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Rudroff T. Frontal-striatal glucose metabolism and fatigue in patients with multiple sclerosis, long COVID, and COVID-19 recovered controls. Exp Brain Res 2024; 242:2125-2136. [PMID: 38970653 DOI: 10.1007/s00221-024-06882-z] [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: 04/20/2024] [Accepted: 06/20/2024] [Indexed: 07/08/2024]
Abstract
This study compared brain glucose metabolism using FDG-PET in the caudate nucleus, putamen, globus pallidus, thalamus, and dorsolateral prefrontal cortex (DLPFC) among patients with Long COVID, patients with fatigue, people with multiple sclerosis (PwMS) patients with fatigue, and COVID recovered controls. PwMS exhibited greater hypometabolism compared to long COVID patients with fatigue and the COVID recovered control group in all studied brain areas except the globus pallidus (effect size range 0.7-1.5). The results showed no significant differences in glucose metabolism between patients with Long COVID and the COVID recovered control group in these regions. These findings suggest that long COVID fatigue may involve non-CNS systems, neurotransmitter imbalances, or psychological factors not captured by FDG-PET, while MS-related fatigue is associated with more severe frontal-striatal circuit dysfunction due to demyelination and neurodegeneration. Symmetrical standardized uptake values (SUVs) between hemispheres in all groups imply that fatigue in these conditions may be related to global or network-level alterations rather than hemisphere-specific changes. Future studies should employ fine-grained analysis methods, explore other brain regions, and control for confounding factors to better understand the pathophysiology of fatigue in MS and long COVID. Longitudinal studies tracking brain glucose metabolism in patients with Long COVID could provide insights into the evolution of metabolic patterns as the condition progresses.
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Affiliation(s)
- Thorsten Rudroff
- Department of Health and Human Physiology, University of Iowa, E432 Field House, Iowa City, IA, 52242, USA.
- Department of Neurology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
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Krolak-Salmon P, Swerdlow RH, Mastain T, Dive-Pouletty C, Pooley N, Kisomi M. Efficacy and Safety of Exogenous Ketones in People with Mild Neurocognitive Disorder and Alzheimer's Disease: A Systematic Literature Review. Nutr Rev 2024:nuae098. [PMID: 39047293 DOI: 10.1093/nutrit/nuae098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2024] Open
Abstract
CONTEXT Mild neurocognitive disorder (NCD), formally known as mild cognitive impairment, is usually the clinical stage preceding the development of Alzheimer's disease (AD), the most prevalent major NCD, and other causes of dementia. Glucose is a major source of energy for human brain metabolism and the uptake of glucose is reduced in patients with mild NCD, AD, and other NCDs. Unlike glucose, the uptake of ketones remains normal in people with mild NCD and AD, suggesting that the use of ketone bodies may compensate for glucose energy deficiency in patients with mild NCD and AD. OBJECTIVE The aim of this systematic review was to summarize the efficacy and safety of exogenic ketones, including medium chain triglycerides (MCTs), on cognitive function in patients with mild NCD and AD. DATA SOURCES The Embase, MEDLINE, MEDLINE In-Process, PubMed Ahead-of-Print, Cochrane Central Register of Controlled Trials, Europe PMC databases were searched from inception to April 2022. Studies reporting cognitive function efficacy and safety outcomes from randomized controlled trials of exogenic ketones in patients with mild NCD and AD were included. DATA EXTRACTION Data were extracted by 1 reviewer and checked by a second reviewer. Risk of bias was assessed using the Cochrane risk of bias tool, version 2. DATA ANALYSIS This review identified 13 individual trials investigating the efficacy and safety of MCT or coconut oil for patients with mild NCD or with AD. Because of the heterogeneity of the studies, a narrative synthesis was used. CONCLUSION Overall, improvements associated with exogenic ketones were observed in multiple aspects of cognitive abilities, although the large heterogeneity between the included studies makes it difficult to draw firm conclusions from the current literature. Although some studies investigated the impact of the apolipoprotein E ε4 allele status on treatment efficacy, the current data are insufficient to conclude whether such an effect is present. SYSTEMATIC REVIEW REGISTRATION PROSPERO registration No. CRD42022336664.
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Affiliation(s)
- Pierre Krolak-Salmon
- Institut du Vieillissement - Hospices Civils de Lyon, Lyon, France
- Emeis, Group Medical Department, Puteaux Cedex, 92813, France
| | - Russell H Swerdlow
- University of Kansas Alzheimer's Disease Research Center, Fairway, KS 66209, USA
| | | | | | - Nick Pooley
- Maverex Ltd, Newcatle Upon Tyne, NE6 2AR, United Kingdom
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Chowdhury GMI, Behar KL, Mason GF, Rothman DL, de Graaf RA. Measurement of neuro-energetics and neurotransmission in the rat olfactory bulb using 1H and 1H-[ 13C] NMR spectroscopy. NMR IN BIOMEDICINE 2024; 37:e4957. [PMID: 37088548 PMCID: PMC10590826 DOI: 10.1002/nbm.4957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 05/03/2023]
Abstract
The olfactory bulb (OB) plays a fundamental role in the sense of smell and has been implicated in several pathologies, including Alzheimer's disease. Despite its importance, high metabolic activity and unique laminar architecture, the OB is not frequently studied using MRS methods, likely due to the small size and challenging location. Here we present a detailed metabolic characterization of OB metabolism, in terms of both static metabolite concentrations using 1H MRS and metabolic fluxes associated with neuro-energetics and neurotransmission by tracing the dynamic 13C flow from intravenously administered [1,6-13C2]-glucose, [2-13C]-glucose and [2-13C]-acetate to downstream metabolites, including [4-13C]-glutamate, [4-13C]-glutamine and [2-13C]-GABA. The unique laminar architecture and associated metabolism of the OB, distinctly different from that of the cerebral cortex, is characterized by elevated GABA and glutamine levels, as well as increased GABAergic and astroglial energy metabolism and neurotransmission. The results show that, despite the technical challenges, high-quality 1H and 1H-[13C] MR spectra can be obtained from the rat OB in vivo. The derived metabolite concentrations and metabolic rates demonstrate a unique metabolic profile for the OB. The metabolic model provides a solid basis for future OB studies on functional activation or pathological conditions.
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Affiliation(s)
- Golam M. I. Chowdhury
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Kevin L. Behar
- Department of Psychiatry, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Graeme F. Mason
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Psychiatry, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Douglas L. Rothman
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
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Stocks J, Gibson E, Popuri K, Beg MF, Rosen H, Wang L. Spatial and Temporal Relationships Between Atrophy and Hypometabolism in Behavioral-Variant Frontotemporal Dementia. Alzheimer Dis Assoc Disord 2024; 38:112-119. [PMID: 38812447 PMCID: PMC11141524 DOI: 10.1097/wad.0000000000000611] [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: 09/18/2023] [Accepted: 02/07/2024] [Indexed: 05/31/2024]
Abstract
PURPOSE Individuals with behavioral-variant frontotemporal dementia (bvFTD) show changes in brain structure as assessed by MRI and brain function assessed by 18FDG-PET hypometabolism. However, current understanding of the spatial and temporal interplay between these measures remains limited. METHODS Here, we examined longitudinal atrophy and hypometabolism relationships in 15 bvFTD subjects with 2 to 4 follow-up MRI and PET scans (56 visits total). Subject-specific slopes of atrophy and hypometabolism over time were extracted across brain regions and correlated with baseline measures both locally, via Pearson correlations, and nonlocally, via sparse canonical correlation analyses (SCCA). RESULTS Notably, we identified a robust link between initial hypometabolism and subsequent cortical atrophy rate changes in bvFTD subjects. Network-level exploration unveiled alignment between baseline hypometabolism and ensuing atrophy rates in the dorsal attention, language, and default mode networks. SCCA identified 2 significant and highly localized components depicting the connection between baseline hypometabolism and atrophy slope over time. The first centered around bilateral orbitofrontal, frontopolar, and medial prefrontal lobes, whereas the second concentrated in the left temporal lobe and precuneus. CONCLUSIONS This study highlights 18FDG-PET as a dependable predictor of forthcoming atrophy in spatially adjacent brain regions for individuals with bvFTD.
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Affiliation(s)
- Jane Stocks
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 60611
| | - Erin Gibson
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada, M4N 3M5
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada, V5A1S6
- Memorial University of Newfoundland, Department of Computer Science, St. John’s, NL, Canada
| | - Mirza Faisal Beg
- School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada, V5A1S6
| | - Howard Rosen
- School of Medicine, University of California, San Francisco, USA, 94143
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 60611
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, USA 43210
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Colvee-Martin H, Parra JR, Gonzalez GA, Barker W, Duara R. Neuropathology, Neuroimaging, and Fluid Biomarkers in Alzheimer's Disease. Diagnostics (Basel) 2024; 14:704. [PMID: 38611617 PMCID: PMC11012058 DOI: 10.3390/diagnostics14070704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 02/05/2024] [Accepted: 02/17/2024] [Indexed: 04/14/2024] Open
Abstract
An improved understanding of the pathobiology of Alzheimer's disease (AD) should lead ultimately to an earlier and more accurate diagnosis of AD, providing the opportunity to intervene earlier in the disease process and to improve outcomes. The known hallmarks of Alzheimer's disease include amyloid-β plaques and neurofibrillary tau tangles. It is now clear that an imbalance between production and clearance of the amyloid beta protein and related Aβ peptides, especially Aβ42, is a very early, initiating factor in Alzheimer's disease (AD) pathogenesis, leading to aggregates of hyperphosphorylation and misfolded tau protein, inflammation, and neurodegeneration. In this article, we review how the AD diagnostic process has been transformed in recent decades by our ability to measure these various elements of the pathological cascade through the use of imaging and fluid biomarkers. The more recently developed plasma biomarkers, especially phosphorylated-tau217 (p-tau217), have utility for screening and diagnosis of the earliest stages of AD. These biomarkers can also be used to measure target engagement by disease-modifying therapies and the response to treatment.
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Affiliation(s)
- Helena Colvee-Martin
- Wien Center for Alzheimer’s Disease & Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL 33140, USA; (H.C.-M.); (W.B.)
| | - Juan Rayo Parra
- Human & Molecular Genetics, Florida International University, Miami, FL 33199, USA; (J.R.P.); (G.A.G.)
| | - Gabriel Antonio Gonzalez
- Human & Molecular Genetics, Florida International University, Miami, FL 33199, USA; (J.R.P.); (G.A.G.)
| | - Warren Barker
- Wien Center for Alzheimer’s Disease & Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL 33140, USA; (H.C.-M.); (W.B.)
| | - Ranjan Duara
- Wien Center for Alzheimer’s Disease & Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL 33140, USA; (H.C.-M.); (W.B.)
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Maruyama H, Gomi M, Lwin TT, Yoneyama A, Sasaki T. [ 18F]-FDG uptake in brain slices prepared from an aged mouse model of Alzheimer's disease using a dynamic autoradiography technique. Ann Nucl Med 2024; 38:120-130. [PMID: 37921921 DOI: 10.1007/s12149-023-01879-0] [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: 08/01/2023] [Accepted: 09/29/2023] [Indexed: 11/05/2023]
Abstract
OBJECTIVE 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography ([18F]-FDG-PET) is a imaging modality that has been used to measure of glucose metabolism in the brain in Alzheimer's disease (AD). Clinically, decreased glucose uptake has been reported in the brain of AD, although the precise underlying mechanisms have not yet been elucidated. To elucidate the mechanisms of decreased [18F]-FDG uptake in the AD by PET, [18F]-FDG uptake in the brain of aged model mouse of AD was investigated using a dynamic autoradiography technique "bioradiography". A X-ray phase-contrast imaging (X-PCI) and a histopathological evaluation were also investigated to elucidate the mechanisms underlying the relationships between decreased [18F]-FDG uptake and the pathological changes in the brain of AD mouse. METHODS In this study, AD model mouse (5XFAD, APP+/PS1+) were used. [18F]-FDG-bioradiography was conducted in fresh slices of brain tissue under the condition of resting (slices immersed in 5 mM K+ solution) and metabolically active (in 50 mM K+ solution). Amyloid β42 (Aβ42) deposition in the brain of AD mouse was confirmed by X-PCI. In addition, the positive cells of phosphated tau protein (P-tau) and deposition of Aβ42 were also examined by immunohistochemical staining. RESULTS No significant differences were observed between the two groups in the resting condition. In the activate condition of the brain, [18F]-FDG uptake was significantly decreased in AD mice compared to WT mice. In X-PCI showed Aβ deposition in the AD mouse, but not in the WT. The AD mouse also showed increased P-tau, accumulation of Aβ42, increase in neuronal apoptosis, and decrease in the number of neurons than that of the WT mouse. CONCLUSION Neuronal damage, and induction of neuronal apoptosis, decreased [18F]-FDG uptake, increased Aβ accumulation and P-tau induced neurofibrillary degeneration are observed in AD mouse. In clinical diagnosis, reduction of [18F]-FDG uptake by PET is one of the means of diagnosing the onset of AD. Our results suggest that decreased uptake of [18F]-FDG in the brains of AD may be associated with neuronal dysfunction and cell death in the brain.
