC11154812 DOI: 10.1002/brb3.3550] [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: 11/27/2023] [Revised: 04/10/2024] [Accepted: 04/13/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Cerebral specialization and interhemispheric cooperation are two vital features of the human brain. Their dysfunction may be associated with disease progression in patients with Alzheimer's disease (AD), which is featured as progressive cognitive degeneration and asymmetric neuropathology. OBJECTIVE This study aimed to examine and define two inherent properties of hemispheric function in patients with AD by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS Sixty-four clinically diagnosed AD patients and 52 age- and sex-matched cognitively normal subjects were recruited and underwent MRI and clinical evaluation. We calculated and compared brain specialization (autonomy index, AI) and interhemispheric cooperation (connectivity between functionally homotopic voxels, CFH). RESULTS In comparison to healthy controls, patients with AD exhibited enhanced AI in the left middle occipital gyrus. This increase in specialization can be attributed to reduced functional connectivity in the contralateral region, such as the right temporal lobe. The CFH of the bilateral precuneus and prefrontal areas was significantly decreased in AD patients compared to controls. Imaging-cognitive correlation analysis indicated that the CFH of the right prefrontal cortex was marginally positively related to the Montreal Cognitive Assessment score in patients and the Auditory Verbal Learning Test score. Moreover, taking abnormal AI and CFH values as features, support vector machine-based classification achieved good accuracy, sensitivity, specificity, and area under the curve by leave-one-out cross-validation. CONCLUSION This study suggests that individuals with AD have abnormal cerebral specialization and interhemispheric cooperation. This provides new insights for further elucidation of the pathological mechanisms of AD.
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Affiliation(s)
- Yue Wu
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Department of Psychology and Sleep Medicinethe Second Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
| | - Manman Gao
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Lingling Lv
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Yibing Yan
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Liying Gao
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Zhi Geng
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Shanshan Zhou
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
| | - Wanqiu Zhu
- Department of Radiologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
| | - Yongqiang Yu
- Department of Radiologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
| | - Yanghua Tian
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
- Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefeiAnhui ProvinceChina
- The School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhui ProvinceChina
| | - Gong‐Jun Ji
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
- The School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhui ProvinceChina
| | - Panpan Hu
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
| | - Xingqi Wu
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
| | - Kai Wang
- Department of Neurologythe First Affiliated Hospital of Anhui Medical UniversityHefeiAnhui ProvinceChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiAnhui ProvinceChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiAnhui ProvinceChina
- Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefeiAnhui ProvinceChina
- The School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhui ProvinceChina
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Kwon MJ, Lee S, Park J, Jo S, Han JW, Oh DJ, Lee JY, Park JH, Kim JH, Kim KW. Textural and Volumetric Changes of the Temporal Lobes in Semantic Variant Primary Progressive Aphasia and Alzheimer's Disease. J Korean Med Sci 2023; 38:e316. [PMID: 37873627 PMCID: PMC10593601 DOI: 10.3346/jkms.2023.38.e316] [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: 04/07/2023] [Accepted: 06/15/2023] [Indexed: 10/25/2023] Open
Abstract
BACKGROUND Texture analysis may capture subtle changes in the gray matter more sensitively than volumetric analysis. We aimed to investigate the patterns of neurodegeneration in semantic variant primary progressive aphasia (svPPA) and Alzheimer's disease (AD) by comparing the temporal gray matter texture and volume between cognitively normal controls and older adults with svPPA and AD. METHODS We enrolled all participants from three university hospitals in Korea. We obtained T1-weighted magnetic resonance images and compared the gray matter texture and volume of regions of interest (ROIs) between the groups using analysis of variance with Bonferroni posthoc comparisons. We also developed models for classifying svPPA, AD and control groups using logistic regression analyses, and validated the models using receiver operator characteristics analysis. RESULTS Compared to the AD group, the svPPA group showed lower volumes in five ROIs (bilateral temporal poles, and the left inferior, middle, and superior temporal cortices) and higher texture in these five ROIs and two additional ROIs (right inferior temporal and left entorhinal cortices). The performances of both texture- and volume-based models were good and comparable in classifying svPPA from normal cognition (mean area under the curve [AUC] = 0.914 for texture; mean AUC = 0.894 for volume). However, only the texture-based model achieved a good level of performance in classifying svPPA and AD (mean AUC = 0.775 for texture; mean AUC = 0.658 for volume). CONCLUSION Texture may be a useful neuroimaging marker for early detection of svPPA in older adults and its differentiation from AD.
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Affiliation(s)
- Min Jeong Kwon
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Korea
| | - Subin Lee
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Korea
| | - Jieun Park
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Korea
| | - Sungman Jo
- Department of Health Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
| | - Dae Jong Oh
- Workplace Mental Health Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jun-Young Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea
- Department of Neuropsychiatry, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea
| | - Joon Hyuk Park
- Department of Neuropsychiatry, Jeju National University Hospital, Jeju, Korea
| | - Jae Hyoung Kim
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Ki Woong Kim
- Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, Korea
- Department of Health Science and Technology, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea.
