1
|
Han T, Peng Y, Du Y, Li Y, Wang Y, Sun W, Cui L, Peng Q. Mining Alzheimer's disease clinical data: reducing effects of natural aging for predicting progression and identifying subtypes. Front Neurosci 2024; 18:1388391. [PMID: 39206114 PMCID: PMC11351280 DOI: 10.3389/fnins.2024.1388391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 07/26/2024] [Indexed: 09/04/2024] Open
Abstract
Introduction Because Alzheimer's disease (AD) has significant heterogeneity in encephalatrophy and clinical manifestations, AD research faces two critical challenges: eliminating the impact of natural aging and extracting valuable clinical data for patients with AD. Methods This study attempted to address these challenges by developing a novel machine-learning model called tensorized contrastive principal component analysis (T-cPCA). The objectives of this study were to predict AD progression and identify clinical subtypes while minimizing the influence of natural aging. Results We leveraged a clinical variable space of 872 features, including almost all AD clinical examinations, which is the most comprehensive AD feature description in current research. T-cPCA yielded the highest accuracy in predicting AD progression by effectively minimizing the confounding effects of natural aging. Discussion The representative features and pathogenic circuits of the four primary AD clinical subtypes were discovered. Confirmed by clinical doctors in Tangdu Hospital, the plaques (18F-AV45) distribution of typical patients in the four clinical subtypes are consistent with representative brain regions found in four AD subtypes, which further offers novel insights into the underlying mechanisms of AD pathogenesis.
Collapse
Affiliation(s)
- Tian Han
- Systems Engineering Institute, School of Automation, Xi’an Jiaotong University, Xi’an, China
| | - Yunhua Peng
- Center for Mitochondrial Biology and Medicine, School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, China
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Xi’an Jiaotong University, Xi’an, China
| | - Ying Du
- Department of Neurology, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - Yunbo Li
- Department of Nuclear Medicine, Tangdu Hospital, Fourth Military Medical University, Xi’an, China
| | - Ying Wang
- Systems Engineering Institute, School of Automation, Xi’an Jiaotong University, Xi’an, China
| | - Wentong Sun
- Systems Engineering Institute, School of Automation, Xi’an Jiaotong University, Xi’an, China
| | - Lanxin Cui
- Systems Engineering Institute, School of Automation, Xi’an Jiaotong University, Xi’an, China
| | - Qinke Peng
- Systems Engineering Institute, School of Automation, Xi’an Jiaotong University, Xi’an, China
- School of Future Technology, Xi’an Jiaotong University, Xi’an, China
| |
Collapse
|
2
|
Heng JG, Zhang J, Bonetti L, Lim WPH, Vuust P, Agres K, Chen SHA. Understanding music and aging through the lens of Bayesian inference. Neurosci Biobehav Rev 2024; 163:105768. [PMID: 38908730 DOI: 10.1016/j.neubiorev.2024.105768] [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: 01/09/2024] [Revised: 06/05/2024] [Accepted: 06/10/2024] [Indexed: 06/24/2024]
Abstract
Bayesian inference has recently gained momentum in explaining music perception and aging. A fundamental mechanism underlying Bayesian inference is the notion of prediction. This framework could explain how predictions pertaining to musical (melodic, rhythmic, harmonic) structures engender action, emotion, and learning, expanding related concepts of music research, such as musical expectancies, groove, pleasure, and tension. Moreover, a Bayesian perspective of music perception may shed new insights on the beneficial effects of music in aging. Aging could be framed as an optimization process of Bayesian inference. As predictive inferences refine over time, the reliance on consolidated priors increases, while the updating of prior models through Bayesian inference attenuates. This may affect the ability of older adults to estimate uncertainties in their environment, limiting their cognitive and behavioral repertoire. With Bayesian inference as an overarching framework, this review synthesizes the literature on predictive inferences in music and aging, and details how music could be a promising tool in preventive and rehabilitative interventions for older adults through the lens of Bayesian inference.