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Affiliation(s)
- Hiroko Maruyama
- Cytopathology, Graduate School of Medical Sciences, School of Allied Health Sciences, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, 252-0373, Japan.
| | - Misaki Gomi
- Cytopathology, Graduate School of Medical Sciences, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, 252-0373, Japan
| | - Thet-Thet Lwin
- Molecular Imaging, Graduate School of Medical Sciences, School of Allied Health Sciences, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, 252-0373, Japan
| | - Akio Yoneyama
- SAGA Light Source, Synchrotron Light Research Center, 8-7 Yayoigaoka, Tosu, Saga, 841-0005, Japan
| | - Toru Sasaki
- Radiation Safety Management, Graduate School of Medical Sciences, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, 252-0373, Japan
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Keith CM, Haut MW, D'Haese PF, Mehta RI, Vieira Ligo Teixeira C, Coleman MM, Miller M, Ward M, Navia RO, Marano G, Wang X, McCuddy WT, Lindberg K, Wilhelmsen KC. More Similar than Different: Memory, Executive Functions, Cortical Thickness, and Glucose Metabolism in Biomarker-Positive Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia. J Alzheimers Dis Rep 2024; 8:57-73. [PMID: 38312533 PMCID: PMC10836603 DOI: 10.3233/adr-230049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 12/13/2023] [Indexed: 02/06/2024] Open
Abstract
Background Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are typically associated with very different clinical and neuroanatomical presentations; however, there is increasing recognition of similarities. Objective To examine memory and executive functions, as well as cortical thickness, and glucose metabolism in AD and bvFTD signature brain regions. Methods We compared differences in a group of biomarker-defined participants with Alzheimer's disease and a group of clinically diagnosed participants with bvFTD. These groups were also contrasted with healthy controls (HC). Results As expected, memory functions were generally more impaired in AD, followed by bvFTD, and both clinical groups performed more poorly than the HC group. Executive function measures were similar in AD compared to bvFTD for motor sequencing and go/no-go, but bvFTD had more difficulty with a set shifting task. Participants with AD showed thinner cortex and lower glucose metabolism in the angular gyrus compared to bvFTD. Participants with bvFTD had thinner cortex in the insula and temporal pole relative to AD and healthy controls, but otherwise the two clinical groups were similar for other frontal and temporal signature regions. Conclusions Overall, the results of this study highlight more similarities than differences between AD and bvFTD in terms of cognitive functions, cortical thickness, and glucose metabolism. Further research is needed to better understand the mechanisms mediating this overlap and how these relationships evolve longitudinally.
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Affiliation(s)
- Cierra M Keith
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Marc W Haut
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, WV, USA
- Department of Neurology, West Virginia University, Morgantown, WV, USA
- Department of Radiology, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Pierre-François D'Haese
- Department of Neuroradiology, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Rashi I Mehta
- Department of Neuroradiology, West Virginia University, Morgantown, WV, USA
- Department of Radiology, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | | | - Michelle M Coleman
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Mark Miller
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Melanie Ward
- Department of Neurology, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - R Osvaldo Navia
- Department of Medicine, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Gary Marano
- Department of Neuroradiology, West Virginia University, Morgantown, WV, USA
- Department of Radiology, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Xiaofei Wang
- Department of Radiology, West Virginia University, Morgantown, WV, USA
| | - William T McCuddy
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, WV, USA
- Department of Medicine, West Virginia University, Morgantown, WV, USA
| | - Katharine Lindberg
- Department of Behavioral Medicine and Psychiatry, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Kirk C Wilhelmsen
- Department of Neurology, West Virginia University, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
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Han JH, Lee S, Bae SH, Yun M, Ye BS, Jung J. Distinct changes in brain metabolism in patients with dementia and hearing loss. Brain Behav 2024; 14:e3374. [PMID: 38376024 PMCID: PMC10771228 DOI: 10.1002/brb3.3374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/07/2023] [Accepted: 12/07/2023] [Indexed: 02/21/2024] Open
Abstract
INTRODUCTION Previous studies have reported that hearing loss (HL) is associated with dementia, although the mechanistic underpinnings remain elusive. This study aimed to evaluate the changes in brain metabolism in patients with HL and different types of dementia. METHODS Patients with cognitive impairment (CI) and HL treated at the university-based memory clinic from May 2016 to October 2021 were included. In total, 108 patients with CI and HL prospectively underwent audiometry, neuropsychological test, magnetic resonance imaging, and 18 F-fluorodeoxyglucose positron emission tomography. Twenty-seven individuals without cognitive impairment and hearing loss were enrolled as a control group. Multivariable regression was performed to evaluate brain regions correlated with each pathology type after adjusting for confounding factors. RESULTS Multivariable regression analyses revealed that Alzheimer's disease-related CI (ADCI) was associated with hypometabolic changes in the right superior temporal gyrus (STG), right middle temporal gyrus (MTG), and bilateral medial temporal lobe. Lewy body disease-related CI (LBDCI) and vascular CI were associated with hypermetabolic and hypometabolic changes in the ascending auditory pathway, respectively. In the pure ADCI group, the degree of HL was positively associated with abnormal increase of brain metabolism in the right MTG, whereas it was negatively associated with decreased brain metabolism in the right STG in the pure LBDCI group. CONCLUSION Each dementia type is associated with distinct changes in brain metabolism in patients with HL.
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Affiliation(s)
- Ji Hyuk Han
- Department of OtorhinolaryngologyYonsei University College of MedicineSeoulRepublic of Korea
| | - Sangwon Lee
- Department of Nuclear MedicineYonsei University College of MedicineSeoulRepublic of Korea
| | - Seong Hoon Bae
- Department of OtorhinolaryngologyYonsei University College of MedicineSeoulRepublic of Korea
| | - Mijin Yun
- Department of Nuclear MedicineYonsei University College of MedicineSeoulRepublic of Korea
| | - Byung Seok Ye
- Department of NeurologyYonsei University College of MedicineSeoulRepublic of Korea
| | - Jinsei Jung
- Department of OtorhinolaryngologyYonsei University College of MedicineSeoulRepublic of Korea
- Graduate School of Medical ScienceYonsei University College of MedicineSeoulRepublic of Korea
- Brain Korea 21 ProjectYonsei University College of MedicineSeoulRepublic of Korea
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Tang J, Yousaf M, Wu YP, Li QQ, Xu YQ, Liu DM. Mechanisms and structure-activity relationships of polysaccharides in the intervention of Alzheimer's disease: A review. Int J Biol Macromol 2024; 254:127553. [PMID: 37865357 DOI: 10.1016/j.ijbiomac.2023.127553] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 10/23/2023]
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disease. Despite several decades of research, the development of effective treatments and responses for Alzheimer's disease remains elusive. The utilization of polysaccharides for Alzheimer's disease became more popular due to their beneficial characteristics, notably their multi-target activity and low toxicity. This review mainly focuses on the researches of recent 5 years in the regulation of AD by naturally derived polysaccharides, systematically lists the possible intervention pathways of polysaccharides from different mechanisms, and explores the structure-activity relationship between polysaccharide structural activities, so as to provide references for the intervention and treatment of AD by polysaccharides.
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Affiliation(s)
- Jun Tang
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510640, Guangdong, China
| | - Muhammad Yousaf
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510640, Guangdong, China
| | - Ya-Ping Wu
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510640, Guangdong, China
| | - Qin-Qin Li
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510640, Guangdong, China
| | - Yi-Qian Xu
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510640, Guangdong, China
| | - Dong-Mei Liu
- School of Food Science and Engineering, South China University of Technology, Guangzhou, 510640, Guangdong, China.
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Caminiti SP, De Francesco S, Tondo G, Galli A, Redolfi A, Perani D. FDG-PET markers of heterogeneity and different risk of progression in amnestic MCI. Alzheimers Dement 2024; 20:159-172. [PMID: 37505996 PMCID: PMC10962797 DOI: 10.1002/alz.13385] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/19/2023] [Accepted: 06/12/2023] [Indexed: 07/30/2023]
Abstract
INTRODUCTION Amnestic mild cognitive impairment (aMCI) is emerging as a heterogeneous condition. METHODS We looked at a cohort of N = 207 aMCI subjects, with baseline fluorodeoxyglucose positron emission tomography (FDG-PET), T1 magnetic resonance imaging, cerebrospinal fluid (CSF), apolipoprotein E (APOE), and neuropsychological assessment. An algorithm based on FDG-PET hypometabolism classified each subject into subtypes, then compared biomarker measures and clinical progression. RESULTS Three subtypes emerged: hippocampal sparing-cortical hypometabolism, associated with younger age and the highest level of Alzheimer's disease (AD)-CSF pathology; hippocampal/cortical hypometabolism, associated with a high percentage of APOE ε3/ε4 or ε4/ε4 carriers; medial-temporal hypometabolism, characterized by older age, the lowest AD-CSF pathology, the most severe hippocampal atrophy, and a benign course. Within the whole cohort, the severity of temporo-parietal hypometabolism, correlated with AD-CSF pathology and marked the rate of progression of cognitive decline. DISCUSSION FDG-PET can distinguish clinically comparable aMCI at single-subject level with different risk of progression to AD dementia or stability. The obtained results can be useful for the optimization of pharmacological trials and automated-classification models. HIGHLIGHTS Algorithm based on FDG-PET hypometabolism demonstrates distinct subtypes across aMCI; Three different subtypes show heterogeneous biological profiles and risk of progression; The cortical hypometabolism is associated with AD pathology and cognitive decline; MTL hypometabolism is associated with the lowest conversion rate and CSF-AD pathology.
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Affiliation(s)
- Silvia Paola Caminiti
- Vita‐Salute San Raffaele UniversityMilanItaly
- Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Silvia De Francesco
- Laboratory of NeuroinformaticsIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Giacomo Tondo
- Vita‐Salute San Raffaele UniversityMilanItaly
- Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Alice Galli
- Vita‐Salute San Raffaele UniversityMilanItaly
- Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Alberto Redolfi
- Laboratory of NeuroinformaticsIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Daniela Perani
- Vita‐Salute San Raffaele UniversityMilanItaly
- Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
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Ryoo HG, Choi H, Shi K, Rominger A, Lee DY, Lee DS. Distinct subtypes of spatial brain metabolism patterns in Alzheimer's disease identified by deep learning-based FDG PET clusters. Eur J Nucl Med Mol Imaging 2024; 51:443-454. [PMID: 37735259 DOI: 10.1007/s00259-023-06440-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 09/08/2023] [Indexed: 09/23/2023]
Abstract
PURPOSE Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clinicopathologic profiles. To date, objective subtyping of AD independent of disease progression using brain imaging has been required. Our study aimed to extract representations of unique brain metabolism patterns different from disease progression to identify objective subtypes of AD. METHODS A total of 3620 FDG brain PET images with AD, mild cognitive impairment (MCI), and cognitively normal (CN) were obtained from the ADNI database from 1607 participants at enrollment and follow-up visits. A conditional variational autoencoder model was trained on FDG brain PET images of AD patients with the corresponding condition of AD severity score. The k-means algorithm was applied to generate clusters from the encoded representations. The trained deep learning-based cluster model was also transferred to FDG PET of MCI patients and predicted the prognosis of subtypes for conversion from MCI to AD. Spatial metabolism patterns, clinical and biological characteristics, and conversion rate from MCI to AD were compared across the subtypes. RESULTS Four distinct subtypes of spatial metabolism patterns in AD with different brain pathologies and clinical profiles were identified: (i) angular, (ii) occipital, (iii) orbitofrontal, and (iv) minimal hypometabolic patterns. The deep learning model was also successfully transferred for subtyping MCI, and significant differences in frequency (P < 0.001) and risk of conversion (log-rank P < 0.0001) from MCI to AD were observed across the subtypes, highest in S2 (35.7%) followed by S1 (23.4%). CONCLUSION We identified distinct subtypes of AD with different clinicopathologic features. The deep learning-based approach to distinguish AD subtypes on FDG PET could have implications for predicting individual outcomes and provide a clue to understanding the heterogeneous pathophysiology of AD.
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Affiliation(s)
- Hyun Gee Ryoo
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine or College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010, Bern, Switzerland
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital, University of Bern, Freiburgstrasse 18, 3010, Bern, Switzerland
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dong Soo Lee
- Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, and College of Medicine or College of Pharmacy, Seoul National University, Seoul, Republic of Korea
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
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12
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Amato LG, Vergani AA, Lassi M, Fabbiani C, Mazzeo S, Burali R, Nacmias B, Sorbi S, Mannella R, Grippo A, Bessi V, Mazzoni A. Personalized modeling of Alzheimer's disease progression estimates neurodegeneration severity from EEG recordings. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12526. [PMID: 38371358 PMCID: PMC10870085 DOI: 10.1002/dad2.12526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 12/13/2023] [Accepted: 12/19/2023] [Indexed: 02/20/2024]
Abstract
INTRODUCTION Early identification of Alzheimer's disease (AD) is necessary for a timely onset of therapeutic care. However, cortical structural alterations associated with AD are difficult to discern. METHODS We developed a cortical model of AD-related neurodegeneration accounting for slowing of local dynamics and global connectivity degradation. In a monocentric study we collected electroencephalography (EEG) recordings at rest from participants in healthy (HC, n = 17), subjective cognitive decline (SCD, n = 58), and mild cognitive impairment (MCI, n = 44) conditions. For each patient, we estimated neurodegeneration model parameters based on individual EEG recordings. RESULTS Our model outperformed standard EEG analysis not only in discriminating between HC and MCI conditions (F1 score 0.95 vs 0.75) but also in identifying SCD patients with biological hallmarks of AD in the cerebrospinal fluid (recall 0.87 vs 0.50). DISCUSSION Personalized models could (1) support classification of MCI, (2) assess the presence of AD pathology, and (3) estimate the risk of cognitive decline progression, based only on economical and non-invasive EEG recordings. Highlights Personalized cortical model estimating structural alterations from EEG recordings.Discrimination of Mild Cognitive Impairment (MCI) and Healthy (HC) subjects (95%)Prediction of biological markers of Alzheimer's in Subjective Decline (SCD) Subjects (87%)Transition correctly predicted for 3/3 subjects that converted from SCD to MCI after 1y.