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Ramezani N, Davanian F, Naghavi S, Riahi R, Zandieh G, Danesh-Mobarhan S, Ashtari F, Shaygannejad V, Sanayei M, Adibi I. Thalamic asymmetry in Multiple Sclerosis. Mult Scler Relat Disord 2023; 77:104853. [PMID: 37473593 DOI: 10.1016/j.msard.2023.104853] [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: 04/04/2023] [Revised: 06/09/2023] [Accepted: 06/22/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND Multiple Sclerosis (MS) is a chronic neuroinflammatory disease that affects the central nervous system. Asymmetry is one of the finding in brain MRI of these patients, which is related to the debilitating symptoms of the disease. This study aimed to investigate and compare the thalamic asymmetry in MS patients and its relationship with other MRI and clinical findings of these patients. METHODS This cross-sectional study conducted on 83 patients with relapse-remitting MS (RRMS), 43 patients with secondary progressive MS (SPMS), and 89 healthy controls. The volumes of total intracranial, total gray matter, total white matter, lesions, thalamus, and also the thalamic asymmetry indices were calculated. The 9-hole peg test (9-HPT) and Expanded Disability Status Scale (EDSS) were assessed as clinical findings. RESULTS We showed that the normalized whole thalamic volume in healthy subjects was higher than MS patients (both RRMS and SPMS). Thalamic asymmetry index (TAI) was significantly different between RRMS patients and SPMS patients (p = 0.011). The absolute value of TAI was significantly lower in healthy subjects than in RRMS (p < 0.001) and SPMS patients (p < 0.001), and SPMS patients had a higher absolute TAI compared to RRMS patients (p = 0.037). CONCLUSIONS In this cross-sectional study we showed a relationship between normalized whole thalamic volume and MS subtype. Also, we showed that the asymmetric indices of the thalamus can be related to the progression of the disease. Eventually, we showed that thalamic asymmetry can be related to the disease progression and subtype changes in MS.
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Affiliation(s)
- Neda Ramezani
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Center for Translational Neuroscience, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Fariba Davanian
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Center for Translational Neuroscience, Isfahan University of Medical Sciences, Isfahan, Iran; Paramedical School, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Saba Naghavi
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Roya Riahi
- Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Ghazal Zandieh
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Safieh Danesh-Mobarhan
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Center for Translational Neuroscience, Isfahan University of Medical Sciences, Isfahan, Iran; Paramedical School, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Fereshteh Ashtari
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Vahid Shaygannejad
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehdi Sanayei
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Center for Translational Neuroscience, Isfahan University of Medical Sciences, Isfahan, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
| | - Iman Adibi
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran; Center for Translational Neuroscience, Isfahan University of Medical Sciences, Isfahan, Iran; Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
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Ge X, Zheng M, Hu M, Fang X, Geng D, Liu S, Wang L, Zhang J, Guan L, Zheng P, Xie Y, Pan W, Zhou M, Zhou L, Tang R, Zheng K, Yu Y, Huang XF. Butyrate ameliorates quinolinic acid-induced cognitive decline in obesity models. J Clin Invest 2023; 133:154612. [PMID: 36787221 PMCID: PMC9927952 DOI: 10.1172/jci154612] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 12/20/2022] [Indexed: 02/15/2023] Open
Abstract
Obesity is a risk factor for neurodegenerative disease associated with cognitive dysfunction, including Alzheimer's disease. Low-grade inflammation is common in obesity, but the mechanism between inflammation and cognitive impairment in obesity is unclear. Accumulative evidence shows that quinolinic acid (QA), a neuroinflammatory neurotoxin, is involved in the pathogenesis of neurodegenerative processes. We investigated the role of QA in obesity-induced cognitive impairment and the beneficial effect of butyrate in counteracting impairments of cognition, neural morphology, and signaling. We show that in human obesity, there was a negative relationship between serum QA levels and cognitive function and decreased cortical gray matter. Diet-induced obese mice had increased QA levels in the cortex associated with cognitive impairment. At single-cell resolution, we confirmed that QA impaired neurons, altered the dendritic spine's intracellular signal, and reduced brain-derived neurotrophic factor (BDNF) levels. Using Caenorhabditis elegans models, QA induced dopaminergic and glutamatergic neuron lesions. Importantly, the gut microbiota metabolite butyrate was able to counteract those alterations, including cognitive impairment, neuronal spine loss, and BDNF reduction in both in vivo and in vitro studies. Finally, we show that butyrate prevented QA-induced BDNF reductions by epigenetic enhancement of H3K18ac at BDNF promoters. These findings suggest that increased QA is associated with cognitive decline in obesity and that butyrate alleviates neurodegeneration.
