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Poniah P, Abdul Rashed A, Abdul Jalil J, Ali EZ. Clinical Significance of Early-Onset Alzheimer's Mutations in Asian and Western Populations: A Scoping Review. Genes (Basel) 2025; 16:345. [PMID: 40149496 PMCID: PMC11942072 DOI: 10.3390/genes16030345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2024] [Revised: 01/09/2025] [Accepted: 01/13/2025] [Indexed: 03/29/2025] Open
Abstract
BACKGROUND/OBJECTIVES Background: Early-onset Alzheimer's disease (EOAD) is primarily inherited in an autosomal dominant pattern, with mutations in the APP, PSEN1, and PSEN2 genes being central contributors. Diagnosing Alzheimer's poses challenges due to the coexistence of various co-pathologies, and treatment options remain limited for most patients, apart from familial cases linked to specific genetic mutations. While significant research on Alzheimer's genetics has been conducted in both Asian and Caucasian populations, the specific mutations and their clinical impacts in EOAD are still inadequately explored. This review aims to provide a detailed analysis of commonly reported genetic mutations and associated clinical features in EOAD patients from Asian and Western populations. METHODS Following the PRISMA-ScR guidelines, a systematic database search was conducted for studies published between 2016 and 2023. After screening 491 records, 36 studies from Asian cohorts and 40 from Western cohorts met the inclusion criteria. RESULTS The analysis revealed 127 unique mutations in the Asian population and 190 in the Western population. About 16.7% of Asian and 21.9% of Western studies covered both familial and sporadic AD, with consistent patterns across groups. Some mutations were shared between the populations and displayed similar clinical features, while others were population-specific. CONCLUSIONS These findings underscore the considerable variability in EOAD mutations and phenotypes, emphasizing the importance of genetic testing in younger patients to enhance diagnostic accuracy and guide treatment strategies effectively.
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Affiliation(s)
- Prevathe Poniah
- Inborn Errors of Metabolism and Genetics Unit, Nutrition, Metabolic and Cardiovascular Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, Setia Alam 41700, Selangor, Malaysia; (J.A.J.); (E.Z.A.)
- Clinical Research Centre, Hospital Raja Permaisuri Bainun, Institute for Clinical Research, National Institutes of Health, Ministry of Health Malaysia, Ipoh 30450, Perak, Malaysia
| | - Aswir Abdul Rashed
- Nutrition Unit, Nutrition, Metabolic and Cardiovascular Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, Shah Alam 41700, Selangor, Malaysia;
| | - Julaina Abdul Jalil
- Inborn Errors of Metabolism and Genetics Unit, Nutrition, Metabolic and Cardiovascular Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, Setia Alam 41700, Selangor, Malaysia; (J.A.J.); (E.Z.A.)
| | - Ernie Zuraida Ali
- Inborn Errors of Metabolism and Genetics Unit, Nutrition, Metabolic and Cardiovascular Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health Malaysia, Setia Alam 41700, Selangor, Malaysia; (J.A.J.); (E.Z.A.)
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2
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Grazia A, Dyrba M, Pomara N, Temp AG, Grothe MJ, Teipel SJ. Basal forebrain global functional connectivity is preserved in asymptomatic presenilin-1 E280A mutation carriers: Results from the Colombia cohort. J Prev Alzheimers Dis 2025; 12:100030. [PMID: 39863323 DOI: 10.1016/j.tjpad.2024.100030] [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: 09/26/2024] [Revised: 11/05/2024] [Accepted: 12/02/2024] [Indexed: 01/27/2025]
Abstract
BACKGROUND Imaging studies showed early atrophy of the cholinergic basal forebrain in prodromal sporadic Alzheimer's disease and reduced posterior basal forebrain functional connectivity in amyloid positive individuals with subjective cognitive decline. Similar investigations in familial cases of Alzheimer's disease are still lacking. OBJECTIVES To test whether presenilin-1 E280A mutation carriers have reduced basal forebrain functional connectivity and whether this is linked to amyloid pathology. DESIGN This is a cross-sectional study that analyzes baseline functional imaging data. SETTING We obtained data from the Colombia cohort Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease Trial. PARTICIPANTS We analyzed data from 215 asymptomatic subjects carrying the presenilin-1 E280A mutation [64% female; 147 carriers (M = 35 years), 68 noncarriers (M = 40 years)]. MEASUREMENTS We extracted functional magnetic resonance imaging data using seed-based connectivity analysis to examine the anterior and posterior subdivisions of the basal forebrain. Subsequently, we performed a Bayesian Analysis of Covariance to assess the impact of carrier status on functional connectivity in relation to amyloid positivity. For comparison, we also investigated hippocampus connectivity. RESULTS We found no effect of carrier status on anterior (Bayesian Factor10 = 1.167) and posterior basal forebrain connectivity (Bayesian Factor10 = 0.033). In carriers, we found no association of amyloid positivity with basal forebrain connectivity. CONCLUSIONS We falsified the hypothesis of basal forebrain connectivity reduction in preclinical mutation carriers with amyloid pathology. If replicated, these findings may not only confirm a discrepancy between familial and sporadic Alzheimer's disease, but also suggest new potential targets for future treatments.