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Affiliation(s)
- Lorenzo Gaetano Amato
- The BioRobotics InstituteSant'Anna School of Advanced StudiesPisaItaly
- Department of Excellence in Robotics and AISant'Anna School of Advanced StudiesPisaItaly
| | - Alberto Arturo Vergani
- The BioRobotics InstituteSant'Anna School of Advanced StudiesPisaItaly
- Department of Excellence in Robotics and AISant'Anna School of Advanced StudiesPisaItaly
| | - Michael Lassi
- The BioRobotics InstituteSant'Anna School of Advanced StudiesPisaItaly
- Department of Excellence in Robotics and AISant'Anna School of Advanced StudiesPisaItaly
| | - Carlo Fabbiani
- IRCSS Fondazione Don Carlo GnocchiFlorenceItaly
- Department of NeurosciencePsychology, Drug Research and Child HealthCareggi University HospitalFlorenceItaly
| | - Salvatore Mazzeo
- IRCSS Fondazione Don Carlo GnocchiFlorenceItaly
- Department of NeurosciencePsychology, Drug Research and Child HealthCareggi University HospitalFlorenceItaly
| | | | - Benedetta Nacmias
- IRCSS Fondazione Don Carlo GnocchiFlorenceItaly
- Department of NeurosciencePsychology, Drug Research and Child HealthCareggi University HospitalFlorenceItaly
| | - Sandro Sorbi
- IRCSS Fondazione Don Carlo GnocchiFlorenceItaly
- Department of NeurosciencePsychology, Drug Research and Child HealthCareggi University HospitalFlorenceItaly
| | | | | | - Valentina Bessi
- Department of NeurosciencePsychology, Drug Research and Child HealthCareggi University HospitalFlorenceItaly
| | - Alberto Mazzoni
- The BioRobotics InstituteSant'Anna School of Advanced StudiesPisaItaly
- Department of Excellence in Robotics and AISant'Anna School of Advanced StudiesPisaItaly
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13
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Na S, Kang DW, Kim GH, Kim KW, Kim Y, Kim HJ, Park KH, Park YH, Byeon G, Suh J, Shin JH, Shim Y, Yang Y, Um YH, Oh SI, Wang SM, Yoon B, Yoon HJ, Lee SM, Lee J, Lee JS, Rhee HY, Lim JS, Jung YH, Chin J, Hong YJ, Jang H, Choi H, Choi M, Jang JW. The Usefulness of 18F-FDG PET to Differentiate Subtypes of Dementia: The Systematic Review and Meta-Analysis. Dement Neurocogn Disord 2024; 23:54-66. [PMID: 38362056 PMCID: PMC10864694 DOI: 10.12779/dnd.2024.23.1.54] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 01/22/2024] [Accepted: 01/22/2024] [Indexed: 02/17/2024] Open
Abstract
Background and Purpose Dementia subtypes, including Alzheimer's dementia (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), pose diagnostic challenges. This review examines the effectiveness of 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) in differentiating these subtypes for precise treatment and management. Methods A systematic review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines was conducted using databases like PubMed and Embase to identify studies on the diagnostic utility of 18F-FDG PET in dementia. The search included studies up to November 16, 2022, focusing on peer-reviewed journals and applying the gold-standard clinical diagnosis for dementia subtypes. Results From 12,815 articles, 14 were selected for final analysis. For AD versus FTD, the sensitivity was 0.96 (95% confidence interval [CI], 0.88-0.98) and specificity was 0.84 (95% CI, 0.70-0.92). In the case of AD versus DLB, 18F-FDG PET showed a sensitivity of 0.93 (95% CI 0.88-0.98) and specificity of 0.92 (95% CI, 0.70-0.92). Lastly, when differentiating AD from non-AD dementias, the sensitivity was 0.86 (95% CI, 0.80-0.91) and the specificity was 0.88 (95% CI, 0.80-0.91). The studies mostly used case-control designs with visual and quantitative assessments. Conclusions 18F-FDG PET exhibits high sensitivity and specificity in differentiating dementia subtypes, particularly AD, FTD, and DLB. This method, while not a standalone diagnostic tool, significantly enhances diagnostic accuracy in uncertain cases, complementing clinical assessments and structural imaging.
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Affiliation(s)
- Seunghee Na
- Department of Neurology, Incheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Incheon, Korea
| | - Dong Woo Kang
- Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Geon Ha Kim
- Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine, Seoul, Korea
| | - Ko Woon Kim
- Department of Neurology, Jeonbuk National University Hospital, Jeonbuk National University College of Medicine, Jeonju, Korea
| | - Yeshin Kim
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Korea
| | - Hee-Jin Kim
- Department of Neurology, Hanyang University Hospital, College of Medicine, Hanyang University, Seoul, Korea
| | - Kee Hyung Park
- Department of Neurology, College of Medicine, Gachon University Gil Medical Center, Incheon, Korea
| | - Young Ho Park
- Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Gihwan Byeon
- Department of Psychiatry, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Korea
| | - Jeewon Suh
- Department of Neurology, National Medical Center, Seoul, Korea
| | | | - YongSoo Shim
- Department of Neurology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - YoungSoon Yang
- Department of Neurology, Soonchunhyang University Cheonan Hospital, Soonchunhyang University School of Medicine, Cheonan, Korea
| | - Yoo Hyun Um
- Department of Psychiatry, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Suwon, Korea
| | - Seong-il Oh
- Department of Neurology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Korea
| | - Sheng-Min Wang
- Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Bora Yoon
- Department of Neurology, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Korea
| | - Hai-Jeon Yoon
- Department of Nuclear Medicine, Ewha Womans University College of Medicine, Seoul, Korea
| | - Sun Min Lee
- Department of Neurology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Korea
| | - Juyoun Lee
- Department of Neurology, Chungnam National University Hospital, Chungnam National University School of Medicine, Daejeon, Korea
| | - Jin San Lee
- Department of Neurology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Korea
| | - Hak Young Rhee
- Department of Neurology, Kyung Hee University Hospital at Gangdong, Kyung Hee University College of Medicine, Seoul, Korea
| | - Jae-Sung Lim
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Young Hee Jung
- Department of Neurology, Myungji Hospital, Goyang, Korea
| | - Juhee Chin
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yun Jeong Hong
- Department of Neurology, Uijeongbu St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu, Korea
| | - Hyemin Jang
- Department of Neurology, Seoul National University Hospital, Seoul, Korea
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Miyoung Choi
- Division of Healthcare Technology Assessment Research, National Evidence-based Healthcare Collaborating Agency, Seoul, Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine, Chuncheon, Korea
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14
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Subtirelu RC, Teichner EM, Su Y, Al-Daoud O, Patel M, Patil S, Writer M, Werner T, Revheim ME, Høilund-Carlsen PF, Alavi A. Aging and Cerebral Glucose Metabolism: 18F-FDG-PET/CT Reveals Distinct Global and Regional Metabolic Changes in Healthy Patients. Life (Basel) 2023; 13:2044. [PMID: 37895426 PMCID: PMC10608490 DOI: 10.3390/life13102044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/01/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
Alterations in cerebral glucose metabolism can be indicative of both normal and pathological aging processes. In this retrospective study, we evaluated global and regional neurological glucose metabolism in 73 healthy individuals (mean age: 35.8 ± 13.1 years; 82.5% female) using 18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). This population exhibited a low prevalence of comorbidities associated with cerebrovascular risk factors. We utilized 18F-FDG-PET/CT imaging and quantitative regional analysis to assess cerebral glucose metabolism. A statistically significant negative correlation was found between age and the global standardized uptake value mean (SUVmean) of FDG uptake (p = 0.000795), indicating a decrease in whole-brain glucose metabolism with aging. Furthermore, region-specific analysis identified significant correlations in four cerebral regions, with positive correlations in the basis pontis, cerebellar hemisphere, and cerebellum and a negative correlation in the lateral orbital gyrus. These results were further confirmed via linear regression analysis. Our findings reveal a nuanced understanding of how aging affects glucose metabolism in the brain, providing insight into normal neurology. The study underscores the utility of 18F-FDG-PET/CT as a sensitive tool in monitoring these metabolic changes, highlighting its potential for the early detection of neurological diseases and disorders related to aging.
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Affiliation(s)
| | - Eric Michael Teichner
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA 19144, USA
| | - Yvonne Su
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Omar Al-Daoud
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Milan Patel
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shiv Patil
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA 19144, USA
| | - Milo Writer
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Thomas Werner
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Mona-Elisabeth Revheim
- The Intervention Center, Division of Technology and Innovation, Oslo University Hospital, Sognsvannsveien 20, 0372 Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Problemveien 7, 0315 Oslo, Norway
| | - Poul Flemming Høilund-Carlsen
- Department of Nuclear Medicine, Odense University Hospital, 5000 Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, 5230 Odense, Denmark
| | - Abass Alavi
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
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15
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Bhujbal SS, Kad MM, Patole VC. Recent diagnostic techniques for the detection of Alzheimer's disease: a short review. Ir J Med Sci 2023; 192:2417-2426. [PMID: 36525239 DOI: 10.1007/s11845-022-03244-y] [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: 07/28/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022]
Abstract
Alzheimer's disease (AD) is a neurological condition that affects millions of individuals around the world and for which there are few effective therapies. Dementia is characterized by the formation of senile plaques and neurofibrillary tangles, which is followed by neurotoxicity, which results in memory loss and mortality. Pathogenesis occurs several years before the onset of disease. As the disease-modifying drugs are most effective in the early stages of Alzheimer's disease, biomarkers for early detection of disease and their development are crucial. This review discusses the diagnostic utility, benefits, and limitations of traditional techniques such as neuroimaging, cognitive testing, positron emission tomography, and biomarkers, as well as the novel techniques such as artificial intelligence, machine learning, immunotherapy, and blood test approaches for early detection, understanding, and treatment of AD.
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Affiliation(s)
- Santosh S Bhujbal
- Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, Pimpri, Pune, India.
| | - Minal M Kad
- Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, Pimpri, Pune, India
| | - Vinita C Patole
- Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, Pimpri, Pune, India
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16
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Chouliaras L, O'Brien JT. The use of neuroimaging techniques in the early and differential diagnosis of dementia. Mol Psychiatry 2023; 28:4084-4097. [PMID: 37608222 PMCID: PMC10827668 DOI: 10.1038/s41380-023-02215-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 07/27/2023] [Accepted: 08/03/2023] [Indexed: 08/24/2023]
Abstract
Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.
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Affiliation(s)
- Leonidas Chouliaras
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Specialist Dementia and Frailty Service, Essex Partnership University NHS Foundation Trust, St Margaret's Hospital, Epping, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK.
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
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17
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Dennison J, Mendez A, Szeto A, Lohse I, Wahlestedt C, Volmar CH. Low-Dose Chidamide Treatment Displays Sex-Specific Differences in the 3xTg-AD Mouse. Biomolecules 2023; 13:1324. [PMID: 37759724 PMCID: PMC10526199 DOI: 10.3390/biom13091324] [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: 06/13/2023] [Revised: 08/21/2023] [Accepted: 08/24/2023] [Indexed: 09/29/2023] Open
Abstract
Epigenetic compounds have become attractive small molecules for targeting the multifaceted aspects of Alzheimer's disease (AD). Although AD disproportionately affects women, most of the current literature investigating epigenetic compounds for the treatment of AD do not report sex-specific results. This is remarkable because there is rising evidence that epigenetic compounds intrinsically affect males and females differently. This manuscript explores the sexual dimorphism observed after chronic, low-dose administration of a clinically relevant histone deacetylase inhibitor, chidamide (Tucidinostat), in the 3xTg-AD mouse model. We found that chidamide treatment significantly improves glucose tolerance and increases expression of glucose transporters in the brain of males. We also report a decrease in total tau in chidamide-treated mice. Differentially expressed genes in chidamide-treated mice were much greater in males than females. Genes involved in the neuroinflammatory pathway and amyloid processing pathway were mostly upregulated in chidamide-treated males while downregulated in chidamide-treated females. This work highlights the need for drug discovery projects to consider sex as a biological variable to facilitate translation.
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Affiliation(s)
- Jessica Dennison
- Department of Psychiatry & Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA; (J.D.)
- Center for Therapeutic Innovation, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Armando Mendez
- Diabetes Research Institute, Division of Endocrinology, Diabetes, and Metabolism, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Angela Szeto
- Diabetes Research Institute, Division of Endocrinology, Diabetes, and Metabolism, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Ines Lohse
- Department of Psychiatry & Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA; (J.D.)
- Center for Therapeutic Innovation, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Claes Wahlestedt
- Department of Psychiatry & Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA; (J.D.)
- Center for Therapeutic Innovation, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Claude-Henry Volmar
- Department of Psychiatry & Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA; (J.D.)
- Center for Therapeutic Innovation, University of Miami Miller School of Medicine, Miami, FL 33136, USA
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18
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Raut S, Bhalerao A, Powers M, Gonzalez M, Mancuso S, Cucullo L. Hypometabolism, Alzheimer's Disease, and Possible Therapeutic Targets: An Overview. Cells 2023; 12:2019. [PMID: 37626828 PMCID: PMC10453773 DOI: 10.3390/cells12162019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/19/2023] [Accepted: 08/06/2023] [Indexed: 08/27/2023] Open
Abstract
The brain is a highly dynamic organ that requires a constant energy source to function normally. This energy is mostly supplied by glucose, a simple sugar that serves as the brain's principal fuel source. Glucose transport across the blood-brain barrier (BBB) is primarily controlled via sodium-independent facilitated glucose transport, such as by glucose transporter 1 (GLUT1) and 3 (GLUT3). However, other glucose transporters, including GLUT4 and the sodium-dependent transporters SGLT1 and SGLT6, have been reported in vitro and in vivo. When the BBB endothelial layer is crossed, neurons and astrocytes can absorb the glucose using their GLUT1 and GLUT3 transporters. Glucose then enters the glycolytic pathway and is metabolized into adenosine triphosphate (ATP), which supplies the energy to support cellular functions. The transport and metabolism of glucose in the brain are impacted by several medical conditions, which can cause neurological and neuropsychiatric symptoms. Alzheimer's disease (AD), Parkinson's disease (PD), epilepsy, traumatic brain injury (TBI), schizophrenia, etc., are a few of the most prevalent disorders, characterized by a decline in brain metabolism or hypometabolism early in the course of the disease. Indeed, AD is considered a metabolic disorder related to decreased brain glucose metabolism, involving brain insulin resistance and age-dependent mitochondrial dysfunction. Although the conventional view is that reduced cerebral metabolism is an effect of neuronal loss and consequent brain atrophy, a growing body of evidence points to the opposite, where hypometabolism is prodromal or at least precedes the onset of brain atrophy and the manifestation of clinical symptoms. The underlying processes responsible for these glucose transport and metabolic abnormalities are complicated and remain poorly understood. This review article provides a comprehensive overview of the current understanding of hypometabolism in AD and potential therapeutic targets.