Collapse
Affiliation(s)
- Jiamin Gladys Heng
- School of Computer Science and Engineering, Nanyang Technological University, Singapore.
| | - Jiayi Zhang
- Interdisciplinary Graduate Program, Nanyang Technological University, Singapore; School of Social Sciences, Nanyang Technological University, Singapore; Centre for Research and Development in Learning, Nanyang Technological University, Singapore
| | - Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus, Aalborg, Denmark; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom; Department of Psychology, University of Bologna, Italy
| | | | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus, Aalborg, Denmark
| | - Kat Agres
- Centre for Music and Health, National University of Singapore, Singapore; Yong Siew Toh Conservatory of Music, National University of Singapore, Singapore
| | - Shen-Hsing Annabel Chen
- School of Social Sciences, Nanyang Technological University, Singapore; Centre for Research and Development in Learning, Nanyang Technological University, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; National Institute of Education, Nanyang Technological University, Singapore.
| |
Collapse
|
3
|
Dai M, Guo Z, Xia H, Zhu H, Li J, Hou H, Zhao G, Liu X. Predicting the efficacy of donepezil intervention in Alzheimer's disease patients using regional homogeneity in the inferior orbitofrontal cortex. Aging Clin Exp Res 2024; 36:94. [PMID: 38630202 PMCID: PMC11024046 DOI: 10.1007/s40520-023-02691-6] [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: 04/22/2023] [Accepted: 12/29/2023] [Indexed: 04/19/2024]
Abstract
BACKGROUND Although donepezil is a commonly used drug for treating Alzheimer's disease (AD), the mechanisms by which it affects patients' functional brain activity, and thus modulates clinical symptoms, remain unclear. METHODS In the present study, we used resting-state functional magnetic resonance imaging (MRI) and regional homogeneity (ReHo) to investigate the effects of donepezil on local brain activity in AD patients. Resting-state functional MRI data were collected from 32 subjects: 16 healthy controls and 16 AD patients. All 16 AD patients underwent 6 months of donepezil treatment and received two MRI scans (pre- and post-intervention). Analysis of covariance and post hoc analyses were used to compare ReHo differences among the healthy controls, pre-intervention AD patients, and post-intervention AD patients. Pearson correlation analysis was used to examine relationships between ReHo values in differential brain regions and clinical symptoms. RESULTS Compared with healthy controls, post-intervention AD patients had reduced ReHo in the orbital part of the inferior frontal gyrus, and pre-intervention AD patients had reduced ReHo in the orbital part of the right inferior frontal gyrus. Pattern recognition models revealed that pre-intervention ReHo values in abnormal brain regions of AD patients were 76% accurate for predicting the efficacy of donepezil on cognitive function and 65% accurate for predicting its efficacy on depressive symptoms. CONCLUSIONS These findings deepen our understanding of the brain mechanisms underlying the clinical efficacy of donepezil in AD patients, and provide a novel way to predict its clinical efficacy in such patients.
Collapse
Affiliation(s)
- Min Dai
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, 109 Xueyuan North Road, Wenzhou, 325027, Zhejiang, China
| | - Zhongwei Guo
- Tongde Hospital of Zhejiang Province, 234 Gucui Road, Hangzhou, 310012, Zhejiang, China
| | - Honglian Xia
- Tongde Hospital of Zhejiang Province, 234 Gucui Road, Hangzhou, 310012, Zhejiang, China
| | - Hong Zhu
- Tongde Hospital of Zhejiang Province, 234 Gucui Road, Hangzhou, 310012, Zhejiang, China
| | - Jiapeng Li
- Tongde Hospital of Zhejiang Province, 234 Gucui Road, Hangzhou, 310012, Zhejiang, China
| | - Hongtao Hou
- Tongde Hospital of Zhejiang Province, 234 Gucui Road, Hangzhou, 310012, Zhejiang, China
| | - Guizhi Zhao
- Tongde Hospital of Zhejiang Province, 234 Gucui Road, Hangzhou, 310012, Zhejiang, China.
| | - Xiaozheng Liu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, 109 Xueyuan North Road, Wenzhou, 325027, Zhejiang, China.
- Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, China.
| |
Collapse
|
4
|
Takase H, Hamanaka G, Hoshino T, Ohtomo R, Guo S, Mandeville ET, Lo EH, Arai K. Transcriptomic Profiling Reveals Neuroinflammation in the Corpus Callosum of a Transgenic Mouse Model of Alzheimer's Disease. J Alzheimers Dis 2024; 97:1421-1433. [PMID: 38277298 DOI: 10.3233/jad-231049] [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] [Indexed: 01/28/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is a widespread neurodegenerative disorder characterized by progressive cognitive decline, affecting a significant portion of the aging population. While the cerebral cortex and hippocampus have been the primary focus of AD research, accumulating evidence suggests that white matter lesions in the brain, particularly in the corpus callosum, play an important role in the pathogenesis of the disease. OBJECTIVE This study aims to investigate the gene expression changes in the corpus callosum of 5xFAD transgenic mice, a widely used AD mouse model. METHODS We conducted behavioral tests for spatial learning and memory in 5xFAD transgenic mice and performed RNA sequencing analyses on the corpus callosum to examine transcriptomic changes. RESULTS Our results show cognitive decline and demyelination in the corpus callosum of 5xFAD transgenic mice. Transcriptomic analysis reveals a predominance of upregulated genes in AD mice, particularly those associated with immune cells, including microglia. Conversely, downregulation of genes related to chaperone function and clock genes such as Per1, Per2, and Cry1 is also observed. CONCLUSIONS This study suggests that activation of neuroinflammation, disruption of chaperone function, and circadian dysfunction are involved in the pathogenesis of white matter lesions in AD. The findings provide insights into potential therapeutic targets and highlight the importance of addressing white matter pathology and circadian dysfunction in AD treatment strategies.
Collapse
Affiliation(s)
- Hajime Takase
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
- YCU Center for Novel and Exploratory Clinical Trials (Y-NEXT), Yokohama City University Hospital, Yokohama, Japan
- Department of Neurosurgery, Yokohama City University Graduate School of Medicine, Yokohama, Japan
| | - Gen Hamanaka
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Tomonori Hoshino
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Ryo Ohtomo
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Shuzhen Guo
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Emiri T Mandeville
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Eng H Lo
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Ken Arai
- Departments of Radiology and Neurology, Neuroprotection Research Laboratory, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| |
Collapse
|
5
|
Ajare EC, Campbell FC, Mgbe EK, Efekemo AO, Onuh AC, Nnamani AO, Okwunodulu O, Ohaegbulam SC. MRI-based morphometric analysis of corpus callosum dimensions of adults in Southeast Nigeria. Libyan J Med 2023; 18:2188649. [PMID: 36946121 PMCID: PMC10035938 DOI: 10.1080/19932820.2023.2188649] [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: 03/23/2023] Open
Abstract
The Corpus callosum (CC) is the largest commissural fibre tract, ensuring swift information transfer and integration in both cerebral hemispheres. Variations in morphometry exist. There is a paucity of data on CC dimensions in our subregion, and no standardized reference is available. The study aims to determine the CC dimensions among the adult population in southeast Nigeria. The result will provide reference ranges and form a benchmark for comparisons of CC-related pathologies. A retrospective study of CC morphometric dimensions in normal subjects who had cranial MRI over two years in Memfys Hospital, Enugu, Southeast Nigeria, using a 1.5T GE© 16 channel machine. The CC was segmentalized into seven subregions using the modified Witelson method with special computer software. All measurements were taken twice from the T1 mid-sagittal image, and the mean was used for computation. The results were analyzed using descriptive and inferential statistics. A total of 200 subjects were recruited for the study. The mean length and height of the CC were 75.58 ± 4.52 mm and 24.64 ± 3.40 mm, respectively. The width dimensions of the genu, body, rostrum and splenium were 10.88 ± 1.81 mm, 5.66 ± 1.32 mm, 3.65 ± 1.25 mm, and 10.02 ± 1.70 mm, respectively. No gender variations were noted among the different dimensions of CC (P = 0.90). The length and height of CC increase gradually with age and show a positive correlation. The width dimensions of the genu and splenium increase till middle age and subsequently decreases in line with brain atrophy (p = 0.0000& p = 0.004). Using Pearson's correlation test, no correlation was noted in the dimensions of the body and rostrum of the corpus callosum when related to age and sex. (P = 0.92 & p = 0.66). Reference ranges of CC dimensions in our subregion were presented, and variations exist in its different morphometric dimensions which are affected by brain atrophy. Gender does not influence the dimensions in our subpopulations.