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Affiliation(s)
- Alice Grazia
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany.
| | - Martin Dyrba
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Greifswald, Rostock, Germany
| | - Nunzio Pomara
- Geriatric Psychiatry Division of Nathan S, Kline Institute, New York, USA
| | - Anna G Temp
- Neurozentrum, BG Klinikum Hamburg GmbH, Germany
| | - Michel J Grothe
- Reina Sofia Alzheimer's Center, CIEN Foundation, ISCIII, Spain
| | - Stefan J Teipel
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany; Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Greifswald, Rostock, Germany
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3
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Liu Y, Jiang Y, Du W, Gao B, Gao J, Hu S, Song Q, Wang W, Miao Y. White matter microstructure alterations in type 2 diabetes mellitus and its correlation with cerebral small vessel disease and cognitive performance. Sci Rep 2024; 14:270. [PMID: 38167604 PMCID: PMC10762026 DOI: 10.1038/s41598-023-50768-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 12/25/2023] [Indexed: 01/05/2024] Open
Abstract
Microstructural abnormalities of white matter fiber tracts are considered as one of the etiology of diabetes-induced neurological disorders. We explored the cerebral white matter microstructure alteration accurately, and to analyze its correlation between cerebral small vessel disease (CSVD) burden and cognitive performance in type 2 diabetes mellitus (T2DM). The clinical-laboratory data, cognitive scores [including mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), California verbal learning test (CVLT), and symbol digit modalities test (SDMT)], CSVD burden scores of the T2DM group (n = 34) and healthy control (HC) group (n = 21) were collected prospectively. Automatic fiber quantification (AFQ) was applied to generate bundle profiles along primary white matter fiber tracts. Diffusion tensor images (DTI) metrics and 100 nodes of white matter fiber tracts between groups were compared. Multiple regression analysis was used to analyze the relationship between DTI metrics and cognitive scores and CSVD burden scores. For fiber-wise and node-wise, DTI metrics in some commissural and association fibers were increased in T2DM. Some white matter fiber tracts DTI metrics were independent predictors of cognitive scores and CSVD burden scores. White matter fiber tracts damage in patients with T2DM may be characterized in specific location, especially commissural and association fibers. Aberrational specific white matter fiber tracts are associated with visuospatial function and CSVD burden.
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Affiliation(s)
- Yangyingqiu Liu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
- Department of Radiology, Zibo Central Hospital, 54 Gongqingtuan Road, Zhangdian, Zibo, China
| | - Yuhan Jiang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Wei Du
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Bingbing Gao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Jie Gao
- Department of Neurology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Shuai Hu
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Qingwei Song
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China
| | - Weiwei Wang
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China.
| | - Yanwei Miao
- Department of Radiology, First Affiliated Hospital of Dalian Medical University, 222 Zhongshan Road, Xigang, Dalian, China.
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4
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Li X, Quan M, Wei Y, Wang W, Xu L, Wang Q, Jia J. Critical thinking of Alzheimer's transgenic mouse model: current research and future perspective. SCIENCE CHINA. LIFE SCIENCES 2023; 66:2711-2754. [PMID: 37480469 DOI: 10.1007/s11427-022-2357-x] [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: 12/22/2022] [Accepted: 04/23/2023] [Indexed: 07/24/2023]
Abstract
Transgenic models are useful tools for studying the pathogenesis of and drug development for Alzheimer's Disease (AD). AD models are constructed usually using overexpression or knock-in of multiple pathogenic gene mutations from familial AD. Each transgenic model has its unique behavioral and pathological features. This review summarizes the research progress of transgenic mouse models, and their progress in the unique mechanism of amyloid-β oligomers, including the first transgenic mouse model built in China based on a single gene mutation (PSEN1 V97L) found in Chinese familial AD. We further summarized the preclinical findings of drugs using the models, and their future application in exploring the upstream mechanisms and multitarget drug development in AD.
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Affiliation(s)
- Xinyue Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Meina Quan
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- National Medical Center for Neurological Diseases and National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Yiping Wei
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Wei Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- National Medical Center for Neurological Diseases and National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Lingzhi Xu
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Qi Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- National Medical Center for Neurological Diseases and National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- National Medical Center for Neurological Diseases and National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China.
- Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, 100053, China.
- Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, 100053, China.
- Center of Alzheimer's Disease, Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, 100053, China.
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053, China.