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Affiliation(s)
- Snehal Raut
- Department of Foundational Medical Studies, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA; (S.R.); (A.B.); (M.G.); (S.M.)
| | - Aditya Bhalerao
- Department of Foundational Medical Studies, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA; (S.R.); (A.B.); (M.G.); (S.M.)
| | - Michael Powers
- Department of Biological and Biomedical Sciences, Oakland University, Rochester, MI 48309, USA;
| | - Minelly Gonzalez
- Department of Foundational Medical Studies, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA; (S.R.); (A.B.); (M.G.); (S.M.)
| | - Salvatore Mancuso
- Department of Foundational Medical Studies, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA; (S.R.); (A.B.); (M.G.); (S.M.)
| | - Luca Cucullo
- Department of Foundational Medical Studies, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA; (S.R.); (A.B.); (M.G.); (S.M.)
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19
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Iosifescu DV, Song X, Gersten MB, Adib A, Cho Y, Collins KM, Yates KF, Hurtado-Puerto AM, McEachern KM, Osorio RS, Cassano P. Protocol Report on the Transcranial Photobiomodulation for Alzheimer's Disease (TRAP-AD) Study. Healthcare (Basel) 2023; 11:2017. [PMID: 37510458 PMCID: PMC10378818 DOI: 10.3390/healthcare11142017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 07/04/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Alzheimer's disease's (AD) prevalence is projected to increase as the population ages and current treatments are minimally effective. Transcranial photobiomodulation (t-PBM) with near-infrared (NIR) light penetrates into the cerebral cortex, stimulates the mitochondrial respiratory chain, and increases cerebral blood flow. Preliminary data suggests t-PBM may be efficacious in improving cognition in people with early AD and amnestic mild cognitive impairment (aMCI). METHODS In this randomized, double-blind, placebo-controlled study with aMCI and early AD participants, we will test the efficacy, safety, and impact on cognition of 24 sessions of t-PBM delivered over 8 weeks. Brain mechanisms of t-PBM in this population will be explored by testing whether the baseline tau burden (measured with 18F-MK6240), or changes in mitochondrial function over 8 weeks (assessed with 31P-MRSI), moderates the changes observed in cognitive functions after t-PBM therapy. We will also use changes in the fMRI Blood-Oxygenation-Level-Dependent (BOLD) signal after a single treatment to demonstrate t-PBM-dependent increases in prefrontal cortex blood flow. CONCLUSION This study will test whether t-PBM, a low-cost, accessible, and user-friendly intervention, has the potential to improve cognition and function in an aMCI and early AD population.
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Affiliation(s)
- Dan V. Iosifescu
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; (K.M.C.); (K.F.Y.); (R.S.O.)
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA; (X.S.); (A.A.)
| | - Xiaotong Song
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA; (X.S.); (A.A.)
| | - Maia B. Gersten
- Department of Psychiatry, Division of Neuropsychiatry, Massachusetts General Hospital, Boston, MA 02129, USA; (M.B.G.); (Y.C.); (A.M.H.-P.); (K.M.M.); (P.C.)
| | - Arwa Adib
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA; (X.S.); (A.A.)
| | - Yoonju Cho
- Department of Psychiatry, Division of Neuropsychiatry, Massachusetts General Hospital, Boston, MA 02129, USA; (M.B.G.); (Y.C.); (A.M.H.-P.); (K.M.M.); (P.C.)
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
| | - Katherine M. Collins
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; (K.M.C.); (K.F.Y.); (R.S.O.)
| | - Kathy F. Yates
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; (K.M.C.); (K.F.Y.); (R.S.O.)
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA; (X.S.); (A.A.)
| | - Aura M. Hurtado-Puerto
- Department of Psychiatry, Division of Neuropsychiatry, Massachusetts General Hospital, Boston, MA 02129, USA; (M.B.G.); (Y.C.); (A.M.H.-P.); (K.M.M.); (P.C.)
| | - Kayla M. McEachern
- Department of Psychiatry, Division of Neuropsychiatry, Massachusetts General Hospital, Boston, MA 02129, USA; (M.B.G.); (Y.C.); (A.M.H.-P.); (K.M.M.); (P.C.)
| | - Ricardo S. Osorio
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; (K.M.C.); (K.F.Y.); (R.S.O.)
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA; (X.S.); (A.A.)
| | - Paolo Cassano
- Department of Psychiatry, Division of Neuropsychiatry, Massachusetts General Hospital, Boston, MA 02129, USA; (M.B.G.); (Y.C.); (A.M.H.-P.); (K.M.M.); (P.C.)
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
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20
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Carlos AF, Josephs KA. The Role of Clinical Assessment in the Era of Biomarkers. Neurotherapeutics 2023; 20:1001-1018. [PMID: 37594658 PMCID: PMC10457273 DOI: 10.1007/s13311-023-01410-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/14/2023] [Indexed: 08/19/2023] Open
Abstract
Hippocratic Medicine revolved around the three main principles of patient, disease, and physician and promoted the systematic observation of patients, rational reasoning, and interpretation of collected information. Although these remain the cardinal features of clinical assessment today, Medicine has evolved from a more physician-centered to a more patient-centered approach. Clinical assessment allows physicians to encounter, observe, evaluate, and connect with patients. This establishes the patient-physician relationship and facilitates a better understanding of the patient-disease relationship, as the ultimate goal is to diagnose, prognosticate, and treat. Biomarkers are at the core of the more disease-centered approach that is currently revolutionizing Medicine as they provide insight into the underlying disease pathomechanisms and biological changes. Genetic, biochemical, radiographic, and clinical biomarkers are currently used. Here, we define a seven-level theoretical construct for the utility of biomarkers in neurodegenerative diseases. Level 1-3 biomarkers are considered supportive of clinical assessment, capable of detecting susceptibility or risk factors, non-specific neurodegeneration or dysfunction, and/or changes at the individual level which help increase clinical diagnostic accuracy and confidence. Level 4-7 biomarkers have the potential to surpass the utility of clinical assessment through detection of early disease stages and prediction of underlying pathology. In neurodegenerative diseases, biomarkers can potentiate, but cannot substitute, clinical assessment. In this current era, aside from adding to the discovery, evaluation/validation, and implementation of more biomarkers, clinical assessment remains crucial to maintaining the personal, humanistic, and sociocultural aspects of patient care. We would argue that clinical assessment is a custom that should never go obsolete.
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Affiliation(s)
- Arenn F Carlos
- Department of Neurology, Mayo Clinic, 200 1st St. S.W., Rochester, MN, 55905, USA.
| | - Keith A Josephs
- Department of Neurology, Mayo Clinic, 200 1st St. S.W., Rochester, MN, 55905, USA
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21
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Cogswell PM, Fan AP. Multimodal comparisons of QSM and PET in neurodegeneration and aging. Neuroimage 2023; 273:120068. [PMID: 37003447 PMCID: PMC10947478 DOI: 10.1016/j.neuroimage.2023.120068] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/17/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) has been used to study susceptibility changes that may occur based on tissue composition and mineral deposition. Iron is a primary contributor to changes in magnetic susceptibility and of particular interest in applications of QSM to neurodegeneration and aging. Iron can contribute to neurodegeneration through inflammatory processes and via interaction with aggregation of disease-related proteins. To better understand the local susceptibility changes observed on QSM, its signal has been studied in association with other imaging metrics such as positron emission tomography (PET). The associations of QSM and PET may provide insight into the pathophysiology of disease processes, such as the role of iron in aging and neurodegeneration, and help to determine the diagnostic utility of QSM as an indirect indicator of disease processes typically evaluated with PET. In this review we discuss the proposed mechanisms and summarize prior studies of the associations of QSM and amyloid PET, tau PET, TSPO PET, FDG-PET, 15O-PET, and F-DOPA PET in evaluation of neurologic diseases with a focus on aging and neurodegeneration.
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Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.
| | - Audrey P Fan
- Department of Biomedical Engineering and Department of Neurology, University of California, Davis, 1590 Drew Avenue, Davis, CA 95618, USA
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22
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Aranha MR, Coutinho AM, Carneiro CDG, Pastorello BF, Studart-Neto A, Guariglia CC, Tsunemi MH, Moreira ELS, Ianof JN, Anghinah R, Nitrini R, Cerri GG, Fortea J, Buchpiguel CA, Leite CC. Brain glucose metabolism and gray matter volume in retired professional soccer players: a cross-sectional [18F]FDG-PET/MRI study. ARQUIVOS DE NEURO-PSIQUIATRIA 2023; 81:433-443. [PMID: 37257463 DOI: 10.1055/s-0043-1768666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
BACKGROUND Professional soccer athletes are exposed to repetitive head impacts and are at risk of developing chronic traumatic encephalopathy. OBJECTIVE To evaluate regional brain glucose metabolism (rBGM) and gray matter (GM) volume in retired soccer players (RSPs). METHODS Male RSPs and age and sex-matched controls prospectively enrolled between 2017 and 2019 underwent neurological and neuropsychological evaluations, brain MRI and [18F]FDG-PET in a 3.0-Tesla PET/MRI scanner. Visual analysis was performed by a blinded neuroradiologist and a blinded nuclear physician. Regional brain glucose metabolism and GM volume were assessed using SPM8 software. Groups were compared using appropriate statistical tests available at SPM8 and R. RESULTS Nineteen RSPs (median [IQR]: 62 [50-64.5] years old) and 20 controls (60 [48-73] years old) were included. Retired soccer players performed worse on mini-mental state examination, digit span, clock drawing, phonemic and semantic verbal fluency tests, and had reduced rBGM in the left temporal pole (pFDR = 0.008) and the anterior left middle temporal gyrus (pFDR = 0.043). Semantic verbal fluency correlated with rBGM in the right hippocampus, left temporal pole, and posterior left middle temporal gyrus (p ≤ 0.042). Gray matter volume reduction was observed in similar anatomic regions but was less extensive and did not survive correction for multiple comparisons (pFDR ≥ 0.085). Individual [18F]FDG-PET visual analysis revealed seven RSPs with overt hypometabolism in the medial and lateral temporal lobes, frontal lobes, and temporoparietal regions. Retired soccer players had a higher prevalence of septum pellucidum abnormalities on MRI. CONCLUSION Retired soccer players had reduced rBGM and GM volume in the temporal lobes and septum pellucidum abnormalities, findings possibly related to repetitive head impacts.
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Affiliation(s)
- Mateus Rozalem Aranha
- Universidade de São Paulo, Faculdade de Medicina, Instituto de Radiologia, São Paulo SP, Brazil
- Universidade de São Paulo, Faculdade de Medicina, Centro de Medicina Nuclear, São Paulo SP, Brazil
- Universidad Autónoma de Barcelona, Institut de Recerca, Hospital de la Santa Creu i Sant Pau, Facultad de Medicina, Barcelona, Spain
| | - Artur Martins Coutinho
- Universidade de São Paulo, Faculdade de Medicina, Centro de Medicina Nuclear, São Paulo SP, Brazil
| | - Camila de Godoi Carneiro
- Universidade de São Paulo, Faculdade de Medicina, Centro de Medicina Nuclear, São Paulo SP, Brazil
| | | | - Adalberto Studart-Neto
- Universidade de São Paulo, Departamento de Neurologia, Faculdade de Medicina, São Paulo SP, Brazil
| | - Carla Cristina Guariglia
- Universidade de São Paulo, Departamento de Neurologia, Faculdade de Medicina, São Paulo SP, Brazil
| | - Miriam Harumi Tsunemi
- Universidade Estadual Paulista, Departamento de Bioestatística, Instituto de Biociências, Botucatu SP, Brazil
| | | | - Jéssica Natuline Ianof
- Universidade de São Paulo, Departamento de Neurologia, Faculdade de Medicina, São Paulo SP, Brazil
| | - Renato Anghinah
- Universidade de São Paulo, Departamento de Neurologia, Faculdade de Medicina, São Paulo SP, Brazil
| | - Ricardo Nitrini
- Universidade de São Paulo, Departamento de Neurologia, Faculdade de Medicina, São Paulo SP, Brazil
| | - Giovanni Guido Cerri
- Universidade de São Paulo, Faculdade de Medicina, Instituto de Radiologia, São Paulo SP, Brazil
| | - Juan Fortea
- Universidad Autónoma de Barcelona, Institut de Recerca, Hospital de la Santa Creu i Sant Pau, Facultad de Medicina, Barcelona, Spain
- Fundación Catalana de Síndrome de Down, Barcelona, Spain
- Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas, Madrid, Spain
| | | | - Claudia Costa Leite
- Universidade de São Paulo, Faculdade de Medicina, Instituto de Radiologia, São Paulo SP, Brazil
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23
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Juras JA, Webb MB, Young LE, Markussen KH, Hawkinson TR, Buoncristiani MD, Bolton KE, Coburn PT, Williams MI, Sun LP, Sanders WC, Bruntz RC, Conroy LR, Wang C, Gentry MS, Smith BN, Sun RC. In situ microwave fixation provides an instantaneous snapshot of the brain metabolome. CELL REPORTS METHODS 2023; 3:100455. [PMID: 37159672 PMCID: PMC10163000 DOI: 10.1016/j.crmeth.2023.100455] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 02/14/2023] [Accepted: 03/27/2023] [Indexed: 05/11/2023]
Abstract
Brain glucose metabolism is highly heterogeneous among brain regions and continues postmortem. In particular, we demonstrate exhaustion of glycogen and glucose and an increase in lactate production during conventional rapid brain resection and preservation by liquid nitrogen. In contrast, we show that these postmortem changes are not observed with simultaneous animal sacrifice and in situ fixation with focused, high-power microwave. We further employ microwave fixation to define brain glucose metabolism in the mouse model of streptozotocin-induced type 1 diabetes. Using both total pool and isotope tracing analyses, we identified global glucose hypometabolism in multiple brain regions, evidenced by reduced 13C enrichment into glycogen, glycolysis, and the tricarboxylic acid (TCA) cycle. Reduced glucose metabolism correlated with a marked decrease in GLUT2 expression and several metabolic enzymes in unique brain regions. In conclusion, our study supports the incorporation of microwave fixation for more accurate studies of brain metabolism in rodent models.