Collapse
Affiliation(s)
- Enyereibe Chuks Ajare
- Department of Radiation Medicine, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Enugu, Nigeria
- Department of Radiology, Memfys Hospital, Enugu, Nigeria
| | | | - Emeka K Mgbe
- Department of Radiation Medicine, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Enugu, Nigeria
| | - Aghogho O Efekemo
- Department of Radiology, University of Benin Teaching Hospital, Benin City, Nigeria
| | - Augustine Chukwudi Onuh
- Department of Radiation Medicine, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Enugu, Nigeria
- Department of Radiology, Memfys Hospital, Enugu, Nigeria
| | - A O Nnamani
- Department of Radiation Medicine, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Enugu, Nigeria
| | | | | |
Collapse
|
6
|
Berkins S, Koshy B, Livingstone RS, Jasper A, Grace H, Ravibabu P, Rai E. Morphometric analysis of Corpus Callosum in autistic and typically developing Indian children. Psychiatry Res Neuroimaging 2023; 328:111580. [PMID: 36481591 DOI: 10.1016/j.pscychresns.2022.111580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 10/29/2022] [Accepted: 11/29/2022] [Indexed: 12/02/2022]
Abstract
Corpus callosum (CC) is the largest commissural white matter bundle in the brain, responsible for the integration of information between hemispheres. Reduction in the size of the CC structure has been predominantly reported in children with autism spectrum disorder (ASD) compared to typically developing children (TD). However, most of these studies are based on high-functioning individuals with ASD but not on an inclusive sample of individuals with ASD with varying abilities. Our current study aimed to examine the CC morphometry between children with ASD and TD in the Indian population. We also compared CC morphometry in autistic children with autism severity, verbal IQ (VIQ) and full-scale IQ (FSIQ). T1-weighted structural images were acquired using a 3T MRI scanner to examine the CC measures in 62 ASD and 17 TD children. The length and height of the CC and the width of genu were decreased in children with ASD compared to TD. There was no significant difference in CC measures based on autism severity, VIQ or FSIQ among children with ASD. To our knowledge, this is the first neuroimaging study to include a significant number (n = 56) of low-functioning ASD children. Our findings suggest the atypical interhemispheric connectivity of CC in ASD.
Collapse
Affiliation(s)
- Samuel Berkins
- Department of Developmental Paediatrics, Christian Medical College, Vellore 632004, Tamil Nadu, India
| | - Beena Koshy
- Department of Developmental Paediatrics, Christian Medical College, Vellore 632004, Tamil Nadu, India.
| | - Roshan S Livingstone
- Department of Radiodiagnosis, Christian Medical College and Hospital, Vellore 632004, India
| | - Anitha Jasper
- Department of Radiodiagnosis, Christian Medical College and Hospital, Vellore 632004, India
| | - Hannah Grace
- Department of Developmental Paediatrics, Christian Medical College, Vellore 632004, Tamil Nadu, India
| | - Preethi Ravibabu
- Department of Developmental Paediatrics, Christian Medical College, Vellore 632004, Tamil Nadu, India
| | - Ekta Rai
- Department of Anaesthesia, Christian Medical College and Hospital, Vellore 632004, India
| |
Collapse
|