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5
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Quan M, Cao S, Wang Q, Wang S, Jia J. Genetic Phenotypes of Alzheimer's Disease: Mechanisms and Potential Therapy. PHENOMICS (CHAM, SWITZERLAND) 2023; 3:333-349. [PMID: 37589021 PMCID: PMC10425323 DOI: 10.1007/s43657-023-00098-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/28/2023] [Accepted: 02/02/2023] [Indexed: 08/18/2023]
Abstract
Years of intensive research has brought us extensive knowledge on the genetic and molecular factors involved in Alzheimer's disease (AD). In addition to the mutations in the three main causative genes of familial AD (FAD) including presenilins and amyloid precursor protein genes, studies have identified several genes as the most plausible genes for the onset and progression of FAD, such as triggering receptor expressed on myeloid cells 2, sortilin-related receptor 1, and adenosine triphosphate-binding cassette transporter subfamily A member 7. The apolipoprotein E ε4 allele is reported to be the strongest genetic risk factor for sporadic AD (SAD), and it also plays an important role in FAD. Here, we reviewed recent developments in genetic and molecular studies that contributed to the understanding of the genetic phenotypes of FAD and compared them with SAD. We further reviewed the advancements in AD gene therapy and discussed the future perspectives based on the genetic phenotypes.
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Affiliation(s)
- Meina Quan
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053 China
- National Medical Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, 100053 China
| | - Shuman Cao
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053 China
| | - Qi Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053 China
- National Medical Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, 100053 China
| | - Shiyuan Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053 China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053 China
- National Medical Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, 100053 China
- Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, 100053 China
- Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, 100053 China
- Center of Alzheimer’s Disease, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Beijing, 100053 China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, 100053 China
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6
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Yang F, Liu R, He S, Ruan S, He B, Li J, Pan L. Being a morning man has causal effects on the cerebral cortex: a Mendelian randomization study. Front Neurosci 2023; 17:1222551. [PMID: 37547136 PMCID: PMC10400340 DOI: 10.3389/fnins.2023.1222551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023] Open
Abstract
Introduction Numerous studies have suggested a connection between circadian rhythm and neurological disorders with cognitive and consciousness impairments in humans, yet little evidence stands for a causal relationship between circadian rhythm and the brain cortex. Methods The top 10,000 morningness-related single-nucleotide polymorphisms of the Genome-wide association study (GWAS) summary statistics were used to filter the instrumental variables. GWAS summary statistics from the ENIGMA Consortium were used to assess the causal relationship between morningness and variates like cortical thickness (TH) or surficial area (SA) on the brain cortex. The inverse-variance weighted (IVW) and weighted median (WM) were used as the major estimates whereas MR-Egger, MR Pleiotropy RESidual Sum and Outlier, leave-one-out analysis, and funnel-plot were used for heterogeneity and pleiotropy detecting. Results Regionally, morningness decreased SA of the rostral middle frontal gyrus with genomic control (IVW: β = -24.916 mm, 95% CI: -47.342 mm to -2.490 mm, p = 0.029. WM: β = -33.208 mm, 95% CI: -61.933 mm to -4.483 mm, p = 0.023. MR Egger: β < 0) and without genomic control (IVW: β = -24.581 mm, 95% CI: -47.552 mm to -1.609 mm, p = 0.036. WM: β = -32.310 mm, 95% CI: -60.717 mm to -3.902 mm, p = 0.026. MR Egger: β < 0) on a nominal significance, with no heterogeneity or no outliers. Conclusions and implications Circadian rhythm causally affects the rostral middle frontal gyrus; this sheds new light on the potential use of MRI in disease diagnosis, revealing the significance of circadian rhythm on the progression of disease, and might also suggest a fresh therapeutic approach for disorders related to the rostral middle frontal gyrus-related.
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Affiliation(s)
- Fan Yang
- Department of Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Province, China
- Department of Anesthesiology, Central Hospital of Shaoyang, Shaoyang, Hunan Province, China
- Guangxi Key Laboratory for Basic Science and Prevention of Perioperative Organ Disfunction, Nanning, Guangxi Province, China
- Guangxi Clinical Research Center for Anesthesiology, Nanning, Guangxi Province, China
- Guangxi Engineering Research Center for Tissue and Organ Injury and Repair Medicine, Nanning, Guangxi Province, China
| | - Ru Liu
- Department of Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Province, China
| | - Sheng He
- Department of Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Province, China
- Department of Anesthesiology, The First Affiliated Hospital of Southern China University, Hengyang, China
| | - Sijie Ruan
- Department of Anesthesiology, Central Hospital of Shaoyang, Shaoyang, Hunan Province, China
| | - Binghua He
- Department of Anesthesiology, Central Hospital of Shaoyang, Shaoyang, Hunan Province, China
| | - Junda Li
- Department of Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Province, China
| | - Linghui Pan
- Department of Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Province, China
- Guangxi Key Laboratory for Basic Science and Prevention of Perioperative Organ Disfunction, Nanning, Guangxi Province, China
- Guangxi Clinical Research Center for Anesthesiology, Nanning, Guangxi Province, China
- Guangxi Engineering Research Center for Tissue and Organ Injury and Repair Medicine, Nanning, Guangxi Province, China
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7
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Quan M, Wang Q, Qin W, Wang W, Li F, Zhao T, Li T, Qiu Q, Cao S, Wang S, Wang Y, Jin H, Zhou A, Fang J, Jia L, Jia J. Shared and unique effects of ApoEε4 and pathogenic gene mutation on cognition and imaging in preclinical familial Alzheimer's disease. Alzheimers Res Ther 2023; 15:40. [PMID: 36850008 PMCID: PMC9972804 DOI: 10.1186/s13195-023-01192-y] [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: 07/26/2022] [Accepted: 02/13/2023] [Indexed: 03/01/2023]
Abstract
BACKGROUND Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD. METHODS One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation. RESULTS Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups. CONCLUSIONS There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.