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Affiliation(s)
- Jelena A. Juras
- Department of Neuroscience, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Madison B. Webb
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Lyndsay E.A. Young
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
| | - Kia H. Markussen
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Tara R. Hawkinson
- Department of Neuroscience, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
- Department of Biochemistry and Molecular Biology, University of Florida, College of Medicine, Gainesville, FL 32611, USA
| | - Michael D. Buoncristiani
- Department of Neuroscience, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Kayli E. Bolton
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Peyton T. Coburn
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Meredith I. Williams
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Lisa P.Y. Sun
- Department of Neuroscience, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
| | - William C. Sanders
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Ronald C. Bruntz
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Lindsey R. Conroy
- Department of Neuroscience, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
| | - Chi Wang
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
- Division of Biostatics, Department of Internal Medicine, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
| | - Matthew S. Gentry
- Department of Molecular and Cellular Biochemistry, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
- Department of Biochemistry and Molecular Biology, University of Florida, College of Medicine, Gainesville, FL 32611, USA
- Center for Advanced Spatial Biomolecule Research, University of Florida, College of Medicine, Gainesville, FL 32611, USA
| | - Bret N. Smith
- Department of Neuroscience, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
- Department of Biomedical Sciences, Colorado State University, Fort Collins, CO 80523, USA
| | - Ramon C. Sun
- Department of Neuroscience, University of Kentucky, College of Medicine, Lexington, KY 40536, USA
- Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA
- Department of Biochemistry and Molecular Biology, University of Florida, College of Medicine, Gainesville, FL 32611, USA
- Center for Advanced Spatial Biomolecule Research, University of Florida, College of Medicine, Gainesville, FL 32611, USA
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24
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Navarro D, Gasparyan A, Martí Martínez S, Díaz Marín C, Navarrete F, García Gutiérrez MS, Manzanares J. Methods to Identify Cognitive Alterations from Animals to Humans: A Translational Approach. Int J Mol Sci 2023; 24:ijms24087653. [PMID: 37108813 PMCID: PMC10143375 DOI: 10.3390/ijms24087653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 04/11/2023] [Accepted: 04/19/2023] [Indexed: 04/29/2023] Open
Abstract
The increasing prevalence of cognitive dysfunction and dementia in developed countries, associated with population aging, has generated great interest in characterizing and quantifying cognitive deficits in these patients. An essential tool for accurate diagnosis is cognitive assessment, a lengthy process that depends on the cognitive domains analyzed. Cognitive tests, functional capacity scales, and advanced neuroimaging studies explore the different mental functions in clinical practice. On the other hand, animal models of human diseases with cognitive impairment are essential for understanding disease pathophysiology. The study of cognitive function using animal models encompasses multiple dimensions, and deciding which ones to investigate is necessary to select the most appropriate and specific tests. Therefore, this review studies the main cognitive tests for assessing cognitive deficits in patients with neurodegenerative diseases. Cognitive tests, the most commonly used functional capacity scales, and those resulting from previous evidence are considered. In addition, the leading behavioral tests that assess cognitive functions in animal models of disorders with cognitive impairment are highlighted.
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Affiliation(s)
- Daniela Navarro
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Avda de Ramón y Cajal s/n, San Juan de Alicante, 03550 Alicante, Spain
- Redes de Investigación Cooperativa Orientada a Resultados en Salud (RICORS), Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Instituto de Salud Carlos III, MICINN and FEDER, 28029 Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010 Alicante, Spain
| | - Ani Gasparyan
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Avda de Ramón y Cajal s/n, San Juan de Alicante, 03550 Alicante, Spain
- Redes de Investigación Cooperativa Orientada a Resultados en Salud (RICORS), Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Instituto de Salud Carlos III, MICINN and FEDER, 28029 Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010 Alicante, Spain
| | - Silvia Martí Martínez
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010 Alicante, Spain
- Servicio de Neurología, Hospital General Dr. Balmis, 03010 Alicante, Spain
| | - Carmen Díaz Marín
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010 Alicante, Spain
- Servicio de Neurología, Hospital General Dr. Balmis, 03010 Alicante, Spain
| | - Francisco Navarrete
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Avda de Ramón y Cajal s/n, San Juan de Alicante, 03550 Alicante, Spain
- Redes de Investigación Cooperativa Orientada a Resultados en Salud (RICORS), Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Instituto de Salud Carlos III, MICINN and FEDER, 28029 Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010 Alicante, Spain
| | - María Salud García Gutiérrez
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Avda de Ramón y Cajal s/n, San Juan de Alicante, 03550 Alicante, Spain
- Redes de Investigación Cooperativa Orientada a Resultados en Salud (RICORS), Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Instituto de Salud Carlos III, MICINN and FEDER, 28029 Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010 Alicante, Spain
| | - Jorge Manzanares
- Instituto de Neurociencias, Universidad Miguel Hernández-CSIC, Avda de Ramón y Cajal s/n, San Juan de Alicante, 03550 Alicante, Spain
- Redes de Investigación Cooperativa Orientada a Resultados en Salud (RICORS), Red de Investigación en Atención Primaria de Adicciones (RIAPAd), Instituto de Salud Carlos III, MICINN and FEDER, 28029 Madrid, Spain
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010 Alicante, Spain
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25
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Yang Z, Cummings JL, Kinney JW, Cordes D. Accelerated hypometabolism with disease progression associated with faster cognitive decline among amyloid positive patients. Front Neurosci 2023; 17:1151820. [PMID: 37123373 PMCID: PMC10140339 DOI: 10.3389/fnins.2023.1151820] [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: 01/26/2023] [Accepted: 03/22/2023] [Indexed: 05/02/2023] Open
Abstract
Objective To evaluate the progression of brain glucose metabolism among participants with biological signature of Alzheimer's disease (AD) and its relevance to cognitive decline. Method We studied 602 amyloid positive individuals who underwent 18F-fluorodeoxyglucose PET (FDG-PET) scan, 18F-AV-45 amyloid PET (AV45-PET) scan, structural MRI scan and neuropsychological examination, including 116 cognitively normal (CN) participants, 314 participants diagnosed as mild cognitive impairment (MCI), and 172 participants diagnosed as AD dementia. The first FDG-PET scan satisfying the inclusion criteria was considered as the baseline scan. Cross-sectional analysis were conducted with the baseline FDG-PET data to compare the regional differences between diagnostic groups after adjusting confounding factors. Among these participants, 229 participants (55 CN, 139 MCI, and 35 AD dementia) had two-year follow-up FDG-PET data available. Regional glucose metabolism was computed and the progression rates of regional glucose metabolism were derived from longitudinal FDG-PET scans. Then the group differences of regional progression rates were examined to assess whether glucose metabolism deficit accelerates or becomes stable with disease progression. The association of cognitive decline rate with baseline regional glucose metabolism, and progression rate in longitudinal data, were evaluated. Results Participants with AD dementia showed substantial glucose metabolism deficit than CN and MCI at left hippocampus, in addition to the traditionally reported frontal and parietal-temporal lobe. More substantial metabolic change was observed with the contrast AD - MCI than the contrast MCI - CN, even after adjusting time duration since cognitive symptom onset. With the longitudinal data, glucose metabolism was observed to decline the most rapidly in the AD dementia group and at a slower rate in MCI. Lower regional glucose metabolism was correlated to faster cognitive decline rate with mild-moderate correlations, and the progression rate was correlated to cognitive decline rate with moderate-large correlations. Discussion and conclusion Hippocampus was identified to experience hypometabolism in AD pathology. Hypometabolism accelerates with disease progression toward AD dementia. FDG-PET, particularly longitudinal scans, could potentially help predict how fast cognition declines and assess the impact of treatment in interventional trials.
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Affiliation(s)
- Zhengshi Yang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
- Department of Brain Health, University of Nevada, Las Vegas, Las Vegas, NV, United States
| | - Jeffrey L. Cummings
- Department of Brain Health, University of Nevada, Las Vegas, Las Vegas, NV, United States
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada, Las Vegas, Las Vegas, NV, United States
| | - Jefferson W. Kinney
- Department of Brain Health, University of Nevada, Las Vegas, Las Vegas, NV, United States
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada, Las Vegas, Las Vegas, NV, United States
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
- Department of Brain Health, University of Nevada, Las Vegas, Las Vegas, NV, United States
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, United States
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26
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Petrovskaya A, Tverskoi A, Medvedeva A, Nazarova M. Is blood-brain barrier a probable mediator of non-invasive brain stimulation effects on Alzheimer's disease? Commun Biol 2023; 6:416. [PMID: 37059824 PMCID: PMC10104838 DOI: 10.1038/s42003-023-04717-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 04/16/2023] Open
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disease with no existing treatment leading to full recovery. The blood-brain barrier (BBB) breakdown usually precedes the advent of first symptoms in AD and accompanies the progression of the disease. At the same time deliberate BBB opening may be beneficial for drug delivery in AD. Non-invasive brain stimulation (NIBS) techniques, primarily transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have shown multiple evidence of being able to alleviate symptoms of AD. Currently, TMS/tDCS mechanisms are mostly investigated in terms of their neuronal effects, while their possible non-neuronal effects, including mitigation of the BBB disruption, are less studied. We argue that studies of TMS/tDCS effects on the BBB in AD are necessary to boost the effectiveness of neuromodulation in AD. Moreover, such studies are important considering the safety issues of TMS/tDCS use in the advanced AD stages when the BBB is usually dramatically deteriorated. Here, we elucidate the evidence of NIBS-induced BBB opening and closing in various models from in vitro to humans, and highlight its importance in AD.
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Affiliation(s)
- Aleksandra Petrovskaya
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia.
| | - Artem Tverskoi
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Angela Medvedeva
- Department of Chemistry, Rice University, Houston, TX, 77005, US
| | - Maria Nazarova
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, 101000, Russian Federation
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27
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Ahmadi K, Pereira JB, Berron D, Vogel J, Ingala S, Strandberg OT, Janelidze S, Barkhof F, Pfeuffer J, Knutsson L, van Westen D, Palmqvist S, Mutsaerts HJ, Hansson O. Gray matter hypoperfusion is a late pathological event in the course of Alzheimer's disease. J Cereb Blood Flow Metab 2023; 43:565-580. [PMID: 36412244 PMCID: PMC10063832 DOI: 10.1177/0271678x221141139] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Several studies have shown decreased cerebral blood flow (CBF) in Alzheimer's disease (AD). However, the role of hypoperfusion in the disease pathogenesis remains unclear. Combining arterial spin labeling MRI, PET, and CSF biomarkers, we investigated the associations between gray matter (GM)-CBF and the key mechanisms in AD including amyloid-β (Aβ) and tau pathology, synaptic and axonal degeneration. Further, we applied a disease progression modeling to characterize the temporal sequence of different AD biomarkers. Lower perfusion was observed in temporo-occipito-parietal cortex in the Aβ-positive cognitively impaired compared to both Aβ-negative and Aβ-positive cognitively unimpaired individuals. In participants along the AD spectrum, GM-CBF was associated with tau, synaptic and axonal dysfunction, but not Aβ in similar cortical regions. Axonal degeneration was further associated with hypoperfusion in cognitively unimpaired individuals. Disease progression modeling revealed that GM-CBF disruption Followed the abnormality of biomarkers of Aβ, tau and brain atrophy. These findings indicate that tau tangles and neurodegeneration are more closely connected with GM-CBF changes than Aβ pathology. Although subjected to the sensitivity of the employed neuroimaging techniques and the modeling approach, these findings suggest that hypoperfusion might not be an early event associated with the build-up of Aβ in preclinical phase of AD.
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Affiliation(s)
- Khazar Ahmadi
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Joana B Pereira
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - David Berron
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Jacob Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location VUmc, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Olof T Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location VUmc, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Queen's Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Josef Pfeuffer
- Application Development, Siemens Healthcare, Erlangen, Germany
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden.,The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Danielle van Westen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Diagnostic Radiology, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Henk Jmm Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location VUmc, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Queen's Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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28
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Sanz Perl Y, Fittipaldi S, Gonzalez Campo C, Moguilner S, Cruzat J, Fraile-Vazquez ME, Herzog R, Kringelbach ML, Deco G, Prado P, Ibanez A, Tagliazucchi E. Model-based whole-brain perturbational landscape of neurodegenerative diseases. eLife 2023; 12:e83970. [PMID: 36995213 PMCID: PMC10063230 DOI: 10.7554/elife.83970] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/15/2023] [Indexed: 03/31/2023] Open
Abstract
The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of reproducing whole-brain functional connectivity in patients diagnosed with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD- and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neurodegeneration.
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Affiliation(s)
- Yonatan Sanz Perl
- Department of Physics, University of Buenos AiresBuenos AiresArgentina
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu FabraBarcelonaSpain
| | - Sol Fittipaldi
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
| | - Cecilia Gonzalez Campo
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
| | - Sebastián Moguilner
- Global Brain Health Institute, University of California, San FranciscoSan FranciscoUnited States
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
| | - Josephine Cruzat
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu FabraBarcelonaSpain
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
| | | | - Rubén Herzog
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
| | - Morten L Kringelbach
- Department of Psychiatry, University of OxfordOxfordUnited Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus UniversityÅrhusDenmark
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBragaPortugal
- Centre for Eudaimonia and Human Flourishing, University of OxfordOxfordUnited Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu FabraBarcelonaSpain
- Department of Information and Communication Technologies, Universitat Pompeu FabraBarcelonaSpain
- Institució Catalana de la Recerca i Estudis Avancats (ICREA)BarcelonaSpain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- School of Psychological Sciences, Monash UniversityClaytonAustralia
| | - Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San SebastiánSantiagoChile
| | - Agustin Ibanez
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
- Global Brain Health Institute, University of California, San FranciscoSan FranciscoUnited States
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
- Trinity College Institute of Neuroscience (TCIN), Trinity College DublinDublinIreland
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos AiresBuenos AiresArgentina
- National Scientific and Technical Research Council (CONICET), CABABuenos AiresArgentina
- Cognitive Neuroscience Center (CNC), Universidad de San AndrésBuenos AiresArgentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo IbáñezSantiagoChile
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29
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Duan J, Liu Y, Wu H, Wang J, Chen L, Chen CLP. Broad learning for early diagnosis of Alzheimer's disease using FDG-PET of the brain. Front Neurosci 2023; 17:1137567. [PMID: 36992851 PMCID: PMC10040750 DOI: 10.3389/fnins.2023.1137567] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/13/2023] [Indexed: 03/14/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease, and the development of AD is irreversible. However, preventive measures in the presymptomatic stage of AD can effectively slow down deterioration. Fluorodeoxyglucose positron emission tomography (FDG-PET) can detect the metabolism of glucose in patients' brains, which can help to identify changes related to AD before brain damage occurs. Machine learning is useful for early diagnosis of patients with AD using FDG-PET, but it requires a sufficiently large dataset, and it is easy for overfitting to occur in small datasets. Previous studies using machine learning for early diagnosis with FDG-PET have either involved the extraction of elaborately handcrafted features or validation on a small dataset, and few studies have explored the refined classification of early mild cognitive impairment (EMCI) and late mild cognitive impairment (LMCI). This article presents a broad network-based model for early diagnosis of AD (BLADNet) through PET imaging of the brain; this method employs a novel broad neural network to enhance the features of FDG-PET extracted via 2D CNN. BLADNet can search for information over a broad space through the addition of new BLS blocks without retraining of the whole network, thus improving the accuracy of AD classification. Experiments conducted on a dataset containing 2,298 FDG-PET images of 1,045 subjects from the ADNI database demonstrate that our methods are superior to those used in previous studies on early diagnosis of AD with FDG-PET. In particular, our methods achieved state-of-the-art results in EMCI and LMCI classification with FDG-PET.