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Affiliation(s)
- Xing Ge
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Mingxuan Zheng
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Minmin Hu
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Xiaoli Fang
- Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Jiangsu, China
| | - Deqin Geng
- Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Jiangsu, China
| | - Sha Liu
- Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Jiangsu, China
| | - Li Wang
- Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China
| | - Jun Zhang
- Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China
| | - Li Guan
- The Second Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China
| | - Peng Zheng
- Illawarra Health and Medical Research Institute (IHMRI) and School of Medical, Indigenous, and Health, University of Wollongong, New South Wales, Australia
| | - Yuanyi Xie
- Illawarra Health and Medical Research Institute (IHMRI) and School of Medical, Indigenous, and Health, University of Wollongong, New South Wales, Australia
| | - Wei Pan
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Menglu Zhou
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Limian Zhou
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Renxian Tang
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Kuiyang Zheng
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Yinghua Yu
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China
| | - Xu-Feng Huang
- Jiangsu Key Laboratory of Immunity and Metabolism, Jiangsu International Laboratory of Immunity and Metabolism, Department of Pathogen Biology and Immunology, Xuzhou Medical University, Jiangsu, China.,Illawarra Health and Medical Research Institute (IHMRI) and School of Medical, Indigenous, and Health, University of Wollongong, New South Wales, Australia
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6
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Atrophy asymmetry in hippocampal subfields in patients with Alzheimer's disease and mild cognitive impairment. Exp Brain Res 2023; 241:495-504. [PMID: 36593344 DOI: 10.1007/s00221-022-06543-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/29/2022] [Indexed: 01/03/2023]
Abstract
Volumetric analysis of hippocampal subfields and their asymmetry assessment recently has been useful biomarkers in neuroscience. In this study, hippocampal subfields atrophy and pattern of their asymmetry in the patient with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were evaluated. MRI images of 20 AD patients, 20 MCI patients, and 20 healthy control (HC) were selected. The volumes of hippocampal subfields were extracted automatically using Freesurfer toolkit. The subfields asymmetry index (AI) and laterality ([Formula: see text]) were also evaluated. Analysis of covariance was used to compare the subfields volume between three patient groups (age and gender as covariates). We used ANOVA (P < 0.05) test for multiple comparisons with Bonferroni's post hoc correction method. Hippocampal subfields volume in AD patients were significantly lower than HC and MCI groups (P < 0.02); however, no significant difference was observed between MCI and HC groups. The asymmetry index (AI) in some subfields was significantly different between AD and MCI, as well as between AD and HC, while there was not any significant difference between MCI groups with HC. In all three patient groups, rightward laterality ([Formula: see text]) was seen in several subfields except subiculum, presubiculum, and parasubiculum, while in AD patient, rightward lateralization slightly decrease. Hippocampal subfields asymmetry can be used as a quantitative biomarker in neurocognitive disorders. In this study, it was observed that the asymmetry index of some subfields in AD is significantly different from MCI. In AD, patient rightward laterality was less MCI an HC group.
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Geng B, Gao M, Wu J, Yang G, Liu C, Piao R, Zhang S, Xu K, Yuan J, Liu P. Smaller volume and altered functional connectivity of the amygdala in patients with lifelong premature ejaculation. Eur Radiol 2021; 31:8429-8437. [PMID: 33928418 DOI: 10.1007/s00330-021-08002-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 04/04/2021] [Accepted: 04/19/2021] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To analyze the abnormal amygdala structure and function in lifelong premature ejaculation (PE) patients compared with healthy controls (HCs). METHODS Forty-four lifelong PE patients and thirty-one HCs were enrolled in this study. Each subject was diagnosed with PE using a Premature Ejaculation Diagnostic Tool (PEDT) and intravaginal ejaculation latency time (IELT) score. Based on t-tests and Pearson correlation analysis, the voxel-based morphometry and functional connectivity (FC) analyses were applied to evaluate brain structural and functional changes by using T1-weighted and resting-state functional magnetic resonance imaging scans. RESULTS Lifelong PE patients had decreased gray matter volume in the bilateral amygdala and increased FC between the amygdala and precuneus, posterior cingulate cortex (PCC), and middle temporal cortex (MTC), as well as decreased FC between the amygdala and precentral gyrus, insula, and inferior frontal gyrus. Moreover, significantly negative correlations between the IELT score and the mean z-score from amygdala-MTC (r = -0.49) and amygdala-PCC (r = -0.48) FC were found in lifelong PE patients. CONCLUSIONS Our study investigated the abnormal amygdala-related structure and connectivity patterns in PE patients, which might provide novel perspective for understanding the crucial role of the amygdala in the neural mechanism of PE. KEY POINTS • As one of the most common diseases in men, PE may be related to abnormal brain mechanisms. • Functional and structural magnetic resonance imaging used to explore amygdala abnormalities in PE patients. • The correlation between clinical scores and functional connectivity was used to assess the reasonability of the results.
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Affiliation(s)
- Bowen Geng
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Ming Gao
- Xi'An DaXing Hospital of Shaanxi University of Chinese Medicine, Xi'an, China.,Assisted Reproduction Center, Northwest Women and Children Hospital Affiliated to Xi'an JiaoTong University, Xi'an, China
| | - Jiayu Wu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Guang Yang
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Chengxiang Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Ruiqing Piao
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Shuming Zhang
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Ke Xu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China.,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Jianlin Yuan
- Department of Urology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Peng Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, China. .,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China.
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