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Affiliation(s)
- Meina Quan
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Qi Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Wei Qin
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Wei Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Fangyu Li
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Tan Zhao
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Tingting Li
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Qiongqiong Qiu
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shuman Cao
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shiyuan Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Yan Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Hongmei Jin
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Aihong Zhou
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Jiliang Fang
- grid.464297.aGuang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Longfei Jia
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China. .,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China. .,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China. .,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China. .,Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China.
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8
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Zeng XX, Zeng JB. Systems Medicine as a Strategy to Deal with Alzheimer's Disease. J Alzheimers Dis 2023; 96:1411-1426. [PMID: 37980671 DOI: 10.3233/jad-230739] [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: 11/21/2023]
Abstract
The traits of Alzheimer's disease (AD) include amyloid plaques made of Aβ1-40 and Aβ1-42, and neurofibrillary tangles by the hyperphosphorylation of tau protein. AD is a complex disorder that is heterogenous in genetical, neuropathological, and clinical contexts. Current available therapeutics are unable to cure AD. Systems medicine is a strategy by viewing the body as a whole system, taking into account each individual's unique health profile, provide treatment and associated nursing care clinically for the patient, aiming for precision. Since the onset of AD can lead towards cognitive impairment, it is vital to intervene and diagnose early and prevent further progressive loss of neurons. Moreover, as the individual's brain functions are impaired due to neurodegeneration in AD, it is essential to reconstruct the neurons or brain cells to enable normal brain functions. Although there are different subtypes of AD due to varied pathological lesions, in the majority cases of AD, neurodegeneration and severe brain atrophy develop at the chronic stage. Novel approaches including RNA based gene therapy, stem cell based technology, bioprinting technology, synthetic biology for brain tissue reconstruction are researched in recent decades in the hope to decrease neuroinflammation and restore normal brain function in individuals of AD. Systems medicine include the prevention of disease, diagnosis and treatment by viewing the individual's body as a whole system, along with systems medicine based nursing as a strategy against AD that should be researched further.
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Affiliation(s)
- Xiao Xue Zeng
- Department of Health Management, Centre of General Practice, The Seventh Affiliated Hospital, Southern Medical University, Lishui Town, Nanhai District, Foshan City, Guangdong Province, P.R. China
| | - Jie Bangzhe Zeng
- Benjoe Institute of Systems Bio-Engineering, High Technology Park, Xinbei District, Changzhou City, Jiangsu Province, P.R. China
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9
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PICALM rs3851179 Variants Modulate Left Postcentral Cortex Thickness, CSF Amyloid β42, and Phosphorylated Tau in the Elderly. Brain Sci 2022; 12:brainsci12121681. [PMID: 36552141 PMCID: PMC9776362 DOI: 10.3390/brainsci12121681] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 11/25/2022] [Accepted: 11/30/2022] [Indexed: 12/13/2022] Open
Abstract
PICALM rs3851179, one of the genes most frequently linked to susceptibility of late-onset Alzheimer's disease (LOAD), plays a crucial role in regulating amyloid precursor protein, and amyloid β (Aβ) transcytosis. To explore the effects of PICALM and AD continuum stage on cortex thickness, CSF Aβ, and tau, 188 cognitively normal controls, 261 MCI patients, and 140 early LOAD patients were recruited, and each group was divided into rs3851179 A-carriers and GG-carriers. A full factorial ANCOVA was used to analyze the main effects and interactive effects of AD continuum stage, and PICALM. The interactive effects of AD continuum stage and PICALM on cortex thickness and CSF biomarkers were not significant. The main effect of PICALM was significant on the left postcentral cortex thickness, and the cortex thickness of A-carriers was less than that of GG-carriers. The rs3851179 A-carriers displayed higher Aβ42 levels and Aβ42/40 ratios, and lower P/T-tau ratios, compared with GG-carriers. A higher MMSE score was found in A-carriers among the LOAD patients. In conclusion, the main effects of PICALM were independent of AD continuum stage, and PICLAM rs3851179 genotypes may modulate left postcentral cortex thickness, Aβ42 level, and P/T-tau ratio. The rs3851179 A-allele may protect the cognitive function of LOAD patients.