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Affiliation(s)
- Junwei Duan
- College of Information Science and Technology, Jinan University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Jinan University, Guangzhou, China
- *Correspondence: Junwei Duan
| | - Yang Liu
- College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Huanhua Wu
- Department of Nuclear Medicine and PET/CT-MRI Centre, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jing Wang
- School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
- Jing Wang
| | - Long Chen
- Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - C. L. Philip Chen
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
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30
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Ren S, Li J, Huang L, Huang Q, Chen K, Hu J, Jessen F, Hu X, Jiang D, Zhu L, Wang X, Guan Y, Hua F, Guo Q, Xie F. Brain Functional Alterations and Association with Cognition in People with Preclinical Subjective Cognitive Decline and Objective Subtle Cognitive Difficulties. Neuroscience 2023; 513:137-144. [PMID: 36634906 DOI: 10.1016/j.neuroscience.2023.01.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 12/24/2022] [Accepted: 01/03/2023] [Indexed: 01/11/2023]
Abstract
Subjective cognitive decline (SCD) and objective subtle cognitive difficulties (Obj-SCD) are considered the initial stages of aberrant cognition prior to mild cognitive impairment (MCI) due to Alzheimer's disease (AD). We aimed to determine the difference of brain function of SCD and Obj-SCD, furthermore, to figure out which one could be the marker of early AD. One hundred and eighty-five participants were enrolled in this study to determine the amyloid pathology and glucose metabolism changes in SCD and Obj-SCD. The association of amyloid deposition and glucose metabolism with cognitive domains were also investigated. Obj-SCD displayed significantly increased amyloid deposition in frontal and temporal lobes compared to SCD and normal cognitive control (NCC). No difference of amyloid deposition between SCD and NCC, and no difference of glucose metabolism among the three groups were observed. Amyloid deposition was associated with function of memory, language and executive domains, and glucose metabolism was only associated with executive function in Obj-SCD. Amyloid deposition was only associated with executive function in SCD. Obj-SCD could be the early stage of AD, which displayed significant increased amyloid deposition, and the increased amyloid deposition was associated with cognitive function in different domains.
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Affiliation(s)
- Shuhua Ren
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Junpeng Li
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Lin Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 200233 Shanghai, China
| | - Qi Huang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Kewei Chen
- Banner Alzheimer Institute, Arizona State University, University of Arizona and Arizona Alzheimer's Consortium, USA
| | - Jingchao Hu
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 200233 Shanghai, China; School of Nursing, Shanghai Jiaotong University, 200025 Shanghai, China
| | - Frank Jessen
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany; German Center for Neurodegenerative Disorder (DZNE), Bonn, Germany
| | - Xiaochen Hu
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
| | - Donglang Jiang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Lin Zhu
- Key Laboratory of Radiopharmaceuticals (Beijing Normal University), Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China
| | - Xiaomin Wang
- Department of Physiology, Capital Medical University, Key Laboratory for Neurodegenerative Disorders of the Ministry of Education, No. 10 Xitoutiao, Youanmen, 100069 Beijing, China
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, 200040 Shanghai, China.
| | - Fengchun Hua
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, 200040 Shanghai, China; Department of Nuclear Medicine, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China.
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 200233 Shanghai, China.
| | - Fang Xie
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, 200040 Shanghai, China.
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31
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Harris WJ, Asselin MC, Hinz R, Parkes LM, Allan S, Schiessl I, Boutin H, Dickie BR. In vivo methods for imaging blood-brain barrier function and dysfunction. Eur J Nucl Med Mol Imaging 2023; 50:1051-1083. [PMID: 36437425 PMCID: PMC9931809 DOI: 10.1007/s00259-022-05997-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 10/09/2022] [Indexed: 11/29/2022]
Abstract
The blood-brain barrier (BBB) is the interface between the central nervous system and systemic circulation. It tightly regulates what enters and is removed from the brain parenchyma and is fundamental in maintaining brain homeostasis. Increasingly, the BBB is recognised as having a significant role in numerous neurological disorders, ranging from acute disorders (traumatic brain injury, stroke, seizures) to chronic neurodegeneration (Alzheimer's disease, vascular dementia, small vessel disease). Numerous approaches have been developed to study the BBB in vitro, in vivo, and ex vivo. The complex multicellular structure and effects of disease are difficult to recreate accurately in vitro, and functional aspects of the BBB cannot be easily studied ex vivo. As such, the value of in vivo methods to study the intact BBB cannot be overstated. This review discusses the structure and function of the BBB and how these are affected in diseases. It then discusses in depth several established and novel methods for imaging the BBB in vivo, with a focus on MRI, nuclear imaging, and high-resolution intravital fluorescence microscopy.
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Affiliation(s)
- William James Harris
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Marie-Claude Asselin
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, UK
| | - Rainer Hinz
- Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
| | - Laura Michelle Parkes
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Stuart Allan
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Ingo Schiessl
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK
| | - Herve Boutin
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK.
- Division of Neuroscience, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, M13 9PL, Manchester, UK.
- Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK.
| | - Ben Robert Dickie
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester, Manchester, UK
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32
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Subramanyam Rallabandi V, Seetharaman K. Deep learning-based classification of healthy aging controls, mild cognitive impairment and Alzheimer’s disease using fusion of MRI-PET imaging. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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33
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Mehta RI, Mehta RI. The Vascular-Immune Hypothesis of Alzheimer's Disease. Biomedicines 2023; 11:408. [PMID: 36830944 PMCID: PMC9953491 DOI: 10.3390/biomedicines11020408] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 01/26/2023] [Accepted: 01/27/2023] [Indexed: 01/31/2023] Open
Abstract
Alzheimer's disease (AD) is a devastating and irreversible neurodegenerative disorder with unknown etiology. While its cause is unclear, a number of theories have been proposed to explain the pathogenesis of AD. In large part, these have centered around potential causes for intracerebral accumulation of beta-amyloid (βA) and tau aggregates. Yet, persons with AD dementia often exhibit autopsy evidence of mixed brain pathologies including a myriad of vascular changes, vascular brain injuries, complex brain inflammation, and mixed protein inclusions in addition to hallmark neuropathologic lesions of AD, namely insoluble βA plaques and neurofibrillary tangles (NFTs). Epidemiological data demonstrate that overlapping lesions diminish the βA plaque and NFT threshold necessary to precipitate clinical dementia. Moreover, a subset of persons who exhibit AD pathology remain resilient to disease while other persons with clinically-defined AD dementia do not exhibit AD-defining neuropathologic lesions. It is increasingly recognized that AD is a pathologically heterogeneous and biologically multifactorial disease with uncharacterized biologic phenomena involved in its genesis and progression. Here, we review the literature with regard to neuropathologic criteria and incipient AD changes, and discuss converging concepts regarding vascular and immune factors in AD.
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Affiliation(s)
- Rashi I. Mehta
- Department of Neuroradiology, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA
| | - Rupal I. Mehta
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
- Department of Pathology, Rush University Medical Center, Chicago, IL 60612, USA
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Abstract
Imaging of mild traumatic brain injury (TBI) using conventional techniques such as CT or MRI often results in no specific imaging correlation that would explain cognitive and clinical symptoms. Molecular imaging of mild TBI suggests that secondary events after injury can be detected using PET. However, no single specific pattern emerges that can aid in diagnosing the injury or determining the prognosis of the long-term behavioral profiles, indicating the heterogeneous and diffuse nature of TBI. Chronic traumatic encephalopathy, a primary tauopathy, has been shown to be strongly associated with repetitive TBI. In vivo data on the available tau PET tracers, however, have produced mixed results and overall low retention profiles in athletes with a history of repetitive mild TBI. Here, we emphasize that the lack of a mechanistic understanding of chronic TBI has posed a challenge when interpreting the results of molecular imaging biomarkers. We advocate for better target identification, improved analysis techniques such as machine learning or artificial intelligence, and novel tracer development.
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Affiliation(s)
- Gérard N. Bischof
- Department of Nuclear Medicine, University of Cologne, Cologne, Germany;,Institute for Neuroscience and Medicine II–Molecular Organization of the Brain, Research Center Juelich, Juelich, Germany; and
| | - Donna J. Cross
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah
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35
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Wang J, Jin C, Zhou J, Zhou R, Tian M, Lee HJ, Zhang H. PET molecular imaging for pathophysiological visualization in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2023; 50:765-783. [PMID: 36372804 PMCID: PMC9852140 DOI: 10.1007/s00259-022-05999-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 10/09/2022] [Indexed: 11/15/2022]
Abstract
Alzheimer's disease (AD) is the most common dementia worldwide. The exact etiology of AD is unclear as yet, and no effective treatments are currently available, making AD a tremendous burden posed on the whole society. As AD is a multifaceted and heterogeneous disease, and most biomarkers are dynamic in the course of AD, a range of biomarkers should be established to evaluate the severity and prognosis. Positron emission tomography (PET) offers a great opportunity to visualize AD from diverse perspectives by using radiolabeled agents involved in various pathophysiological processes; PET imaging technique helps to explore the pathomechanisms of AD comprehensively and find out the most appropriate biomarker in each AD phase, leading to a better evaluation of the disease. In this review, we discuss the application of PET in the course of AD and summarized radiolabeled compounds with favorable imaging characteristics.
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Affiliation(s)
- Jing Wang
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XInstitute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009 Zhejiang China ,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 Zhejiang China
| | - Chentao Jin
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China
| | - Jinyun Zhou
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China
| | - Rui Zhou
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China
| | - Mei Tian
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XInstitute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009 Zhejiang China ,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 Zhejiang China
| | - Hyeon Jeong Lee
- grid.13402.340000 0004 1759 700XCollege of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310014 Zhejiang China
| | - Hong Zhang
- grid.412465.0Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XInstitute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, 310009 Zhejiang China ,Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009 Zhejiang China ,grid.13402.340000 0004 1759 700XCollege of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, 310014 Zhejiang China ,grid.13402.340000 0004 1759 700XKey Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310014 Zhejiang China
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36
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Iannaccone S, Houdayer E, Spina A, Nocera G, Alemanno F. Quantitative EEG for early differential diagnosis of dementia with Lewy bodies. Front Psychol 2023; 14:1150540. [PMID: 37151310 PMCID: PMC10157484 DOI: 10.3389/fpsyg.2023.1150540] [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: 01/25/2023] [Accepted: 03/31/2023] [Indexed: 05/09/2023] Open
Abstract
Introduction Differentiating between the two most common forms of dementia, Alzheimer's dementia and dementia with Lewy bodies (DLB) remains difficult and requires the use of invasive, expensive, and resource-intensive techniques. We aimed to investigate the sensitivity and specificity of electroencephalography quantified using the statistical pattern recognition method (qEEG-SPR) for identifying dementia and DLB. Methods Thirty-two outpatients and 16 controls underwent clinical assessment (by two blinded neurologists), EEG recording, and a 6-month follow-up clinical assessment. EEG data were processed using a qEEG-SPR protocol to derive a Dementia Index (positive or negative) and DLB index (positive or negative) for each participant which was compared against the diagnosis given at clinical assessment. Confusion matrices were used to calculate sensitivity, specificity, and predictive values for identifying dementia and DLB specifically. Results Clinical assessment identified 30 cases of dementia, 2 of which were diagnosed clinically with possible DLB, 14 with probable DLB and DLB was excluded in 14 patients. qEEG-SPR confirmed the dementia diagnosis in 26 out of the 32 patients and led to 6.3% of false positives (FP) and 9.4% of false negatives (FN). qEEG-SPR was used to provide a DLB diagnosis among patients who received a positive or inconclusive result of Dementia index and led to 13.6% of FP and 13.6% of FN. Confusion matrices indicated a sensitivity of 80%, a specificity of 89%, a positive predictive value of 92%, a negative predictive value of 72%, and an accuracy of 83% to diagnose dementia. The DLB index showed a sensitivity of 60%, a specificity of 90%, a positive predictive value of 75%, a negative predictive value of 81%, and an accuracy of 75%. Neuropsychological scores did not differ significantly between DLB and non- DLB patients. Head trauma or story of stroke were identified as possible causes of FP results for DLB diagnosis. Conclusion qEEG-SPR is a sensitive and specific tool for diagnosing dementia and differentiating DLB from other forms of dementia in the initial state. This non-invasive, low-cost, and environmentally friendly method is a promising diagnostic tool for dementia diagnosis which could be implemented in local care settings.