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10
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Lin B, Zhang L, Yin X, Chen X, Ruan C, Wu T, Liu Z, Huang J. Modulation of entorhinal cortex–hippocampus connectivity and recognition memory following electroacupuncture on 3×Tg-AD model: Evidence from multimodal MRI and electrophysiological recordings. Front Neurosci 2022; 16:968767. [PMID: 35968386 PMCID: PMC9372370 DOI: 10.3389/fnins.2022.968767] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Abstract
Memory loss and aberrant neuronal network activity are part of the earliest hallmarks of Alzheimer’s disease (AD). Electroacupuncture (EA) has been recognized as a cognitive stimulation for its effects on memory disorder, but whether different brain regions or neural circuits contribute to memory recovery in AD remains unknown. Here, we found that memory deficit was ameliorated in 3×Tg-AD mice with EA-treatment, as shown by the increased number of exploring and time spent in the novel object. In addition, reduced locomotor activity was observed in 3×Tg-AD mice, but no significant alteration was seen in the EA-treated mice. Based on the functional magnetic resonance imaging, the regional spontaneous activity alterations of 3×Tg-AD were mainly concentrated in the accumbens nucleus, auditory cortex, caudate putamen, entorhinal cortex (EC), hippocampus, insular cortex, subiculum, temporal cortex, visual cortex, and so on. While EA-treatment prevented the chaos of brain activity in parts of the above regions, such as the auditory cortex, EC, hippocampus, subiculum, and temporal cortex. And then we used the whole-cell voltage-clamp recording to reveal the neurotransmission in the hippocampus, and found that EA-treatment reversed the synaptic spontaneous release. Since the hippocampus receives most of the projections of the EC, the hippocampus-EC circuit is one of the neural circuits related to memory impairment. We further applied diffusion tensor imaging (DTI) tracking and functional connectivity, and found that hypo-connected between the hippocampus and EC with EA-treatment. These data indicate that the hippocampus–EC connectivity is responsible for the recognition memory deficit in the AD mice with EA-treatment, and provide novel insight into potential therapies for memory loss in AD.
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Affiliation(s)
- Bingbing Lin
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Lanlan Zhang
- TCM Rehabilitation Research Center of State Administration of Traditional Chinese Medicine (SATCM), Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Xiaolong Yin
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Xiaocheng Chen
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Chendong Ruan
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Tiecheng Wu
- Key Laboratory of Orthopedics & Traumatology of Traditional Chinese Medicine and Rehabilitation, Ministry of Education, Fuzhou, China
| | - Zhizhen Liu
- TCM Rehabilitation Research Center of State Administration of Traditional Chinese Medicine (SATCM), Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jia Huang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
- *Correspondence: Jia Huang,
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11
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Qiu Q. Neural Networks in Autosomal Dominant Alzheimer’s Disease: Insights From Functional Magnetic Resonance Imaging Studies. Front Aging Neurosci 2022; 14:903269. [PMID: 35928996 PMCID: PMC9343946 DOI: 10.3389/fnagi.2022.903269] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/03/2022] [Indexed: 11/13/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common form of dementia, with no cure to stop its progression. Early detection, diagnosis, and intervention have become the hot spots in AD research. The long asymptomatic and slightly symptomatic phases of autosomal dominant AD (ADAD) allow studies to explore early biomarkers and the underlying pathophysiological changes. Functional magnetic resonance imaging (fMRI) provides a method to detect abnormal patterns of brain activity and functional connectivity in vivo, which correlates with cognitive decline earlier than structural changes and more strongly than amyloid deposition. Here, we will provide a brief overview of the network-level findings in ADAD in fMRI studies. In general, abnormalities in brain activity were mainly found in the hippocampus, the medial temporal lobe (MTL), the posterior cortex, the cingulate cortices, and the frontal regions in ADAD. Moreover, ADAD and sporadic AD (SAD) have similar fMRI changes, but not with aging.
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Affiliation(s)
- Qiongqiong Qiu
- Innovation Center for Neurological Disorders, Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China
- Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China
- Center of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China
- Key Laboratory of Neurodegenerative Diseases, Ministry of Education, National Clinical Research Center for Geriatric Disorders, Beijing, China
- *Correspondence: Qiongqiong Qiu,
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12
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Qiu T, Xie F, Zeng Q, Shen Z, Du G, Xu X, Wang C, Li X, Luo X, Li K, Huang P, Zhang T, Zhang J, Dai S, Zhang M. Interactions between cigarette smoking and cognitive status on functional connectivity of the cortico-striatal circuits in individuals without dementia: A resting-state functional MRI study. CNS Neurosci Ther 2022; 28:1195-1204. [PMID: 35506354 PMCID: PMC9253779 DOI: 10.1111/cns.13852] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 04/12/2022] [Accepted: 04/16/2022] [Indexed: 11/27/2022] Open
Abstract
Aims Cigarette smoking is a modifiable risk factor for Alzheimer's disease (AD), and controlling risk factors may curb the progression of AD. However, the underlying neural mechanisms of the effects of smoking on cognition remain largely unclear. Therefore, we aimed to explore the interaction effects of smoking × cognitive status on cortico‐striatal circuits, which play a crucial role in addiction and cognition, in individuals without dementia. Methods We enrolled 304 cognitively normal (CN) non‐smokers, 44 CN smokers, 130 mild cognitive impairment (MCI) non‐smokers, and 33 MCI smokers. The mixed‐effect analysis was performed to explore the interaction effects between smoking and cognitive status (CN vs. MCI) based on functional connectivity (FC) of the striatal subregions (caudate, putamen, and nucleus accumbens [NAc]). Results The significant interaction effects of smoking × cognitive status on FC of the striatal subregions were detected in the left inferior parietal lobule (IPL), bilateral cuneus, and bilateral anterior cingulate cortex (ACC). Specifically, increased FC of right caudate to left IPL was found in CN smokers compared with non‐smokers. The MCI smokers showed decreased FC of right caudate to left IPL and of right putamen to bilateral cuneus and increased FC of bilateral NAc to bilateral ACC compared with CN smokers and MCI non‐smokers. Furthermore, a positive correlation between FC of the NAc to ACC with language and memory was detected in MCI smokers. Conclusions Cigarette smoking could affect the function of cortico‐striatal circuits in patients with MCI. Our findings suggest that quitting smoking in the prodromal stage of AD may have the potential to prevent disease progression.
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Affiliation(s)
- Tiantian Qiu
- Department of Radiology, Linyi People's Hospital, Linyi, China
| | - Fei Xie
- Department of Equipment and Medical Engineering, Linyi People's Hospital, Linyi, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhujing Shen
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Guijin Du
- Department of Radiology, Linyi People's Hospital, Linyi, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Chao Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaodong Li
- Department of Radiology, Linyi People's Hospital, Linyi, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Tianyi Zhang
- Department of Neurology, Tongde Hospital of Zhejiang Province, Hangzhou, China
| | - Jinling Zhang
- Cancer Center, Linyi People's Hospital, Linyi, China
| | - Shouping Dai
- Department of Radiology, Linyi People's Hospital, Linyi, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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13
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Levitis E, Vogel JW, Funck T, Hachinski V, Gauthier S, Vöglein J, Levin J, Gordon BA, Benzinger T, Iturria-Medina Y, Evans AC. Differentiating amyloid beta spread in autosomal dominant and sporadic Alzheimer's disease. Brain Commun 2022; 4:fcac085. [PMID: 35602652 PMCID: PMC9116976 DOI: 10.1093/braincomms/fcac085] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 12/05/2021] [Accepted: 04/08/2022] [Indexed: 11/12/2022] Open
Abstract
Amyloid-beta deposition is one of the hallmark pathologies in both sporadic Alzheimer's disease and autosomal-dominant Alzheimer's disease, the latter of which is caused by mutations in genes involved in amyloid-beta processing. Despite amyloid-beta deposition being a centrepiece to both sporadic Alzheimer's disease and autosomal-dominant Alzheimer's disease, some differences between these Alzheimer's disease subtypes have been observed with respect to the spatial pattern of amyloid-beta. Previous work has shown that the spatial pattern of amyloid-beta in individuals spanning the sporadic Alzheimer's disease spectrum can be reproduced with high accuracy using an epidemic spreading model which simulates the diffusion of amyloid-beta across neuronal connections and is constrained by individual rates of amyloid-beta production and clearance. However, it has not been investigated whether amyloid-beta deposition in the rarer autosomal-dominant Alzheimer's disease can be modelled in the same way, and if so, how congruent the spreading patterns of amyloid-beta across sporadic Alzheimer's disease and autosomal-dominant Alzheimer's disease are. We leverage the epidemic spreading model as a data-driven approach to probe individual-level variation in the spreading patterns of amyloid-beta across three different large-scale imaging datasets (2 sporadic Alzheimer's disease, 1 autosomal-dominant Alzheimer's disease). We applied the epidemic spreading model separately to the Alzheimer's Disease Neuroimaging initiative (n = 737), the Open Access Series of Imaging Studies (n = 510) and the Dominantly Inherited Alzheimer's Network (n = 249), the latter two of which were processed using an identical pipeline. We assessed inter- and intra-individual model performance in each dataset separately and further identified the most likely subject-specific epicentre of amyloid-beta spread. Using epicentres defined in previous work in sporadic Alzheimer's disease, the epidemic spreading model provided moderate prediction of the regional pattern of amyloid-beta deposition across all three datasets. We further find that, whilst the most likely epicentre for most amyloid-beta-positive subjects overlaps with the default mode network, 13% of autosomal-dominant Alzheimer's disease individuals were best characterized by a striatal origin of amyloid-beta spread. These subjects were also distinguished by being younger than autosomal-dominant Alzheimer's disease subjects with a default mode network amyloid-beta origin, despite having a similar estimated age of symptom onset. Together, our results suggest that most autosomal-dominant Alzheimer's disease patients express amyloid-beta spreading patterns similar to those of sporadic Alzheimer's disease, but that there may be a subset of autosomal-dominant Alzheimer's disease patients with a separate, striatal phenotype.