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Affiliation(s)
- Sandro Iannaccone
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elise Houdayer
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
- *Correspondence: Elise Houdayer,
| | - Alfio Spina
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Gianluca Nocera
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Alemanno
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
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37
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Ramesh M, Govindaraju T. Multipronged diagnostic and therapeutic strategies for Alzheimer's disease. Chem Sci 2022; 13:13657-13689. [PMID: 36544728 PMCID: PMC9710308 DOI: 10.1039/d2sc03932j] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 10/13/2022] [Indexed: 12/24/2022] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and a major contributor to dementia cases worldwide. AD is clinically characterized by learning, memory, and cognitive deficits. The accumulation of extracellular amyloid β (Aβ) plaques and neurofibrillary tangles (NFTs) of tau are the pathological hallmarks of AD and are explored as targets for clinical diagnosis and therapy. AD pathology is poorly understood and there are no fully approved diagnosis and treatments. Notwithstanding the gap, decades of research in understanding disease mechanisms have revealed the multifactorial nature of AD. As a result, multipronged and holistic approaches are pertinent to targeting multiple biomarkers and targets for developing effective diagnosis and therapeutics. In this perspective, recent developments in Aβ and tau targeted diagnostic and therapeutic tools are discussed. Novel indirect, combination, and circulating biomarkers as potential diagnostic targets are highlighted. We underline the importance of multiplexing and multimodal detection of multiple biomarkers to generate biomarker fingerprints as a reliable diagnostic strategy. The classical therapeutics targeting Aβ and tau aggregation pathways are described with bottlenecks in the strategy. Drug discovery efforts targeting multifaceted toxicity involving protein aggregation, metal toxicity, oxidative stress, mitochondrial damage, and neuroinflammation are highlighted. Recent efforts focused on multipronged strategies to rationally design multifunctional modulators targeting multiple pathological factors are presented as future drug development strategies to discover potential therapeutics for AD.
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Affiliation(s)
- Madhu Ramesh
- Bioorganic Chemistry Laboratory, New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research Jakkur P.O. Bengaluru Karnataka 560064 India
| | - Thimmaiah Govindaraju
- Bioorganic Chemistry Laboratory, New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research Jakkur P.O. Bengaluru Karnataka 560064 India
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38
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Palandira SP, Carrion J, Turecki L, Falvey A, Zeng Q, Liu H, Tsaava T, Herschberg D, Brines M, Chavan SS, Chang EH, Vo A, Ma Y, Metz CN, Al-Abed Y, Tracey KJ, Pavlov VA. A dual tracer [ 11C]PBR28 and [ 18F]FDG microPET evaluation of neuroinflammation and brain energy metabolism in murine endotoxemia. Bioelectron Med 2022; 8:18. [PMID: 36451231 PMCID: PMC9710165 DOI: 10.1186/s42234-022-00101-2] [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: 10/18/2022] [Accepted: 11/09/2022] [Indexed: 12/09/2022] Open
Abstract
BACKGROUND Brain metabolic alterations and neuroinflammation have been reported in several peripheral inflammatory conditions and present significant potential for targeting with new diagnostic approaches and treatments. However, non-invasive evaluation of these alterations remains a challenge. METHODS Here, we studied the utility of a micro positron emission tomography (microPET) dual tracer ([11C]PBR28 - for microglial activation and [18F]FDG for energy metabolism) approach to assess brain dysfunction, including neuroinflammation in murine endotoxemia. MicroPET imaging data were subjected to advanced conjunction and individual analyses, followed by post-hoc analysis. RESULTS There were significant increases in [11C]PBR28 and [18F]FDG uptake in the hippocampus of C57BL/6 J mice 6 h following LPS (2 mg/kg) intraperitoneal (i.p.) administration compared with saline administration. These results confirmed previous postmortem observations. In addition, patterns of significant simultaneous activation were demonstrated in the hippocampus, the thalamus, and the hypothalamus in parallel with other tracer-specific and region-specific alterations. These changes were observed in the presence of robust systemic inflammatory responses manifested by significantly increased serum cytokine levels. CONCLUSIONS Together, these findings demonstrate the applicability of [11C]PBR28 - [18F]FDG dual tracer microPET imaging for assessing neuroinflammation and brain metabolic alterations in conditions "classically" characterized by peripheral inflammatory and metabolic pathogenesis.
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Affiliation(s)
| | - Joseph Carrion
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Lauren Turecki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Aidan Falvey
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Qiong Zeng
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Hui Liu
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Tea Tsaava
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Dov Herschberg
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Michael Brines
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Sangeeta S Chavan
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Eric H Chang
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - An Vo
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Yilong Ma
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Christine N Metz
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Yousef Al-Abed
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Kevin J Tracey
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Valentin A Pavlov
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
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Ryoo HG, Byun JI, Choi H, Jung KY. Deep learning signature of brain [ 18F]FDG PET associated with cognitive outcome of rapid eye movement sleep behavior disorder. Sci Rep 2022; 12:19259. [PMID: 36357491 PMCID: PMC9649732 DOI: 10.1038/s41598-022-23347-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 10/30/2022] [Indexed: 11/12/2022] Open
Abstract
An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder (iRBD) is crucial for the management. This study aimed to investigate cognitive signature of brain [18F]FDG PET based on deep learning (DL) for evaluating patients with iRBD. Fifty iRBD patients, 19 with mild cognitive impairment (MCI) (RBD-MCI) and 31 without MCI (RBD-nonMCI), were prospectively enrolled. A DL model for the cognitive signature was trained by using Alzheimer's Disease Neuroimaging Initiative database and transferred to baseline [18F]FDG PET from the iRBD cohort. The results showed that the DL-based cognitive dysfunction score was significantly higher in RBD-MCI than in RBD-nonMCI. The AUC of ROC curve for differentiating RBD-MCI from RBD-nonMCI was 0.70 (95% CI 0.56-0.82). The baseline DL-based cognitive dysfunction score was significantly higher in iRBD patients who showed a decrease in CERAD scores during 2 years than in those who did not. Brain metabolic features related to cognitive dysfunction-related regions of individual iRBD patients mainly included posterior cortical regions. This work demonstrates that the cognitive signature based on DL could be used to objectively evaluate cognitive function in iRBD. We suggest that this approach could be extended to an objective biomarker predicting cognitive decline and neurodegeneration in iRBD.
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Affiliation(s)
- Hyun Gee Ryoo
- grid.412484.f0000 0001 0302 820XDepartment of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080 Republic of Korea ,grid.412480.b0000 0004 0647 3378Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Jung-Ick Byun
- grid.289247.20000 0001 2171 7818Department of Neurology, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Hongyoon Choi
- grid.412484.f0000 0001 0302 820XDepartment of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080 Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ki-Young Jung
- grid.412484.f0000 0001 0302 820XDepartment of Neurology, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080 Republic of Korea ,grid.31501.360000 0004 0470 5905Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Korea
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40
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Gregory S, Saunders S, Ritchie CW. Science disconnected: the translational gap between basic science, clinical trials, and patient care in Alzheimer's disease. THE LANCET. HEALTHY LONGEVITY 2022; 3:e797-e803. [PMID: 36356629 DOI: 10.1016/s2666-7568(22)00219-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 08/22/2022] [Accepted: 09/08/2022] [Indexed: 11/09/2022] Open
Abstract
Both research and clinical practice have traditionally centred on the dementia syndrome of Alzheimer's disease rather than its preclinical and prodromal stages. However, there is a strong scientific and ethical impetus to shift focus to earlier disease stages to improve brain health outcomes and help to keep affected individuals symptom-free (dementia-free) for as long as possible. We provide an overview of recent advancements in early detection, drug development, and trial methodology that should be utilised in the development of new therapies for use in brain health clinics. We propose a triad approach to Alzheimer's disease clinical trials, encompassing (1) experimental medicine studies to gather greater knowledge of disease mechanisms, (2) a more comprehensive platform of phase 2 learning trials to inform phase 3 confirmatory trials, and (3) precision medicine involving smaller subgroups of patients with shared characteristics. This triad would ensure that treatment targets are identified accurately, trial methodology focuses on at-risk populations, and sensitive outcome measures capture potential treatment effects. Clinical services around the world must embrace the brain health clinic model so that neurodegenerative diseases can be detected in their earliest phase to quicken drug development pipelines and potentially improve prognosis.
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Affiliation(s)
- Sarah Gregory
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatient Department 2, Western General Hospital, University of Edinburgh, Edinburgh, UK.
| | - Stina Saunders
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatient Department 2, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatient Department 2, Western General Hospital, University of Edinburgh, Edinburgh, UK; Brain Health Scotland, Edinburgh, UK
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41
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Correlation of Global and Regional Amyloid Burden by 18F-Florbetaben PET/CT With Cognitive Impairment Profile and Severity. Clin Nucl Med 2022; 47:923-930. [DOI: 10.1097/rlu.0000000000004370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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42
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Image restoration algorithm incorporating methods to remove noise and blurring from positron emission tomography imaging for Alzheimer's disease diagnosis. Phys Med 2022; 103:181-189. [DOI: 10.1016/j.ejmp.2022.10.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/26/2022] [Accepted: 10/22/2022] [Indexed: 11/11/2022] Open
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Dickie BR, Jin T, Wang P, Hinz R, Harris W, Boutin H, Parker GJ, Parkes LM, Matthews JC. Quantitative kinetic modelling and mapping of cerebral glucose transport and metabolism using glucoCESL MRI. J Cereb Blood Flow Metab 2022; 42:2066-2079. [PMID: 35748031 PMCID: PMC9580170 DOI: 10.1177/0271678x221108841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Chemical-exchange spin-lock (CESL) MRI can map regional uptake and utilisation of glucose in the brain at high spatial resolution (i.e sub 0.2 mm3 voxels). We propose two quantitative kinetic models to describe glucose-induced changes in tissue R1ρ and apply them to glucoCESL MRI data acquired in tumour-bearing and healthy rats. When assuming glucose transport is saturable, the maximal transport capacity (Tmax) measured in normal tissue was 3.2 ± 0.6 µmol/min/mL, the half saturation constant (Kt) was 8.8 ± 2.2 mM, the metabolic rate of glucose consumption (MRglc) was 0.21 ± 0.13 µmol/min/mL, and the cerebral blood volume (vb) was 0.006 ± 0.005 mL/mL. Values in tumour were: Tmax = 7.1 ± 2.7 µmol/min/mL, Kt = 14 ± 1.7 mM, MRglc = 0.22 ± 0.09 µmol/min/mL, vb = 0.030 ± 0.035 mL/mL. Tmax and Kt were significantly higher in tumour tissue than normal tissue (p = 0.006 and p = 0.011, respectively). When assuming glucose uptake also occurs via free diffusion, the free diffusion rate (kd) was 0.061 ± 0.017 mL/min/mL in normal tissue and 0.12 ± 0.042 mL/min/mL in tumour. These parameter estimates agree well with literature values obtained using other approaches (e.g. NMR spectroscopy).
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Affiliation(s)
- Ben R Dickie
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Ping Wang
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Rainer Hinz
- Division of Informatics, Imaging, and Data Science, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK
| | - William Harris
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Hervé Boutin
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Geoff Jm Parker
- Bioxydyn Limited, Manchester, UK.,Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of Neuroinflammation, University College London, London, UK
| | - Laura M Parkes
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Julian C Matthews
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.,Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
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Schroyen G, Schramm G, Van Weehaeghe D, Leenaerts N, Vande Casteele T, Blommaert J, Koole M, Smeets A, Van Laere K, Sunaert S, Deprez S. Cerebral glucose changes after chemotherapy and their relation to long-term cognitive complaints and fatigue. Front Oncol 2022; 12:1021615. [PMID: 36313711 PMCID: PMC9612406 DOI: 10.3389/fonc.2022.1021615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 09/21/2022] [Indexed: 11/25/2022] Open
Abstract
Purpose To investigate the short-term cerebral metabolic effects of intravenous chemotherapy and their association with long-term fatigue/cognitive complaints. Experimental design Using [18F]-FDG-PET/CT whole-body scans, we retrospectively quantified relative cerebral glucose metabolism before and after neoadjuvant chemotherapy in a cohort of patients treated for non-metastatic breast cancer (2009-2019). Self-report of cognitive complaints and fatigue were prospectively assessed 7 ± 3 years after therapy. Metabolic changes were estimated with i) robust mixed-effects modelling in regions-of-interest (frontal, parietal, temporal, occipital, and insular cortex) and ii) general-linear modelling of whole-brain voxel-wise outcomes. iii) The association between metabolic changes and self-reported outcomes was evaluated using linear regression-analysis. Results Of the 667 screened patients, 263 underwent PET/CT before and after chemotherapy and 183 (48 ± 9 years) met the inclusion criteria. After chemotherapy, decreased frontal and increased parietal and insular metabolism were observed (|ß|>0.273, pFDR<0.008). Separately, additional increased occipital metabolism after epiribucin+ cyclophosphamide (EC) and temporal metabolism after EC+ fluorouracil chemotherapy were observed (ß>0.244, pFDR≤0.048). Voxel-based analysis (pcluster-FWE<0.001) showed decreased metabolism in the paracingulate gyrus (-3.2 ± 3.9%) and putamen (3.1 ± 4.1%) and increased metabolism in the lateral cortex (L=2.9 ± 3.1%) and pericentral gyri (3.0 ± 4.4%). Except for the central sulcus, the same regions showed changes in EC, but not in FEC patients. Of the 97 self-reported responders, 23% and 27% experienced extreme fatigue and long-term cognitive complaints, respectively, which were not associated with metabolic changes. Conclusion Both hyper- and hypometabolism were observed after chemotherapy for breast cancer. Combined with earlier findings, this study could support inflammatory mechanisms resulting in relative hypermetabolism, mainly in the parietal/occipital cortices. As early metabolic changes did not precede long-term complaints, further research is necessary to identify vulnerable patients.
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Affiliation(s)
- Gwen Schroyen
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Leuven Cancer Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, Translational MRI, KU Leuven, Leuven, Belgium
- *Correspondence: Gwen Schroyen,
| | - Georg Schramm
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven, Belgium
| | - Donatienne Van Weehaeghe
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven, Belgium
- Division of Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Nicolas Leenaerts
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Neurosciences, Mind-Body Research, KU Leuven, Leuven, Belgium
- University Psychiatric Centre, KU Leuven, Leuven, Belgium
- Department of Psychiatry, University Hospitals Leuven, Leuven, Belgium
| | - Thomas Vande Casteele
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- University Psychiatric Centre, KU Leuven, Leuven, Belgium
- Department of Psychiatry, University Hospitals Leuven, Leuven, Belgium
- Department of Neurosciences, Neuropsychiatry, KU Leuven, Leuven, Belgium
| | - Jeroen Blommaert
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Leuven Cancer Institute, KU Leuven, Leuven, Belgium
- Department of Oncology, Gynaecological Oncology, KU Leuven, Leuven, Belgium
| | - Michel Koole
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Leuven Cancer Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven, Belgium
| | - Ann Smeets
- Leuven Cancer Institute, KU Leuven, Leuven, Belgium
- Department of Oncology, Surgical Oncology, KU Leuven, Leuven, Belgium
- Surgical Oncology, University Hospitals Leuven, Leuven, Belgium
| | - Koen Van Laere
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Leuven Cancer Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven, Belgium
- Division of Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Stefan Sunaert
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, Translational MRI, KU Leuven, Leuven, Belgium
- Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Sabine Deprez
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Leuven Cancer Institute, KU Leuven, Leuven, Belgium
- Department of Imaging and Pathology, Translational MRI, KU Leuven, Leuven, Belgium
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Paranjpe MD, Chaffin M, Zahid S, Ritchie S, Rotter JI, Rich SS, Gerszten R, Guo X, Heckbert S, Tracy R, Danesh J, Lander ES, Inouye M, Kathiresan S, Butterworth AS, Khera AV. Neurocognitive trajectory and proteomic signature of inherited risk for Alzheimer's disease. PLoS Genet 2022; 18:e1010294. [PMID: 36048760 PMCID: PMC9436054 DOI: 10.1371/journal.pgen.1010294] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 06/14/2022] [Indexed: 11/18/2022] Open
Abstract
For Alzheimer's disease-a leading cause of dementia and global morbidity-improved identification of presymptomatic high-risk individuals and identification of new circulating biomarkers are key public health needs. Here, we tested the hypothesis that a polygenic predictor of risk for Alzheimer's disease would identify a subset of the population with increased risk of clinically diagnosed dementia, subclinical neurocognitive dysfunction, and a differing circulating proteomic profile. Using summary association statistics from a recent genome-wide association study, we first developed a polygenic predictor of Alzheimer's disease comprised of 7.1 million common DNA variants. We noted a 7.3-fold (95% CI 4.8 to 11.0; p < 0.001) gradient in risk across deciles of the score among 288,289 middle-aged participants of the UK Biobank study. In cross-sectional analyses stratified by age, minimal differences in risk of Alzheimer's disease and performance on a digit recall test were present according to polygenic score decile at age 50 years, but significant gradients emerged by age 65. Similarly, among 30,541 participants of the Mass General Brigham Biobank, we again noted no significant differences in Alzheimer's disease diagnosis at younger ages across deciles of the score, but for those over 65 years we noted an odds ratio of 2.0 (95% CI 1.3 to 3.2; p = 0.002) in the top versus bottom decile of the polygenic score. To understand the proteomic signature of inherited risk, we performed aptamer-based profiling in 636 blood donors (mean age 43 years) with very high or low polygenic scores. In addition to the well-known apolipoprotein E biomarker, this analysis identified 27 additional proteins, several of which have known roles related to disease pathogenesis. Differences in protein concentrations were consistent even among the youngest subset of blood donors (mean age 33 years). Of these 28 proteins, 7 of the 8 proteins with concentrations available were similarly associated with the polygenic score in participants of the Multi-Ethnic Study of Atherosclerosis. These data highlight the potential for a DNA-based score to identify high-risk individuals during the prolonged presymptomatic phase of Alzheimer's disease and to enable biomarker discovery based on profiling of young individuals in the extremes of the score distribution.
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Affiliation(s)
- Manish D. Paranjpe
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Mark Chaffin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Sohail Zahid
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Scott Ritchie
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Cambridge Baker Systems Genomics Initiative, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, United Kingdom
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, United Kingdom
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-University of California, Los Angeles Medical Center, Torrance, California, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Robert Gerszten
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-University of California, Los Angeles Medical Center, Torrance, California, United States of America
| | - Susan Heckbert
- Department of Epidemiology, University of Washington, Seattle, Washington, United States of America
| | - Russ Tracy
- Department of Biochemistry, Larner College of Medicine, University of Vermont, Burlington, Vermont, United States of America
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, United Kingdom
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, United Kingdom
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, United Kingdom
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, United Kingdom
| | - Eric S. Lander
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Cambridge Baker Systems Genomics Initiative, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, United Kingdom
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, United Kingdom
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom
- Department of Clinical Pathology, University of Melbourne, Parkville, Victoria, Australia
- The Alan Turing Institute, London, United Kingdom
| | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Verve Therapeutics, Cambridge, Massachusetts, United States of America
- Division of Cardiology and Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Adam S. Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, United Kingdom
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, United Kingdom
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, United Kingdom
| | - Amit V. Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Verve Therapeutics, Cambridge, Massachusetts, United States of America
- Division of Cardiology and Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail:
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Carneiro CDG, Faria DDP, Coutinho AM, Ono CR, Duran FLDS, da Costa NA, Garcez AT, da Silveira PS, Forlenza OV, Brucki SMD, Nitrini R, Busatto G, Buchpiguel CA. Evaluation of 10-minute post-injection 11C-PiB PET and its correlation with 18F-FDG PET in older adults who are cognitively healthy, mildly impaired, or with probable Alzheimer's disease. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2022; 44:495-506. [PMID: 36420910 PMCID: PMC9561831 DOI: 10.47626/1516-4446-2021-2374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/14/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Positron emission tomography (PET) allows in vivo evaluation of molecular targets in neurodegenerative diseases, such as Alzheimer's disease. Mild cognitive impairment is an intermediate stage between normal cognition and Alzheimer-type dementia. In vivo fibrillar amyloid-beta can be detected in PET using [11C]-labeled Pittsburgh compound B (11C-PiB). In contrast, [18F]fluoro-2-deoxy-d-glucose (18F-FDG) is a neurodegeneration biomarker used to evaluate cerebral glucose metabolism, indicating neuronal injury and synaptic dysfunction. In addition, early cerebral uptake of amyloid-PET tracers can determine regional cerebral blood flow. The present study compared early-phase 11C-PiB and 18F-FDG in older adults without cognitive impairment, amnestic mild cognitive impairment, and clinical diagnosis of probable Alzheimer's disease. METHODS We selected 90 older adults, clinically classified as healthy controls, with amnestic mild cognitive impairment, or with probable Alzheimer's disease, who underwent an 18F-FDG PET, early-phase 11C-PiB PET and magnetic resonance imaging. All participants were also classified as amyloid-positive or -negative in late-phase 11C-PiB. The data were analyzed using statistical parametric mapping. RESULTS We found that the probable Alzheimer's disease and amnestic mild cognitive impairment group had lower early-phase 11C-PiB uptake in limbic structures than 18F-FDG uptake. The images showed significant interactions between amyloid-beta status (negative or positive). However, early-phase 11C-PiB appears to provide different information from 18F-FDG about neurodegeneration. CONCLUSIONS Our study suggests that early-phase 11C-PiB uptake correlates with 18F-FDG, irrespective of the particular amyloid-beta status. In addition, we observed distinct regional distribution patterns between both biomarkers, reinforcing the need for more robust studies to investigate the real clinical value of early-phase amyloid-PET imaging.
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Affiliation(s)
- Camila de Godoi Carneiro
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil,Centro de Investigação Translacional em Oncologia, Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Daniele de Paula Faria
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil,Centro de Investigação Translacional em Oncologia, Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Artur Martins Coutinho
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Carla Rachel Ono
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Fábio Luís de Souza Duran
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Naomi Antunes da Costa
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Alexandre Teles Garcez
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Paula Squarzoni da Silveira
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Orestes Vicente Forlenza
- Laboratório de Neurociências (LIM 27), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Sonia Maria Dozzi Brucki
- Departamento de Neurologia, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Ricardo Nitrini
- Departamento de Neurologia, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Geraldo Busatto
- Laboratório Neuro-Imagem em Psiquiatria (LIM 21), Departamento de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil
| | - Carlos Alberto Buchpiguel
- Laboratório de Medicina Nuclear (LIM 43), Departamento de Radiologia e Oncologia, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil,Correspondence: Carlos Alberto Buchpiguel, Universidade de São Paulo, Faculdade de Medicina da Universidade de São Paulo, Av. Dr. Arnaldo, 455, CEP 01255-090, São Paulo, SP, Brazil. E-mail:
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GC-CNNnet: Diagnosis of Alzheimer’s Disease with PET Images Using Genetic and Convolutional Neural Network. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2022; 2022:7413081. [PMID: 35983158 PMCID: PMC9381254 DOI: 10.1155/2022/7413081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 06/01/2022] [Accepted: 06/10/2022] [Indexed: 11/17/2022]
Abstract
There is a wide variety of effects of Alzheimer's disease (AD), a neurodegenerative disease that can lead to cognitive decline, deterioration of daily life, and behavioral and psychological changes. A polymorphism of the ApoE gene ε 4 is considered a genetic risk factor for Alzheimer's disease. The purpose of this paper is to demonstrate that single-nucleotide polymorphic markers (SNPs) have a causal relationship with quantitative PET imaging traits. Additionally, the classification of AD is based on the frequency of brain tissue variations in PET images using a combination of k-nearest-neighbor (KNN), support vector machine (SVM), linear discrimination analysis (LDA), and convolutional neural network (CNN) techniques. According to the results, the suggested SNPs appear to be associated with quantitative traits more strongly than the SNPs in the ApoE genes. Regarding the classification result, the highest accuracy is obtained by the CNN with 91.1%. These results indicate that the KNN and CNN methods are beneficial in diagnosing AD. Nevertheless, the LDA and SVM are demonstrated with a lower level of accuracy.
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Doering E, Hoenig MC, Bischof GN, Bohn KP, Ellingsen LM, van Eimeren T, Drzezga A. Introducing a gatekeeping system for amyloid status assessment in mild cognitive impairment. Eur J Nucl Med Mol Imaging 2022; 49:4478-4489. [PMID: 35831715 PMCID: PMC9605923 DOI: 10.1007/s00259-022-05879-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/14/2022] [Indexed: 11/19/2022]
Abstract
Background In patients with mild cognitive impairment (MCI), enhanced cerebral amyloid-β plaque burden is a high-risk factor to develop dementia with Alzheimer’s disease (AD). Not all patients have immediate access to the assessment of amyloid status (A-status) via gold standard methods. It may therefore be of interest to find suitable biomarkers to preselect patients benefitting most from additional workup of the A-status. In this study, we propose a machine learning–based gatekeeping system for the prediction of A-status on the grounds of pre-existing information on APOE-genotype 18F-FDG PET, age, and sex. Methods Three hundred and forty-two MCI patients were used to train different machine learning classifiers to predict A-status majority classes among APOE-ε4 non-carriers (APOE4-nc; majority class: amyloid negative (Aβ-)) and carriers (APOE4-c; majority class: amyloid positive (Aβ +)) from 18F-FDG-PET, age, and sex. Classifiers were tested on two different datasets. Finally, frequencies of progression to dementia were compared between gold standard and predicted A-status. Results Aβ- in APOE4-nc and Aβ + in APOE4-c were predicted with a precision of 87% and a recall of 79% and 51%, respectively. Predicted A-status and gold standard A-status were at least equally indicative of risk of progression to dementia. Conclusion We developed an algorithm allowing approximation of A-status in MCI with good reliability using APOE-genotype, 18F-FDG PET, age, and sex information. The algorithm could enable better estimation of individual risk for developing AD based on existing biomarker information, and support efficient selection of patients who would benefit most from further etiological clarification. Further potential utility in clinical routine and clinical trials is discussed. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-022-05879-6.
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Affiliation(s)
- E Doering
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany. .,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany.
| | - M C Hoenig
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.,Institute for Neuroscience and Medicine II-Molecular Organization of the Brain, Research Center Juelich, Jülich, Germany
| | - G N Bischof
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.,Institute for Neuroscience and Medicine II-Molecular Organization of the Brain, Research Center Juelich, Jülich, Germany
| | - K P Bohn
- Klinikum Dritter Orden, Department of Radiology and Nuclear Medicine, Munich, Germany
| | - L M Ellingsen
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA.,Department of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
| | - T van Eimeren
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
| | - A Drzezga
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany.,University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany.,Institute for Neuroscience and Medicine II-Molecular Organization of the Brain, Research Center Juelich, Jülich, Germany
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Rai H, Gupta S, Kumar S, Yang J, Singh SK, Ran C, Modi G. Near-Infrared Fluorescent Probes as Imaging and Theranostic Modalities for Amyloid-Beta and Tau Aggregates in Alzheimer's Disease. J Med Chem 2022; 65:8550-8595. [PMID: 35759679 DOI: 10.1021/acs.jmedchem.1c01619] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A person suspected of having Alzheimer's disease (AD) is clinically diagnosed for the presence of principal biomarkers, especially misfolded amyloid-beta (Aβ) and tau proteins in the brain regions. Existing radiotracer diagnostic tools, such as PET imaging, are expensive and have limited availability for primary patient screening and pre-clinical animal studies. To change the status quo, small-molecular near-infrared (NIR) probes have been rapidly developed, which may serve as an inexpensive, handy imaging tool to comprehend the dynamics of pathogenic progression in AD and assess therapeutic efficacy in vivo. This Perspective summarizes the biochemistry of Aβ and tau proteins and then focuses on structurally diverse NIR probes with coverages of their spectroscopic properties, binding affinity toward Aβ and tau species, and theranostic effectiveness. With the summarized information and perspective discussions, we hope that this paper may serve as a guiding tool for designing novel in vivo imaging fluoroprobes with theranostic capabilities in the future.
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Affiliation(s)
- Himanshu Rai
- Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (BHU), Varanasi, U.P.-221005, India
| | - Sarika Gupta
- Molecular Science Laboratory, National Institute of Immunology, New Delhi-110067, India
| | - Saroj Kumar
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi-110029, India
| | - Jian Yang
- School of Medicine, Shanghai University, Shanghai 200444, China
| | - Sushil K Singh
- Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (BHU), Varanasi, U.P.-221005, India
| | - Chongzhao Ran
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, United States
| | - Gyan Modi
- Department of Pharmaceutical Engineering & Technology, Indian Institute of Technology (BHU), Varanasi, U.P.-221005, India
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