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Affiliation(s)
- Elizabeth Levitis
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Correspondence to: Elizabeth Levitis Magnuson Clinical Center Room 4N244, MSC 1367 Bethesda, MD 20814, USA E-mail:
| | - Jacob W Vogel
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Thomas Funck
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Serge Gauthier
- McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada
| | - Jonathan Vöglein
- German Center for Neurodegenerative Diseases, Munich, Germany,Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Johannes Levin
- German Center for Neurodegenerative Diseases, Munich, Germany
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine in Saint Louis, St Louis, Missouri, USA
| | - Tammie Benzinger
- Department of Radiology, Washington University School of Medicine in Saint Louis, St Louis, Missouri, USA
| | - Yasser Iturria-Medina
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Correspondence may also be addressed to: Alan C. Evans Montreal Neurological Institute Montreal, H3A 2B4, Quebec Canada E-mail:
| | - Alan C Evans
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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14
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Wang J, Ma L, Liu G, Bai W, Ai K, Zhang P, Hu W, Zhang J. Tractography in Type 2 Diabetes Mellitus With Subjective Memory Complaints: A Diffusion Tensor Imaging Study. Front Neurosci 2022; 15:800420. [PMID: 35462734 PMCID: PMC9019711 DOI: 10.3389/fnins.2021.800420] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 12/31/2021] [Indexed: 12/12/2022] Open
Abstract
The brain white matter (WM) structural injury caused by type 2 diabetes mellitus (T2DM) has been linked to cognitive impairment. However, the focus was mainly on the mild cognitive impairment (MCI) stage in most previous studies, with little attention made to subjective memory complaints (SMC). The main purpose of the current study was to investigate the characteristics of WM injury in T2DM patients and its correlation with SMC symptoms. In a group of 66 participants (33 HC and 33 T2DM-S), pointwise differences along WM tracts were identified using the automated fiber quantification (AFQ) approach. Then we investigated the utility of DTI properties along major WM tracts as features to distinguish patients with T2DM-S from HC via the support vector machine (SVM). Based on AFQ analysis, 10 primary fiber tracts that represent the subtle alterations of WM in T2DM-S were identified. Lower fractional anisotropy (FA) in the right SLF tract (r = −0.538, p = 0.0013), higher radial diffusivity (RD) in the thalamic radiation (TR) tract (r = 0.433, p = 0.012), and higher mean diffusivity (MD) in the right inferior fronto-occipital fasciculus (IFOF) tract (r = 0.385, p = 0.0029) were significantly associated with a long period of disease. Decreased axial diffusivity (AD) in the left arcuate was associated with HbA1c (r = −0.368, p = 0.049). In addition, we found a significant negative correlation between delayed recall and abnormal MD in the left corticospinal tract (r = −0.546, p = 0.001). The FA of the right SLF tracts and bilateral arcuate can be used to differentiate the T2DM-S and the HC at a high accuracy up to 88.45 and 87.8%, respectively. In conclusion, WM microstructure injury in T2DM may be associated with SMC, and these abnormalities identified by DTI can be used as an effective biomarker.
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Affiliation(s)
- Jun Wang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Laiyang Ma
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Wenjuan Bai
- Department of Endocrine, Lanzhou University Second Hospital, Lanzhou, China
| | - Kai Ai
- Department of Clinical Science, Philips Healthcare, Xi’an, China
| | - Pengfei Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Wanjun Hu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
- *Correspondence: Jing Zhang,
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15
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Forno G, Lladó A, Hornberger M. Going round in circles-The Papez circuit in Alzheimer's disease. Eur J Neurosci 2021; 54:7668-7687. [PMID: 34656073 DOI: 10.1111/ejn.15494] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 10/01/2021] [Accepted: 10/12/2021] [Indexed: 11/29/2022]
Abstract
The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer's disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is 'only' one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit 'downstream' of the hippocampus. However, this notion is oversimplistic, and increasing evidence suggests that other Papez regions might be affected before or concurrently with the hippocampus. In addition, AD research has mostly focused on episodic memory deficits, whereas spatial navigation processes are also subserved by the Papez circuit with increasing evidence supporting its valuable potential as a diagnostic measure of incipient AD pathophysiology. In the current review, we take a step forward analysing recent evidence on the structural and functional integrity of the Papez circuit across AD disease stages. Specifically, we will review the integrity of specific Papez regions from at-genetic-risk (APOE4 carriers), to mild cognitive impairment (MCI), to dementia stage of sporadic AD and autosomal dominant AD (ADAD). We related those changes to episodic memory and spatial navigation/orientation deficits in AD. Finally, we provide an overview of how the Papez circuit is affected in AD diseases and their specific symptomology contributions. This overview strengthened the need for moving away from a hippocampal-centric view to a network approach on how the whole Papez circuit is affected in AD and contributes to its symptomology, informing future research and clinical approaches.
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Affiliation(s)
- Gonzalo Forno
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain.,School of Psychology, Universidad de los Andes, Santiago, Chile.,Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department, ICBM, Neurosciences Department, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
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16
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Montal V, Vilaplana E, Pegueroles J, Bejanin A, Alcolea D, Carmona-Iragui M, Clarimón J, Levin J, Cruchaga C, Graff-Radford NR, Noble JM, Lee JH, Allegri R, Karch CM, Laske C, Schofield P, Salloway S, Ances B, Benzinger T, McDale E, Bateman R, Blesa R, Sánchez-Valle R, Lleó A, Fortea J. Biphasic cortical macro- and microstructural changes in autosomal dominant Alzheimer's disease. Alzheimers Dement 2021; 17:618-628. [PMID: 33196147 PMCID: PMC8043974 DOI: 10.1002/alz.12224] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 09/20/2020] [Accepted: 10/09/2020] [Indexed: 12/21/2022]
Abstract
INTRODUCTION A biphasic model for brain structural changes in preclinical Alzheimer's disease (AD) could reconcile some conflicting and paradoxical findings in observational studies and anti-amyloid clinical trials. METHODS In this study we tested this model fitting linear versus quadratic trajectories and computed the timing of the inflection points vertexwise of cortical thickness and cortical diffusivity-a novel marker of cortical microstructure-changes in 389 participants from the Dominantly Inherited Alzheimer Network. RESULTS In early preclinical AD, between 20 and 15 years before estimated symptom onset, we found increases in cortical thickness and decreases in cortical diffusivity followed by cortical thinning and cortical diffusivity increases in later preclinical and symptomatic stages. The inflection points 16 to 19 years before estimated symptom onset are in agreement with the start of tau biomarker alterations. DISCUSSION These findings confirm a biphasic trajectory for brain structural changes and have direct implications when interpreting magnetic resonance imaging measures in preventive AD clinical trials.
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Affiliation(s)
- Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Eduard Vilaplana
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Jordi Pegueroles
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alex Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - María Carmona-Iragui
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center. Fundació Catalana de Síndrome de Down. Barcelona, Spain
| | - Jordi Clarimón
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Carlos Cruchaga
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | | | - James M Noble
- Department of Neurology, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Jae-Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, BuenosAires, Argentina
| | - Celeste M. Karch
- Department of Psychiatry, Washington University School of Medicine, Saint Lous, MO, USA
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Germany
| | - Peter Schofield
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Stephen Salloway
- Neurology and the Memory and Aging Program, Butler Hospital, Providence, RI, USA
| | - Beau Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, Missouri, USA
| | - Tammie Benzinger
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, Missouri, USA
| | - Eric McDale
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Randall Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- The Hope Center for Neurological Disorders, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Raquel Sánchez-Valle
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Barcelona Down Medical Center. Fundació Catalana de Síndrome de Down. Barcelona, Spain
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17
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Qorri B, Tsay M, Agrawal A, Au R, Gracie J. Using machine intelligence to uncover Alzheimer’s disease progression heterogeneity. EXPLORATION OF MEDICINE 2020. [DOI: 10.37349/emed.2020.00026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Aim: Research suggests that Alzheimer’s disease (AD) is heterogeneous with numerous subtypes. Through a proprietary interactive ML system, several underlying biological mechanisms associated with AD pathology were uncovered. This paper is an introduction to emerging analytic efforts that can more precisely elucidate the heterogeneity of AD.
Methods: A public AD data set (GSE84422) consisting of transcriptomic data of postmortem brain samples from healthy controls (n = 121) and AD (n = 380) subjects was analyzed. Data were processed by an artificial intelligence platform designed to discover potential drug repurposing candidates, followed by an interactive augmented intelligence program.
Results: Using perspective analytics, six perspective classes were identified: Class I is defined by TUBB1, ASB4, and PDE5A; Class II by NRG2 and ZNF3; Class III by IGF1, ASB4, and GTSE1; Class IV is defined by cDNA FLJ39269, ITGA1, and CPM; Class V is defined by PDE5A, PSEN1, and NDUFS8; and Class VI is defined by DCAF17, cDNA FLJ75819, and SLC33A1. It is hypothesized that these classes represent biological mechanisms that may act alone or in any combination to manifest an Alzheimer’s pathology.
Conclusions: Using a limited transcriptomic public database, six different classes that drive AD were uncovered, supporting the premise that AD is a heterogeneously complex disorder. The perspective classes highlighted genetic pathways associated with vasculogenesis, cellular signaling and differentiation, metabolic function, mitochondrial function, nitric oxide, and metal ion metabolism. The interplay among these genetic factors reveals a more profound underlying complexity of AD that may be responsible for the confluence of several biological factors. These results are not exhaustive; instead, they demonstrate that even within a relatively small study sample, next-generation machine intelligence can uncover multiple genetically driven subtypes. The models and the underlying hypotheses generated using novel analytic methods may translate into potential treatment pathways.
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Affiliation(s)
- Bessi Qorri
- Department of Biomedical and Molecular Sciences, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Mike Tsay
- NetraMark Corp, Toronto, ON M4E 1G8, Canada
| | | | - Rhoda Au
- Department of Anatomy & Neurobiology, Neurology and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA 02218, USA
| | - Joseph Gracie
- NetraMark Corp, Toronto, ON M4E 1G8, Canada 5Department of Pathology and Molecular Medicine, Queen’s University, Kingston, ON K7L 3N6, Canada
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